WorldWideScience

Sample records for electricity demand response

  1. Hawaiian Electric Company Demand Response Roadmap Project

    Energy Technology Data Exchange (ETDEWEB)

    Levy, Roger [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-01-12

    The objective of this project was to develop a “roadmap” to guide the Hawaiian Electric Company (HECO) demand response (DR) planning and implementation in support of the Hawaii Clean Energy Initiative (HCEI) 70% clean energy goal by 2030.

  2. Use of demand response in electricity markets

    DEFF Research Database (Denmark)

    Singh, Sri Niwas; Østergaard, Jacob

    2010-01-01

    Demand response (DR) can provide sufficient measure, if implemented successfully, to provide economic, secure and stable supply to the customers even under the variability of the generated output from renewable energy source such as wind and solar. However, there are several issues to be analyzed...... market is analyzed. This paper also addresses the key issues and challenges in the implementation of DR in the electricity markets....... before DR implementation. This paper critically examines the present practices of the DR in the various electricity markets existing in the world including Europe. The prospect of DR in various market levels such as day-ahead (spot) market, hour-ahead market, real time/regulating market and ancillary...

  3. Demand response in experimental electricity markets

    Directory of Open Access Journals (Sweden)

    Barreda-Tarrazona, Iván

    2012-03-01

    Full Text Available We study consumers’ behavior in an experimental electricity market. Subjects make decisions concerning the quantity of electric energy they want to consume in three different pricing environments. In the baseline framework, they decide under a system of fixed prices, invariant to consumption schedule as well as to network restrictions. The other two environments correspond to dynamic pricing systems combined with incentives that aim at cutting energy consumption in a number of selected situations characterized by high network congestion. In such situations, in the first environment subjects get a bonus if they reduce their peak consumption below a certain level, while in the second one, consumers are sanctioned for consuming in peak times. From a social welfare perspective, our experimental data confirm that a dynamic system for prices is more efficient than a fixed one. Moreover, a dynamic scheme with sanctions, although less preferred by consumers, is more effective than the one with bonuses in order to reduce peak consumption. Dynamic pricing with bonuses reaches a good balance between efficiency and consumer acceptance.

    Estudiamos el comportamiento de los consumidores en un mercado de electricidad diseñado en el laboratorio. Los sujetos experimentales toman decisiones sobre la cantidad de electricidad que desean consumir en tres contextos diferentes. En el tratamiento base, los consumidores deciden bajo un sistema de precios fijos, en el que el precio es invariable tanto a la franja horaria de consumo como a las restricciones de la red. Los otros dos contextos corresponden a sistemas dinámicos de precios combinados con incentivos cuyo objetivo es la reducción del consumo en algunas situaciones seleccionadas caracterizadas por una alta congestión de la red. En estas situaciones, en el primer contexto, se bonifica la reducción del consumo en la hora punta por debajo de cierto nivel, mientras que en el segundo, los consumidores

  4. Analyses of demand response in Denmark[Electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Moeller Andersen, F.; Grenaa Jensen, S.; Larsen, Helge V.; Meibom, P.; Ravn, H.; Skytte, K.; Togeby, M.

    2006-10-15

    Due to characteristics of the power system, costs of producing electricity vary considerably over short time intervals. Yet, many consumers do not experience corresponding variations in the price they pay for consuming electricity. The topic of this report is: are consumers willing and able to respond to short-term variations in electricity prices, and if so, what is the social benefit of consumers doing so? Taking Denmark and the Nord Pool market as a case, the report focuses on what is known as short-term consumer flexibility or demand response in the electricity market. With focus on market efficiency, efficient allocation of resources and security of supply, the report describes demand response from a micro-economic perspective and provides empirical observations and case studies. The report aims at evaluating benefits from demand response. However, only elements contributing to an overall value are presented. In addition, the analyses are limited to benefits for society, and costs of obtaining demand response are not considered. (au)

  5. Benefits and challenges of electrical demand response: A critical review

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Pinson, Pierre; Madsen, Henrik

    2014-01-01

    in generation capacity requirements. Nevertheless, demand response is not without its challenges. The key challenges for demand response centre around establishing reliable control strategies and market frameworks so that the demand response resource can be used optimally. One of the greatest challenges...

  6. Quantifying Changes in Building Electricity Use, with Application to Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Mathieu, Johanna L.; Price, Phillip N.; Kiliccote, Sila; Piette, Mary Ann

    2010-11-17

    We present methods for analyzing commercial and industrial facility 15-minute-interval electric load data. These methods allow building managers to better understand their facility's electricity consumption over time and to compare it to other buildings, helping them to ask the right questions to discover opportunities for demand response, energy efficiency, electricity waste elimination, and peak load management. We primarily focus on demand response. Methods discussed include graphical representations of electric load data, a regression-based electricity load model that uses a time-of-week indicator variable and a piecewise linear and continuous outdoor air temperature dependence, and the definition of various parameters that characterize facility electricity loads and demand response behavior. In the future, these methods could be translated into easy-to-use tools for building managers.

  7. The value of online information for demand response in Walrasian electricity markets

    NARCIS (Netherlands)

    F.N. Claessen (Felix); B.J. Liefers (Bart); M. Kaisers (Michael); J.A. La Poutré (Han)

    2015-01-01

    textabstractSmart energy systems integrate renewables and demand response. Most European electricity markets coordinate the resulting time-varying flexibility in demand and supply by organising day-ahead trade with Walrasian mechanisms, using simultaneous call auctions and sealed bids. These

  8. Modelling of Hot Water Storage Tank for Electric Grid Integration and Demand Response Control

    DEFF Research Database (Denmark)

    Sinha, Rakesh; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    boilers for grid integration are investigated: single mass model (with uniform temperature inside tank) and two mass model (with ideal single stratified layers). In order to investigate the influence of demand response and grid voltage quality with the measurable parameter of electrical boiler in practice......, selection of a proper model is equally important. The results obtained from comparison of two models (when input to the model is thermal energy demand) are present with their significance and advantages for grid integration and demand response. Models mathematics are shown in detail with the validation...

  9. A fuzzy chance-constrained program for unit commitment problem considering demand response, electric vehicle and wind power

    DEFF Research Database (Denmark)

    Zhang, Ning; Hu, Zhaoguang; Han, Xue

    2015-01-01

    commitment model is proposed in this paper considering demand response and electric vehicles, which can promote the exploitation of wind power. On the one hand, demand response and electric vehicles have the feasi- bility to change the load demand curve to solve the mismatch problem. On the other hand...... system operation more eco-friendly and economical....

  10. Important Factors for Early Market Microgrids: Demand Response and Plug-in Electric Vehicle Charging

    OpenAIRE

    White, David

    2016-01-01

    Microgrids are evolving concepts that are growing in interest due to their potential reliability, economic and environmental benefits. As with any new concept, there are many unresolved issues with regards to planning and operation. In particular, demand response (DR) and plug-in electric vehicle (PEV) charging are viewed as two key components of the future grid and both will likely be active technologies in the microgrid market. However, a better understanding of the economics associated w...

  11. Impacts of demand response and renewable generation in electricity power market

    Science.gov (United States)

    Zhao, Zhechong

    This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating

  12. Ice Storage Air-Conditioning System Simulation with Dynamic Electricity Pricing: A Demand Response Study

    Directory of Open Access Journals (Sweden)

    Chi-Chun Lo

    2016-02-01

    Full Text Available This paper presents an optimal dispatch model of an ice storage air-conditioning system for participants to quickly and accurately perform energy saving and demand response, and to avoid the over contact with electricity price peak. The schedule planning for an ice storage air-conditioning system of demand response is mainly to transfer energy consumption from the peak load to the partial-peak or off-peak load. Least Squares Regression (LSR is used to obtain the polynomial function for the cooling capacity and the cost of power consumption with a real ice storage air-conditioning system. Based on the dynamic electricity pricing, the requirements of cooling loads, and all technical constraints, the dispatch model of the ice-storage air-conditioning system is formulated to minimize the operation cost. The Improved Ripple Bee Swarm Optimization (IRBSO algorithm is proposed to solve the dispatch model of the ice storage air-conditioning system in a daily schedule on summer. Simulation results indicate that reasonable solutions provide a practical and flexible framework allowing the demand response of ice storage air-conditioning systems to demonstrate the optimization of its energy savings and operational efficiency and offering greater energy efficiency.

  13. An Economic Demand Response Model in Liberalized Electricity Markets with Respect to Flexibility of Consumers

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2017-01-01

    Before restructuring in the electricity industry, the primary decision-makers of the electricity market were deemed to be power generation and transmission companies, market regulation boards, and power industry regulators. In this traditional structure, consumers were interested in receiving....... The most important solution can be demand response (DR) programs. This paper proposes an economic DR model for residential consumers in liberalized electricity markets to change their consumption pattern from times of high energy prices to other times to maximize their utility functions. This economic...... model is developed based on constant elasticity of substitution (CES) utility function known as one of the most popular utility functions in microeconomics. Simulation results indicate that the proposed model is adaptable to any group of residential consumers with any disposition toward participation...

  14. Reducing Gridlock on the Grid: Utility Trends in Managing Peak Electric Load through Residential Demand Response

    Science.gov (United States)

    McDonald, Betsy

    Utilities across the United States are piloting residential demand response programs to help manage peak electric demand. Using publicly available program evaluations, this thesis analyzes nine such programs to uncover and synthesize the range of program offerings, goals, enrollment strategies, and customer experiences. This review reveals that program participation, components, and results differ based on a variety of factors, including geographic characteristics, program goals, and implementation strategies. The diversity of program designs and evaluation findings suggests an underlying tension between the need to generate cost-effective program impacts and the desire to increase accessibility so that program benefits are not exclusive to certain segments of the population. For more significant and impactful engagement, program goals may need to shift. State level policy support could help shift program goals toward increasing program accessibility. Future research should explore creative strategies that target existing barriers and allow for more inclusive deployment.

  15. Household electricity demand profiles

    DEFF Research Database (Denmark)

    Marszal, Anna Joanna; Heiselberg, Per Kvols; Larsen, Olena Kalyanova

    2016-01-01

    Highlights •A 1-min resolution household electricity load model is presented. •Model adapts a bottom-up approach with single appliance as the main building block. •Load profiles are used to analyse the flexibility potential of household appliances. •Load profiles can be applied in other domains, e.......g. building energy simulations. •The demand level of houses with different number of occupants is well captured....

  16. Review of Real-time Electricity Markets for Integrating Distributed Energy Resources and Demand Response

    DEFF Research Database (Denmark)

    Wang, Qi; Zhang, Chunyu; Ding, Yi

    2015-01-01

    The high penetration of both Distributed Energy Resources (DER) and Demand Response (DR) in modern power systems requires a sequence of advanced strategies and technologies for maintaining system reliability and flexibility. Real-time electricity markets (RTM) are the nondiscriminatory transaction...... platforms for providing necessary balancing services, where the market clearing (nodal or zonal prices depending on markets) is very close to real time operations of power systems. One of the primary functions of RTMs in modern power systems is establishing an efficient and effective mechanism for small DER...... and DR to participate in balancing market transactions, while handling their meteorological or intermittent characteristics, facilitating asset utilization, and stimulating their active responses. Consequently, RTMs are dedicated to maintaining the flexibility and reliability of power systems. This paper...

  17. Modelling momentary electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Perrels, A.H.

    1991-01-01

    The aim of this dissertation is to develop a load shape simulation model for the public electricity network in the Netherlands with special reference to social and economic phenomena underlying its development. The main structure of the model consists of the electric power planning environment in which the altering requirements concerning load shape assessment are defined, and three subsets of modules describing the manufacturing industry, the services and the residential sector (households). The load shapes of the three main sectors are aggregated and augmented with the loads of the remaining sectors in order to produce an overall load shape. Part A of this book depicts the planning environment, and gives historical and future aspects of the Dutch electricity demand. Part B offers a theoretical and methodological discussion about the translation of a firm's operational behaviour into electricity demand by time of day, describes the simulation modules for the manufacturing industry and services, and several simulation experiments are discussed. Part C, devoted to the residential sector, deals with household behaviour and time allocation, presents an operational model of timing integrated in the household model. Also various simulation results are presented and compared with other simulation studies. Part D contains comprehensive experiments with the model system. Comparisons are made with load shapes of the public network in recent years. Next, overall forecasts are made in the framework of three scenario's: (a) low growth - normal conservation; (b) high growth - more conservation - extension of production times; (c) as (b) plus extensive teleworking. The results of the scenario exercises are discussed in connection with strategic management prospects of the public network. 65 figs., 26 tabs., 11 apps., 126 refs.

  18. Important Factors for Early Market Microgrids: Demand Response and Plug-in Electric Vehicle Charging

    Science.gov (United States)

    White, David Masaki

    Microgrids are evolving concepts that are growing in interest due to their potential reliability, economic and environmental benefits. As with any new concept, there are many unresolved issues with regards to planning and operation. In particular, demand response (DR) and plug-in electric vehicle (PEV) charging are viewed as two key components of the future grid and both will likely be active technologies in the microgrid market. However, a better understanding of the economics associated with DR, the impact DR can have on the sizing of distributed energy resource (DER) systems and how to accommodate and price PEV charging is necessary to advance microgrid technologies. This work characterizes building based DR for a model microgrid, calculates the DER systems for a model microgrid under DR through a minimization of total cost, and determines pricing methods for a PEV charging station integrated with an individual building on the model microgrid. It is shown that DR systems which consist only of HVAC fan reductions provide potential economic benefits to the microgrid through participation in utility DR programs. Additionally, peak shaving DR reduces the size of power generators, however increasing DR capacity does not necessarily lead to further reductions in size. As it currently stands for a microgrid that is an early adopter of PEV charging, current installation costs of PEV charging equipment lead to a system that is not competitive with established commercial charging networks or to gasoline prices for plug-in hybrid electric vehicles (PHEV).

  19. Distributed energy resources management using plug-in hybrid electric vehicles as a fuel-shifting demand response resource

    DEFF Research Database (Denmark)

    Morais, Hugo; Sousa, Tiago; Soares, J.

    2015-01-01

    , namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting...... to develop adequate methodologies to schedule the electric vehicles' charge and discharge processes, avoiding network congestions and providing ancillary services.This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed...

  20. A bilevel model for electricity retailers' participation in a demand response market environment

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre

    2013-01-01

    consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers......Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small...

  1. An Economic Customer-Oriented Demand Response Model in Electricity Markets

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2018-01-01

    Consumer choice theory is a branch of microeconomics. This theory relates to adjusting consumption expenditures and consumer demand curve. Consumer choice science is trying to realize the buyer's decision-making process. This science studies customer characteristics, such as behavioral criteria...... demand response (DR) models have been developed based on this concept, this will also be deemed as a disadvantage for them. In this paper, we propose an economic DR model based on economic theories and mathematical methods. In addition to abate the defects of price-elasticity based DR models...

  2. Modeling Demand Response in Electricity Retail Markets as a Stackelberg Game

    DEFF Research Database (Denmark)

    Zugno, Marco; Morales González, Juan Miguel; Pinson, Pierre

    We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price-sequence, w......We model the retail market with dynamic pricing as a Stackelberg game where both retailers (leaders) and flexible consumers (followers) solve an economic cost-minimization problem. The electricity retailer optimizes an economic objective over a daily horizon by setting an hourly price...... with Equilibrium Constraints (MPEC) and cast as a Mixed Integer Linear Program (MILP), which can be solved using off-the-shelf optimization software. In an illustrative example, we consider a retailer associated with both flexible demand and wind power production. Such an example shows the efficiency of dynamic...... pricing as a way to control the load for minimizing the imbalances due to wind power, assesses the overall economic results for the retailer and the consumers as well as the dynamic properties of consumer flexibility....

  3. DC microgrids with energy storage systems and demand response for providing support to frequency regulation of electrical power systems

    DEFF Research Database (Denmark)

    Basic, Hrvoje; Dragicevic, Tomislav; Pandzic, Hrvoje

    2017-01-01

    Frequency regulation of electric power systems efficiency depends on response time and on power reserves for frequency regulation. As integration of non-dispatchable renewable generation in the power system results with increased need for power reserves from fast responding power units, the idea...... of using aggregated DC microgrids in frequency regulation is presented. Model proposed in this work is based on using battery energy storage, combined with demand response for achieving efficient usage of battery energy storage. It is shown that large number of DC microgrids can provide sufficient....

  4. Day-ahead resource scheduling including demand response for electric vehicles

    DEFF Research Database (Denmark)

    Soares, Joao; Morais, Hugo; Sousa, Tiago

    2014-01-01

    Summary form only given. The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering...... the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs in the V2G approach. Three different DR programs....... Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method....

  5. Demand Response Spinning Reserve Demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Eto, Joseph H.; Nelson-Hoffman, Janine; Torres, Carlos; Hirth,Scott; Yinger, Bob; Kueck, John; Kirby, Brendan; Bernier, Clark; Wright,Roger; Barat, A.; Watson, David S.

    2007-05-01

    The Demand Response Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.

  6. Enabling demand response by extending the European electricity markets with a real-time market

    NARCIS (Netherlands)

    Nyeng, P.; Kok, K.; Pineda, S.; Grande, O.; Sprooten, J.; Hebb, B.; Nieuwenhout, F.

    2013-01-01

    The EcoGrid concept proposes to extend the current wholesale electricity market to allow participation of Distributed Energy Resources (DERs) and domestic end-consumers in system balancing. Taking advantage of the smart grid technology, the EcoGrid market publishes the real-time prices that entail

  7. Social Welfare implications of demand response programs in competitive electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Boisvert, Richard N.; Neenan, Bernard F.

    2003-08-01

    The price volatility exhibited by wholesale electricity markets has stymied the movement to restructure the industry, and may derail it altogether. Market designers argue that prices are superior to regulation for directing long-term investments to the proper location and function, and that price volatility is a natural manifestation of a robustly competitive market. However, episodes of prices that soar to previously unimaginable heights try customers' patience and cause policy makers to reconsider if the prize is worth the consequences.

  8. Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

    DEFF Research Database (Denmark)

    Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio

    2015-01-01

    Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price...... to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also...... taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand....

  9. The alchemy of demand response: turning demand into supply

    Energy Technology Data Exchange (ETDEWEB)

    Rochlin, Cliff

    2009-11-15

    Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demand response should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

  10. Addressing Energy Demand through Demand Response. International Experiences and Practices

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Bo [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ghatikar, Girish [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ni, Chun Chun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dudley, Junqiao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Martin, Phil [Enernoc, Inc., Boston, MA (United States); Wikler, Greg

    2012-06-01

    Demand response (DR) is a load management tool which provides a cost-effective alternative to traditional supply-side solutions to address the growing demand during times of peak electrical load. According to the US Department of Energy (DOE), demand response reflects “changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized.” 1 The California Energy Commission (CEC) defines DR as “a reduction in customers’ electricity consumption over a given time interval relative to what would otherwise occur in response to a price signal, other financial incentives, or a reliability signal.” 2 This latter definition is perhaps most reflective of how DR is understood and implemented today in countries such as the US, Canada, and Australia where DR is primarily a dispatchable resource responding to signals from utilities, grid operators, and/or load aggregators (or DR providers).

  11. Demand Response on domestic thermostatically controlled loads

    DEFF Research Database (Denmark)

    Lakshmanan, Venkatachalam

    Electricity has become an inevitable part of human life in present day world. In the past two centuries, the electric power system has undergone a lot of changes. Due to the awareness about the adverse impact of the fossil fuels, the power industry is adopting green and sustainable energy sources....... For a safe and reliable operation of electric power systems, the balance between electricity generation and consumption has to be maintained. The conventional fossil fuel based power generation achieves this balance by adjusting the generation to follow the consumption. In the electric power system...... with renewable energy sources, the production cannot be adjusted to match the demand due to the fluctuating nature of the renewable energy sources. Therefore, the demand has to be adjusted to match the power production. The concept of adjusting the demand to match the production is called demand response...

  12. An econometric analysis of electricity demand response to price changes at the intra-day horizon: The case of manufacturing industry in West Denmark

    Directory of Open Access Journals (Sweden)

    Niels Framroze Møller

    2015-06-01

    Full Text Available The use of renewable energy implies a more variable supply of power. Market efficiency may improve if demand can absorb some of this variability by being more flexible, e.g. by responding quickly to changes in the market price of power. To learn about this, in particular, whether demand responds already within the same day, we suggest an econometric model for hourly consumption- and price time series. This allows for multi-level seasonality and that information about day-ahead prices does not arrive every hour but every 24th hour (as a vector of 24 prices. We confront the model with data from the manufacturing industry of West Denmark (2007-2011. The results clearly suggest a lack of response. The policy implication is that relying exclusively on hourly price response by consumers for integrating volatile renewable electricity production is questionable. Either hourly price variation has to increase considerably or demand response technologies be installed.

  13. Demand response in a market environment

    DEFF Research Database (Denmark)

    Larsen, Emil Mahler

    This thesis addresses the design, deployment and benefits of demand response in a market environment. Demand response is consumption that can be controlled by an external stimulus in the power system. Flexible consumption is a useful tool for absorbing volatile power from renewable sources like...... and sometimes not, that will lead to power system failure. The type of demand response investigated is consumption controlled by indirect means, like an electricity price. Initially, algorithms responding to real-time electricity prices are researched and benchmarked according to comfort and cost. After...... pricing and to classify different types of customers. The proposed models are then embedded into new fiveminute electricity markets for system balancing and local congestion management. New market tools for exploiting and maintaining a degree of control over demand are developed, and the value of DR using...

  14. Coordination of Energy Efficiency and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

    2010-01-29

    This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

  15. Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices

    Science.gov (United States)

    Chassin, David P.; Donnelly, Matthew K.; Dagle, Jeffery E.

    2006-12-12

    Electrical power distribution control methods, electrical energy demand monitoring methods, and power management devices are described. In one aspect, an electrical power distribution control method includes providing electrical energy from an electrical power distribution system, applying the electrical energy to a load, providing a plurality of different values for a threshold at a plurality of moments in time and corresponding to an electrical characteristic of the electrical energy, and adjusting an amount of the electrical energy applied to the load responsive to an electrical characteristic of the electrical energy triggering one of the values of the threshold at the respective moment in time.

  16. Forecasting residential electricity demand in provincial China.

    Science.gov (United States)

    Liao, Hua; Liu, Yanan; Gao, Yixuan; Hao, Yu; Ma, Xiao-Wei; Wang, Kan

    2017-03-01

    In China, more than 80% electricity comes from coal which dominates the CO2 emissions. Residential electricity demand forecasting plays a significant role in electricity infrastructure planning and energy policy designing, but it is challenging to make an accurate forecast for developing countries. This paper forecasts the provincial residential electricity consumption of China in the 13th Five-Year-Plan (2016-2020) period using panel data. To overcome the limitations of widely used predication models with unreliably prior knowledge on function forms, a robust piecewise linear model in reduced form is utilized to capture the non-deterministic relationship between income and residential electricity consumption. The forecast results suggest that the growth rates of developed provinces will slow down, while the less developed will be still in fast growing. The national residential electricity demand will increase at 6.6% annually during 2016-2020, and populous provinces such as Guangdong will be the main contributors to the increments.

  17. The value of demand response in Florida

    Energy Technology Data Exchange (ETDEWEB)

    Stoll, Brady; Buechler, Elizabeth; Hale, Elaine

    2017-11-01

    Many electrical loads may be operated flexibly to provide grid services, including peaking capacity, reserves, and load shifting. The authors model 14 demand end uses in Florida and analyze their operational impacts and overall value for a wide range of solar penetrations and grid flexibility options. They find demand response is able to reduce production costs, reduce the number of low-load hours for traditional generators, reduce starting of gas generators, and reduce curtailment.

  18. Load-shift incentives for household demand response: Evaluation of hourly dynamic pricing and rebate schemes in a wind-based electricity system

    DEFF Research Database (Denmark)

    Katz, Jonas; Møller Andersen, Frits; Morthorst, Poul Erik

    2016-01-01

    Applying a partial equilibrium model of the electricity market we analyse effects of exposing household electricity customers to retail products with variable pricing. Both short-term and long-term effects of exposing customers to hourly spot market prices and a simpler rebate scheme are analysed...... under scenarios with large shares of wind power in a Danish case study. Our results indicate strategies that could be favourable in ensuring high adoption of products and efficient response by households. We find that simple pricing schemes, though economically less efficient, could become important...... in an early phase to initialise the development of household demand response. At a later point, when long-term dynamics take effect, a larger effort should be made to shift consumers onto real-time rates, and an increased focus on overall adoption of variable pricing will be required. Another finding...

  19. Demand Response in Smart Grids

    DEFF Research Database (Denmark)

    Hansen, Jacob; Knudsen, Jesper Viese; Annaswamy, Anuradha M.

    2014-01-01

    In recent decades, moves toward higher integration of Renewable Energy Resources have called for fundamental changes in both the planning and operation of the overall power grid. One such change is the incorporation of Demand Response (DR), the process by which consumers can adjust their demand...

  20. Market design for rapid demand response

    DEFF Research Database (Denmark)

    Nielsen, Kurt; Tamirat, Tseganesh Wubale

    We suggest a market design for rapid demand response in electricity markets. The solution consists of remotely controlled switches, meters, forecasting models as well as a flexible auction market to set prices and select endusers job by job. The auction market motivates truth-telling and makes...... it simple to involve the endusers in advance and to activate demand response immediately. The collective solution is analyzed and economic simulations are conducted for the case of Kenya. Kenya has been su ering from unreliable electricity supply for many years and companies and households have learned...... as the Transmission System Operator (TSO) requests demand response and the winning endusers are disconnected immediately if the TSO accepts the result of the auction. The endusers are compensated with a uniform auction price job by job and the Aggregator receives part of the surplus. The simulation captures...

  1. Indications for a changing electricity demand pattern : The temperature dependence of electricity demand in the Netherlands

    NARCIS (Netherlands)

    Hekkenberg, M.; Benders, R. M. J.; Moll, H. C.; Uiterkamp, A. J. M. Schoot

    This study assesses the electricity demand pattern in the relatively temperate climate of the Netherlands (latitude 52 degrees 30'N). Daily electricity demand and average temperature during the period from 1970 until 2007 are investigated for possible trends in the temperature dependence of

  2. Indonesia’s Electricity Demand Dynamic Modelling

    Science.gov (United States)

    Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

    2017-06-01

    Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

  3. Restructuring Electricity Markets when Demand is Uncertain

    DEFF Research Database (Denmark)

    Boom, Anette; Buehler, Stefan

    2006-01-01

    We examine the effects of reorganizing electricity markets on capacity investments, retail prices and welfare when demand is uncertain. We study the following market configurations: (i) integrated monopoly, (ii) integrated duopoly with wholesale trade, and (iii) separated duopoly with wholesale...... are such that the separated (integrated) duopoly with wholesale trade performs best (worst) in terms of welfare.Keywords: Electricity, Investments, Generating Capacities, Vertical Integration, Monopoly and Competition.JEL-Classification: D42, D43, D44, L11, L12, L13...

  4. Households' hourly electricity consumption and peak demand in Denmark

    DEFF Research Database (Denmark)

    Møller Andersen, Frits; Baldini, Mattia; Hansen, Lars Gårn

    2017-01-01

    The electrification of residential energy demand for heating and transportation is expected to increase peak load and require additional generation and transmission capacities. Electrification also provides an opportunity to increase demand response. With a focus on household electricity consumpt......The electrification of residential energy demand for heating and transportation is expected to increase peak load and require additional generation and transmission capacities. Electrification also provides an opportunity to increase demand response. With a focus on household electricity...... consumption, we analyse the contribution of appliances and new services, such as individual heat pumps and electric vehicles, to peak consumption and the need for demand response incentives to reduce the peak.Initially, the paper presents a new model that represents the hourly electricity consumption profile...... to a considerable introduction of electric vehicles and individual heat pumps, household consumption is expected to increase considerably, especially peak hour consumption is expected to increase.Next the paper presents results from a new experiment where household customers are given economic and/or environmental...

  5. Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model

    Energy Technology Data Exchange (ETDEWEB)

    Hummon, Marissa [National Renewable Energy Lab. (NREL), Golden, CO (United States); Palchak, David [National Renewable Energy Lab. (NREL), Golden, CO (United States); Denholm, Paul [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jorgenson, Jennie [National Renewable Energy Lab. (NREL), Golden, CO (United States); Olsen, Daniel J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Matson, Nance [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rose, Cody [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dudley, Junqiao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ma, Ookie [U.S. Dept. of Energy, Washington, DC (United States)

    2013-12-01

    This report is one of a series stemming from the U.S. Department of Energy (DOE) Demand Response and Energy Storage Integration Study. This study is a multi-national-laboratory effort to assess the potential value of demand response (DR) and energy storage to electricity systems with different penetration levels of variable renewable resources and to improve our understanding of associatedmarkets and institutions. This report implements DR resources in the commercial production cost model PLEXOS.

  6. Economic Rebalancing and Electricity Demand in China

    Energy Technology Data Exchange (ETDEWEB)

    He, Gang [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Advanced Light Source (ALS); Stony Brook Univ., NY (United States); Lin, Jiang [Energy Foundation, Beijing (China); Yuan, Alexandria [Energy Foundation, Beijing (China)

    2015-11-01

    Understanding the relationship between economic growth and electricity use is essential for power systems planning. This need is particularly acute now in China, as the Chinese economy is going through a transition to a more consumption and service oriented economy. This study uses 20 years of provincial data on gross domestic product (GDP) and electricity consumption to examine the relationship between these two factors. We observe a plateauing effect of electricity consumption in the richest provinces, as the electricity demand saturates and the economy develops and moves to a more service-based economy. There is a wide range of forecasts for electricity use in 2030, ranging from 5,308 to 8,292 kWh per capita, using different estimating functions, as well as in existing studies. It is therefore critical to examine more carefully the relationship between electricity use and economic development, as China transitions to a new growth phase that is likely to be less energy and resource intensive. The results of this study suggest that policymakers and power system planners in China should seriously re-evaluate power demand projections and the need for new generation capacity to avoid over-investment that could lead to stranded generation assets.

  7. Utility Sector Impacts of Reduced Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Coughlin, Katie

    2014-12-01

    This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

  8. Managing electricity demand through dynamic pricing

    Science.gov (United States)

    Peddie, Robert A.; Bulleit, Douglas A.

    1985-11-01

    As electrical energy cannot be stored in large quantities with current technology, the energy balance of the electricity supply system has to be maintained continually by adjustments in supply to meet an unrestricted customer demand. Electricity over the projected peak tends to be very expensive, so utilities have sought to restrict demand during such periods to improve internal economic efficiency. The techniques used can be shown to be inefficient and disruptive if widely applied. Due to the way the utility and the regulators have homogenized costs, rate structures provide the customer no useful cost message as motivation to economically control utilization. Advances in microelectronics and communications remove these restrictions by allowing the customer to be informed continually of the cost of a kiloWatt hour (kWh) at the time of use. For the first time, the ensuing control of demand by the customer enables efficient utilization and simplifies the dynamic control of the electric system. This paper describes the method of formulating dynamic prices, the main elements and examples of the system, and how it can be introduced. The enumerated benefits show that greater customer satisfaction and improved economic management of the nation's resources and the utility's assets would result.

  9. Voltage Controlled Dynamic Demand Response

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte; Mahat, Pukar

    2013-01-01

    central or dispersed generations might not be sufficient for future scenario. One of the effective methods to cope with this scenario is to enable demand response. This paper proposes a dynamic voltage regulation based demand response technique to be applied in low voltage (LV) distribution feeders....... An adaptive dynamic model has been developed to determine composite voltage dependency of an aggregated load on feeder level. Following the demand dispatch or control signal, optimum voltage setting at the LV substation is determined based on the voltage dependency of the load. Furthermore, a new technique...... has been proposed to estimate the voltage at consumer point of connection (POC) to ensure operation within voltage limits. Finally, the effectiveness of the proposed method is analyzed comprehensively with reference to three different scenarios on a low voltage (LV) feeder (Borup feeder) owned...

  10. Policy analysis of electricity demand flexibility

    DEFF Research Database (Denmark)

    Katz, Jonas

    The large-scale development of variable renewable energy sources, like wind and solar power, increases the demand for flexibility in power systems. At the same time, their electricity production replaces that of conventional power plants – the traditional suppliers of flexibility, and consequently......-term vision of becoming independent of fossil fuels; and second, a commitment to liberalised energy sectors with a notably progressive approach to market-based operations. The crucial question of how it will be possible to balance the Danish electricity system with large amounts of variable renewable...... that is required for the successful transition to a fossil-free energy system....

  11. Meeting residential space heating demand with wind-generated electricity

    Energy Technology Data Exchange (ETDEWEB)

    Hughes, Larry [Electrical and Computer Engineering, Energy Research Group, Dalhousie University, Halifax, Nova Scotia (Canada)

    2010-08-15

    Worldwide, many electricity suppliers are faced with the challenge of trying to integrate intermittent renewables, notably wind, into their energy mix to meet the needs of those services that require a continuous supply of electricity. Solutions to intermittency include the use of rapid-response backup generation and chemical or mechanical storage of electricity. Meanwhile, in many jurisdictions with lengthy heating seasons, finding secure and preferably environmentally benign supplies of energy for space heating is also becoming a significant challenge because of volatile energy markets. Most, if not all, electricity suppliers treat these twin challenges as separate issues: supply (integrating intermittent renewables) and demand (electric space heating). However, if space heating demand can be met from an intermittent supply of electricity, then both of these issues can be addressed simultaneously. One such approach is to use off-the-shelf electric thermal storage systems. This paper examines the potential of this approach by applying the output from a 5.15 MW wind farm to the residential heating demands of detached households in the Canadian province of Prince Edward Island. The paper shows that for the heating season considered, up to 500 households could have over 95 percent of their space heating demand met from the wind farm in question. The benefits as well as the limitations of the approach are discussed in detail. (author)

  12. Demand Response as a System Reliability Resource

    Energy Technology Data Exchange (ETDEWEB)

    Eto, Joseph H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Lewis, Nancy Jo [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Watson, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Auslander, David [Univ. of California, Berkeley, CA (United States); Paprotny, Igor [Univ. of California, Berkeley, CA (United States); Makarov, Yuri [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2012-12-31

    The Demand Response as a System Reliability Resource project consists of six technical tasks: • Task 2.1. Test Plan and Conduct Tests: Contingency Reserves Demand Response (DR) Demonstration—a pioneering demonstration of how existing utility load-management assets can provide an important electricity system reliability resource known as contingency reserve. • Task 2.2. Participation in Electric Power Research Institute (EPRI) IntelliGrid—technical assistance to the EPRI IntelliGrid team in developing use cases and other high-level requirements for the architecture. • Task 2.3. Research, Development, and Demonstration (RD&D) Planning for Demand Response Technology Development—technical support to the Public Interest Energy Research (PIER) Program on five topics: Sub-task 1. PIER Smart Grid RD&D Planning Document; Sub-task 2. System Dynamics of Programmable Controllable Thermostats; Sub-task 3. California Independent System Operator (California ISO) DR Use Cases; Sub-task 4. California ISO Telemetry Requirements; and Sub-task 5. Design of a Building Load Data Storage Platform. • Task 2.4. Time Value of Demand Response—research that will enable California ISO to take better account of the speed of the resources that it deploys to ensure compliance with reliability rules for frequency control. • Task 2.5. System Integration and Market Research: Southern California Edison (SCE)—research and technical support for efforts led by SCE to conduct demand response pilot demonstrations to provide a contingency reserve service (known as non-spinning reserve) through a targeted sub-population of aggregated residential and small commercial customers enrolled in SCE’s traditional air conditioning (AC) load cycling program, the Summer Discount Plan. • Task 2.6. Demonstrate Demand Response Technologies: Pacific Gas and Electric (PG&E)—research and technical support for efforts led by PG&E to conduct a demand response pilot demonstration to provide non

  13. Estimating Reduced Consumption for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Chelmis, Charalampos [Univ. of Southern California, Los Angeles, CA (United States); Aman, Saima [Univ. of Southern California, Los Angeles, CA (United States); Saeed, Muhammad Rizwan [Univ. of Southern California, Los Angeles, CA (United States); Frincu, Marc [Univ. of Southern California, Los Angeles, CA (United States); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

    2015-01-30

    Growing demand is straining our existing electricity generation facilities and requires active participation of the utility and the consumers to achieve energy sustainability. One of the most effective and widely used ways to achieve this goal in the smart grid is demand response (DR), whereby consumers reduce their electricity consumption in response to a request sent from the utility whenever it anticipates a peak in demand. To successfully plan and implement demand response, the utility requires reliable estimate of reduced consumption during DR. This also helps in optimal selection of consumers and curtailment strategies during DR. While much work has been done on predicting normal consumption, reduced consumption prediction is an open problem that is under-studied. In this paper, we introduce and formalize the problem of reduced consumption prediction, and discuss the challenges associated with it. We also describe computational methods that use historical DR data as well as pre-DR conditions to make such predictions. Our experiments are conducted in the real-world setting of a university campus microgrid, and our preliminary results set the foundation for more detailed modeling.

  14. Refrigerated Warehouse Demand Response Strategy Guide

    Energy Technology Data Exchange (ETDEWEB)

    Scott, Doug [VaCom Technologies, San Luis Obispo, CA (United States); Castillo, Rafael [VaCom Technologies, San Luis Obispo, CA (United States); Larson, Kyle [VaCom Technologies, San Luis Obispo, CA (United States); Dobbs, Brian [VaCom Technologies, San Luis Obispo, CA (United States); Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-11-01

    This guide summarizes demand response measures that can be implemented in refrigerated warehouses. In an appendix, it also addresses related energy efficiency opportunities. Reducing overall grid demand during peak periods and energy consumption has benefits for facility operators, grid operators, utility companies, and society. State wide demand response potential for the refrigerated warehouse sector in California is estimated to be over 22.1 Megawatts. Two categories of demand response strategies are described in this guide: load shifting and load shedding. Load shifting can be accomplished via pre-cooling, capacity limiting, and battery charger load management. Load shedding can be achieved by lighting reduction, demand defrost and defrost termination, infiltration reduction, and shutting down miscellaneous equipment. Estimation of the costs and benefits of demand response participation yields simple payback periods of 2-4 years. To improve demand response performance, it’s suggested to install air curtains and another form of infiltration barrier, such as a rollup door, for the passageways. Further modifications to increase efficiency of the refrigeration unit are also analyzed. A larger condenser can maintain the minimum saturated condensing temperature (SCT) for more hours of the day. Lowering the SCT reduces the compressor lift, which results in an overall increase in refrigeration system capacity and energy efficiency. Another way of saving energy in refrigerated warehouses is eliminating the use of under-floor resistance heaters. A more energy efficient alternative to resistance heaters is to utilize the heat that is being rejected from the condenser through a heat exchanger. These energy efficiency measures improve efficiency either by reducing the required electric energy input for the refrigeration system, by helping to curtail the refrigeration load on the system, or by reducing both the load and required energy input.

  15. Progress toward Producing Demand-Response-Ready Appliances

    Energy Technology Data Exchange (ETDEWEB)

    Hammerstrom, Donald J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sastry, Chellury [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2009-12-01

    This report summarizes several historical and ongoing efforts to make small electrical demand-side devices like home appliances more responsive to the dynamic needs of electric power grids. Whereas the utility community often reserves the word demand response for infrequent 2 to 6 hour curtailments that reduce total electrical system peak load, other beneficial responses and ancillary services that may be provided by responsive electrical demand are of interest. Historically, demand responses from the demand side have been obtained by applying external, retrofitted, controlled switches to existing electrical demand. This report is directed instead toward those manufactured products, including appliances, that are able to provide demand responses as soon as they are purchased and that require few, or no, after-market modifications to make them responsive to needs of power grids. Efforts to be summarized include Open Automated Demand Response, the Association of Home Appliance Manufacturer standard CHA 1, a simple interface being developed by the U-SNAP Alliance, various emerging autonomous responses, and the recent PinBus interface that was developed at Pacific Northwest National Laboratory.

  16. An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

    Science.gov (United States)

    Haghnevis, Moeed

    The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

  17. Impacts of Demand-Side Resources on Electric Transmission Planning

    Energy Technology Data Exchange (ETDEWEB)

    Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sanstad, Alan H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-01-01

    Will demand resources such as energy efficiency (EE), demand response (DR), and distributed generation (DG) have an impact on electricity transmission requirements? Five drivers for transmission expansion are discussed: interconnection, reliability, economics, replacement, and policy. With that background, we review the results of a set of transmission studies that were conducted between 2010 and 2013 by electricity regulators, industry representatives, and other stakeholders in the three physical interconnections within the United States. These broad-based studies were funded by the US Department of Energy and included scenarios of reduced load growth due to EE, DR, and DG. While the studies were independent and used different modeling tools and interconnect-specific assumptions, all provided valuable results and insights. However, some caveats exist. Demand resources were evaluated in conjunction with other factors, and limitations on transmission additions between scenarios made understanding the role of demand resources difficult. One study, the western study, included analyses over both 10- and 20-year planning horizons; the 10-year analysis did not show near-term reductions in transmission, but the 20-year indicated fewer transmission additions, yielding a 36percent capital cost reduction. In the eastern study the reductions in demand largely led to reductions in local generation capacity and an increased opportunity for low-cost and renewable generation to export to other regions. The Texas study evaluated generation changes due to demand, and is in the process of examining demand resource impacts on transmission.

  18. Installation and Commissioning Automated Demand Response Systems

    Energy Technology Data Exchange (ETDEWEB)

    Global Energy Partners; Pacific Gas and Electric Company; Kiliccote, Sila; Kiliccote, Sila; Piette, Mary Ann; Wikler, Greg; Prijyanonda, Joe; Chiu, Albert

    2008-04-21

    Demand Response (DR) can be defined as actions taken to reduce electric loads when contingencies, such as emergencies and congestion, occur that threaten supply-demand balance, or market conditions raise supply costs. California utilities have offered price and reliability DR based programs to customers to help reduce electric peak demand. The lack of knowledge about the DR programs and how to develop and implement DR control strategies is a barrier to participation in DR programs, as is the lack of automation of DR systems. Most DR activities are manual and require people to first receive notifications, and then act on the information to execute DR strategies. Levels of automation in DR can be defined as follows. Manual Demand Response involves a labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. The receipt of the external signal initiates pre-programmed demand response strategies. We refer to this as Auto-DR (Piette et. al. 2005). Auto-DR for commercial and industrial facilities can be defined as fully automated DR initiated by a signal from a utility or other appropriate entity and that provides fully-automated connectivity to customer end-use control strategies. One important concept in Auto-DR is that a homeowner or facility manager should be able to 'opt out' or 'override' a DR event if the event comes at time when the reduction in end-use services is not desirable. Therefore, Auto-DR is not handing over total control of the equipment or the facility to the utility but simply allowing the utility to pass on grid related information which then triggers facility

  19. High-resolution temperature fields to evaluate the response of Italian electricity demand to meteorological variables: an example of climate service for the energy sector

    Science.gov (United States)

    Scapin, Simone; Apadula, Francesco; Brunetti, Michele; Maugeri, Maurizio

    2016-08-01

    The dependence of Italian daily electricity demand on cooling degree-days, heating degree-days and solar radiation is investigated by means of a regression model applied to 12 consecutive 2-year intervals in the 1990-2013 period. The cooling and heating degree-days records used in the model are obtained by (i) estimating, by means of a network of 92 synoptic stations and high-resolution gridded temperature climatologies, a daily effective temperature record for all urbanised grid points of a high-resolution grid covering Italy; (ii) using these records to calculate corresponding grid point degree-days records; and (iii) averaging them to get national degree-days records representative of urban areas. The solar radiation record is obtained with the same averaging approach, with grid point solar radiation estimated from the corresponding daily temperature range. The model is based on deterministic components related to the weekly cyclical pattern of demand and to long-term demand changes and on weather-sensitive components related to cooling degree-days, heating degree-days and solar radiation. It establishes a strong contribution of cooling degree-days to the Italian electricity demand, with values peaking in summer months of the latest years up to 211 GWh day-1 (i.e. about 23 % of the corresponding average Italian electricity demand). This contribution shows a strong positive trend in the period considered here: the coefficient of the cooling degree-days term in the regression models increases from the first 2-year period (1990-1991) to the last one (2012-2013) by a factor 3.5, which is much greater than the increase of the Italian total electricity demand.

  20. Interoperability of Demand Response Resources Demonstration in NY

    Energy Technology Data Exchange (ETDEWEB)

    Wellington, Andre

    2014-03-31

    The Interoperability of Demand Response Resources Demonstration in NY (Interoperability Project) was awarded to Con Edison in 2009. The objective of the project was to develop and demonstrate methodologies to enhance the ability of customer sited Demand Response resources to integrate more effectively with electric delivery companies and regional transmission organizations.

  1. Demand Response Resource Quantification with Detailed Building Energy Models

    Energy Technology Data Exchange (ETDEWEB)

    Hale, Elaine; Horsey, Henry; Merket, Noel; Stoll, Brady; Nag, Ambarish

    2017-04-03

    Demand response is a broad suite of technologies that enables changes in electrical load operations in support of power system reliability and efficiency. Although demand response is not a new concept, there is new appetite for comprehensively evaluating its technical potential in the context of renewable energy integration. The complexity of demand response makes this task difficult -- we present new methods for capturing the heterogeneity of potential responses from buildings, their time-varying nature, and metrics such as thermal comfort that help quantify likely acceptability of specific demand response actions. Computed with an automated software framework, the methods are scalable.

  2. Bayesian Analysis of Demand Elasticity in the Italian Electricity Market

    Directory of Open Access Journals (Sweden)

    Maria Chiara D'Errico

    2015-09-01

    Full Text Available The liberalization of the Italian electricity market is a decade old. Within these last ten years, the supply side has been extensively analyzed, but not the demand side. The aim of this paper is to provide a new method for estimation of the demand elasticity, based on Bayesian methods applied to the Italian electricity market. We used individual demand bids data in the day-ahead market in the Italian Power Exchange (IPEX, for 2011, in order to construct an aggregate demand function at the hourly level. We took into account the existence of both elastic and inelastic bidders on the demand side. The empirical results show that elasticity varies significantly during the day and across periods of the year. In addition, the elasticity hourly distribution is clearly skewed and more so in the daily hours. The Bayesian method is a useful tool for policy-making, insofar as the regulator can start with a priori historical information on market behavior and estimate actual market outcomes in response to new policy actions.

  3. Climate, extreme heat, and electricity demand in California

    Energy Technology Data Exchange (ETDEWEB)

    Miller, N.L.; Hayhoe, K.; Jin, J.; Auffhammer, M.

    2008-04-01

    Climate projections from three atmosphere-ocean climate models with a range of low to mid-high temperature sensitivity forced by the Intergovernmental Panel for Climate Change SRES higher, middle, and lower emission scenarios indicate that, over the 21st century, extreme heat events for major cities in heavily air-conditioned California will increase rapidly. These increases in temperature extremes are projected to exceed the rate of increase in mean temperature, along with increased variance. Extreme heat is defined here as the 90 percent exceedance probability (T90) of the local warmest summer days under the current climate. The number of extreme heat days in Los Angeles, where T90 is currently 95 F (32 C), may increase from 12 days to as many as 96 days per year by 2100, implying current-day heat wave conditions may last for the entire summer, with earlier onset. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-2099 tend to be 20-30 percent higher than those projected under the lower B1 emission scenario, ranging from approximately double the historical number of days for inland California cities (e.g. Sacramento and Fresno), up to four times for previously temperate coastal cities (e.g. Los Angeles, San Diego). These findings, combined with observed relationships between high temperature and electricity demand for air-conditioned regions, suggest potential shortfalls in transmission and supply during T90 peak electricity demand periods. When the projected extreme heat and peak demand for electricity are mapped onto current availability, maintaining technology and population constant only for demand side calculations, we find the potential for electricity deficits as high as 17 percent. Similar increases in extreme heat days are suggested for other locations across the U.S. southwest, as well as for developing nations with rapidly increasing electricity demands. Electricity response to recent extreme heat events, such

  4. Does Knowledge Contribute to the Acceptance of Demand Response?

    Directory of Open Access Journals (Sweden)

    Salla Annala

    2014-03-01

    Full Text Available More flexible demand side would benefit the electricity markets, networks and sustainable power generation in many ways. The success of demand response programs, however, relies on consumer acceptance. This paper reviews previous studies about acceptability of different kinds of residential demand response programs. Furthermore, it discusses whether consumers who are more aware of the principles and benefits of demand response have more positive attitudes towards demand response programs. The results of the literature review and two survey studies suggest that price and security of supply are currently bigger motives to change consumption behaviour than environmental issues and that the savings expected to trigger any action (and to lead to lasting change in behaviour may be relatively high. Therefore, the framing of demand response programs goals may affect the acceptance. Additionally, consumers seem to prefer simple price structures that remain constant for a long time to more dynamic options.

  5. Home Network Technologies and Automating Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    McParland, Charles

    2009-12-01

    Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively

  6. Electricity demand forecasting using regression, scenarios and pattern analysis

    CSIR Research Space (South Africa)

    Khuluse, S

    2009-02-01

    Full Text Available The objective of the study is to forecast national electricity demand patterns for a period of twenty years: total annual consumption and understanding seasonal effects. No constraint on the supply of electricity was assumed...

  7. Demand Response With Micro-CHP Systems

    NARCIS (Netherlands)

    Houwing, M.; Negenborn, R.R.; De Schutter, B.

    2011-01-01

    With the increasing application of distributed energy resources and novel information technologies in the electricity infrastructure, innovative possibilities to incorporate the demand side more actively in power system operation are enabled. A promising, controllable, residential distributed

  8. Opportunities for Automated Demand Response in California Agricultural Irrigation

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Aghajanzadeh, Arian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-08-01

    Pumping water for agricultural irrigation represents a significant share of California’s annual electricity use and peak demand. It also represents a large source of potential flexibility, as farms possess a form of storage in their wetted soil. By carefully modifying their irrigation schedules, growers can participate in demand response without adverse effects on their crops. This report describes the potential for participation in demand response and automated demand response by agricultural irrigators in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use in California. Typical on-­farm controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Case studies of demand response programs in California and across the country are reviewed, and their results along with overall California demand estimates are used to estimate statewide demand response potential. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

  9. Opportunities for Automated Demand Response in California Wastewater Treatment Facilities

    Energy Technology Data Exchange (ETDEWEB)

    Aghajanzadeh, Arian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wray, Craig [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-08-30

    Previous research over a period of six years has identified wastewater treatment facilities as good candidates for demand response (DR), automated demand response (Auto-­DR), and Energy Efficiency (EE) measures. This report summarizes that work, including the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy used and demand, as well as details of the wastewater treatment process. It also discusses control systems and automated demand response opportunities. Furthermore, this report summarizes the DR potential of three wastewater treatment facilities. In particular, Lawrence Berkeley National Laboratory (LBNL) has collected data at these facilities from control systems, submetered process equipment, utility electricity demand records, and governmental weather stations. The collected data were then used to generate a summary of wastewater power demand, factors affecting that demand, and demand response capabilities. These case studies show that facilities that have implemented energy efficiency measures and that have centralized control systems are well suited to shed or shift electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. In summary, municipal wastewater treatment energy demand in California is large, and energy-­intensive equipment offers significant potential for automated demand response. In particular, large load reductions were achieved by targeting effluent pumps and centrifuges. One of the limiting factors to implementing demand response is the reaction of effluent turbidity to reduced aeration at an earlier stage of the process. Another limiting factor is that cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities, limit a facility’s potential to participate in other DR activities.

  10. Open Automated Demand Response Communications Specification (Version 1.0)

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Koch, Ed; Hennage, Dan; Palensky, Peter; McParland, Charles

    2009-02-28

    The development of the Open Automated Demand Response Communications Specification, also known as OpenADR or Open Auto-DR, began in 2002 following the California electricity crisis. The work has been carried out by the Demand Response Research Center (DRRC), which is managed by Lawrence Berkeley National Laboratory. This specification describes an open standards-based communications data model designed to facilitate sending and receiving demand response price and reliability signals from a utility or Independent System Operator to electric customers. OpenADR is one element of the Smart Grid information and communications technologies that are being developed to improve optimization between electric supply and demand. The intention of the open automated demand response communications data model is to provide interoperable signals to building and industrial control systems that are preprogrammed to take action based on a demand response signal, enabling a demand response event to be fully automated, with no manual intervention. The OpenADR specification is a flexible infrastructure to facilitate common information exchange between the utility or Independent System Operator and end-use participants. The concept of an open specification is intended to allow anyone to implement the signaling systems, the automation server or the automation clients.

  11. Loads as a Resource: Frequency Responsive Demand

    Energy Technology Data Exchange (ETDEWEB)

    Kalsi, Karanjit [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Tess L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Marinovici, Laurentiu D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lian, Jianming [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-11-30

    Demand-side frequency control can complement traditional generator controls to maintain the stability of large electric systems in the face of rising uncertainty and variability associated with renewable energy resources. This report presents a hierarchical frequency-based load control strategy that uses a supervisor to flexibly adjust control gains that a population of end-use loads respond to in a decentralized manner to help meet the NERC BAL-003-1 frequency response standard at both the area level and interconnection level. The load model is calibrated and used to model populations of frequency-responsive water heaters in a PowerWorld simulation of the U.S. Western Interconnection (WECC). The proposed design is implemented and demonstrated on physical water heaters in a laboratory setting. A significant fraction of the required frequency response in the WECC could be supplied by electric water heaters alone at penetration levels of less than 15%, while contributing to NERC requirements at the interconnection and area levels.

  12. Investigation of structural changes in residential electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Chern, W.S.; Bouis, H.E.

    1982-09-23

    The purpose of this study was to investigate the stability of aggregate national residential electricity demand coefficients over time. The hypothesis is maintained that the aggregate residential demand is the sum of various end-use demand components. Since the end-use composition changes over time, the demand relationship may change as well. Since the end-use composition differs among regions, the results obtained from this study can be used for making inferences about regional differences in electricity demand relationships. There are two additional sources for a possible structural change. One is that consumers may react differently to declining and rising prices, secondly, the impact of the 1973 oil embargo may have shifted demand preferences. The electricity demand model used for this study is presented. A moving regression method was employed to investigate changes in residential electricity demand over time. The statistical results show a strikingly consistent pattern of change for most of the structural variables. The most important finding of this study is that the estimated structure of residential electricity demand changes systematically over time as a result of changes in the characteristics (both durability and saturation level) of the stock of appliances. Furthermore, there is not strong evidence that the structural changes in demand occurred due to either the reversal of the declining trend of electricity prices or the impact of the 1973 oil embarge. (LCL)

  13. Econometric Modeling: An Application to the Demand for Electricity ...

    African Journals Online (AJOL)

    This study investigates the nature of the demand for electricity in Nigeria using recent development in the cointegration theory. The empirical results show an inverse relationship between real appliance purchase price, the real per capita income and the demand for electricity. Also the rate of population growth rate as a ...

  14. Future demand for electricity in the Nassau--Suffolk region

    Energy Technology Data Exchange (ETDEWEB)

    Carroll, T.W.; Palmedo, P.F.; Stern, R.

    1977-12-01

    Brookhaven National Laboratory established a new technology for load forecasting for the Long Island Lighting Company and prepared an independent forecast of the demand for electricity in the LILCO area. The method includes: demand for electricity placed in a total energy perspective so that substitutions between electricity and other fuels can be examined; assessment of the impact of conservation, new technology, gas curtailment, and other factors upon demand for electricity; and construction of the probability distribution of the demand for electricity. A detailed analysis of changing levels of demand for electricity, and other fuels, associated with these new developments is founded upon a disaggregated end-use characterization of energy utilization, including space heat, lighting, process energy, etc., coupled to basic driving forces for future demand, namely: population, housing mix, and economic growth in the region. The range of future events covers conservation, heat pumps, solar systems, storage resistance heaters, electric vehicles, extension of electrified rail, total energy systems, and gas curtailment. Based upon cost and other elements of the competition between technologies, BNL assessed the likelihood of these future developments. An optimistic view toward conservation leads to ''low'' demand for electricity, whereas rapid development of new technologies suggests ''high'' demand. (MCW)

  15. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  16. Demand side management of electric car charging

    DEFF Research Database (Denmark)

    Finn, P.; Fitzpatrick, C.; Connolly, David

    2012-01-01

    Ireland is currently striving to source 10% of the energy required for its transport fleet from renewable energy sources by 2020. As part of the measures being implemented in order to help realise this ambitious target a number of Government schemes have been introduced to financially subsidise...... in terms of distributed energy storage and flexible load. This paper examines how optimising the charging cycles of an electriccar using DSM (DemandSideManagement) based on a number of criteria could be used to achieve financial savings, increased demand on renewable energy, reduce demand on thermal...

  17. Open Automated Demand Response Communications in Demand Response for Wholesale Ancillary Services

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Piette, Mary Ann; Ghatikar, Girish; Koch, Ed; Hennage, Dan; Hernandez, John; Chiu, Albert; Sezgen, Osman; Goodin, John

    2009-11-06

    The Pacific Gas and Electric Company (PG&E) is conducting a pilot program to investigate the technical feasibility of bidding certain demand response (DR) resources into the California Independent System Operator's (CAISO) day-ahead market for ancillary services nonspinning reserve. Three facilities, a retail store, a local government office building, and a bakery, are recruited into the pilot program. For each facility, hourly demand, and load curtailment potential are forecasted two days ahead and submitted to the CAISO the day before the operation as an available resource. These DR resources are optimized against all other generation resources in the CAISO ancillary service. Each facility is equipped with four-second real time telemetry equipment to ensure resource accountability and visibility to CAISO operators. When CAISO requests DR resources, PG&E's OpenADR (Open Automated DR) communications infrastructure is utilized to deliver DR signals to the facilities energy management and control systems (EMCS). The pre-programmed DR strategies are triggered without a human in the loop. This paper describes the automated system architecture and the flow of information to trigger and monitor the performance of the DR events. We outline the DR strategies at each of the participating facilities. At one site a real time electric measurement feedback loop is implemented to assure the delivery of CAISO dispatched demand reductions. Finally, we present results from each of the facilities and discuss findings.

  18. Estimating elasticity for residential electricity demand in China.

    Science.gov (United States)

    Shi, G; Zheng, X; Song, F

    2012-01-01

    Residential demand for electricity is estimated for China using a unique household level dataset. Household electricity demand is specified as a function of local electricity price, household income, and a number of social-economic variables at household level. We find that the residential demand for electricity responds rather sensitively to its own price in China, which implies that there is significant potential to use the price instrument to conserve electricity consumption. Electricity elasticities across different heterogeneous household groups (e.g., rich versus poor and rural versus urban) are also estimated. The results show that the high income group is more price elastic than the low income group, while rural families are more price elastic than urban families. These results have important policy implications for designing an increasing block tariff.

  19. Deregulation of Electricity Market and Drivers of Demand for Electrical Energy in Industry

    OpenAIRE

    Bojnec Štefan; Papler Drago

    2016-01-01

    This paper investigates deregulation of electricity market focusing on electricity prices and drivers of demand for electrical energy in industry in Slovenia. The patterns in evolution of real electricity price developments and the three main components of the electricity price are calculated: liberalized market share for purchased electricity price, regulated infrastructure share for use of electricity network grids and mandatory state charges in the sale of electricity (duty, excise duty an...

  20. Dispatchable Hydrogen Production at the Forecourt for Electricity Demand Shaping

    Directory of Open Access Journals (Sweden)

    Abdulla Rahil

    2017-10-01

    Full Text Available Environmental issues and concerns about depletion of fossil fuels have driven rapid growth in the generation of renewable energy (RE and its use in electricity grids. Similarly, the need for an alternative to hydrocarbon fuels means that the number of fuel cell vehicles is also expected to increase. The ability of electricity networks to balance supply and demand is greatly affected by the variable, intermittent output of RE generators; however, this could be relieved using energy storage and demand-side response (DSR techniques. One option would be production of hydrogen by electrolysis powered from wind and solar sources. The use of tariff structures would provide an incentive to operate electrolysers as dispatchable loads. The aim of this paper is to compare the cost of hydrogen production by electrolysis at garage forecourts in Libya, for both dispatchable and continuous operation, without interruption of fuel supply to vehicles. The coastal city of Derna was chosen as a case study, with the renewable energy being produced via a wind turbine farm. Wind speed was analysed in order to determine a suitable turbine, then the capacity was calculated to estimate how many turbines would be needed to meet demand. Finally, the excess power was calculated, based on the discrepancy between supply and demand. The study looked at a hydrogen refueling station in both dispatchable and continuous operation, using an optimisation algorithm. The following three scenarios were considered to determine whether the cost of electrolytic hydrogen could be reduced by a lower off-peak electricity price. These scenarios are: Standard Continuous, in which the electrolyser operates continuously on a standard tariff of 12 p/kWh; Off-peak Only, in which the electrolyser operates only during off-peak periods at the lower price of 5 p/kWh; and 2-Tier Continuous, in which the electrolyser operates continuously on a low tariff at off-peak times and a high tariff at other

  1. Meteorology and electric power demand; Variabili meteorologici e fabbisogno elettrico

    Energy Technology Data Exchange (ETDEWEB)

    Bonelli, P. [CESI Rubattino, Milan (Italy); Starita, S. [Associazione Ingegneri per l' Ambiente e il Territorio, Partecipazione a iniziative di terzi, Milan (Italy)

    2001-06-01

    A predictable correlation between electric power demand and meteorology variation is analyzed. [Italian] Esiste una correlazione prevedibile tra l'anadamento del fabbisogno elettrico e le variabili meteorologiche.

  2. Dynamics of Electricity Demand in Lesotho: A Kalman Filter Approach

    Directory of Open Access Journals (Sweden)

    Thamae Retselisitsoe Isaiah

    2015-04-01

    Full Text Available This study provides an empirical analysis of the time-varying price and income elasticities of electricity demand in Lesotho for the period 1995-2012 using the Kalman filter approach. The results reveal that economic growth has been one of the main drivers of electricity consumption in Lesotho while electricity prices are found to play a less significant role since they are monopoly-driven and relatively low when compared to international standards. These findings imply that increases in electricity prices in Lesotho might not have a significant impact on consumption in the short-run. However, if the real electricity prices become too high over time, consumers might change their behavior and sensitivity to price and hence, energy policymakers will need to reconsider their impact in the long-run. Furthermore, several exogenous shocks seem to have affected the sensitivity of electricity demand during the period prior to regulation, which made individuals, businesses and agencies to be more sensitive to electricity costs. On the other hand, the period after regulation has been characterized by more stable and declining sensitivity of electricity demand. Therefore, factors such as regulation and changes in the country’s economic activities appear to have affected both price and income elasticities of electricity demand in Lesotho.

  3. Simulation of annual electric lighting demand using various occupancy profiles

    DEFF Research Database (Denmark)

    Iversen, Anne; Andersen, Philip Hvidthøft Delff; Svendsen, Svend

    2013-01-01

    This paper describes an investigation of the effect on electric lighting demand of applying occupancy models of various resolution to climate-based daylight modelling. The lighting demand was evaluated for a building zone with the occupant always present, with occupancy corresponding to absence f...

  4. Turkey opens electricity markets as demand grows

    Energy Technology Data Exchange (ETDEWEB)

    McKeigue, J.; Da Cunha, A.; Severino, D. [Global Business Reports (United States)

    2009-06-15

    Turkey's growing power market has attracted investors and project developers for over a decade, yet their plans have been dashed by unexpected political or financial crises or, worse, obstructed by a lengthy bureaucratic approval process. Now, with a more transparent retail electricity market, government regulators and investors are bullish on Turkey. Is Turkey ready to turn the power on? This report closely examine Turkey's plans to create a power infrastructure capable of providing the reliable electricity supplies necessary for sustained economic growth. It was compiled with on-the-ground research and extensive interview with key industrial and political figures. Today, hard coal and lignite account for 21% of Turkey's electricity generation and gas-fired plants account for 50%. The Alfin Elbistan-B lignite-fired plant has attracted criticism for its lack of desulfurization units and ash dam facilities that have tarnished the industry's image. A 1,100 MW hard-coal fired plant using supercritical technology is under construction. 9 figs., 1 tab.

  5. Research on electricity market operation mechanism and its benefit of demand side participation

    Science.gov (United States)

    Han, Shuai; Yan, Xu; Qin, Li-juan; Lin, Xi-qiao; Zeng, Bo

    2017-08-01

    Demand response plays an important role in maintaining the economic stability of the system, and has the characteristics of high efficiency, low cost, fast response, good environmental benefits and so on. Demand side resource is an important part of electricity market. The research of demand side resources in our country is still in the initial stage, but the opening of the electricity sales side provides a broad prospect for the development of electricity market. This paper summarizes the main types of demand side resources in our country, analyzes the economic principle of demand response from the micro perspective, puts forward some suggestions on the operation mechanism of China’s demand side resources participating in the electricity market under the condition of electricity sales side opening, analyzes the current situation of pricing in the electricity wholesale market and sets up the pricing strategy of the centralized wholesale market with the demand side power supply participating in quotation, which makes the social and economic benefits reach the maximum.

  6. Load Reduction, Demand Response and Energy Efficient Technologies and Strategies

    Energy Technology Data Exchange (ETDEWEB)

    Boyd, Paul A.; Parker, Graham B.; Hatley, Darrel D.

    2008-11-19

    The Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) was tasked by the DOE Office of Electricity (OE) to recommend load reduction and grid integration strategies, and identify additional demand response (energy efficiency/conservation opportunities) and strategies at the Forest City Housing (FCH) redevelopment at Pearl Harbor and the Marine Corps Base Hawaii (MCBH) at Kaneohe Bay. The goal was to provide FCH staff a path forward to manage their electricity load and thus reduce costs at these FCH family housing developments. The initial focus of the work was at the MCBH given the MCBH has a demand-ratchet tariff, relatively high demand (~18 MW) and a commensurate high blended electricity rate (26 cents/kWh). The peak demand for MCBH occurs in July-August. And, on average, family housing at MCBH contributes ~36% to the MCBH total energy consumption. Thus, a significant load reduction in family housing can have a considerable impact on the overall site load. Based on a site visit to the MCBH and meetings with MCBH installation, FCH, and Hawaiian Electric Company (HECO) staff, recommended actions (including a "smart grid" recommendation) that can be undertaken by FCH to manage and reduce peak-demand in family housing are made. Recommendations are also made to reduce overall energy consumption, and thus reduce demand in FCH family housing.

  7. Demand Response and Energy Storage Integration Study

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Ookie; Cheung, Kerry; Olsen, Daniel J.; Matson, Nance; Sohn, Michael D.; Rose, Cody M.; Dudley, Junqiao Han; Goli, Sasank; Kiliccote, Sila; Cappers, Peter; MacDonald, Jason; Denholm, Paul; Hummon, Marissa; Jorgenson, Jennie; Palchak, David; Starke, Michael; Alkadi, Nasr; Bhatnagar, Dhruv; Currier, Aileen; Hernandez, Jaci; Kirby, Brendan; O' Malley, Mark

    2016-03-01

    Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable integration studies have evaluated many of the challenges associated with deploying large amounts of variable wind and solar generation technologies, integration analyses have not yet fully incorporated demand response and energy storage resources. This report represents an initial effort in analyzing the potential integration value of demand response and energy storage, focusing on the western United States. It evaluates two major aspects of increased deployment of demand response and energy storage: (1) Their operational value in providing bulk power system services and (2) Market and regulatory issues, including potential barriers to deployment.

  8. Demand Response at the Naval Postgraduate School

    National Research Council Canada - National Science Library

    Stouffer, Dean; Wilson, Daryl

    2008-01-01

    The purpose of this MBA project is to assist the Naval Postgraduate School's Public Works department to assimilate into a Demand Response program that will not only benefit the school but also the community...

  9. A novel incentive-based retail demand response program for collaborative participation of small customers

    NARCIS (Netherlands)

    Zehir, M. A.; Wevers, M. H.; Batman, A.; Bagriyanik, M.; Hurink, J. L.; Kucuk, U.; Soares, F. J.; Ozdemir, A.

    2017-01-01

    Integration of aggregated demand response into the wholesale electricity market is an emerging field of research. Contrary to conventional service providers, most of the demand side participants act voluntarily. However, due to wholesale market regulations, reliable and effective participation of

  10. Review of barriers to the introduction of residential demand response : A case study in the Netherlands

    NARCIS (Netherlands)

    Weck, M. H J; van Hooff, J.; van Sark, W. G J H M

    Demand response, defined as the shifting of electricity demand, is generally believed to have value both for the grid and for the market: by matching demand more closely to supply, consumers could profit from lower prices, while in a smart grid environment, more renewable electricity can be used and

  11. Estimation of Iranian price elasticities of residential electricity demand

    Directory of Open Access Journals (Sweden)

    Yeganeh Mousavi Jahromi

    2014-06-01

    Full Text Available This paper presents a study to determine demand for electricity in city of Yazd, Iran over the period of 1998-2008. Using vector error correction model (VECM based on seasonal information, the study determines that electricity has no elasticity in short term in household expenditure. Therefore, government policy on increasing price of electricity will not influence demand. However, electricity maintains elasticity over the long-term period and an increase on price of electricity could motivate consumers to reduce their consumption by purchasing energy efficient facilities. Therefore, any governmental strategy to increase price may have positive impact on economy. The study also detects a positive and meaningful relationship between temperature and electricity consumption.

  12. US electric utility demand-side management, 1994

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-26

    The report presents comprehensive information on electric power industry demand-side management (DSM) activities in US at the national, regional, and utility levels. Objective is provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it relates to the US electric power industry. The first chapter, ``Profile: US Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions, and costs attributable to DSM.

  13. An Empirical Analysis of Electricity Demand in Pakistan

    Directory of Open Access Journals (Sweden)

    Noel Alter

    2011-01-01

    Full Text Available Study utilizes cointegration and vector error correction analysis to determination the long and short run dynamics between electricity demand and its determinants. Study uses time series data for Pakistan from 1970 to 2010. Johansen cointegration test indicate that variables integrate in the long run. Error correction term reflects the convergence of variables towards equilibrium. Electricity acts as a necessity in short run and luxury in long run. Study concludes that effective price and income policies, group pricing policy and peak-load pricing policy should be exercised for electricity demand management.

  14. Potential demand and cost-benefit analysis of electric cars

    OpenAIRE

    Zito, Pietro; Salerno, Silvia

    2004-01-01

    In this study an analysis of electric family car performances is carried out. In particular, the aim of this research is to appraise the possibility of introducing electric cars in urban mobility and the evaluation of its economic feasibility. First of all, we determined the potential electric car demand, which was forecasted using a stated preference (SP) analysis. The survey was carried out at the University of Palermo considering a particular target of consumer: ‘the hybrid household’. A l...

  15. U.S. electric utility demand-side management 1996

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-01

    The US Electric Utility Demand-Side Management report presents comprehensive information on electric power industry demand-side management (DSM) activities in the US at the national, regional, and utility levels. The objective of the publication is to provide industry decision makers, government policy makers, analysts, and the general public with historical data that may be used in understanding DSM as it related to the US electric power industry. The first chapter, ``Profile: U.S. Electric Utility Demand-Side Management,`` presents a general discussion of DSM, its history, current issues, and a review of key statistics for the year. Subsequent chapters present discussions and more detailed data on energy savings, peak load reductions and costs attributable to DSM. 9 figs., 24 tabs.

  16. Modeling and Forecasting Electricity Demand in Azerbaijan Using Cointegration Techniques

    Directory of Open Access Journals (Sweden)

    Fakhri J. Hasanov

    2016-12-01

    Full Text Available Policymakers in developing and transitional economies require sound models to: (i understand the drivers of rapidly growing energy consumption and (ii produce forecasts of future energy demand. This paper attempts to model electricity demand in Azerbaijan and provide future forecast scenarios—as far as we are aware this is the first such attempt for Azerbaijan using a comprehensive modelling framework. Electricity consumption increased and decreased considerably in Azerbaijan from 1995 to 2013 (the period used for the empirical analysis—it increased on average by about 4% per annum from 1995 to 2006 but decreased by about 4½% per annum from 2006 to 2010 and increased thereafter. It is therefore vital that Azerbaijani planners and policymakers understand what drives electricity demand and be able to forecast how it will grow in order to plan for future power production. However, modeling electricity demand for such a country has many challenges. Azerbaijan is rich in energy resources, consequently GDP is heavily influenced by oil prices; hence, real non-oil GDP is employed as the activity driver in this research (unlike almost all previous aggregate energy demand studies. Moreover, electricity prices are administered rather than market driven. Therefore, different cointegration and error correction techniques are employed to estimate a number of per capita electricity demand models for Azerbaijan, which are used to produce forecast scenarios for up to 2025. The resulting estimated models (in terms of coefficients, etc. and forecasts of electricity demand for Azerbaijan in 2025 prove to be very similar; with the Business as Usual forecast ranging from about of 19½ to 21 TWh.

  17. Open Automated Demand Response for Small Commerical Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2009-05-01

    This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

  18. Reducing Electricity Demand Peaks by Scheduling Home Appliances Usage

    DEFF Research Database (Denmark)

    Rossello Busquet, Ana; Kardaras, Georgios; Iversen, Villy Bæk

    2011-01-01

    Nowadays there is a tendency to consume electricity during the same period of the day leading to demand peaks. Regular energy consumption habits lead to demand peaks at specific temporal intervals, because users consume power at the same time. In order to avoid demand peaks, users’ appliances...... should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power...... consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions...

  19. Demand response scheme based on lottery-like rebates

    KAUST Repository

    Schwartz, Galina A.

    2014-08-24

    In this paper, we develop a novel mechanism for reducing volatility of residential demand for electricity. We construct a reward-based (rebate) mechanism that provides consumers with incentives to shift their demand to off-peak time. In contrast to most other mechanisms proposed in the literature, the key feature of our mechanism is its modest requirements on user preferences, i.e., it does not require exact knowledge of user responsiveness to rewards for shifting their demand from the peak to the off-peak time. Specifically, our mechanism utilizes a probabilistic reward structure for users who shift their demand to the off-peak time, and is robust to incomplete information about user demand and/or risk preferences. We approach the problem from the public good perspective, and demonstrate that the mechanism can be implemented via lottery-like schemes. Our mechanism permits to reduce the distribution losses, and thus improve efficiency of electricity distribution. Finally, the mechanism can be readily incorporated into the emerging demand response schemes (e.g., the time-of-day pricing, and critical peak pricing schemes), and has security and privacy-preserving properties.

  20. Wireless Demand Response Controls for HVAC Systems

    Energy Technology Data Exchange (ETDEWEB)

    Federspiel, Clifford

    2009-06-30

    The objectives of this scoping study were to develop and test control software and wireless hardware that could enable closed-loop, zone-temperature-based demand response in buildings that have either pneumatic controls or legacy digital controls that cannot be used as part of a demand response automation system. We designed a SOAP client that is compatible with the Demand Response Automation Server (DRAS) being used by the IOUs in California for their CPP program, design the DR control software, investigated the use of cellular routers for connecting to the DRAS, and tested the wireless DR system with an emulator running a calibrated model of a working building. The results show that the wireless DR system can shed approximately 1.5 Watts per design CFM on the design day in a hot, inland climate in California while keeping temperatures within the limits of ASHRAE Standard 55: Thermal Environmental Conditions for Human Occupancy.

  1. Drivers for the Value of Demand Response under Increased Levels of Wind and Solar Power; NREL (National Renewable Energy Laboratory)

    Energy Technology Data Exchange (ETDEWEB)

    Hale, Elaine

    2015-07-30

    Demand response may be a valuable flexible resource for low-carbon electric power grids. However, there are as many types of possible demand response as there are ways to use electricity, making demand response difficult to study at scale in realistic settings. This talk reviews our state of knowledge regarding the potential value of demand response in several example systems as a function of increasing levels of wind and solar power, sometimes drawing on the analogy between demand response and storage. Overall, we find demand response to be promising, but its potential value is very system dependent. Furthermore, demand response, like storage, can easily saturate ancillary service markets.

  2. The role of building technologies in reducing and controlling peak electricity demand

    Energy Technology Data Exchange (ETDEWEB)

    Koomey, Jonathan; Brown, Richard E.

    2002-09-01

    Peak power demand issues have come to the fore recently because of the California electricity crisis. Uncertainties surrounding the reliability of electric power systems in restructured markets as well as security worries are the latest reasons for such concerns, but the issues surrounding peak demand are as old as the electric utility system itself. The long lead times associated with building new capacity, the lack of price response in the face of time-varying costs, the large difference between peak demand and average demand, and the necessity for real-time delivery of electricity all make the connection between system peak demand and system reliability an important driver of public policy in the electric utility sector. This exploratory option paper was written at the request of Jerry Dion at the U.S.Department of Energy (DOE). It is one of several white papers commissioned in 2002 exploring key issues of relevance to DOE. This paper explores policy-relevant issues surrounding peak demand, to help guide DOE's research efforts in this area. The findings of this paper are as follows. In the short run, DOE funding of deployment activities on peak demand can help society achieve a more economically efficient balance between investments in supply and demand-side technologies. DOE policies can promote implementation of key technologies to ameliorate peak demand, through government purchasing, technology demonstrations, and improvements in test procedures, efficiency standards, and labeling programs. In the long run, R&D is probably the most important single leverage point for DOE to influence the peak demand issue. Technologies for time-varying price response hold great potential for radically altering the way people use electricity in buildings, but are decades away from widespread use, so DOE R&D and expertise can make a real difference here.

  3. The Residential Demand for Electricity in South Korea

    OpenAIRE

    Tingwen Liu

    2015-01-01

    We study the residential sector electricity demand in South Korea based on aggregate monthly time series data from 2003 to 2013. We show that, on aggregate, households respond to the previous month average electricity price by encompassing tests, which can be explained by the households' cognitive cost of obtaining the price information for current billing cycle as Ito (2014) implied. Methodology: Based on a linear double-logarithmic specification, the estimated price and income elasticities ...

  4. Opportunities for Automated Demand Response in California’s Dairy Processing Industry

    Energy Technology Data Exchange (ETDEWEB)

    Homan, Gregory K. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Aghajanzadeh, Arian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-08-30

    During periods of peak electrical demand on the energy grid or when there is a shortage of supply, the stability of the grid may be compromised or the cost of supplying electricity may rise dramatically, respectively. Demand response programs are designed to mitigate the severity of these problems and improve reliability by reducing the demand on the grid during such critical times. In 2010, the Demand Response Research Center convened a group of industry experts to suggest potential industries that would be good demand response program candidates for further review. The dairy industry was suggested due to the perception that the industry had suitable flexibility and automatic controls in place. The purpose of this report is to provide an initial description of the industry with regard to demand response potential, specifically automated demand response. This report qualitatively describes the potential for participation in demand response and automated demand response by dairy processing facilities in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use. Typical process equipment and controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Two case studies of demand response at dairy facilities in California and across the country are reviewed. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

  5. Providing Reliability Services through Demand Response: A Prelimnary Evaluation of the Demand Response Capabilities of Alcoa Inc.

    Energy Technology Data Exchange (ETDEWEB)

    Starke, Michael R [ORNL; Kirby, Brendan J [ORNL; Kueck, John D [ORNL; Todd, Duane [Alcoa; Caulfield, Michael [Alcoa; Helms, Brian [Alcoa

    2009-02-01

    Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower green house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter

  6. Scheduling Optimization of Smart Homes Based on Demand Response

    OpenAIRE

    Zhu, Jiawei; Lauri, Fabrice; Koukam, Abderrafiaa; Hilaire, Vincent

    2015-01-01

    Part 4: Smart Environments, Agents, and Robots; International audience; Demand response can potentially lead to economic and environmental advantages, but non-coordinated scheduling and operation of controllable devices in a set of smart homes will make peak rebounds at periods with lower electricity prices happen, which may damage the power grid, cause unforeseen disasters, and reduce the global profit. In this work, we advocate the use of a metaheuristic algorithm based on Cooperative Parti...

  7. Taxonomy for Modeling Demand Response Resources

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel; Kiliccote, Sila; Sohn, Michael; Dunn, Laura; Piette, Mary, A

    2014-08-01

    Demand response resources are an important component of modern grid management strategies. Accurate characterizations of DR resources are needed to develop systems of optimally managed grid operations and to plan future investments in generation, transmission, and distribution. The DOE Demand Response and Energy Storage Integration Study (DRESIS) project researched the degree to which demand response (DR) and energy storage can provide grid flexibility and stability in the Western Interconnection. In this work, DR resources were integrated with traditional generators in grid forecasting tools, specifically a production cost model of the Western Interconnection. As part of this study, LBNL developed a modeling framework for characterizing resource availability and response attributes of DR resources consistent with the governing architecture of the simulation modeling platform. In this report, we identify and describe the following response attributes required to accurately characterize DR resources: allowable response frequency, maximum response duration, minimum time needed to achieve load changes, necessary pre- or re-charging of integrated energy storage, costs of enablement, magnitude of controlled resources, and alignment of availability. We describe a framework for modeling these response attributes, and apply this framework to characterize 13 DR resources including residential, commercial, and industrial end-uses. We group these end-uses into three broad categories based on their response capabilities, and define a taxonomy for classifying DR resources within these categories. The three categories of resources exhibit different capabilities and differ in value to the grid. Results from the production cost model of the Western Interconnection illustrate that minor differences in resource attributes can have significant impact on grid utilization of DR resources. The implications of these findings will be explored in future DR valuation studies.

  8. Unlocking the potential for efficiency and demand response throughadvanced metering

    Energy Technology Data Exchange (ETDEWEB)

    Levy, Roger; Herter, Karen; Wilson, John

    2004-06-30

    Reliance on the standard cumulative kilowatt-hour meter substantially compromises energy efficiency and demand response programs. Without advanced metering, utilities cannot support time-differentiated rates or collect the detailed customer usage information necessary to (1)educate the customer to the economic value of efficiency and demand response options, or (2) distribute load management incentives proportional to customer contribution. These deficiencies prevent the customer feedback mechanisms that would otherwise encourage economically sound demand-side investments and behaviors. Thus, the inability to collect or properly price electricity usage handicaps the success of almost all efficiency and demand response options. Historically, implementation of the advanced metering infrastructure (AMI) necessary for the successful efficiency and demand response programs has been prevented by inadequate cost-benefit analyses. A recent California effort has produced an expanded cost-effectiveness methodology for AMI that introduces previously excluded benefits. In addition to utility-centric costs and benefits, the new model includes qualitative and quantitative costs and benefits that accrue to both customers and society.

  9. Deregulation of Electricity Market and Drivers of Demand for Electrical Energy in Industry

    Directory of Open Access Journals (Sweden)

    Bojnec Štefan

    2016-09-01

    Full Text Available This paper investigates deregulation of electricity market focusing on electricity prices and drivers of demand for electrical energy in industry in Slovenia. The patterns in evolution of real electricity price developments and the three main components of the electricity price are calculated: liberalized market share for purchased electricity price, regulated infrastructure share for use of electricity network grids and mandatory state charges in the sale of electricity (duty, excise duty and value-added tax. To calculate the real value of electricity prices, producer price index of industrial commodities for electricity prices in industry is used as deflator and implicit deflator of gross domestic product for the size of the economy. In the empirical econometric part is used regression analysis for the amount electricity consumption in the industry depending on the real gross domestic product, direct and cross-price elasticity for natural gas prices in the industry. The results confirmed volatility in real electricity price developments with their increasing tendency and the increasing share of different taxes and state charges in the electricity prices for industry. Demand for electrical energy in industry is positively associated with gross domestic product and price of natural gas as substitute for electrical energy in industry use, and negatively associated with prices of electrical energy for industry.

  10. Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach

    Directory of Open Access Journals (Sweden)

    Jeyhun I. Mikayilov

    2017-11-01

    Full Text Available Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan.

  11. Two-Stage Electricity Demand Modeling Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Krzysztof Gajowniczek

    2017-10-01

    Full Text Available Forecasting of electricity demand has become one of the most important areas of research in the electric power industry, as it is a critical component of cost-efficient power system management and planning. In this context, accurate and robust load forecasting is supposed to play a key role in reducing generation costs, and deals with the reliability of the power system. However, due to demand peaks in the power system, forecasts are inaccurate and prone to high numbers of errors. In this paper, our contributions comprise a proposed data-mining scheme for demand modeling through peak detection, as well as the use of this information to feed the forecasting system. For this purpose, we have taken a different approach from that of time series forecasting, representing it as a two-stage pattern recognition problem. We have developed a peak classification model followed by a forecasting model to estimate an aggregated demand volume. We have utilized a set of machine learning algorithms to benefit from both accurate detection of the peaks and precise forecasts, as applied to the Polish power system. The key finding is that the algorithms can detect 96.3% of electricity peaks (load value equal to or above the 99th percentile of the load distribution and deliver accurate forecasts, with mean absolute percentage error (MAPE of 3.10% and resistant mean absolute percentage error (r-MAPE of 2.70% for the 24 h forecasting horizon.

  12. Estimating Demand Response Market Potential Among Large Commercialand Industrial Customers:A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Cappers, Peter

    2007-01-01

    Demand response is increasingly recognized as an essentialingredient to well functioning electricity markets. This growingconsensus was formalized in the Energy Policy Act of 2005 (EPACT), whichestablished demand response as an official policy of the U.S. government,and directed states (and their electric utilities) to considerimplementing demand response, with a particular focus on "price-based"mechanisms. The resulting deliberations, along with a variety of stateand regional demand response initiatives, are raising important policyquestions: for example, How much demand response is enough? How much isavailable? From what sources? At what cost? The purpose of this scopingstudy is to examine analytical techniques and data sources to supportdemand response market assessments that can, in turn, answer the secondand third of these questions. We focus on demand response for large(>350 kW), commercial and industrial (C&I) customers, althoughmany of the concepts could equally be applied to similar programs andtariffs for small commercial and residential customers.

  13. Electricity demand for Sri Lanka: A time series analysis

    Energy Technology Data Exchange (ETDEWEB)

    Amarawickrama, Himanshu A. [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom); Infrastructure Advisory, Ernst and Young LLP, 1 More London Place, London SE1 2AF (United Kingdom); Hunt, Lester C. [Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

    2008-05-15

    This study estimates electricity demand functions for Sri Lanka using six econometric techniques. It shows that the preferred specifications differ somewhat and there is a wide range in the long-run price and income elasticities with the estimated long-run income elasticity ranging from 1.0 to 2.0 and the long-run price elasticity from 0 to -0.06. There is also a wide range of estimates of the speed with which consumers would adjust to any disequilibrium, although the estimated impact income elasticities tended to be more in agreement ranging from 1.8 to 2.0. Furthermore, the estimated effect of the underlying energy demand trend varies between the different techniques; ranging from being positive to zero to predominantly negative. Despite these differences, the forecasts generated from the six models up until 2025 do not differ significantly. It is therefore encouraging that the Sri Lanka electricity authorities can have some faith in econometrically estimated models used for forecasting. Nonetheless, by the end of the forecast period in 2025 there is a variation of around 452 MW in the base forecast peak demand that, in relative terms for a small electricity generation system like Sri Lanka's, represents a considerable difference. (author)

  14. Household Characteristics That Influence Simple Household Demand on Electricity

    Directory of Open Access Journals (Sweden)

    Tongam Sihol Nababan

    2015-08-01

    Full Text Available This research aims to analyze the characteristics of households that affect the electric energy consumption of simple households. The second objective is to analyze the probability of each of the factors affecting the electricity energy consumption of small household. The research was conducted in Medan City in the period of March 2014 to November 2014 with samples of 143 small households, the customer of PT. PLN (Persero Medan, which use the power of electricity for TR-1 /450VA. Data were analyzed by using the logistic regression model. The estimation results indicated that (1 the higher the willingnes to pay (WTP of households, the higher the tendency to consume elec trical energy per month. (2 the closer the households residence to the city center, the higher the tendency to consume electrical energy than of the households residence in the suburbs, (3 increasingly unfavourable response to electrical quality, the higher the opportunity to consume a greater electric power monthly.

  15. Laboratory Testing of Demand-Response Enabled Household Appliances

    Energy Technology Data Exchange (ETDEWEB)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  16. Laboratory Testing of Demand-Response Enabled Household Appliances

    Energy Technology Data Exchange (ETDEWEB)

    Sparn, B. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jin, X. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Earle, L. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses. The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  17. Northwest Open Automated Demand Response Technology Demonstration Project

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Piette, Mary Ann; Dudley, Junqiao

    2010-03-17

    The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibility of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also

  18. Aligning PEV Charging Times with Electricity Supply and Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, Cabell [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-06-05

    Plug-in electric vehicles (PEVs) are a growing source of electricity consumption that could either exacerbate supply shortages or smooth electricity demand curves. Extensive research has explored how vehicle-grid integration (VGI) can be optimized by controlling PEV charging timing or providing vehicle-to-grid (V2G) services, such as storing energy in vehicle batteries and returning it to the grid at peak times. While much of this research has modeled charging, implementation in the real world requires a cost-effective solution that accounts for consumer behavior. To function across different contexts, several types of charging administrators and methods of control are necessary to minimize costs in the VGI context.

  19. The design of optimal electric power demand management contracts

    Science.gov (United States)

    Fahrioglu, Murat

    1999-11-01

    Our society derives a quantifiable benefit from electric power. In particular, forced outages or blackouts have enormous consequences on society, one of which is loss of economic surplus. Electric utilities try to provide reliable supply of electric power to their customers. Maximum customer benefit derives from minimum cost and sufficient supply availability. Customers willing to share in "availability risk" can derive further benefit by participating in controlled outage programs. Specifically, whenever utilities foresee dangerous loading patterns, there is a need for a rapid reduction in demand either system-wide or at specific locations. The utility needs to get relief in order to solve its problems quickly and efficiently. This relief can come from customers who agree to curtail their loads upon request in exchange for an incentive fee. This thesis shows how utilities can get efficient load relief while maximizing their economic benefit. This work also shows how estimated customer cost functions can be calibrated, using existing utility data, to help in designing efficient demand management contracts. In order to design such contracts, optimal mechanism design is adopted from "Game Theory" and applied to the interaction between a utility and its customers. The idea behind mechanism design is to design an incentive structure that encourages customers to sign up for the right contract and reveal their true value of power. If a utility has demand management contracts with customers at critical locations, most operational problems can be solved efficiently. This thesis illustrates how locational attributes of customers incorporated into demand management contract design can have a significant impact in solving system problems. This kind of demand management contracts can also be used by an Independent System Operator (ISO). During times of congestion a loss of economic surplus occurs. When the market is too slow or cannot help relieve congestion, demand management

  20. A Generalized Formulation of Demand Response under Market Environments

    Science.gov (United States)

    Nguyen, Minh Y.; Nguyen, Duc M.

    2015-06-01

    This paper presents a generalized formulation of Demand Response (DR) under deregulated electricity markets. The problem is scheduling and controls the consumption of electrical loads according to the market price to minimize the energy cost over a day. Taking into account the modeling of customers' comfort (i.e., preference), the formulation can be applied to various types of loads including what was traditionally classified as critical loads (e.g., air conditioning, lights). The proposed DR scheme is based on Dynamic Programming (DP) framework and solved by DP backward algorithm in which the stochastic optimization is used to treat the uncertainty, if any occurred in the problem. The proposed formulation is examined with the DR problem of different loads, including Heat Ventilation and Air Conditioning (HVAC), Electric Vehicles (EVs) and a newly DR on the water supply systems of commercial buildings. The result of simulation shows significant saving can be achieved in comparison with their traditional (On/Off) scheme.

  1. Electricity demand and storage dispatch modeling for buildings and implications for the smartgrid

    Science.gov (United States)

    Zheng, Menglian; Meinrenken, Christoph

    2013-04-01

    As an enabler for demand response (DR), electricity storage in buildings has the potential to lower costs and carbon footprint of grid electricity while simultaneously mitigating grid strain and increasing its flexibility to integrate renewables (central or distributed). We present a stochastic model to simulate minute-by-minute electricity demand of buildings and analyze the resulting electricity costs under actual, currently available DR-enabling tariffs in New York State, namely a peak/offpeak tariff charging by consumed energy (monthly total kWh) and a time of use tariff charging by power demand (monthly peak kW). We then introduce a variety of electrical storage options (from flow batteries to flywheels) and determine how DR via temporary storage may increase the overall net present value (NPV) for consumers (comparing the reduced cost of electricity to capital and maintenance costs of the storage). We find that, under the total-energy tariff, only medium-term storage options such as batteries offer positive NPV, and only at the low end of storage costs (optimistic scenario). Under the peak-demand tariff, however, even short-term storage such as flywheels and superconducting magnetic energy offer positive NPV. Therefore, these offer significant economic incentive to enable DR without affecting the consumption habits of buildings' residents. We discuss implications for smartgrid communication and our future work on real-time price tariffs.

  2. Demand Response Availability Profiles for California in the Year 2020

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-11-01

    Demand response (DR) is being considered as a valuable resource for keeping the electrical grid stable and efficient, and deferring upgrades to generation, transmission, and distribution systems. However, simulations to determine how much infrastructure upgrades can be deferred are necessary in order to plan optimally. Production cost modeling is a technique, which simulates the dispatch of generators to meet demand and reserves in each hour of the year, at minimal cost. By integrating demand response resources into a production cost model (PCM), their value to the grid can be estimated and used to inform operations and infrastructure planning. DR availability profiles and constraints for 13 end-uses in California for the year 2020 were developed by Lawrence Berkeley National Laboratory (LBNL), and integrated into a production cost model by Lawrence Livermore National Laboratory (LLNL), for the California Energy Commission’s Value of Energy Storage and Demand Response for Renewable Integration in California Study. This report summarizes the process for developing the DR availability profiles for California, and their aggregate capabilities. While LBNL provided potential DR hourly profiles for regulation product in the ancillary services market and five-minute load following product in the energy market for LLNL’s study, additional results in contingency reserves and an assumed flexible product are also defined. These additional products are included in the analysis for managing high ramps associated with renewable generation and capacity products and they are also presented in this report.

  3. The analysis of Taiwan's residential electricity demand under the electricity tariff policy

    Science.gov (United States)

    Chen, Po-Jui

    In October 2013, the Taiwan Power Company (Taipower), the monopolized state utility service in Taiwan, implemented an electricity tariff adjustment policy to reduce residential electricity demand. Using bi-monthly billing data from 6,932 electricity consumers, this study examine how consumers respond to an increase in electricity prices. This study employs an empirical approach that takes advantage of quasi-random variation over a period of time when household bills were affected by a change in electricity price. The study found that this price increase caused a 1.78% decline in residential electricity consumption, implying a price elasticity of -0.19 for summer-season months and -0.15 for non-summer-season months. The demand for electricity is therefore relatively inelastic, likely because it is hard for people to change their electricity consumption behavior in the short-term. The results of this study highlight that demand-side management cannot be the only lever used to address Taiwan's forecasted decrease in electricity supply.

  4. Estimating the price elasticity for demand for electricity by sector in South Africa

    Directory of Open Access Journals (Sweden)

    Roula Inglesi-Lotz

    2011-12-01

    Full Text Available This paper analyses electricity consumption patterns in South Africa in an attempt to understand and identify the roots of the current electricity crisis. This is done by investigating various economic sectors’ responses to price changes using panel data for the period 1993–2004. Positive and statistically significant price elasticities over this period were found for the transport (rail and commercial sectors while there are positive, but small and statistically insignificant responses to price changes in the agriculture and mining sectors. Only the industrial sector responded to changes in electricity prices according to theory, namely illustrating negative demand elasticities. This sector, however, dominates electricity consumption resulting in aggregate demand elasticities that are negative. These results explain, in part, the current electricity crisis. Given the historic low level of electricity prices in conjunction with, on the whole, a real price decline, i.e. price increases lower than the inflation rate; there was no major incentive to reduce electricity consumption and/or to be efficient. This result supports the notion that prices do have an important signalling effect in the economy. Hence, the electricity prices should be considered not only from an economic growth or social vantage point, but also from a supply and technocratic perspective, which includes environmental factors such as CO2-emissions. Prices should not be determined without considering the system-wide implications thereof.

  5. Demand for Electric Vehicles in Hybrid Households: An Exploratory Analysis

    OpenAIRE

    Kurani, Kenneth S.; Turrentine, Tom; Sperling, Daniel

    1994-01-01

    Previous studies of the potential market for battery electric vehicles (BEVs) have reached contradictory conclusions. What they share are untested or implausible assumptions about consumer response to new transportation technology. We frame the BEV purchase decision in terms of a household's entire stock of vehicles, car purchase behavior and travel behavior. Within this framework, households which own both electric vehicles and gasoline vehicles are called "hybrid households". Because nearly...

  6. Demand side management in recycling and electricity retail pricing

    Science.gov (United States)

    Kazan, Osman

    This dissertation addresses several problems from the recycling industry and electricity retail market. The first paper addresses a real-life scheduling problem faced by a national industrial recycling company. Based on their practices, a scheduling problem is defined, modeled, analyzed, and a solution is approximated efficiently. The recommended application is tested on the real-life data and randomly generated data. The scheduling improvements and the financial benefits are presented. The second problem is from electricity retail market. There are well-known patterns in daily usage in hours. These patterns change in shape and magnitude by seasons and days of the week. Generation costs are multiple times higher during the peak hours of the day. Yet most consumers purchase electricity at flat rates. This work explores analytic pricing tools to reduce peak load electricity demand for retailers. For that purpose, a nonlinear model that determines optimal hourly prices is established based on two major components: unit generation costs and consumers' utility. Both are analyzed and estimated empirically in the third paper. A pricing model is introduced to maximize the electric retailer's profit. As a result, a closed-form expression for the optimal price vector is obtained. Possible scenarios are evaluated for consumers' utility distribution. For the general case, we provide a numerical solution methodology to obtain the optimal pricing scheme. The models recommended are tested under various scenarios that consider consumer segmentation and multiple pricing policies. The recommended model reduces the peak load significantly in most cases. Several utility companies offer hourly pricing to their customers. They determine prices using historical data of unit electricity cost over time. In this dissertation we develop a nonlinear model that determines optimal hourly prices with parameter estimation. The last paper includes a regression analysis of the unit generation cost

  7. Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage

    NARCIS (Netherlands)

    Korkas, C; Baldi, S.; Michailidis, I; Kosmatopoulos, EB

    2016-01-01

    Integration of renewable energy sources in microgrids can be achieved via demand response programs, which change the electric usage in response to changes in the availability and price of electricity over time. This paper presents a novel control algorithm for joint demand response management and

  8. Dynamic pricing for demand response considering market price uncertainty

    DEFF Research Database (Denmark)

    Ghazvini, Mohammad Ali Fotouhi; Soares, Joao; Morais, Hugo

    2017-01-01

    Retail energy providers (REPs) can employ different strategies such as offering demand response (DR) programs, participating in bilateral contracts, and employing self-generation distributed generation (DG) units to avoid financial losses in the volatile electricity markets. In this paper......, the problem of setting dynamic retail sales price by a REP is addressed with a robust optimization technique. In the proposed model, the REP offers price-based DR programs while it faces uncertainties in the wholesale market price. The main contribution of this paper is using a robust optimization approach...

  9. Chance-constrained optimization of demand response to price signals

    DEFF Research Database (Denmark)

    Dorini, Gianluca Fabio; Pinson, Pierre; Madsen, Henrik

    2013-01-01

    Household-based demand response is expected to play an increasing role in supporting the large scale integration of renewable energy generation in existing power systems and electricity markets. While the direct control of the consumption level of households is envisaged as a possibility......, a credible alternative is that of indirect control based on price signals to be sent to these end-consumers. A methodology is described here allowing to estimate in advance the potential response of flexible end-consumers to price variations, subsequently embedded in an optimal price-signal generator....... In contrast to some real-time pricing proposals in the literature, here prices are estimated and broadcast once a day for the following one, for households to optimally schedule their consumption. The price-response is modeled using stochastic finite impulse response (FIR) models. Parameters are estimated...

  10. The Dynamics of Electricity Demand and Comsumption in Nigeria: Application of the Bounds Testing Approach

    OpenAIRE

    Udo N. Ekpo; Chuku A. Chuku; Effiong, Ekpeno L.

    2011-01-01

    Clear insights about the dynamic nature of electricity demand and consumption is essential for capacity additions, investments and effective optimal energy policies. This paper provides background analysis of electricity demand and consumption trends in Nigeria, with the key determinants of electricity demand and the investment requirements clearly highlighted. Further, the paper utilizes the bounds testing approach to empirically investigate the dynamics of electricity demand and consumption...

  11. The relationship between wind power, electricity demand and winter weather patterns in Great Britain

    Science.gov (United States)

    Thornton, Hazel E.; Scaife, Adam A.; Hoskins, Brian J.; Brayshaw, David J.

    2017-06-01

    Wind power generation in Great Britain has increased markedly in recent years. However due to its intermittency its ability to provide power during periods of high electricity demand has been questioned. Here we characterise the winter relationship between electricity demand and the availability of wind power. Although a wide range of wind power capacity factors is seen for a given demand, the average capacity factor reduces by a third between low and high demand. However, during the highest demand average wind power increases again, due to strengthening easterly winds. The nature of the weather patterns affecting Great Britain are responsible for this relationship. High demand is driven by a range of high pressure weather types, each giving cold conditions, but variable wind power availability. Offshore wind power is sustained at higher levels and offers a more secure supply compared to that onshore. However, during high demand periods in Great Britain neighbouring countries may struggle to provide additional capacity due to concurrent low temperatures and low wind power availability.

  12. Demand Response in the West: Lessons for States and Provinces

    Energy Technology Data Exchange (ETDEWEB)

    Douglas C. Larson; Matt Lowry; Sharon Irwin

    2004-06-29

    OAK-B135 This paper is submitted in fulfillment of DOE Grant No. DE-FG03-015F22369 on the experience of western states/provinces with demand response (DR) in the electricity sector. Demand-side resources are often overlooked as a viable option for meeting load growth and addressing the challenges posed by the region's aging transmission system. Western states should work together with utilities and grid operators to facilitate the further deployment of DR programs which can provide benefits in the form of decreased grid congestion, improved system reliability, market efficiency, price stabilization, hedging against volatile fuel prices and reduced environmental impacts of energy production. This report describes the various types of DR programs; provides a survey of DR programs currently in place in the West; considers the benefits, drawbacks and barriers to DR; and presents lessons learned and recommendations for states/provinces.

  13. Optimal Demand Response of Smart Home with PV Generators

    Directory of Open Access Journals (Sweden)

    Chao-Rong Chen

    2014-01-01

    Full Text Available Demand response (DR is used mainly to help to schedule a customer’s power utilization based on the electricity price that is announced by the power distribution company so that both demand and supply can optimally benefit. The work proposes a users’ load model and the interior point method for optimal scheduling with elastic power utilization to minimize power price. The interior point method has the advantages of rapid convergence and robustness. Customers can not only use PV generators and battery sets as backup power sources, but also benefit from green energy. As revealed by the results herein, the use of elastic power utilization time intervals enables customers to pay less power price.

  14. Design and Implementation of Demand Response Information Interactive Service Platform Based on “Internet Plus” Smart Energy

    Science.gov (United States)

    Cui, Gaoying; Fan, Jie; Qin, Yuchen; Wang, Dong; Chen, Guangyan

    2017-05-01

    In order to promote the effective use of demand response load side resources, promote the interaction between supply and demand, enhance the level of customer service and achieve the overall utilization of energy, this paper briefly explain the background significance of design demand response information platform and current situation of domestic and foreign development; Analyse the new demand of electricity demand response combined with the application of Internet and big data technology; Design demand response information platform architecture, construct demand responsive system, analyse process of demand response strategy formulate and intelligent execution implement; study application which combined with the big data, Internet and demand response technology; Finally, from information interaction architecture, control architecture and function design perspective design implementation of demand response information platform, illustrate the feasibility of the proposed platform design scheme implemented in a certain extent.

  15. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    2012-06-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  16. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, Donna [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Belzer, David B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hadley, Stanton W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Markel, Tony [National Renewable Energy Lab. (NREL), Golden, CO (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kintner-Meyer, Michael [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2012-06-15

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

  17. Loads as a Resource: Frequency Responsive Demand

    Energy Technology Data Exchange (ETDEWEB)

    Kalsi, Karanjit [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hansen, Jacob [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Fuller, Jason C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Marinovici, Laurentiu D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Tess L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lian, Jianming [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Sun, Yannan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-12-01

    Current power grid operation predominantly relies on scheduling and regulating generation resources to supply loads and balance load changes. Due to the inherent intermittency of renewable energy, more flexible and fast ramping capacity is required to compensate for the uncertainty and variability introduced by renewable energy resources. With the advancement of information technologies, power system end-use loads are becoming more agile and can participate in provision of balancing energy and other grid services. The use of demand response can greatly reduce the required generation reserve in a clean and environmentally friendly way. In this report, a new frequency responsive load (FRL) controller was proposed based on the GFA controller, which can respond to both over and under-frequency events. A supervisory control was introduced to coordinate the autonomous response from FRLs in order to overcome the issues of excessive system response due to high penetration of FRLs. The effectiveness of the proposed FRL controller was demonstrated by large-scale simulation studies on the WECC system. Specifically, the FRLs were deployed in the WECC system at different penetration levels to analyze the performance of the proposed strategy both with and without supervisory level control. While both methods have their own advantages, the case without supervisory control could lead to system-wide instability depending on the size of the contingency and the number of FRLs deployed in the system. In addition, the voltage impacts of this controller on distribution system were also carefully investigated. Finally, a preliminary measurement and verification approach was also developed.

  18. Loads as a Resource: Frequency Responsive Demand

    Energy Technology Data Exchange (ETDEWEB)

    Kalsi, Karanjit [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lian, Jianming [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Marinovici, Laurentiu D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elizondo, Marcelo A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhang, Wei [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moya, Christian [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-10-08

    Frequency control plays an important role in preserving the power balance of a multi-machine power system. Generators modify their power output when a non-zero frequency deviation is presented in order to restore power balance across the network. However, with plans for large-scale penetration of renewable energy resources, performing primary frequency control using only supply-side resources becomes not only prohibitively expensive, but also technically difficult. Frequency control from the demand side or load control presents a novel and viable way for providing the desired frequency response. Loads can measure frequency locally and change their power consumption after a non-zero frequency deviation is presented in order to achieve power balance between generation and consumption. The specific objectives of this project are to: •Provide a framework to facilitate large-scale deployment of frequency responsive end-use devices •Systematically design decentralized frequency-based load control strategies for enhanced stability performance •Ensure applicability over wide range of operating conditions while accounting for unpredictable end-use behavior and physical device constraints •Test and validate control strategy using large-scale simulations and field demonstrations •Create a level-playing field for smart grid assets with conventional generators

  19. The Role of Demand Response in Default Service Pricing

    Energy Technology Data Exchange (ETDEWEB)

    Barbose, Galen; Goldman, Charles; Neenan, Bernie

    2005-11-09

    Dynamic retail pricing, especially real-time pricing (RTP), has been widely heralded as a panacea for providing much-needed demand response in electricity markets. However, in designing default service for competitive retail markets, demand response has been an afterthought, and in some cases not given any weight at all. But that may be changing, as states that initiated customer choice in the past 5-7 years reach an important juncture in retail market design. Most states with retail choice established an initial transitional period during which utilities were required to offer a default or standard offer generation service, often at a capped or otherwise administratively-determined rate. Many retail choice states have reached the end of their transitional period, and several have adopted or are actively considering an RTP-type default service for large commercial and industrial (C&I) customers. In most cases, the primary reason for adopting RTP as the default service has been to advance policy objectives related to the development of competitive retail markets. However, if attention is paid in its design and implementation, default RTP service can also provide a solid foundation for developing price responsive demand, creating an important link between wholesale and retail market transactions. This article, which draws from a lengthier report, describes experience to date with RTP as a default service, focusing on its role as an instrument for cultivating price responsive demand.1 As of summer 2005, default service RTP was in place or approved for future implementation in five U.S. states: New Jersey, Maryland, Pennsylvania, New York, and Illinois. For each of these states, we conducted a detailed review of the regulatory proceedings leading to adoption of default RTP and interviewed regulatory staff and utilities in these states, as well as eight competitive retail suppliers active in these markets.

  20. Demand Response Performance of GE Hybrid Heat Pump Water Heater

    Energy Technology Data Exchange (ETDEWEB)

    Widder, Sarah H.; Parker, Graham B.; Petersen, Joseph M.; Baechler, Michael C.

    2013-07-01

    This report describes a project to evaluate and document the DR performance of HPWH as compared to ERWH for two primary types of DR events: peak curtailments and balancing reserves. The experiments were conducted with GE second-generation “Brillion”-enabled GeoSpring hybrid water heaters in the PNNL Lab Homes, with one GE GeoSpring water heater operating in “Standard” electric resistance mode to represent the baseline and one GE GeoSpring water heater operating in “Heat Pump” mode to provide the comparison to heat pump-only demand response. It is expected that “Hybrid” DR performance, which would engage both the heat pump and electric elements, could be interpolated from these two experimental extremes. Signals were sent simultaneously to the two water heaters in the side-by-side PNNL Lab Homes under highly controlled, simulated occupancy conditions. This report presents the results of the evaluation, which documents the demand-response capability of the GE GeoSpring HPWH for peak load reduction and regulation services. The sections describe the experimental protocol and test apparatus used to collect data, present the baselining procedure, discuss the results of the simulated DR events for the HPWH and ERWH, and synthesize key conclusions based on the collected data.

  1. Modeling and Analysis of Commercial Building Electrical Loads for Demand Side Management

    Science.gov (United States)

    Berardino, Jonathan

    In recent years there has been a push in the electric power industry for more customer involvement in the electricity markets. Traditionally the end user has played a passive role in the planning and operation of the power grid. However, many energy markets have begun opening up opportunities to consumers who wish to commit a certain amount of their electrical load under various demand side management programs. The potential benefits of more demand participation include reduced operating costs and new revenue opportunities for the consumer, as well as more reliable and secure operations for the utilities. The management of these load resources creates challenges and opportunities to the end user that were not present in previous market structures. This work examines the behavior of commercial-type building electrical loads and their capacity for supporting demand side management actions. This work is motivated by the need for accurate and dynamic tools to aid in the advancement of demand side operations. A dynamic load model is proposed for capturing the response of controllable building loads. Building-specific load forecasting techniques are developed, with particular focus paid to the integration of building management system (BMS) information. These approaches are tested using Drexel University building data. The application of building-specific load forecasts and dynamic load modeling to the optimal scheduling of multi-building systems in the energy market is proposed. Sources of potential load uncertainty are introduced in the proposed energy management problem formulation in order to investigate the impact on the resulting load schedule.

  2. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    Energy Technology Data Exchange (ETDEWEB)

    Goli, Sasank; McKane, Aimee; Olsen, Daniel

    2011-06-14

    Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated Demand Response (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their Demand Response (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

  3. Demand Response Integration Through Agent-Based Coordination of Consumers in Virtual Power Plants

    DEFF Research Database (Denmark)

    Clausen, Anders; Umair, Aisha; Ma, Zheng

    2016-01-01

    Power Plant design that is able to balance the demand of energy-intensive, industrial loads with the supply situation in the electricity grid. The proposed Virtual Power Plant design uses a novel inter-agent, multi-objective, multi-issue negotiation mechanism, to coordinate the electricity demands...... of industrial loads. Coordination happens in response to Demand Response events, while considering local objectives in the industrial domain. We illustrate the applicability of our approach on a Virtual Power Plant scenario with three simulated greenhouses. The results suggest that the proposed design is able...

  4. The impact of residential demand response on the costs of a fossil-free system reserve

    DEFF Research Database (Denmark)

    Katz, Jonas; Balyk, Olexandr; Hevia Koch, Pablo Alejandro

    2016-01-01

    to contribute to determining the least-cost options for regulation in a fossil-free power system. We extend an existing energy system model with demand response and reserve modelling and analyse the impact for the case of Denmark in 2035 to reflect a system based on renewable resources for electricity......In order to achieve a better understanding of the system value of residential demand response, we study the potential impact of flexible demand on the costs of system reserves in a fossil-free electricity supply. Comparing these costs with traditional means of regulation our analysis aims...

  5. Power System Transient Stability Improvement Using Demand Side Management in Competitive Electricity Markets

    DEFF Research Database (Denmark)

    Hu, Weihao; Wang, Chunqi; Chen, Zhe

    2012-01-01

    price is proposed. A 102-bus power system which represents a simplified model of the western Danish power system is chosen as the study case. Simulation results show that the optimal load response to electricity prices is an effective measure to improve the power system transient stability with high......Since the hourly spot market price is available one day ahead in Denmark, the price could be transferred to the consumers and they may shift some of their loads from high price periods to the low price periods in order to save their energy costs. The optimal load response to an electricity price...... for demand side management generates different load profiles and may provide an opportunity to improve the transient stability of power systems with high wind power penetrations. In this paper, the idea of the power system transient stability improvement by using optimal load response to the electricity...

  6. Electric response in superfluid helium

    Science.gov (United States)

    Chagovets, Tymofiy V.

    2016-05-01

    We report an experimental investigation of the electric response of superfluid helium that arises in the presence of a second sound standing wave. It was found that the signal of the electric response is observed in a narrow range of second sound excitation power. The linear dependence of the signal amplitude has been derived at low excitation power, however, above some critical power, the amplitude of the signal is considerably decreased. It was established that the rapid change of the electric response is not associated with a turbulent regime generated by the second sound wave. A model of the appearance of the electric response as a result of the oscillation of electron bubbles in the normal fluid velocity field in the second sound wave is presented. Possible explanation for the decrease of the electric response are presented.

  7. 2015 California Demand Response Potential Study - Charting California’s Demand Response Future. Interim Report on Phase 1 Results

    Energy Technology Data Exchange (ETDEWEB)

    Alstone, Peter; Potter, Jennifer; Piette, Mary Ann; Schwartz, Peter; Berger, Michael A.; Dunn, Laurel N.; Smith, Sarah J.; Sohn, Michael D.; Aghajanzadeh, Arian; Stensson, Sofia; Szinai, Julia

    2016-04-01

    Demand response (DR) is an important resource for keeping the electricity grid stable and efficient; deferring upgrades to generation, transmission, and distribution systems; and providing other customer economic benefits. This study estimates the potential size and cost of the available DR resource for California’s three investor-owned utilities (IOUs), as the California Public Utilities Commission (CPUC) evaluates how to enhance the role of DR in meeting California’s resource planning needs and operational requirements. As the state forges a clean energy future, the contributions of wind and solar electricity from centralized and distributed generation will fundamentally change the power grid’s operational dynamics. This transition requires careful planning to ensure sufficient capacity is available with the right characteristics – flexibility and fast response – to meet reliability needs. Illustrated is a snapshot of how net load (the difference between demand and intermittent renewables) is expected to shift. Increasing contributions from renewable generation introduces steeper ramps and a shift, into the evening, of the hours that drive capacity needs. These hours of peak capacity need are indicated by the black dots on the plots. Ultimately this study quantifies the ability and the cost of using DR resources to help meet the capacity need at these forecasted critical hours in the state.

  8. Reliability evaluation of microgrid considering incentive-based demand response

    Science.gov (United States)

    Huang, Ting-Cheng; Zhang, Yong-Jun

    2017-07-01

    Incentive-based demand response (IBDR) can guide customers to adjust their behaviour of electricity and curtail load actively. Meanwhile, distributed generation (DG) and energy storage system (ESS) can provide time for the implementation of IBDR. The paper focus on the reliability evaluation of microgrid considering IBDR. Firstly, the mechanism of IBDR and its impact on power supply reliability are analysed. Secondly, the IBDR dispatch model considering customer’s comprehensive assessment and the customer response model are developed. Thirdly, the reliability evaluation method considering IBDR based on Monte Carlo simulation is proposed. Finally, the validity of the above models and method is studied through numerical tests on modified RBTS Bus6 test system. Simulation results demonstrated that IBDR can improve the reliability of microgrid.

  9. A Distributed Intelligent Automated Demand Response Building Management System

    Energy Technology Data Exchange (ETDEWEB)

    Auslander, David [Univ. of California, Berkeley, CA (United States); Culler, David [Univ. of California, Berkeley, CA (United States); Wright, Paul [Univ. of California, Berkeley, CA (United States); Lu, Yan [Siemens Corporate Research Inc., Princeton, NJ (United States); Piette, Mary [Univ. of California, Berkeley, CA (United States)

    2013-03-31

    The goal of the 2.5 year Distributed Intelligent Automated Demand Response (DIADR) project was to reduce peak electricity load of Sutardja Dai Hall at UC Berkeley by 30% while maintaining a healthy, comfortable, and productive environment for the occupants. We sought to bring together both central and distributed control to provide “deep” demand response1 at the appliance level of the building as well as typical lighting and HVAC applications. This project brought together Siemens Corporate Research and Siemens Building Technology (the building has a Siemens Apogee Building Automation System (BAS)), Lawrence Berkeley National Laboratory (leveraging their Open Automated Demand Response (openADR), Auto-­Demand Response, and building modeling expertise), and UC Berkeley (related demand response research including distributed wireless control, and grid-­to-­building gateway development). Sutardja Dai Hall houses the Center for Information Technology Research in the Interest of Society (CITRIS), which fosters collaboration among industry and faculty and students of four UC campuses (Berkeley, Davis, Merced, and Santa Cruz). The 141,000 square foot building, occupied in 2009, includes typical office spaces and a nanofabrication laboratory. Heating is provided by a district heating system (steam from campus as a byproduct of the campus cogeneration plant); cooling is provided by one of two chillers: a more typical electric centrifugal compressor chiller designed for the cool months (Nov-­ March) and a steam absorption chiller for use in the warm months (April-­October). Lighting in the open office areas is provided by direct-­indirect luminaries with Building Management System-­based scheduling for open areas, and occupancy sensors for private office areas. For the purposes of this project, we focused on the office portion of the building. Annual energy consumption is approximately 8053 MWh; the office portion is estimated as 1924 MWh. The maximum peak load

  10. Managing Residential Electricity Demand Through Provision of Better Feedback

    Science.gov (United States)

    Collins, Myles

    New and affordable technology for providing detailed feedback on household electricity usage presents a host of opportunities for utilities and policy-makers to manage demand. This dissertation examines ways to use these devices to reduce - and shift the timing of - energy use in the residential sector by influencing consumers' behavior. The first portion of the study analyzes the impact of programmable thermostats (PTs) on energy use, focusing on residents' knowledge of climate control settings in the dwelling. I found that of households with natural gas heating systems, young households with PTs used 17 percent less heating energy on average. In addition, residents who did not know their thermostat settings tended to use 10 percent more energy for heating. The main portion of the dissertation focuses specifically on the potential for better feedback on electricity usage to reduce household energy consumption. The existing literature suggests that feedback can reduce electricity consumption in homes by 5 to 20 percent, but that significant uncertainties remain in our knowledge of the effectiveness of feedback. These uncertainties include the variation in feedback effectiveness between demographic groups and consumers in different climate regions. This analysis uses these uncertainties to perform an exploratory analysis to determine the conditions under which the benefits of feedback outweigh the costs and to compare the cost-effectiveness of providing feedback against that of other DSM programs. I found that benefits would likely outweigh costs for enhanced monthly billing and real-time feedback and that cost-effectiveness was superior to that of other DSM programs for these types of feedback. For feedback that is disaggregated by appliance type, cost effectiveness was competitive with other DSM programs under a limited set of cases. This study also examines how energy consumption devices should display feedback on GHG emissions from electricity use under a real

  11. Automated Dynamic Demand Response Implementation on a Micro-grid

    Energy Technology Data Exchange (ETDEWEB)

    Kuppannagari, Sanmukh R.; Kannan, Rajgopal; Chelmis, Charalampos; Prasanna, Viktor K.

    2016-11-16

    In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D2R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D2R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability to dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D2R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.

  12. Impact of peak electricity demand in distribution grids: a stress test

    NARCIS (Netherlands)

    Hoogsteen, Gerwin; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria; Schuring, Friso; Kootstra, Ben

    2015-01-01

    The number of (hybrid) electric vehicles is growing, leading to a higher demand for electricity in distribution grids. To investigate the effects of the expected peak demand on distribution grids, a stress test with 15 electric vehicles in a single street is conducted and described in this paper.

  13. Residential Demand Response Scheduling with Consideration of Consumer Preferences

    Directory of Open Access Journals (Sweden)

    Raka Jovanovic

    2016-01-01

    Full Text Available This paper proposes a new demand response scheduling framework for an array of households, which are grouped into different categories based on socio-economic factors, such as the number of occupants, family decomposition and employment status. Each of the households is equipped with a variety of appliances. The model takes the preferences of participating households into account and aims to minimize the overall production cost and, in parallel, to lower the individual electricity bills. In the existing literature, customers submit binary values for each time period to indicate their operational preferences. However, turning the appliances “on” or “off” does not capture the associated discomfort levels, as each appliance provides a different service and leads to a different level of satisfaction. The proposed model employs integer values to indicate household preferences and models the scheduling problem as a multi-objective mixed integer programming. The main thrust of the framework is that the multi-level preference modeling of appliances increases their “flexibility”; hence, the job scheduling can be done at a lower cost. The model is evaluated by using the real data provided by the Department of Energy & Climate Change, UK. In the computational experiments, we examine the relation between the satisfaction of consumers based on the appliance usage preferences and the electricity costs by exploring the Pareto front of the related objective functions. The results show that the proposed model leads to significant savings in electricity cost, while maintaining a good level of customer satisfaction.

  14. The Role of Demand Response in Reducing Water-Related Power Plant Vulnerabilities

    Science.gov (United States)

    Macknick, J.; Brinkman, G.; Zhou, E.; O'Connell, M.; Newmark, R. L.; Miara, A.; Cohen, S. M.

    2015-12-01

    The electric sector depends on readily available water supplies for reliable and efficient operation. Elevated water temperatures or low water levels can trigger regulatory or plant-level decisions to curtail power generation, which can affect system cost and reliability. In the past decade, dozens of power plants in the U.S. have curtailed generation due to water temperatures and water shortages. Curtailments occur during the summer, when temperatures are highest and there is greatest demand for electricity. Climate change could alter the availability and temperature of water resources, exacerbating these issues. Constructing alternative cooling systems to address vulnerabilities can be capital intensive and can also affect power plant efficiencies. Demand response programs are being implemented by electric system planners and operators to reduce and shift electricity demands from peak usage periods to other times of the day. Demand response programs can also play a role in reducing water-related power sector vulnerabilities during summer months. Traditionally, production cost modeling and demand response analyses do not include water resources. In this effort, we integrate an electricity production cost modeling framework with water-related impacts on power plants in a test system to evaluate the impacts of demand response measures on power system costs and reliability. Specifically, we i) quantify the cost and reliability implications of incorporating water resources into production cost modeling, ii) evaluate the impacts of demand response measures on reducing system costs and vulnerabilities, and iii) consider sensitivity analyses with cooling systems to highlight a range of potential benefits of demand response measures. Impacts from climate change on power plant performance and water resources are discussed. Results provide key insights to policymakers and practitioners for reducing water-related power plant vulnerabilities via lower cost methods.

  15. The physical demands of electrical utilities work in North America.

    Science.gov (United States)

    Meade, Robert D; Lauzon, Martin; Poirier, Martin P; Flouris, Andreas D; Kenny, Glen P

    2016-01-01

    We assessed the physical demands associated with electrical utilities work in North America and how they influence the level of thermal and cardiovascular strain experienced. Three common job categories were monitored as they are normally performed in thirty-two electrical utility workers: (i) Ground Work (n = 11), (ii) Bucket Work (n = 9), and (iii) Manual Pole Work (n = 12). Video analysis was performed to determine the proportion of the work monitoring period (duration: 187 ± 104 min) spent at different levels of physical effort (i.e., rest as well as light, moderate and heavy effort). Core and skin temperatures as well as heart rate were measured continuously. On average, workers spent 35.9 ± 15.9, 36.8 ± 17.8, 24.7 ± 12.8, and 2.6 ± 3.3% of the work period at rest and performing work classified as light, moderate, and heavy physical effort, respectively. Moreover, a greater proportion of the work period was spent performing heavy work in Ground Work (1.6 ± 1.4%) relative to Bucket Work (0.0 ± 0.0%; PPole Climbing (5.5 ± 3.6%) in comparison to both other work job (both P≤0.03). Furthermore, the proportion of time spent during work classified as heavy physical effort was positively correlated to the mean (r = 0.51, Pshift; however, no differences in the proportion of the work spent at the different intensity classifications were observed. We show that Manual Pole Work is associated with greater levels of physical effort compared to Ground or Bucket Work. Moreover, we suggest that the proportion of time spent performing work classified as heavy physical exertion is related to the level of thermal and cardiovascular strain experienced and that workers may not be employing self-pacing as a strategy to manage their level of physiological strain.

  16. Demand Response in Low Voltage Distribution Networks with High PV Penetration

    DEFF Research Database (Denmark)

    Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    generation and load forecasts, network topology and market price signals as inputs, limits of network voltages, line power flows, transformer loading and demand response dynamics as constraints to find the required demand response at each time step. The proposed method can be used by the DSOs to purchase...... the required flexibility from the electricity market through an aggregator. The optimum demand response enables consumption of maximum renewable energy within the network constraints. Simulation studies are conducted using Matlab and DigSilent Power factory software on a Danish low-voltage distribution system...

  17. Automation of Capacity Bidding with an Aggregator Using Open Automated Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Piette, Mary Ann

    2008-10-01

    This report summarizes San Diego Gas& Electric Company?s collaboration with the Demand Response Research Center to develop and test automation capability for the Capacity Bidding Program in 2007. The report describes the Open Automated Demand Response architecture, summarizes the history of technology development and pilot studies. It also outlines the Capacity Bidding Program and technology being used by an aggregator that participated in this demand response program. Due to delays, the program was not fully operational for summer 2007. However, a test event on October 3, 2007, showed that the project successfully achieved the objective to develop and demonstrate how an open, Web?based interoperable automated notification system for capacity bidding can be used by aggregators for demand response. The system was effective in initiating a fully automated demand response shed at the aggregated sites. This project also demonstrated how aggregators can integrate their demand response automation systems with San Diego Gas& Electric Company?s Demand Response Automation Server and capacity bidding program.

  18. Electricity pricing as a demand-side management strategy: Western lessons for developing countries

    Energy Technology Data Exchange (ETDEWEB)

    Hill, L.J.

    1990-12-01

    Electric utilities in the Western world have increasingly realized that load commitments can be met not only by constructing new generating plants but also by influencing electricity demand. This demand-side management (DSM) process requires that electric utilities promote measures on the customer's side of the meter to directly or indirectly influence electricity consumption to meet desired load objectives. An important demand-side option to achieve these load objectives is innovative electricity pricing, both by itself and as a financial incentive for other demand-site measures. This study explores electricity pricing as a DSM strategy, addressing four questions in the process: What is the Western experience with DSM in general and electricity pricing in particular Do innovative pricing strategies alter the amount and pattern of electricity consumption Do the benefits of these pricing strategies outweigh the costs of implementation What are future directions in electricity pricing Although DSM can be used to promote increases in electricity consumption for electric utilities with excess capacity as well as to slow demand growth for capacity-short utilities, emphasis here is placed on the latter. The discussion should be especially useful for electric utilities in developing countries that are exploring alternatives to capacity expansion to meet current and future electric power demand.

  19. Field Demonstration of Automated Demand Response for Both Winter and Summer Events in Large Buildings in the Pacific Northwest

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Kiliccote, Sila; Dudley, Junqiao H.

    2011-11-11

    There are growing strains on the electric grid as cooling peaks grow and equipment ages. Increased penetration of renewables on the grid is also straining electricity supply systems and the need for flexible demand is growing. This paper summarizes results of a series of field test of automated demand response systems in large buildings in the Pacific Northwest. The objective of the research was two fold. One objective was to evaluate the use demand response automation technologies. A second objective was to evaluate control strategies that could change the electric load shape in both winter and summer conditions. Winter conditions focused on cold winter mornings, a time when the electric grid is often stressed. The summer test evaluated DR strategies in the afternoon. We found that we could automate both winter and summer control strategies with the open automated demand response communication standard. The buildings were able to provide significant demand response in both winter and summer events.

  20. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    Energy Technology Data Exchange (ETDEWEB)

    Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

    2011-08-15

    Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

  1. A case study of electric utility demand reduction with commerical solar water heaters

    Energy Technology Data Exchange (ETDEWEB)

    Ewert, M.; Hoffner, J.E.; Panico, D. (City of Austin Electric Utility Dept., Austin, TX (US))

    1991-05-01

    The City of Austin, is studying the impact of solar water heaters on summer peak electric demand. One passive and two active solar water heating systems were installed on city owned commercial buildings which had electric water heaters in 1985 and have been monitored for two years. This paper reports on a method that has been developed to determine the peak demand reduction attributable to the solar systems. Results show that solar water heating systems are capable of large demand reductions as long as there is a large hot water demand to displace. The average noncoincident demand reduction (during the water heater's peak output) ranged from 0.8 to 5.8 kilowatts per system, however, the coincident demand reduction during the utility peak demand period was 0.3 to 0.8 kilowatts per system. Thus, a critical factor when assessing the benefit to the electric utility is the time of hot water demand.

  2. Climate change and peak demand for electricity: Evaluating policies for reducing peak demand under different climate change scenarios

    Science.gov (United States)

    Anthony, Abigail Walker

    This research focuses on the relative advantages and disadvantages of using price-based and quantity-based controls for electricity markets. It also presents a detailed analysis of one specific approach to quantity based controls: the SmartAC program implemented in Stockton, California. Finally, the research forecasts electricity demand under various climate scenarios, and estimates potential cost savings that could result from a direct quantity control program over the next 50 years in each scenario. The traditional approach to dealing with the problem of peak demand for electricity is to invest in a large stock of excess capital that is rarely used, thereby greatly increasing production costs. Because this approach has proved so expensive, there has been a focus on identifying alternative approaches for dealing with peak demand problems. This research focuses on two approaches: price based approaches, such as real time pricing, and quantity based approaches, whereby the utility directly controls at least some elements of electricity used by consumers. This research suggests that well-designed policies for reducing peak demand might include both price and quantity controls. In theory, sufficiently high peak prices occurring during periods of peak demand and/or low supply can cause the quantity of electricity demanded to decline until demand is in balance with system capacity, potentially reducing the total amount of generation capacity needed to meet demand and helping meet electricity demand at the lowest cost. However, consumers need to be well informed about real-time prices for the pricing strategy to work as well as theory suggests. While this might be an appropriate assumption for large industrial and commercial users who have potentially large economic incentives, there is not yet enough research on whether households will fully understand and respond to real-time prices. Thus, while real-time pricing can be an effective tool for addressing the peak load

  3. Price, environment and security: Exploring multi-modal motivation in voluntary residential peak demand response

    Energy Technology Data Exchange (ETDEWEB)

    Gyamfi, Samuel [Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch (New Zealand); Krumdieck, Susan, E-mail: susan.krumdieck@canterbury.ac.n [Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch (New Zealand)

    2011-05-15

    Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response projects aim to manage peak demand by applying price signals and automated load shedding technologies. This research investigates voluntary load shedding in response to information about the security of supply, the emission profile and the cost of meeting critical peak demand in the customers' network. Customer willingness to change behaviour in response to this information was explored through mail-back survey. The diversified demand modelling method was used along with energy audit data to estimate the potential peak load reduction resulting from the voluntary demand response. A case study was conducted in a suburb of Christchurch, New Zealand, where electricity is the main source for water and space heating. On this network, all water heating cylinders have ripple-control technology and about 50% of the households subscribe to differential day/night pricing plan. The survey results show that the sensitivity to supply security is on par with price, with the emission sensitivity being slightly weaker. The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. - Highlights: {yields} Multiple-factor behaviour intervention is necessarily for effective residential demand response. {yields} Security signals can achieve result comparable to price. {yields} The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. {yields} New Zealand's energy policy should include innovation and development of VDR programmes and technologies.

  4. Economic Dispatch of Demand Response Balancing through Asymmetric Block Offers

    DEFF Research Database (Denmark)

    O'Connell, Niamh; Pinson, Pierre; Madsen, Henrik

    2015-01-01

    load to provide a response to the power system and the subsequent need to recover. The conventional system dispatch algorithm is altered to facilitate the dispatch of demand response units alongside generating units using the proposed offer structure. The value of demand response is assessed through......%. For comparative purposes, the cost savings achievable with a fully observable and controllable demand response resource are evaluated, using a time series model of the refrigeration loads. The fully modeled resource offers greater savings; however the difference is small and potentially insufficient to justify...

  5. Development and evaluation of fully automated demand response in large facilities

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Sezgen, Osman; Watson, David S.; Motegi, Naoya; Shockman, Christine; ten Hope, Laurie

    2004-03-30

    This report describes the results of a research project to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. The two main drivers for widespread demand responsiveness are the prevention of future electricity crises and the reduction of electricity prices. Additional goals for price responsiveness include equity through cost of service pricing, and customer control of electricity usage and bills. The technology developed and evaluated in this report could be used to support numerous forms of DR programs and tariffs. For the purpose of this report, we have defined three levels of Demand Response automation. Manual Demand Response involves manually turning off lights or equipment; this can be a labor-intensive approach. Semi-Automated Response involves the use of building energy management control systems for load shedding, where a preprogrammed load shedding strategy is initiated by facilities staff. Fully-Automated Demand Response is initiated at a building or facility through receipt of an external communications signal--facility staff set up a pre-programmed load shedding strategy which is automatically initiated by the system without the need for human intervention. We have defined this approach to be Auto-DR. An important concept in Auto-DR is that a facility manager is able to ''opt out'' or ''override'' an individual DR event if it occurs at a time when the reduction in end-use services is not desirable. This project sought to improve the feasibility and nature of Auto-DR strategies in large facilities. The research focused on technology development, testing

  6. Modeling, Analysis, and Control of Demand Response Resources

    Energy Technology Data Exchange (ETDEWEB)

    Mathieu, Johanna L. [Univ. of California, Berkeley, CA (United States)

    2012-05-01

    While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in power systems via Demand Response (DR), defined by the Department of Energy (DOE) as “a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized” [29]. DR can provide a variety of benefits including reducing peak electric loads when the power system is stressed and fast timescale energy balancing. Therefore, DR can improve grid reliability and reduce wholesale energy prices and their volatility. This dissertation focuses on analyzing both recent and emerging DR paradigms. Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present methods for using 15-minute-interval electric load data, commonly available from C&I facilities, to help building managers understand building energy consumption and ‘ask the right questions’ to discover opportunities for DR. Additionally, we present a regression-based model of whole building electric load, i.e., a baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of 38 C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are expected to exhibit the same response each DR event. We find that baseline model error makes it difficult to precisely quantify changes in electricity consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. Therefore, we present a method to compute baseline model error and a metric to determine how much observed DR variability results from baseline model error rather than real

  7. Assessment of demand for natural gas from the electricity sector in India

    DEFF Research Database (Denmark)

    Shukla, P.R.; Dhar, Subash; Victor, David G.

    2009-01-01

    Electricity sector is among the key users of natural gas. The sustained electricity deficit and environment policies have added to an already rising demand for gas. This paper tries to understand gas demand in future from electricity sector. This paper models the future demand for gas in India from...... the electricity sector under alternative scenarios for the period 2005–2025, using bottom-up ANSWER MARKAL model. The scenarios are differentiated by alternate economic growth projections and policies related to coal reforms, infrastructure choices and local environment. The results across scenarios show that gas...... competes with coal as a base-load option if price difference is below US $ 4 per MBtu. At higher price difference gas penetrates only the peak power market. Gas demand is lower in the high economic growth scenario, since electricity sector is more flexible in substitution of primary energy. Gas demand...

  8. Assessment of Industrial Load for Demand Response across Western Interconnect

    Energy Technology Data Exchange (ETDEWEB)

    Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL; Ma, Ookie [United States Department of Energy (DOE), Office of Efficiency and Renewable Energy (EERE)

    2013-11-01

    Demand response (DR) has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles that can provide more regional understanding and can be inserted into analysis software for further study. The developed framework utilizes a number of different informational resources, algorithms, and real-world measurements to perform a bottom-up approach in the development of a new database with representation of the potential demand response resource in the industrial sector across the U.S. This tool houses statistical values of energy and demand response (DR) potential by industrial plant and geospatially locates the information for aggregation for different territories without proprietary information. This report will discuss this framework and the analyzed quantities of demand response for Western Interconnect (WI) in support of evaluation of the cost production modeling with power grid modeling efforts of demand response.

  9. Northwest Open Automated Demand Response Technology Demonstration Project

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Dudley, Junqiao Han; Piette, Mary Ann

    2009-08-01

    Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) performed a technology demonstration and evaluation for Bonneville Power Administration (BPA) in Seattle City Light's (SCL) service territory. This report summarizes the process and results of deploying open automated demand response (OpenADR) in Seattle area with winter morning peaking commercial buildings. The field tests were designed to evaluate the feasibility of deploying fully automated demand response (DR) in four to six sites in the winter and the savings from various building systems. The project started in November of 2008 and lasted 6 months. The methodology for the study included site recruitment, control strategy development, automation system deployment and enhancements, and evaluation of sites participation in DR test events. LBNL subcontracted McKinstry and Akuacom for this project. McKinstry assisted with recruitment, site survey collection, strategy development and overall participant and control vendor management. Akuacom established a new server and enhanced its operations to allow for scheduling winter morning day-of and day-ahead events. Each site signed a Memorandum of Agreement with SCL. SCL offered each site $3,000 for agreeing to participate in the study and an additional $1,000 for each event they participated. Each facility and their control vendor worked with LBNL and McKinstry to select and implement control strategies for DR and developed their automation based on the existing Internet connectivity and building control system. Once the DR strategies were programmed, McKinstry commissioned them before actual test events. McKinstry worked with LBNL to identify control points that can be archived at each facility. For each site LBNL collected meter data and trend logs from the energy management and control system. The communication system allowed the sites to receive day-ahead as well as day-of DR test event signals. Measurement of DR was

  10. Opportunities for Energy Efficiency and Automated Demand Response in Industrial Refrigerated Warehouses in California

    Energy Technology Data Exchange (ETDEWEB)

    Lekov, Alex; Thompson, Lisa; McKane, Aimee; Rockoff, Alexandra; Piette, Mary Ann

    2009-05-11

    This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

  11. Role of Storage and Demand Response, Greening the Grid

    Energy Technology Data Exchange (ETDEWEB)

    2015-09-01

    Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid. This document, part of a Greening the Grid toolkit, examines storage and demand response as means to match renewable energy supply with demand.

  12. Forecasting the demand for electric vehicles: accounting for attitudes and perceptions

    OpenAIRE

    Glerum, Aurélie; Stankovikj, Lidija; Thémans, Michaël; Bierlaire, Michel

    2012-01-01

    In the context of the arrival of electric vehicles on the car market, new mathematical models are needed to understand and predict the impact on the market shares. This research provides a comprehensive methodology to forecast the demand of a technology which is not widespread yet, such as electric cars. It aims at providing contributions regarding three issues related to the prediction of the demand for electric vehicles: survey design, model estimation and forecasting. We develop a stated p...

  13. Economic Microgrid Planning Algorithm with Electric Vehicle Charging Demands

    National Research Council Canada - National Science Library

    Sung-Guk Yoon; Seok-Gu Kang

    2017-01-01

    .... The microgrid is an important technology to promote renewable generation, and the increased demand and changed load curve should be considered in the microgrid planning stage to install robust and economical microgrids...

  14. Flexibility dynamics in clusters of residential demand response and distributed generation

    NARCIS (Netherlands)

    MacDougall, P.A.; Kok, J.K.; Warmer, C.; Roossien, B.

    2013-01-01

    Supply and demand response is a untapped resource in the current electrical system. However little work has been done to investigate the dynamics of utilizing such flexibility as well as the potential effects it could have on the infrastructure. This paper provides a starting point to seeing the

  15. Demand Response and Open Automated Demand Response Opportunities for Data Centers

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish; Piette, Mary Ann; Fujita, Sydny; McKane, Aimee; Dudley, Junqiao Han; Radspieler, Anthony; Mares, K.C.; Shroyer, Dave

    2009-12-30

    This study examines data center characteristics, loads, control systems, and technologies to identify demand response (DR) and automated DR (Open Auto-DR) opportunities and challenges. The study was performed in collaboration with technology experts, industrial partners, and data center facility managers and existing research on commercial and industrial DR was collected and analyzed. The results suggest that data centers, with significant and rapidly growing energy use, have significant DR potential. Because data centers are highly automated, they are excellent candidates for Open Auto-DR. 'Non-mission-critical' data centers are the most likely candidates for early adoption of DR. Data center site infrastructure DR strategies have been well studied for other commercial buildings; however, DR strategies for information technology (IT) infrastructure have not been studied extensively. The largest opportunity for DR or load reduction in data centers is in the use of virtualization to reduce IT equipment energy use, which correspondingly reduces facility cooling loads. DR strategies could also be deployed for data center lighting, and heating, ventilation, and air conditioning. Additional studies and demonstrations are needed to quantify benefits to data centers of participating in DR and to address concerns about DR's possible impact on data center performance or quality of service and equipment life span.

  16. Letter to the Editor: Electric Vehicle Demand Model for Load Flow Studies

    DEFF Research Database (Denmark)

    Garcia-Valle, Rodrigo; Vlachogiannis, Ioannis (John)

    2009-01-01

    This paper introduces specific and simple model for electric vehicles suitable for load flow studies. The electric vehicles demand system is modelled as PQ bus with stochastic characteristics based on the concept of queuing theory. All appropriate variables of stochastic PQ buses are given...... with closed formulae as a function of charging time. Specific manufacturer model of electric vehicles is used as study case....

  17. Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load

    Directory of Open Access Journals (Sweden)

    Shengchun Yang

    2016-01-01

    Full Text Available Demand response (DR programs provide an effective approach for dealing with the challenge of wind power output fluctuations. Given that uncertain DR, such as price elastic load (PEL, plays an important role, the uncertainty of demand response behavior must be studied. In this paper, a multi-objective stochastic optimization problem of PEL is proposed on the basis of the analysis of the relationship between price elasticity and probabilistic characteristic, which is about stochastic demand models for consumer loads. The analysis aims to improve the capability of accommodating wind output uncertainty. In our approach, the relationship between the amount of demand response and interaction efficiency is developed by actively participating in power grid interaction. The probabilistic representation and uncertainty range of the PEL demand response amount are formulated differently compared with those of previous research. Based on the aforementioned findings, a stochastic optimization model with the combined uncertainties from the wind power output and the demand response scenario is proposed. The proposed model analyzes the demand response behavior of PEL by maximizing the electricity consumption satisfaction and interaction benefit satisfaction of PEL. Finally, a case simulation on the provincial power grid with a 151-bus system verifies the effectiveness and feasibility of the proposed mechanism and models.

  18. Machine Learning for Identifying Demand Patterns of Home Energy Management Systems with Dynamic Electricity Pricing

    Directory of Open Access Journals (Sweden)

    Derck Koolen

    2017-11-01

    Full Text Available Energy management plays a crucial role in providing necessary system flexibility to deal with the ongoing integration of volatile and intermittent energy sources. Demand Response (DR programs enhance demand flexibility by communicating energy market price volatility to the end-consumer. In such environments, home energy management systems assist the use of flexible end-appliances, based upon the individual consumer’s personal preferences and beliefs. However, with the latter heterogeneously distributed, not all dynamic pricing schemes are equally adequate for the individual needs of households. We conduct one of the first large scale natural experiments, with multiple dynamic pricing schemes for end consumers, allowing us to analyze different demand behavior in relation with household attributes. We apply a spectral relaxation clustering approach to show distinct groups of households within the two most used dynamic pricing schemes: Time-Of-Use and Real-Time Pricing. The results indicate that a more effective design of smart home energy management systems can lead to a better fit between customer and electricity tariff in order to reduce costs, enhance predictability and stability of load and allow for more optimal use of demand flexibility by such systems.

  19. Impact of Uncoordinated Plug-in Electric Vehicle Charging on Residential Power Demand

    Energy Technology Data Exchange (ETDEWEB)

    Muratori, Matteo [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-01-22

    Electrification of transport offers opportunities to increase energy security, reduce carbon emissions, and improve local air quality. Plug-in electric vehicles (PEVs) are creating new connections between the transportation and electric sectors, and PEV charging will create opportunities and challenges in a system of growing complexity. Here, I use highly resolved models of residential power demand and PEV use to assess the impact of uncoordinated in-home PEV charging on residential power demand. While the increase in aggregate demand might be minimal even for high levels of PEV adoption, uncoordinated PEV charging could significantly change the shape of the aggregate residential demand, with impacts for electricity infrastructure, even at low adoption levels. Clustering effects in vehicle adoption at the local level might lead to high PEV concentrations even if overall adoption remains low, significantly increasing peak demand and requiring upgrades to the electricity distribution infrastructure. This effect is exacerbated when adopting higher in-home power charging.

  20. Using high frequency consumption data to identify demand response potential for solar energy integration

    Science.gov (United States)

    Jin, L.; Borgeson, S.; Fredman, D.; Hans, L.; Spurlock, A.; Todd, A.

    2015-12-01

    California's renewable portfolio standard (2012) requires the state to get 33% of its electricity from renewable sources by 2020. Increased share of variable renewable sources such as solar and wind in the California electricity system may require more grid flexibility to insure reliable power services. Such grid flexibility can be potentially provided by changes in end use electricity consumptions in response to grid conditions (demand-response). In the solar case, residential consumption in the late afternoon can be used as reserve capacity to balance the drop in solar generation. This study presents our initial attempt to identify, from a behavior perspective, residential demand response potentials in relation to solar ramp events using a data-driven approach. Based on hourly residential energy consumption data, we derive representative daily load shapes focusing on discretionary consumption with an innovative clustering analysis technique. We aggregate the representative load shapes into behavior groups in terms of the timing and rhythm of energy use in the context of solar ramp events. Households of different behavior groups that are active during hours with high solar ramp rates are identified for capturing demand response potential. Insights into the nature and predictability of response to demand-response programs are provided.

  1. Automated Demand Response Approaches to Household Energy Management in a Smart Grid Environment

    Science.gov (United States)

    Adika, Christopher Otieno

    The advancement of renewable energy technologies and the deregulation of the electricity market have seen the emergence of Demand response (DR) programs. Demand response is a cost-effective load management strategy which enables the electricity suppliers to maintain the integrity of the power grid during high peak periods, when the customers' electrical load is high. DR programs are designed to influence electricity users to alter their normal consumption patterns by offering them financial incentives. A well designed incentive-based DR scheme that offer competitive electricity pricing structure can result in numerous benefits to all the players in the electricity market. Lower power consumption during peak periods will significantly enhance the robustness of constrained networks by reducing the level of power of generation and transmission infrastructure needed to provide electric service. Therefore, this will ease the pressure of building new power networks as we avoiding costly energy procurements thereby translating into huge financial savings for the power suppliers. Peak load reduction will also reduce the inconveniences suffered by end users as a result of brownouts or blackouts. Demand response will also drastically lower the price peaks associated with wholesale markets. This will in turn reduce the electricity costs and risks for all the players in the energy market. Additionally, DR is environmentally friendly since it enhances the flexibility of the power grid through accommodation of renewable energy resources. Despite its many benefits, DR has not been embraced by most electricity networks. This can be attributed to the fact that the existing programs do not provide enough incentives to the end users and, therefore, most electricity users are not willing to participate in them. To overcome these challenges, most utilities are coming up with innovative strategies that will be more attractive to their customers. Thus, this dissertation presents various

  2. Mining residential water and electricity demand data in Southern California to inform demand management strategies

    Science.gov (United States)

    Cominola, A.; Spang, E. S.; Giuliani, M.; Castelletti, A.; Loge, F. J.; Lund, J. R.

    2016-12-01

    Demand side management strategies are key to meet future water and energy demands in urban contexts, promote water and energy efficiency in the residential sector, provide customized services and communications to consumers, and reduce utilities' costs. Smart metering technologies allow gathering high temporal and spatial resolution water and energy consumption data and support the development of data-driven models of consumers' behavior. Modelling and predicting resource consumption behavior is essential to inform demand management. Yet, analyzing big, smart metered, databases requires proper data mining and modelling techniques, in order to extract useful information supporting decision makers to spot end uses towards which water and energy efficiency or conservation efforts should be prioritized. In this study, we consider the following research questions: (i) how is it possible to extract representative consumers' personalities out of big smart metered water and energy data? (ii) are residential water and energy consumption profiles interconnected? (iii) Can we design customized water and energy demand management strategies based on the knowledge of water- energy demand profiles and other user-specific psychographic information? To address the above research questions, we contribute a data-driven approach to identify and model routines in water and energy consumers' behavior. We propose a novel customer segmentation procedure based on data-mining techniques. Our procedure consists of three steps: (i) extraction of typical water-energy consumption profiles for each household, (ii) profiles clustering based on their similarity, and (iii) evaluation of the influence of candidate explanatory variables on the identified clusters. The approach is tested onto a dataset of smart metered water and energy consumption data from over 1000 households in South California. Our methodology allows identifying heterogeneous groups of consumers from the studied sample, as well as

  3. Personality predicts brain responses to cognitive demands.

    Science.gov (United States)

    Kumari, Veena; ffytche, Dominic H; Williams, Steven C R; Gray, Jeffrey A

    2004-11-24

    Eysenck (1981) proposed that the personality dimension of introversion- extraversion (E) reflects individual differences in a cortical arousal system modulated by reticulothalamic- cortical pathways: it is chronically more active in introverts relative to extraverts and influences cognitive performance in interaction with task parameters. A circuit with connections to this system, including the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate (AC) cortex, has been identified in studies applying functional magnetic resonance imaging (fMRI) to a broad range of cognitive tasks. We examined the influence of E, assessed with the Eysenck Personality Questionnaire-Revised (Eysenck and Eysenck, 1991), in fMRI activity during an "n-back" task involving four memory loads (0-, 1-, 2-, and 3-back) and a rest condition in healthy men. To confirm the specificity of E effects, we also examined the effects of neuroticism and psychoticism (P) scores. We observed that, as predicted by Eysenck's model, the higher the E score, the greater the change in fMRI signal from rest to the 3-back condition in the DLPFC and AC. In addition, E scores were negatively associated with resting fMRI signals in the thalamus and Broca's area extending to Wernicke's area, supporting the hypothesized (negative) relationship between E and resting arousal. P scores negatively correlated with resting fMRI signal in the globus pallidus-putamen, extending previous findings of a negative relationship of schizotypy to striatal activity seen with older neuroimaging modalities to fMRI. These observations suggest that individual differences affect brain responses during cognitive activity and at rest and provide evidence for the hypothesized neurobiological basis of personality.

  4. Grid-Aware Demand Management in Electricity Distribution Grids

    DEFF Research Database (Denmark)

    Bessler, Sanford; Kemal, Mohammed Seifu; Silva, Nuno

    2018-01-01

    prices. This paper presents an extended demand management approach that focuses on two aspects: (1) introduction of an interface to the Distribution System Operator in order to allow for grid load management (overload avoidance); (2) end-to-end robustness to changes of real-time information......, in particular addressing variable communication network behavior as it may result from the use of shared communication network infrastructure. The paper presents algorithms that realize such demand management on different levels in a hierarchical control system, defines and implements the related protocols...

  5. Automated Price and Demand Response Demonstration for Large Customers in New York City using OpenADR

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Joyce Jihyun; Yin, Rongxin; Kiliccote, Sila

    2013-10-01

    Open Automated Demand Response (OpenADR), an XML-based information exchange model, is used to facilitate continuous price-responsive operation and demand response participation for large commercial buildings in New York who are subject to the default day-ahead hourly pricing. We summarize the existing demand response programs in New York and discuss OpenADR communication, prioritization of demand response signals, and control methods. Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management and demand response capabilities of two commercial buildings in New York City. Preliminary results reveal that providing machine-readable prices to commercial buildings can facilitate both demand response participation and continuous energy cost savings. Hence, efforts should be made to develop more sophisticated algorithms for building control systems to minimize customer's utility bill based on price and reliability information from the electricity grid.

  6. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2010-08-02

    This study examines the use of OpenADR communications specification, related data models, technologies, and strategies to send dynamic prices (e.g., real time prices and peak prices) and Time of Use (TOU) rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open information model that has been used in California utilities' commercial automated demand response programs since 2007. We find that data models can be used to send real time prices. These same data models can also be used to support peak pricing and TOU rates. We present a data model that can accommodate all three types of rates. For demonstration purposes, the data models were generated from California Independent System Operator's real-time wholesale market prices, and a California utility's dynamic prices and TOU rates. Customers can respond to dynamic prices by either using the actual prices, or prices can be mapped into"operation modes," which can act as inputs to control systems. We present several different methods for mapping actual prices. Some of these methods were implemented in demonstration projects. The study results demonstrate show that OpenADR allows interoperability with existing/future systems/technologies and can be used within related dynamic pricing activities within Smart Grid.

  7. An Informatics Approach to Demand Response Optimization in Smart Grids

    Energy Technology Data Exchange (ETDEWEB)

    Simmhan, Yogesh; Aman, Saima; Cao, Baohua; Giakkoupis, Mike; Kumbhare, Alok; Zhou, Qunzhi; Paul, Donald; Fern, Carol; Sharma, Aditya; Prasanna, Viktor K

    2011-03-03

    Power utilities are increasingly rolling out “smart” grids with the ability to track consumer power usage in near real-time using smart meters that enable bidirectional communication. However, the true value of smart grids is unlocked only when the veritable explosion of data that will become available is ingested, processed, analyzed and translated into meaningful decisions. These include the ability to forecast electricity demand, respond to peak load events, and improve sustainable use of energy by consumers, and are made possible by energy informatics. Information and software system techniques for a smarter power grid include pattern mining and machine learning over complex events and integrated semantic information, distributed stream processing for low latency response,Cloud platforms for scalable operations and privacy policies to mitigate information leakage in an information rich environment. Such an informatics approach is being used in the DoE sponsored Los Angeles Smart Grid Demonstration Project, and the resulting software architecture will lead to an agile and adaptive Los Angeles Smart Grid.

  8. Projected Demand and Potential Impacts to the National Airspace System of Autonomous, Electric, On-Demand Small Aircraft

    Science.gov (United States)

    Smith, Jeremy C.; Viken, Jeffrey K.; Guerreiro, Nelson M.; Dollyhigh, Samuel M.; Fenbert, James W.; Hartman, Christopher L.; Kwa, Teck-Seng; Moore, Mark D.

    2012-01-01

    Electric propulsion and autonomy are technology frontiers that offer tremendous potential to achieve low operating costs for small-aircraft. Such technologies enable simple and safe to operate vehicles that could dramatically improve regional transportation accessibility and speed through point-to-point operations. This analysis develops an understanding of the potential traffic volume and National Airspace System (NAS) capacity for small on-demand aircraft operations. Future demand projections use the Transportation Systems Analysis Model (TSAM), a tool suite developed by NASA and the Transportation Laboratory of Virginia Polytechnic Institute. Demand projections from TSAM contain the mode of travel, number of trips and geographic distribution of trips. For this study, the mode of travel can be commercial aircraft, automobile and on-demand aircraft. NASA's Airspace Concept Evaluation System (ACES) is used to assess NAS impact. This simulation takes a schedule that includes all flights: commercial passenger and cargo; conventional General Aviation and on-demand small aircraft, and operates them in the simulated NAS. The results of this analysis projects very large trip numbers for an on-demand air transportation system competitive with automobiles in cost per passenger mile. The significance is this type of air transportation can enhance mobility for communities that currently lack access to commercial air transportation. Another significant finding is that the large numbers of operations can have an impact on the current NAS infrastructure used by commercial airlines and cargo operators, even if on-demand traffic does not use the 28 airports in the Continental U.S. designated as large hubs by the FAA. Some smaller airports will experience greater demand than their current capacity allows and will require upgrading. In addition, in future years as demand grows and vehicle performance improves other non-conventional facilities such as short runways incorporated into

  9. Electric power supply and demand for the contiguous United States, 1980-1989

    Energy Technology Data Exchange (ETDEWEB)

    None

    1980-06-01

    A limited review is presented of the outlook for the electric power supply and demand during the period 1980 to 1989. Only the adequacy and reliability aspects of bulk electric power supply in the contiguous US are considered. The economic, financial and environmental aspects of electric power system planning and the distribution of electricity (below the transmission level) are topics of prime importance, but they are outside the scope of this report.

  10. Impacts of +2 °C global warming on electricity demand in Europe

    Directory of Open Access Journals (Sweden)

    Andrea Damm

    2017-08-01

    Full Text Available The electricity sector is not only a substantial source of carbon emissions, but also vulnerable to climate change, both due to the growing share of renewables and due to temperature related changes in seasonal demand patterns. In this study we provide information on the impacts of +2 °C global warming on heating and cooling electricity demand for 26 European countries, based on 11 EURO-CORDEX climate simulations, presenting mean changes but also weather-induced changes in peak demand. Smooth transition regression models are used to estimate the relationship between daily electricity consumption and population weighted temperature. Assuming present demographic and economic structures, global warming by 2 °C reduces electricity consumption in most European countries. The reduced heating electricity demand outweighs the increase in cooling demand. The highest decrease in relative terms is found for Norway (up to −5.2%, followed by Sweden, Estonia, Finland, and France. Italy is the only country for which an overall increase in electricity demand is projected. The decrease of electricity demand in absolute terms is projected to be by far the highest in France (between −10 TW h and −16 TW h p. a.. In most countries peak demand of electricity for cooling and heating increases, whereby climate scenario uncertainties in case of heating are high. Altogether, a cross-country comparison heavily suggests that climate is not the main driver for the amount of electricity used for heating and cooling purposes, but rather energy policy.

  11. The Power of Electric Vehicles - Exploring the Value of Flexible Electricity Demand in a Multi-actor Context

    NARCIS (Netherlands)

    Verzijlbergh, R.A.

    2013-01-01

    Electric vehicles (EVs) have the potential to play a crucial role in clean and intelligent power systems. The key to this potential lies in the flexibility that EVs provide by the ability to shift their electricity demand in time. This flexibility can be used to facilitate the integration of

  12. Risk implications of investments in demand response from an aggregator perspective

    DEFF Research Database (Denmark)

    Katz, Jonas; Kitzing, Lena

    2016-01-01

    Aggregators are expected to play an important role in making households provide flexibility to the electricity system. We investigate the business case of aggregators offering a demand response product in a competitive retail market, then directly accessing their customers’ flexibility through...... remotely controlled demand response devices and marketing it on the electricity markets. As the value of flexibility largely relies on price variations, we use a stochastic electricity price model, which we combine with a linear optimisation program and a cash-flow model to determine expected operating...... equipment. Furthermore, a Value-at-Risk analysis shows that income expectations are rather stable with more upside than downside potential. With foreseeable cost reductions for smart devices the aggregator business case might soon become attractive, particularly in markets with high shares of renewable...

  13. The Cobweb Effect in Balancing Markets with Demand Response

    DEFF Research Database (Denmark)

    Larsen, Emil Mahler; Pinson, Pierre; Wang, Jianhui

    2015-01-01

    to control and integrate DR into the power system remains an open question. Integration into existing electricity markets is one option, but dynamic pricing with DR has been observed to be unstable, resulting in oscillations in supply and demand. This socalled Cobweb effect is presented here using the market...... structure and measurements from the EcoGrid EU demonstration, where five minute electricity pricing is sent to 1900 houses. A new tool for quantifying volatility is presented, and the causes for volatility are investigated. A key outcome of this study shows that increases in social welfare due to DR appear...

  14. Simulation-based Strategies for Smart Demand Response

    Directory of Open Access Journals (Sweden)

    Ines Leobner

    2018-03-01

    Full Text Available Demand Response can be seen as one effective way to harmonize demand and supply in order to achieve high self-coverage of energy consumption by means of renewable energy sources. This paper presents two different simulation-based concepts to integrate demand-response strategies into energy management systems in the customer domain of the Smart Grid. The first approach is a Model Predictive Control of the heating and cooling system of a low-energy office building. The second concept aims at industrial Demand Side Management by integrating energy use optimization into industrial automation systems. Both approaches are targeted at day-ahead planning. Furthermore, insights gained into the implications of the concepts onto the design of the model, simulation and optimization will be discussed. While both approaches share a similar architecture, different modelling and simulation approaches were required by the use cases.

  15. Opportunities and Challenges of Demand Response in Active Distribution Grids

    DEFF Research Database (Denmark)

    Ponnaganti, Pavani; Pillai, Jayakrishnan Radhakrishna; Bak-Jensen, Birgitte

    2018-01-01

    -shaving power or help to integrate fluctuating renewable resources. All these DR modes of operation needs conventional regulatory frameworks and market design for capitalizing the available resources. Therefore the objective of the paper is to discuss the DR classification and their control strategies, DR role...... operator to shed the load in order to maintain security of the system. With the advent of advanced smart metering infrastructure, communication between system operator and end-use customers makes it possible to adjust/curtail/shift the demand with respect to the state of the system. The response...... of the demand commonly termed as Demand Response (DR) can be attained either by incentive-based or price-based. With the help of DR, the renewable energy generation capacity can be increased by tuning the demand to match the variable and unpredictable power from renewable generation. It can also bring other...

  16. E3 Success Story - Reducing Electrical Demand in San Antonio, TX

    Science.gov (United States)

    To meet its goal of reducing electrical demand by 9 megawatts CPS Energy in San Antonio, TX partnered with the Texas Manufacturing Assistance Center (TMAC) and the Southwest Research Institute to provide lean, clean and energy efficiency training.

  17. A Methodology for Defining Electricity Demand in Energy Simulations Referred to the Italian Context

    National Research Council Canada - National Science Library

    Paola Caputo; Costa Gaia; Valentina Zanotto

    2013-01-01

      Electricity consumption in Europe is constantly increasing, despite the fact that in recent years, huge efforts in terms of programs and regulations have been made towards energy demand reduction...

  18. A Review of Demand Forecast for Charging Facilities of Electric Vehicles

    Science.gov (United States)

    Jiming, Han; Lingyu, Kong; Yaqi, Shen; Ying, Li; Wenting, Xiong; Hao, Wang

    2017-05-01

    The demand forecasting of charging facilities is the basis of its planning and locating, which has important role in promoting the development of electric vehicles and alleviating the energy crisis. Firstly, this paper analyzes the influence of the charging mode, the electric vehicle population and the user’s charging habits on the demand of charging facilities; Secondly, considering these factors, the recent analysis on charging and switching equipment demand forecast is divided into two methods—forecast based on electric vehicle population and user traveling behavior. Then, the article analyzes the two methods and puts forward the advantages and disadvantages. Finally, in view of the defects of current research, combined with the current situation of the development of the city and comprehensive consideration of economic, political, environmental and other factors, this paper proposes an improved demand forecasting method which has great practicability and pertinence and lays the foundation for the plan of city electric facilities.

  19. Energy Optimization and Management of Demand Response Interactions in a Smart Campus

    Directory of Open Access Journals (Sweden)

    Antimo Barbato

    2016-05-01

    Full Text Available The proposed framework enables innovative power management in smart campuses, integrating local renewable energy sources, battery banks and controllable loads and supporting Demand Response interactions with the electricity grid operators. The paper describes each system component: the Energy Management System responsible for power usage scheduling, the telecommunication infrastructure in charge of data exchanging and the integrated data repository devoted to information storage. We also discuss the relevant use cases and validate the framework in a few deployed demonstrators.

  20. Demand response pilot event conducted August 2,2011 : summary report.

    Energy Technology Data Exchange (ETDEWEB)

    Lincoln, Donald; Evans, Christoper

    2012-01-01

    Energy management in a commercial facility can be segregated into two areas: energy efficiency and demand response (DR). Energy efficiency focuses on steady-state load minimization. Demand response reduces load for event driven periods during the peak load. Demand-response-driven changes in electricity use are designed to be short-term in nature, centered on critical hours during the day when demand is high or when the electricity supplier's reserve margins are low. Due to the recent Federal Energy Regulatory Commission (FERC) Order 745, Demand Response Compensation in Organized Wholesale Energy Markets the potential annual compensation to Sandia National Laboratories (SNL) from performing DR ranges from $300K to $2,400K. While the current energy supply contract does not offer any compensation for participating in DR, there is benefit in understanding the issues and potential value in performing a DR event. This Report will be helpful in upcoming energy supply contract negotiations to quantify the energy savings and power reduction potential from DR at SNL. On August 25, 2011 the Facilities Management and Operations Center (FMOC) performed the first DR pilot event at SNL/NM. This report describes the details and results of this DR event.

  1. Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Marks, Gary [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wilcox, Edmund [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-01-02

    California agricultural irrigation consumes more than ten billion kilowatt hours of electricity annually and has significant potential for contributing to a reduction of stress on the grid through demand response, permanent load shifting, and energy efficiency measures. To understand this potential, a scoping study was initiated for the purpose of determining the associated opportunities, potential, and adoption challenges in California agricultural irrigation. The primary research for this study was conducted in two ways. First, data was gathered and parsed from published sources that shed light on where the best opportunities for load shifting and demand response lie within the agricultural irrigation sector. Secondly, a small limited survey was conducted as informal face-to-face interviews with several different California growers to get an idea of their ability and willingness to participate in permanent load shifting and/or demand response programs. Analysis of the data obtained from published sources and the survey reveal demand response and permanent load shifting opportunities by growing region, irrigation source, irrigation method, grower size, and utility coverage. The study examines some solutions for demand response and permanent load shifting in agricultural irrigation, which include adequate irrigation system capacity, automatic controls, variable frequency drives, and the contribution from energy efficiency measures. The study further examines the potential and challenges for grower acceptance of demand response and permanent load shifting in California agricultural irrigation. As part of the examination, the study considers to what extent permanent load shifting, which is already somewhat accepted within the agricultural sector, mitigates the need or benefit of demand response for agricultural irrigation. Recommendations for further study include studies on how to gain grower acceptance of demand response as well as other related studies such as

  2. The United Kingdom demand for renewable electricity in a liberalised market

    Energy Technology Data Exchange (ETDEWEB)

    Fouquet, R. [Imperial College of Science, Technology and Medicine, London (United Kingdom). Centre for Environmental Technology

    1998-03-01

    This paper analyses how the liberalisation of the UK electricity market in 1998 may encourage demand for renewable electricity through pricing and informational incentives. The analysis argues that prices and beliefs will be crucial for influencing customers` willingness to pay for environmental costs associated with electricity generation, as well as their decision to not just buy the cheapest electricity. In 1998, when UK electricity markets are liberated, a small price differential between renewable and standard electricity - certainly less than 20% - and clear, credible and captivating information about the external costs of electricity generation could create a considerable demand for renewable electricity. But, because renewable generating capacity will initially be small and slow to adjust to incentives, initially high demand may drive up prices, discouraging customers from wanting to buy renewable electricity. Low demand, on the other hand, will not provide the incentives to invest new capacity, which probably means that renewable technology will not be able to reduce its unit costs of electricity generation and compete in a liberalised market without continued financial support. To avoid either scenario, this paper recommends that Government should extend the non-fossil fuel obligation (NFFO) to promote investment in renewable technology, provide tax incentives to minimise the price differential between renewable and standard electricity, encourage non-governmental organisations to develop schemes for providing customers with clear, consistent and reliable information about sources of renewable electricity, and stagger the introduction of electricity liberalisation. While the analysis is of a speculative nature, such policies may create incentives for markets to reduce environmental damage associated with electricity generation. (Author)

  3. Electricity supply and demand scenarios for the Southern African power pool

    CSIR Research Space (South Africa)

    Spalding-Fecher, R

    2017-02-01

    Full Text Available The study presents long-term electricity supply and demand scenarios for the twelve countries in the Southern African Power Pool, based on detailed bottom-up demand analysis for all countries and a set of internally consistent development scenarios...

  4. Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

    Directory of Open Access Journals (Sweden)

    Pedro Faria

    2015-06-01

    Full Text Available Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the present paper is proposes a methodology focusing on the aggregation of consumers and generators, providing adequate tolls for the demand response program’s adoption by evolved players. The methodology proposed in the present paper focuses on a Virtual Power Player that manages and aggregates the available demand response and distributed generation resources in order to satisfy the required electrical energy demand and reserve. The aggregation of resources is addressed by the use of clustering algorithms, and operation costs for the VPP are minimized. The presented case study is based on a set of 32 consumers and 66 distributed generation units, running on 180 distinct operation scenarios.

  5. Estimating short and long-term residential demand for electricity. New evidence from Sri Lanka

    Energy Technology Data Exchange (ETDEWEB)

    Athukorala, P.P.A Wasantha; Wilson, Clevo [School of Economics and Finance, Queensland University of Technology, Brisbane (Australia)

    2010-09-15

    This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand - per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas - using annual data for Sri Lanka for the period, 1960-2007. The study uses unit root, cointegration and error-correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, - 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 0.32, - 0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity of 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity and (4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages in the country. (author)

  6. Evaluation of Representative Smart Grid Investment Project Technologies: Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Fuller, Jason C.; Prakash Kumar, Nirupama; Bonebrake, Christopher A.

    2012-02-14

    This document is one of a series of reports estimating the benefits of deploying technologies similar to those implemented on the Smart Grid Investment Grant (SGIG) projects. Four technical reports cover the various types of technologies deployed in the SGIG projects, distribution automation, demand response, energy storage, and renewables integration. A fifth report in the series examines the benefits of deploying these technologies on a national level. This technical report examines the impacts of a limited number of demand response technologies and implementations deployed in the SGIG projects.

  7. Impacts of +2 °C global warming on electricity demand in Europe

    OpenAIRE

    Damm, Andrea; Köberl, Judith; Prettenthaler, Franz; Rogler, Nikola; Töglhofer, Christoph

    2017-01-01

    The electricity sector is not only a substantial source of carbon emissions, but also vulnerable to climate change, both due to the growing share of renewables and due to temperature related changes in seasonal demand patterns. In this study we provide information on the impacts of +2 °C global warming on heating and cooling electricity demand for 26 European countries, based on 11 EURO-CORDEX climate simulations, presenting mean changes but also weather-induced changes in peak demand. Smooth...

  8. Estimated performance of solar PV and wind turbine systems compared to coincident electrical demand in Minnesota

    Energy Technology Data Exchange (ETDEWEB)

    Artig, R. [Minnesota Dept. of Public Service, St. Paul, MN (United States)

    1995-10-01

    The Minnesota Department of Public Service (department), with the cooperation of Northern States Power (NSP) and US Department of Energy, is making a detailed study of wind and solar resources in the Buffalo Ridge area of southwestern Minnesota. The purpose of the study is to determine the viability of using a combination of wind and solar generation facilities to help meet electrical demand in the region. Through the Solar/Wind Study, five monitoring sites have been established to collect solar radiation and temperature data as well as to record wind speed and direction information at multiple elevations. In this paper, the data from the first year of the Solar/Wind Study are used to directly compare the projected hourly production of electricity from the wind and solar resources to hourly electrical demand. This study compares the potential electrical production from these renewable resources concurrent with peak or near peak occurrences in electrical demand. The electrical demand information used in this study is from two utilities: NSP, a utility that supplies electricity to a combination of urban residential, commercial, and industrial customers; and Cooperative Power (CP), which provides power primarily to suburban and rural residential customers. Estimates of the performance of solar PV systems were made using PVFORM, a simulation program from Sandia National Laboratories. Analysis of first year data indicates that the availability of electricity generated from a combination of solar and wind resources matches period of high peak demand for Northern States Power. The value of adding wind and solar generated electricity to the utility`s resource mix merits further investigation. The match between solar and wind power availability and Cooperative Power`s peak demand period is not apparent, but here, too, further study is needed.

  9. A long- and short-run analysis of electricity demand in Ciudad Juarez

    Science.gov (United States)

    Mendez-Carrillo, Ericka Cecilia

    Economic growth and appliance saturation are increasing electricity consumption in Mexico. Annual frequency data from 1990 to 2012 are utilized to develop an error correction framework that sheds light on short- and long-run electricity consumption behavior in Ciudad Juarez, a large Mexican metropolitan economy at the border with the United States. The results for this study reveal that electricity is an inelastic normal good in this market. Moreover, natural gas is found to be a weak complement to electricity. With regards to the customer base in this urban economy, population, employment, and income exercise positive and statistically significant impacts on the demand for electricity hook-ups.

  10. Demand Response an Alternative Solution to Prevent Load Shedding Triggering

    Directory of Open Access Journals (Sweden)

    K. Mollah

    2014-12-01

    Full Text Available This paper investigates an alternative solution to prevent Load Shedding (LS triggering during underfrequency and proposes a new technique to restore the frequency during emergency events. Demand response (DR is considered as one of the most promising Smart Grid concepts that can be used to support the peak demand, whereas, LS is an existing last resort method during emergency grid situations. Both schemes aim to balance the load and generation in real-time and restore the frequency very quickly. This paper incorporates integrating Incentive based Demand Response (IDR with spinning reserve for smaller underfrequency events to manage the system peak demand. It also introduces a new frequency band for an Emergency Demand Response (EDR as an alternative inexpensive solution that can replace costly spinning reserves and help to prevent LS. An energy index factor is used to identify the consumption pattern of consumers to enable them to participate in IDR. An illustrative example of the performance of the proposed scheme on a modified 15 bus test system is shown. Simulation results on different scenarios confirm that the proposed method is effective to improve the frequency restoration process along with enabling participation of new services.

  11. Approaches for Accommodating Demand Response in Operational Problems and Assessing its Value

    DEFF Research Database (Denmark)

    O'Connell, Niamh

    welfare value it generates by reducing overall power system operation costs, and the commercial value it can accrue by participating in competitive electricity markets. Social welfare value provides an indicator of the viability of any new power system resource, but does not guarantee that the necessary...... in this thesis that the value offered by demand response is very low under current power system conditions, and when it is restricted to operating within existing operational frameworks. Prices and costs on the studied power systems are insufficient to allow demand response to generate significant value......This thesis deals with the development of operational models of demand response and the evaluation of this novel resource within existing frameworks for power system dispatch and market clearing. Increasing shares of power generation from variable renewable sources, and climate change policies...

  12. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes.

    Science.gov (United States)

    Kelly, Jack; Knottenbelt, William

    2015-01-01

    Many countries are rolling out smart electricity meters. These measure a home's total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the 'ground truth' demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

  13. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes

    Science.gov (United States)

    Kelly, Jack; Knottenbelt, William

    2015-03-01

    Many countries are rolling out smart electricity meters. These measure a home’s total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the ‘ground truth’ demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

  14. Energy Systems Scenario Modelling and Long Term Forecasting of Hourly Electricity Demand

    DEFF Research Database (Denmark)

    Alberg Østergaard, Poul; Møller Andersen, Frits; Kwon, Pil Seok

    2015-01-01

    . The results show that even with a limited short term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrate wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant...... or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model...... effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps...

  15. Hybrid Forecasting Approach Based on GRNN Neural Network and SVR Machine for Electricity Demand Forecasting

    Directory of Open Access Journals (Sweden)

    Weide Li

    2017-01-01

    Full Text Available Accurate electric power demand forecasting plays a key role in electricity markets and power systems. The electric power demand is usually a non-linear problem due to various unknown reasons, which make it difficult to get accurate prediction by traditional methods. The purpose of this paper is to propose a novel hybrid forecasting method for managing and scheduling the electricity power. EEMD-SCGRNN-PSVR, the proposed new method, combines ensemble empirical mode decomposition (EEMD, seasonal adjustment (S, cross validation (C, general regression neural network (GRNN and support vector regression machine optimized by the particle swarm optimization algorithm (PSVR. The main idea of EEMD-SCGRNN-PSVR is respectively to forecast waveform and trend component that hidden in demand series to substitute directly forecasting original electric demand. EEMD-SCGRNN-PSVR is used to predict the one week ahead half-hour’s electricity demand in two data sets (New South Wales (NSW and Victorian State (VIC in Australia. Experimental results show that the new hybrid model outperforms the other three models in terms of forecasting accuracy and model robustness.

  16. Day-Ahead Congestion Management in Distribution Systems through Household Demand Response and Distribution Congestion Prices

    DEFF Research Database (Denmark)

    Liu, Weijia; Wu, Qiuwei; Wen, Fushuan

    2014-01-01

    , the proposed DCPs are able to reflect the real congestion cost and further direct the schedule of the responses of electric demands. Based on the NordPool Spot market structure, the interactions between aggregators and the distribution system operator (DSO) are discussed, and the procedure for calculating DCPs......With the development of smart grid technologies, some of the electric demands which are traditionally considered fixed and inflexible will become promising distributed energy resources (DERs) in future power systems. However, the participation of small scale or household energy sources...... into balancing power might challenge the operation of electric distribution systems and cause congestions. This paper presents a distribution congestion price (DCP) based market mechanism to alleviate possible distribution system congestions. By employing the loca- tional marginal pricing (LMP) model...

  17. On the demand for prescription drugs: heterogeneity in price responses.

    Science.gov (United States)

    Skipper, Niels

    2013-07-01

    This paper estimates the price elasticity of demand for prescription drugs using an exogenous shift in consumer co-payment caused by a reform in the Danish subsidy scheme for the general public. Using purchasing records for the entire Danish population, I show that the average price response for the most commonly used drug yields demand elasticities in the range of -0.36 to -0.5. The reform is shown to affect women, the elderly, and immigrants the most. Furthermore, this paper shows significant heterogeneity in the price response over different types of antibiotics, suggesting that the price elasticity of demand varies considerably even across relatively similar drugs. Copyright © 2012 John Wiley & Sons, Ltd.

  18. Price freezes, durables and residential electricity demand - Evidence from the Greater Buenos Aires

    Energy Technology Data Exchange (ETDEWEB)

    Casarin, Ariel; Delfino, Maria Eugenia

    2010-09-15

    This paper examines the determinants of residential electricity demand in the Greater Buenos Aires between 1997 and 2006. During the second half of this period, residential tariffs remained nominally fixed, while an income boom boosted up the sales of durables. This study differs from previous works in that it explicitly considers the impact of the stock of air-conditioners on residential demand. The paper reports short- and long-run elasticities and examines the contribution of prices and durables to recent demand growth. Simulations illustrate the impact of prices and durables on future demand.

  19. An Assessment of Global Electric-Sector Water Demands to 2100 under the Latest Scenarios

    Science.gov (United States)

    Ando, N.; Yoshikawa, S.; Kanae, S.

    2016-12-01

    Electricity demands are likely to continue growing in the coming decades, due to population and economy growth. The electric growth could lead water demands to increase because some kinds of power generation methods such as thermal power generation require large amount of water. Many countries still rely on thermal power generation. Thus, we are concerned that electricity generation could be a big factor to accelerate water scarcity. In this study, to assess the electric-sector impacts on water demands, we estimated future electric-sector water withdrawal and consumption in 17 regions from 2010 to 2100. The water withdrawal and consumption are calculated by using electricity generation and water demand intensities. The data set of future electricity generation is derived by the Asia-Pacific Integrated Model. This model applied the latest scenarios for global climate change studies, the socio-economic scenario (SSPs) and the radiative forcing scenario (RCPs). We used the water demands intensity data set of Macknick et al. (2012). Water demand intensities for power plants considerably varies by power plant cooling systems. Therefore, we constructed cooling system share scenarios. Our results indicated that by 2100, the water withdrawal and consumption in current developing countries increased and caught up with that in current developed countries. We found that socio-economic scenarios (SSPs) has large impacts on the water withdrawal and consumption. Sustainable society (SSP1) and conventional development society (SSP5) have higher economic growth than fragmentation society (SSP3). The sustainable society needs smaller amount of the water withdrawal and consumption compared with fragmentation society. In contrast, the conventional development society needs larger amount of the water withdrawal and consumption compared with fragmentation society. Therefore, higher economic growth did not always lead less electric-sector water withdrawal and consumption. A shift of

  20. Electric Boiler and Heat Pump Thermo-Electrical Models for Demand Side Management Analysis in Low Voltage Grids

    DEFF Research Database (Denmark)

    Diaz de Cerio Mendaza, Iker; Bak-Jensen, Birgitte; Chen, Zhe

    2013-01-01

    The last fifteen years many European countries have integrated large percentage of renewable energy on their electricity generation mix. In Denmark the 21.3% of the electricity consumed nowadays is produced by the wind, and it has planned to be the 50% by 2025. In order to front future challenges...... as active loads. The models were simulated under different Danish daily domestic hot water and space heating profiles. Results showed that under high heating demand conditions the flexibility of this kind of units may be drastically restricted due to their continuous operation....... on the power system control and operation, created by this unstable way of generation, Demand Side Management turns to be a promising solution. The storage capacity from thermo-electric units, like electric boilers and heat pumps, allows operating them with certain freedom. Hence they can be employed under...

  1. Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

    DEFF Research Database (Denmark)

    Soares, Tiago; Faria, Pedro; Vale, Zita

    2014-01-01

    The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the wh......The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits...... the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity...

  2. The Effect of Temperature on the Electricity Demand: An Empirical Investigation

    Science.gov (United States)

    Kim, H.; Kim, I. G.; Park, K. J.; Yoo, S. H.

    2015-12-01

    This paper attempts to estimate the electricity demand function in Korea with quarterly data of average temperature, GDP and electricity price over the period 2005-2013. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the electricity demand function. The results show that short-run price and income elasticities of the electricity demand are estimated to be -0.569 and 0.631 respectively. They are statistically significant at the 1% level. Moreover, long-run income and price elasticities are estimated to be 1.589 and -1.433 respectively. Both of results reveal that the demand for electricity demand is about 15.2℃. It is shown that power of explanation and goodness-of-fit statistics are improved in the use of the lagged dependent variable model rather than conventional model. Acknowledgements: This research was carried out as a part of "Development and application of technology for weather forecast" supported by the 2015 National Institute of Meteorological Research (NIMR) in the Korea Meteorological Administration.

  3. Improving demand response potential of a supermarket refrigeration system

    DEFF Research Database (Denmark)

    Pedersen, Rasmus; Schwensen, John; Biegel, Benjamin

    2017-01-01

    through tests on a full scale supermarket refrigeration system made available by Danfoss A/S. The conducted application test shows that feedback based on food temperature can increase the demand flexibility during a step by approx. 60 % the first 70 minutes and up to 100%over the first 150 minutes...... a method for estimating food temperature based on measurements of evaporator expansion valve opening degree. This method requires no additional hardware or system modeling. We demonstrate the estimation method on a real supermarket display case and the applicability of knowing food temperature is shown...... - thereby strengthening the demand response potential of supermarket refrigeration systems....

  4. Opportunities for Automated Demand Response in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Faulkner, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2012-12-20

    This report details a study into the demand response potential of a large wastewater treatment facility in San Francisco. Previous research had identified wastewater treatment facilities as good candidates for demand response and automated demand response, and this study was conducted to investigate facility attributes that are conducive to demand response or which hinder its implementation. One years' worth of operational data were collected from the facility's control system, submetered process equipment, utility electricity demand records, and governmental weather stations. These data were analyzed to determine factors which affected facility power demand and demand response capabilities The average baseline demand at the Southeast facility was approximately 4 MW. During the rainy season (October-March) the facility treated 40% more wastewater than the dry season, but demand only increased by 4%. Submetering of the facility's lift pumps and centrifuges predicted load shifts capabilities of 154 kW and 86 kW, respectively, with large lift pump shifts in the rainy season. Analysis of demand data during maintenance events confirmed the magnitude of these possible load shifts, and indicated other areas of the facility with demand response potential. Load sheds were seen to be possible by shutting down a portion of the facility's aeration trains (average shed of 132 kW). Load shifts were seen to be possible by shifting operation of centrifuges, the gravity belt thickener, lift pumps, and external pump stations These load shifts were made possible by the storage capabilities of the facility and of the city's sewer system. Large load reductions (an average of 2,065 kW) were seen from operating the cogeneration unit, but normal practice is continuous operation, precluding its use for demand response. The study also identified potential demand response opportunities that warrant further study: modulating variable-demand aeration loads, shifting

  5. Evaluation and assessment of demand response potential applied to the meat industry

    OpenAIRE

    Alcázar Ortega, Manuel; Álvarez Bel, Carlos María; Escrivá Escrivá, Guillermo; Domijan, Alexander

    2012-01-01

    Demand response has proven to be a useful mechanism that produces important benefits for both the customer and the power system. In the context of an increasingly competitive electricity market, where prices are constantly rising and the presence of renewable energy resources is gaining prominence, this paper analyzes the flexibility potential of customers in the meat industry, based on the management of the most energy consuming process in this type of segment: cooling production...

  6. Distribution transformer lifetime analysis in the presence of demand response and rooftop PV integration

    OpenAIRE

    Behi Behnaz; Arefi Ali; Pezeshki Houman; Shahnia Farhad

    2017-01-01

    Many distribution transformers have already exceeded half of their expected service life of 35 years in the infrastructure of Western Power, the electric distribution company supplying southwest of Western Australia, Australia. Therefore, it is anticipated that a high investment on transformer replacement happens in the near future. However, high renewable integration and demand response (DR) are promising resources to defer the investment on infrastructure upgrade and extend the lifetime of ...

  7. Assessment of factors affecting industrial electricity demand. Final report (revision version)

    Energy Technology Data Exchange (ETDEWEB)

    None

    1983-07-01

    In Chapter 2, we identify those factors affecting the industrial product mix - taste, relative output prices, and relative input prices - and isolate several determinants which have not been adequately accounted for to date in industrial electricity demand forecasts. We discuss how the lower energy prices of foreign producers affect domestic producers and how the growth in the number of substitutes for intermediate products such as steel and aluminum with plastics and composites affects the composition of production and, hence, the demand for electricity. We also investigate how the changing age structure of the population brought on by the baby boom could change the mix of outputs produced by the industrial sector. In Chapter 3, we review the history of the 1970s with regard to changes in output mix and the manufacturing demand for electricity, and with regard to changes in the use of electricity vis-a-vis the other inputs in the production process. In Chapter 4, we generate forecasts using two models which control for efficiency changes, but in different ways. In this chapter we present the sensitivity of these projections using three sets of assumptions about product mix. The last chapter summarizes our results and draw from those results implications regarding public policy and industrial electricity demand. Two appendices present ISTUM2 results from selected electricity intensive industries, describes the ISTUM and ORIM models.

  8. Efficient Customer Selection for Sustainable Demand Response in Smart Grids

    Energy Technology Data Exchange (ETDEWEB)

    Zois, Vasileios; Frincu, Marc; Chelmis, Charalambos; Saeed, Muhammad Rizwan; Prasanna, Viktor K.

    2014-11-03

    Regulating the power consumption to avoid peaks in demand is a common practice. Demand Response(DR) is being used by utility providers to minimize costs or ensure system reliability. Although it has been used extensively there is a shortage of solutions dealing with dynamic DR. Past attempts focus on minimizing the load demand without considering the sustainability of the reduced energy. In this paper an efficient algorithm is presented which solves the problem of dynamic DR scheduling. Data from the USC campus micro grid were used to evaluate the efficiency as well as the robustness of the proposed solution. The targeted energy reduction is achieved with a maximum average approximation error of ≈ 0.7%. Sustainability of the reduced energy is achieved with respect to the optimal available solution providing a maximum average error less than 0.6%. It is also shown that a solution is provided with a low computational cost fulfilling the requirements of dynamic DR.

  9. ON THE DEMAND DYNAMICS OF ELECTRICITY IN GHANA: DO EXOGENOUS NON-ECONOMIC VARIABLES COUNT?

    Directory of Open Access Journals (Sweden)

    Ishmael Ackah

    2014-04-01

    Full Text Available The purpose of this study is to identify and quantify the effect of endogenous and exogenous economic factors on electricity demand in Ghana. The Structural Time Series Model is employed due to its ability to capture exogenous non-economic variables. The findings reveal that education has significant effect on electricity consumption in both the short and the long run. Education has inverse relationship with electricity consumption implying that the more consumers are educated, the less electricity they consume. The study also reveals that price changes have less impact on electricity consumption in the short run and that efficiency in electricity consumption has improved since 1971 and will continue for the next twenty years. The study recommends that more public education should be carried out to enhance energy conservation and also, realistic prices should be charge for electricity consumption to allow private investment into the sector.

  10. The Risk of Residential Peak Electricity Demand: A Comparison of Five European Countries

    Directory of Open Access Journals (Sweden)

    Jacopo Torriti

    2017-03-01

    Full Text Available The creation of a Europe-wide electricity market combined with the increased intermittency of supply from renewable sources calls for an investigation into the risk of aggregate peak demand. This paper makes use of a risk model to assess differences in time-use data from residential end-users in five different European electricity markets. Drawing on the Multinational Time-Use Survey database, it assesses risk in relation to the probability of electrical appliance use within households for five European countries. Findings highlight in which countries and for which activities the risk of aggregate peak demand is higher and link smart home solutions (automated load control, dynamic pricing and smart appliances to different levels of peak demand risk.

  11. Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

    DEFF Research Database (Denmark)

    Morais, Hugo; Sousa, Tiago; Vale, Zita

    2014-01-01

    be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve...... and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32...... for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs...

  12. Data-driven Demand Response Characterization and Quantification

    DEFF Research Database (Denmark)

    Le Ray, Guillaume; Pinson, Pierre; Larsen, Emil Mahler

    2017-01-01

    Analysis of load behavior in demand response (DR) schemes is important to evaluate the performance of participants. Very few real-world experiments have been carried out and quantification and characterization of the response is a difficult task. Nevertheless it will be a necessary tool...... for portfolio management of consumers in a DR framework. In this paper we develop methods to quantify and characterize the amount of DR in a load. The contribution to the aggregated load from each household is quantified on a daily basis, showing the potential variability of the response in time. Clustering...

  13. Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Kiliccote, Sila; Piette, Mary Ann; Mathieu, Johanna; Parrish, Kristen

    2010-05-14

    California is a leader in automating demand response (DR) to promote low-cost, consistent, and predictable electric grid management tools. Over 250 commercial and industrial facilities in California participate in fully-automated programs providing over 60 MW of peak DR savings. This paper presents a summary of Open Automated DR (OpenADR) implementation by each of the investor-owned utilities in California. It provides a summary of participation, DR strategies and incentives. Commercial buildings can reduce peak demand from 5 to 15percent with an average of 13percent. Industrial facilities shed much higher loads. For buildings with multi-year savings we evaluate their load variability and shed variability. We provide a summary of control strategies deployed, along with costs to install automation. We report on how the electric DR control strategies perform over many years of events. We benchmark the peak demand of this sample of buildings against their past baselines to understand the differences in building performance over the years. This is done with peak demand intensities and load factors. The paper also describes the importance of these data in helping to understand possible techniques to reach net zero energy using peak day dynamic control capabilities in commercial buildings. We present an example in which the electric load shape changed as a result of a lighting retrofit.

  14. Modeling demand for electric vehicles: the effect of car users' attitudes and perceptions

    OpenAIRE

    Glerum, Aurélie; Thémans, Michaël; Bierlaire, Michel

    2011-01-01

    The near arrival of electric vehicles on the car market generates a need for new models in order to understand and predict the impact it has on the current market shares. This research aims at providing contributions regarding several issues related to the evaluation of the demand for electric vehicles, i.e. related to the survey design, demand models and forecasting. In this paper we focus on the first of these three methodological issues. We present the design of a stated preference survey ...

  15. Forecasting electricity demand in South Africa: A critique of Eskom’s projections

    Directory of Open Access Journals (Sweden)

    Anastassios Pouris

    2010-03-01

    Full Text Available Within a short period, Eskom has applied to the National Energy Regulator of South Africa (NERSA for the third time since the 2008 electricity crisis, proposing a multiyear price determination for the periods 2010−2011 and 2012−2013. The new application, submitted at the end of September 2009, motivated for the debate of strategies with which the consequences of the proposed price hikes could be predicted, measured and controlled. In his presentation to Parliament in February 2009, Eskom’s then CEO, Mr Jacob Maroga presented the current energy situation in the country, the reasons for the crisis in 2007−2008, as well as the challenges of the future. The purpose of this paper is to contribute some new ideas and perspectives to Eskom’s existing arguments regarding the demand for electricity. The most important issue is the fact that Eskom does not sufficiently take into account the impact of the electricity prices in their electricity demand forecast. This study proposed that prices have a high impact on the demand for electricity (price elasticity of -0.5. Employing similar assumptions for the country’s economic growth as Eskom, the results of the forecasting exercise indicated a substantial decrease in demand (scenario 1: -31% in 2025 and scenario 2:-18% in 2025. This study’s findings contrasted significantly with Eskom’s projection, which has extensive implications as far as policy is concerned.

  16. Stochastic Security and Risk-Constrained Scheduling for an Autonomous Microgrid with Demand Response and Renewable Energy Resources

    DEFF Research Database (Denmark)

    Vahedipour-Dahraie, Mostafa; Rashidizadeh-Kermani, Homa; Najafi, Hamid Reza

    2017-01-01

    Increasing penetration of intermittent renewable energy sources and the development of advanced information give rise to questions on how responsive loads can be managed to optimise the use of resources and assets. In this context, demand response as a way for modifying the consumption pattern...... of customers can be effectively applied to balance the demand and supply in electricity networks. This study presents a novel stochastic model from a microgrid (MG) operator perspective for energy and reserve scheduling considering risk management strategy. It is assumed that the MG operator can procure energy...... from various sources, including local generating units and demand-side resources to serve the customers. The operator sells electricity to customers under real-time pricing scheme and the customers response to electricity prices by adjusting their loads to reduce consumption costs. The objective...

  17. Approaches to Enable Demand Response by Industrial Loads for Ancillary Services Provision

    Science.gov (United States)

    Zhang, Xiao

    Demand response has gained significant attention in recent years as it demonstrates potentials to enhance the power system's operational flexibility in a cost-effective way. Industrial loads such as aluminum smelters, steel manufacturers, and cement plants demonstrate advantages in supporting power system operation through demand response programs, because of their intensive power consumption, already existing advanced monitoring and control infrastructure, and the strong economic incentive due to the high energy costs. In this thesis, we study approaches to efficiently integrate each of these types of manufacturing processes as demand response resources. The aluminum smelting process is able to change its power consumption both accurately and quickly by controlling the pots' DC voltage, without affecting the production quality. Hence, an aluminum smelter has both the motivation and the ability to participate in demand response. First, we focus on determining the optimal regulation capacity that such a manufacturing plant should provide. Next, we focus on determining its optimal bidding strategy in the day-ahead energy and ancillary services markets. Electric arc furnaces (EAFs) in steel manufacturing consume a large amount of electric energy. However, a steel plant can take advantage of time-based electricity prices by optimally arranging energy-consuming activities to avoid peak hours. We first propose scheduling methods that incorporate the EAFs' flexibilities to reduce the electricity cost. We then propose methods to make the computations more tractable. Finally, we extend the scheduling formulations to enable the provision of spinning reserve. Cement plants are able to quickly adjust their power consumption rate by switching on/off the crushers. However, switching on/off the loading units only achieves discrete power changes, which restricts the load from offering valuable ancillary services such as regulation and load following, as continuous power changes

  18. Spatial–Temporal Analysis of the Heat and Electricity Demand of the Swiss Building Stock

    Directory of Open Access Journals (Sweden)

    Stefan Schneider

    2017-08-01

    Full Text Available In 2015, space heating and domestic hot water production accounted for around 40% of the Swiss final energy consumption. Reaching the goals of the 2050 energy strategy will require significantly reducing this share despite the growing building stock. Renewables are numerous but subject to spatial–temporal constraints. Territorial planning of energy distribution systems enabling the integration of renewables requires having a spatial–temporal characterization of the energy demand. This paper presents two bottom-up statistical extrapolation models for the estimation of the geo-dependent heat and electricity demand of the Swiss building stock. The heat demand is estimated by means of a statistical bottom-up model applied at the building level. At the municipality level, the electricity load curve is estimated by combining socio-economic indicators with average consumption per activity and/or electric device. This approach also allows to break down the estimated electricity demand according to activity type (e.g., households, various industry, and service activities and appliance type (e.g., lighting, motor force, fridges. The total estimated aggregated demand is 94 TWh for heat and 58 TWh for electricity, which represent a deviation of 2.9 and 0.5%, respectively compared to the national energy consumption statistics. In addition, comparisons between estimated and measured electric load curves are done to validate the proposed approach. Finally, these models are used to build a geo-referred database of heat and electricity demand for the entire Swiss territory. As an application of the heat demand model, a realistic saving potential is estimated for the existing building stock; this potential could be achieved through by a deep retrofit program. One advantage of the statistical bottom-up model approach is that it allows to simulate a building stock that replicates the diversity of building demand. This point is important in order to

  19. Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Page, Janie; Kiliccote, Sila; Dudley, Junqiao Han; Piette, Mary Ann; Chiu, Albert K.; Kellow, Bashar; Koch, Ed; Lipkin, Paul

    2011-07-01

    Small and medium commercial customers in California make up about 20-25% of electric peak load in California. With the roll out of smart meters to this customer group, which enable granular measurement of electricity consumption, the investor-owned utilities will offer dynamic prices as default tariffs by the end of 2011. Pacific Gas and Electric Company, which successfully deployed Automated Demand Response (AutoDR) Programs to its large commercial and industrial customers, started investigating the same infrastructures application to the small and medium commercial customers. This project aims to identify available technologies suitable for automating demand response for small-medium commercial buildings; to validate the extent to which that technology does what it claims to be able to do; and determine the extent to which customers find the technology useful for DR purpose. Ten sites, enabled by eight vendors, participated in at least four test AutoDR events per site in the summer of 2010. The results showed that while existing technology can reliably receive OpenADR signals and translate them into pre-programmed response strategies, it is likely that better levels of load sheds could be obtained than what is reported here if better understanding of the building systems were developed and the DR response strategies had been carefully designed and optimized for each site.

  20. Machine learning for identifying demand patterns of home energy management systems with dynamic electricity pricing

    NARCIS (Netherlands)

    Koolen, D. (Derck); Sadat-Razavi, N. (Navid); W. Ketter (Wolfgang)

    2017-01-01

    textabstractEnergy management plays a crucial role in providing necessary system flexibility to deal with the ongoing integration of volatile and intermittent energy sources. Demand Response (DR) programs enhance demand flexibility by communicating energy market price volatility to the end-consumer.

  1. Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Karin Kandananond

    2011-08-01

    Full Text Available Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA, artificial neural network (ANN and multiple linear regression (MLR—were utilized to formulate prediction models of the electricity demand in Thailand. The objective was to compare the performance of these three approaches and the empirical data used in this study was the historical data regarding the electricity demand (population, gross domestic product: GDP, stock index, revenue from exporting industrial products and electricity consumption in Thailand from 1986 to 2010. The results showed that the ANN model reduced the mean absolute percentage error (MAPE to 0.996%, while those of ARIMA and MLR were 2.80981 and 3.2604527%, respectively. Based on these error measures, the results indicated that the ANN approach outperformed the ARIMA and MLR methods in this scenario. However, the paired test indicated that there was no significant difference among these methods at α = 0.05. According to the principle of parsimony, the ARIMA and MLR models might be preferable to the ANN one because of their simple structure and competitive performance

  2. Demand response evaluation and forecasting — Methods and results from the EcoGrid EU experiment

    DEFF Research Database (Denmark)

    Larsen, Emil Mahler; Pinson, Pierre; Leimgruber, Fabian

    2017-01-01

    into a real-time market. EcoGrid EU is a smart grid experiment with 1900 residential customers who are equipped with smart meters and automated devices reacting to five-minute electricity pricing. Customers are grouped and analysed according to the manufacturer that controlled devices. A number of advanced......Understanding electricity consumers participating in new demand response schemes is important for investment decisions and the design and operation of electricity markets. Important metrics include peak response, time to peak response, energy delivered, ramping, and how the response changes...... with respect to external conditions. Such characteristics dictate the services DR is capable of offering, like primary frequency reserves, peak load shaving, and system balancing. In this paper, we develop methods to characterise price-responsive demand from the EcoGrid EU demonstration in a way that was bid...

  3. The Impact of Uncertain Physical Parameters on HVAC Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Yannan; Elizondo, Marcelo A.; Lu, Shuai; Fuller, Jason C.

    2014-03-01

    HVAC units are currently one of the major resources providing demand response (DR) in residential buildings. Models of HVAC with DR function can improve understanding of its impact on power system operations and facilitate the deployment of DR technologies. This paper investigates the importance of various physical parameters and their distributions to the HVAC response to DR signals, which is a key step to the construction of HVAC models for a population of units with insufficient data. These parameters include the size of floors, insulation efficiency, the amount of solid mass in the house, and efficiency of the HVAC units. These parameters are usually assumed to follow Gaussian or Uniform distributions. We study the effect of uncertainty in the chosen parameter distributions on the aggregate HVAC response to DR signals, during transient phase and in steady state. We use a quasi-Monte Carlo sampling method with linear regression and Prony analysis to evaluate sensitivity of DR output to the uncertainty in the distribution parameters. The significance ranking on the uncertainty sources is given for future guidance in the modeling of HVAC demand response.

  4. Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand.

    Directory of Open Access Journals (Sweden)

    Jim Lewis

    Full Text Available Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers' peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers' location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs such as tariffs, price, managed supply, etc., in a conceptual 'map' of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each

  5. Systems Modelling of the Socio-Technical Aspects of Residential Electricity Use and Network Peak Demand.

    Science.gov (United States)

    Lewis, Jim; Mengersen, Kerrie; Buys, Laurie; Vine, Desley; Bell, John; Morris, Peter; Ledwich, Gerard

    2015-01-01

    Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers' peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers' location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual 'map' of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations

  6. Adaptation possibilities of the nuclear electricity production to the demand; Possibilites d'adaptation de la production d'electricite nucleaires a la demande

    Energy Technology Data Exchange (ETDEWEB)

    Acket, C

    2009-02-15

    Meeting about the CO{sub 2} emissions from electric heating showed that the leak of adaptation from nuclear reactors led the use of thermal power plants (coal, petroleum, gas) to control the demand variations. This argument is analyzed in the document: is it possible to replace those thermal power plants by nuclear reactors? In this framework the author analyzes the network needs, the electricity sources and the demand answer and the specificities of the nuclear. (A.L.B.)

  7. A Methodology for Defining Electricity Demand in Energy Simulations Referred to the Italian Context

    Directory of Open Access Journals (Sweden)

    Paola Caputo

    2013-12-01

    Full Text Available Electricity consumption in Europe is constantly increasing, despite the fact that in recent years, huge efforts in terms of programs and regulations have been made towards energy demand reduction and energy systems improvement. Since the electricity demand affects both the operation of the supply and distribution plants and the thermal loads of buildings, the importance of providing a proper definition of demand profiles is evident. The main aim of the paper is to provide a set of standard electricity profiles that can reasonably be adopted as input in energy simulations related to the built environment, with particular regards to the Italian context. The work presented in this paper originated within a wider long lasting research aimed at developing a platform for buildings’ energy simulations at district level, with particular reference to the Italian conditions. In this context, it was necessary to define hourly profiles regarding both occupancy and electricity use for lighting and appliances related to different building uses and typologies. For this purpose, the main methods and references for defining electricity loads in buildings were evaluated and average hourly profiles were accordingly developed for residential and commercial buildings. Then the related internal gains were determined and compared to the current Italian standards.

  8. An integrated assessment of global and regional water demands for electricity generation to 2095

    Science.gov (United States)

    Davies, Evan G. R.; Kyle, Page; Edmonds, James A.

    2013-02-01

    Electric power plants account for approximately half the global industrial water withdrawal. Although continued electric-sector expansion is probable, significant variations in water intensity by electricity technology and cooling system type make its effects on water demands uncertain. Using GCAM, an integrated assessment model of energy, agriculture, and climate change, we establish lower-, median-, and upper-bound estimates for current electric-sector water withdrawals and consumption in 14 geopolitical regions, and compare them with available estimates. We then explore water use for electricity to 2095, focusing on uncertainties in water withdrawal and consumption intensities, power plant cooling system changes, and adoption rates of water-saving technologies. Results reveal a probable decrease in the water withdrawal intensity with capital stock turnover, but a corresponding increase in consumptive use, for which technologies under development may compensate. At a regional scale, water use varies significantly based on the existing capital stock and its evolution over the century.

  9. Distributed generation and demand response dispatch for a virtual power player energy and reserve provision

    DEFF Research Database (Denmark)

    Faria, Pedro; Soares, Tiago; Vale, Zita

    2014-01-01

    operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper...... proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources’ participation can be performed in both energy and reserve contexts. This methodology contemplates...... the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers....

  10. Efficient Use of Behavioral Tools to Reduce Electricity Demand of Domestic Consumers

    Directory of Open Access Journals (Sweden)

    Elbaz Shimon

    2016-12-01

    Full Text Available Purpose: The present study investigated the main literature on the subject of methods and policies for reducing the electricity demand of domestic consumers, in order to identify the place of behavioral tools. Methodology: We used secondary sources, performing a literature review, together with analysis and synthesis. Findings: Policy makers prefer to use tools offered by neoclassical economics, such as various forms of taxation, fines and financial incentives in order to make domestic electricity consumers save electricity, on the assumption that consumers will make rational decisions while maximizing their personal benefit. However, studies conducted in recent years in the field of behavioral economics, which are based on the assumption that consumers’ decisions are not rational and are affected by cognitive biases, showed that the use of behavioral tools, such as detailed online information (feedback,social comparison information, information on varying rates (dynamic pricing and general information (advertising campaign, are tools that are not less appropriate than the ones the neoclassical economics offers, mainly because electricity is an invisible product and consumers are unable to assess it by normal cognitive measures. Using an interdisciplinary combination of behavioral tools that come from a variety of approaches taken from a wide variety of different academic fields, it is possible to receive efficient results in the endeavor of reducing electricity demand. Implications: Although the neoclassical economics still remains the fundamental theory used by policymakers, it is recommended to consider behavioral economics as a complementary approach to the neoclassical economics, and combine behavioral tools in the policymakers’ toolbox, especially when those tools do not require a significant financial investment, thus efficiently maximizing the reduction of electricity demand among domestic consumers. These theoretical results will be

  11. Impact of Demand Side Response on a Commercial Retail Refrigeration System

    Directory of Open Access Journals (Sweden)

    Ibrahim M. Saleh

    2018-02-01

    Full Text Available The UK National Grid has placed increased emphasis on the development of Demand Side Response (DSR tariff mechanisms to manage load at peak times. Refrigeration systems, along with HVAC, are estimated to consume 14% of the UK’s electricity and could have a significant role for DSR application. However, characterized by relatively low individual electrical loads and massive asset numbers, multiple low power refrigerators need aggregation for inclusion in these tariffs. In this paper, the impact of the Demand Side Response (DSR control mechanisms on food retailing refrigeration systems is investigated. The experiments are conducted in a test-rig built to resemble a typical small supermarket store. The paper demonstrates how the temperature and pressure profiles of the system, the active power and the drawn current of the compressors are affected following a rapid shut down and subsequent return to normal operation as a response to a DSR event. Moreover, risks and challenges associated with primary and secondary Firm Frequency Response (FFR mechanisms, where the load is rapidly shed at high speed in response to changes in grid frequency, is considered. For instance, measurements are included that show a significant increase in peak inrush currents of approx. 30% when the system returns to normal operation at the end of a DSR event. Consideration of how high inrush currents after a DSR event can produce voltage fluctuations of the supply and we assess risks to the local power supply system.

  12. Demand Responsive and Energy Efficient Control Technologies andStrategies in Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Piette, Mary Ann; Kiliccote, Sila

    2006-09-01

    Commercial buildings account for a large portion of summer peak electric demand. Research results show that there is significant potential to reduce peak demand in commercial buildings through advanced control technologies and strategies. However, a better understanding of commercial buildings contribution to peak demand and the use of energy management and control systems is required to develop this demand response resource to its full potential. The main objectives of the study were: (1) To evaluate the size of contributions of peak demand commercial buildings in the U.S.; (2) To understand how commercial building control systems support energy efficiency and DR; and (3) To disseminate the results to the building owners, facility managers and building controls industry. In order to estimate the commercial buildings contribution to peak demand, two sources of data are used: (1) Commercial Building Energy Consumption Survey (CBECS) and (2) National Energy Modeling System (NEMS). These two sources indicate that commercial buildings noncoincidental peak demand is about 330GW. The project then focused on technologies and strategies that deliver energy efficiency and also target 5-10% of this peak. Based on a building operations perspective, a demand-side management framework with three main features: (1) daily energy efficiency, (2) daily peak load management and (3) dynamic, event-driven DR are outlined. A general description of DR, its benefits, and nationwide DR potential in commercial buildings are presented. Case studies involving these technologies and strategies are described. The findings of this project are shared with building owners, building controls industry, researchers and government entities through a webcast and their input is requested. Their input is presented in the appendix section of this report.

  13. Distributed Energy Systems Integration and Demand Optimization for Autonomous Operations and Electric Grid Transactions

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Greenlots, San Francisco, CA (United States); Mashayekh, Salman [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Stadler, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Center for Energy and Innovation Technologies (Austria); Yin, Rongxin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Liu, Zhenhua [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-11-29

    Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost, energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. Our paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). Furthermore, our results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.

  14. Energy systems scenario modelling and long term forecasting of hourly electricity demand

    Directory of Open Access Journals (Sweden)

    Poul Alberg Østergaard

    2015-06-01

    Full Text Available The Danish energy system is undergoing a transition from a system based on storable fossil fuels to a system based on fluctuating renewable energy sources. At the same time, more of and more of the energy system is becoming electrified; transportation, heating and fuel usage in industry and elsewhere. This article investigates the development of the Danish energy system in a medium year 2030 situation as well as in a long-term year 2050 situation. The analyses are based on scenario development by the Danish Climate Commission. In the short term, it is investigated what the effects will be of having flexible or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model. The results show that even with a limited short-term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrated wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long-term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps and electric vehicles in the long-term future overshadows any effects of changes in hourly demand curve profiles.

  15. Static Electricity-Responsive Supramolecular Assembly.

    Science.gov (United States)

    Jintoku, Hirokuni; Ihara, Hirotaka; Matsuzawa, Yoko; Kihara, Hideyuki

    2017-12-01

    Stimuli-responsive materials can convert between molecular scale and macroscopic scale phenomena. Two macroscopic static electricity-responsive phenomena based on nanoscale supramolecular assemblies of a zinc porphyrin derivative are presented. One example involves the movement of supramolecular assemblies in response to static electricity. The assembly of a pyridine (Py) complex of the above-mentioned derivative in cyclohexane is drawn to a positively charged material, whereas the assembly of a 3,5-dimethylpyridine complex is drawn to a negatively charged material. The second phenomenon involves the movement of a non-polar solvent in response to static electrical stimulation. A cyclohexane solution containing a small quantity of the Py-complexed assembly exhibited a strong movement response towards negatively charged materials. Based on spectroscopic measurements and electron microscope observations, it was revealed that the assembled formation generates the observed response to static electricity. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Demand Intensity, Market Parameters and Policy Responses towards Demand and Supply of Private Supplementary Tutoring in China

    Science.gov (United States)

    Kwok, Percy Lai Yin

    2010-01-01

    Based on some longitudinal studies of private tutoring in twelve cities, towns, municipalities and provinces of China, the paper endeavours to depict demand intensity, articulate market parameters and reflect on policy responses towards the demand-supply mechanism of the vast shadowy educational phenomena at primary and secondary levels. Such…

  17. Regulating electricity demand peaks for home appliances using reversible fair scheduling

    DEFF Research Database (Denmark)

    Kardaras, Georgios; Rossello Busquet, Ana; Iversen, Villy Bæk

    2010-01-01

    of home appliances into priority classes and the definition of a maximum power consumption threshold which is not allowed to be exceeded during peak hours. According to the bandwidth demand and priority of each class, the reversible fair scheduling algorithm delays some of the appliances and prolongs......This paper describes a novel methodology for regulating electricity demand peaks for home appliances. To achieve this objective, we will make use of the reversible fair scheduling algorithm originally developed for telecommunication networks. The main concept behind this approach is the aggregation...

  18. Identifying Demand Responses to Illegal Drug Supply Interdictions.

    Science.gov (United States)

    Cunningham, Scott; Finlay, Keith

    2016-10-01

    Successful supply-side interdictions into illegal drug markets are predicated on the responsiveness of drug prices to enforcement and the price elasticity of demand for addictive drugs. We present causal estimates that targeted interventions aimed at methamphetamine input markets ('precursor control') can temporarily increase retail street prices, but methamphetamine consumption is weakly responsive to higher drug prices. After the supply interventions, purity-adjusted prices increased then quickly returned to pre-treatment levels within 6-12 months, demonstrating the short-term effects of precursor control. The price elasticity of methamphetamine demand is -0.13 to -0.21 for self-admitted drug treatment admissions and between -0.24 and -0.28 for hospital inpatient admissions. We find some evidence of a positive cross-price effect for cocaine, but we do not find robust evidence that increases in methamphetamine prices increased heroin, alcohol, or marijuana drug use. This study can inform policy discussions regarding other synthesized drugs, including illicit use of pharmaceuticals. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

  19. Demand-side management as an equilibrium response to uncertainty

    Science.gov (United States)

    Rossmann, Charles Greer

    1997-08-01

    The thesis shows that a competitive firm with a strictly concave technology will increase its fixed inputs in response to an increase in the uncertainty it faces with respect to the productivity of variable inputs. Further, this result is shown to lead to bias in the estimation of the technology of the firm when the econometric model is misspecified with respect this behavior of firms. These results are extended to the situation of a regulated monopoly and the extended results are used to show that it is plausible that the conservation investment phenomenon known as demand-side management (DSM) is such an equilibrium response to the disruptions in the energy markets in the 1970s and 1980s.

  20. Connecting plug-in vehicles with green electricity through consumer demand

    Science.gov (United States)

    Axsen, Jonn; Kurani, Kenneth S.

    2013-03-01

    The environmental benefits of plug-in electric vehicles (PEVs) increase if the vehicles are powered by electricity from ‘green’ sources such as solar, wind or small-scale hydroelectricity. Here, we explore the potential to build a market that pairs consumer purchases of PEVs with purchases of green electricity. We implement a web-based survey with three US samples defined by vehicle purchases: conventional new vehicle buyers (n = 1064), hybrid vehicle buyers (n = 364) and PEV buyers (n = 74). Respondents state their interest in a PEV as their next vehicle, in purchasing green electricity in one of three ways, i.e., monthly subscription, two-year lease or solar panel purchase, and in combining the two products. Although we find that a link between PEVs and green electricity is not presently strong in the consciousness of most consumers, the combination is attractive to some consumers when presented. Across all three respondent segments, pairing a PEV with a green electricity program increased interest in PEVs—with a 23% demand increase among buyers of conventional vehicles. Overall, about one-third of respondents presently value the combination of a PEV with green electricity; the proportion is much higher among previous HEV and PEV buyers. Respondents’ reported motives for interest in both products and their combination include financial savings (particularly among conventional buyers), concerns about air pollution and the environment, and interest in new technology (particularly among PEV buyers). The results provide guidance regarding policy and marketing strategies to advance PEVs and green electricity demand.

  1. Determining marginal electricity for near-term plug-in and fuel cell vehicle demands in California: Impacts on vehicle greenhouse gas emissions

    Science.gov (United States)

    McCarthy, Ryan; Yang, Christopher

    California has taken steps to reduce greenhouse gas emissions from the transportation sector. One example is the recent adoption of the Low Carbon Fuel Standard, which aims to reduce the carbon intensity of transportation fuels. To effectively implement this and similar policies, it is necessary to understand well-to-wheels emissions associated with distinct vehicle and fuel platforms, including those using electricity. This analysis uses an hourly electricity dispatch model to simulate and investigate operation of the current California grid and its response to added vehicle and fuel-related electricity demands in the near term. The model identifies the "marginal electricity mix" - the mix of power plants that is used to supply the incremental electricity demand from vehicles and fuels - and calculates greenhouse gas emissions from those plants. It also quantifies the contribution from electricity to well-to-wheels greenhouse gas emissions from battery-electric, plug-in hybrid, and fuel cell vehicles and explores sensitivities of electricity supply and emissions to hydro-power availability, timing of electricity demand (including vehicle recharging), and demand location within the state. The results suggest that the near-term marginal electricity mix for vehicles and fuels in California will come from natural gas-fired power plants, including a significant fraction (likely as much as 40%) from relatively inefficient steam- and combustion-turbine plants. The marginal electricity emissions rate will be higher than the average rate from all generation - likely to exceed 600 gCO 2 equiv. kWh -1 during most hours of the day and months of the year - and will likely be more than 60% higher than the value estimated in the Low Carbon Fuel Standard. But despite the relatively high fuel carbon intensity of marginal electricity in California, alternative vehicle and fuel platforms still reduce emissions compared to conventional gasoline vehicles and hybrids, through improved

  2. Analysis and Estimation of Electric Power Demand in Russian Far East

    Science.gov (United States)

    Oleinik, E. B.; Sidorova, N. G.

    2017-10-01

    This article reviews the current situation in the fuel and energy complex (FEC) of the Russian Far East, distinguishes its specific features, estimates the volume of investments required for further development of FEC in the Russian Far East. The use of econometric models makes it possible to get a forecast of electric power production, which serves as a basis of evaluation of the region’s electric power demand. It is noted that the main problem of the region development is surplus of energy production and a continuous population decline. The authors offer major strategic directions of development and mechanisms of energy policy implementation.

  3. Future Electricity Demand of the Emerging European Countries and the CIS Countries

    Directory of Open Access Journals (Sweden)

    Mehmet Fatih Bayramoglu

    2016-10-01

    Full Text Available Nowadays, one of the leading factors used in the evaluation of a country’s economic development is energy consumption. Because of economic growth, demand for energy is also increasing. In this study, the emerging European countries’ (the Czech Republic, Poland, Romania, Turkey and the CIS countries’ (Kazakhstan, Russia, Ukraine, Uzbekistan  electricity consumption has been forecasted for five years period (2015-2019. In the study, GM(1,1 Rolling Model, which is developed in the framework of Grey System Theory is used as a mathematical model for real-time forecasting. The results of the study show that there will not be a significant change in electricity demand in this two area during the 2015-2109 period.

  4. Medium- and long-term electric power demand forecasting based on the big data of smart city

    Science.gov (United States)

    Wei, Zhanmeng; Li, Xiyuan; Li, Xizhong; Hu, Qinghe; Zhang, Haiyang; Cui, Pengjie

    2017-08-01

    Based on the smart city, this paper proposed a new electric power demand forecasting model, which integrates external data such as meteorological information, geographic information, population information, enterprise information and economic information into the big database, and uses an improved algorithm to analyse the electric power demand and provide decision support for decision makers. The data mining technology is used to synthesize kinds of information, and the information of electric power customers is analysed optimally. The scientific forecasting is made based on the trend of electricity demand, and a smart city in north-eastern China is taken as a sample.

  5. Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies (City Energy: From Data to Decisions)

    Energy Technology Data Exchange (ETDEWEB)

    Office of Strategic Programs, Strategic Priorities and Impact Analysis Team

    2017-09-29

    This fact sheet "Asheville, North Carolina: Reducing Electricity Demand through Building Programs & Policies" explains how the City of Asheville used data from the U.S. Department of Energy's Cities Leading through Energy Analysis and Planning (Cities-LEAP) and the State and Local Energy Data (SLED) programs to inform its city energy planning. It is one of ten fact sheets in the "City Energy: From Data to Decisions" series.

  6. Energy shift estimation of demand response activation on domestic refrigerators – A field test study

    DEFF Research Database (Denmark)

    Lakshmanan, Venkatachalam; Gudmand-Høyer, Kristian; Marinelli, Mattia

    2014-01-01

    This paper presents a method to estimate the amount of energy that can be shifted during demand response (DR) activation on domestic refrigerator. Though there are many methods for DR activation like load reduction, load shifting and onsite generation, the method under study is load shifting....... Electric heating and cooling equipment like refrigerators, water heaters and space heaters and coolers are preferred for such DR activation because of their energy storing capacity. Accurate estimation of available regulating power and energy shift is important to understand the value of DR activation...

  7. Opportunities, Barriers and Actions for Industrial Demand Response in California

    Energy Technology Data Exchange (ETDEWEB)

    McKane, Aimee T.; Piette, Mary Ann; Faulkner, David; Ghatikar, Girish; Radspieler Jr., Anthony; Adesola, Bunmi; Murtishaw, Scott; Kiliccote, Sila

    2008-01-31

    In 2006 the Demand Response Research Center (DRRC) formed an Industrial Demand Response Team to investigate opportunities and barriers to implementation of Automated Demand Response (Auto-DR) systems in California industries. Auto-DR is an open, interoperable communications and technology platform designed to: Provide customers with automated, electronic price and reliability signals; Provide customers with capability to automate customized DR strategies; Automate DR, providing utilities with dispatchable operational capability similar to conventional generation resources. This research began with a review of previous Auto-DR research on the commercial sector. Implementing Auto-DR in industry presents a number of challenges, both practical and perceived. Some of these include: the variation in loads and processes across and within sectors, resource-dependent loading patterns that are driven by outside factors such as customer orders or time-critical processing (e.g. tomato canning), the perceived lack of control inherent in the term 'Auto-DR', and aversion to risk, especially unscheduled downtime. While industry has demonstrated a willingness to temporarily provide large sheds and shifts to maintain grid reliability and be a good corporate citizen, the drivers for widespread Auto-DR will likely differ. Ultimately, most industrial facilities will balance the real and perceived risks associated with Auto-DR against the potential for economic gain through favorable pricing or incentives. Auto-DR, as with any ongoing industrial activity, will need to function effectively within market structures. The goal of the industrial research is to facilitate deployment of industrial Auto-DR that is economically attractive and technologically feasible. Automation will make DR: More visible by providing greater transparency through two-way end-to-end communication of DR signals from end-use customers; More repeatable, reliable, and persistent because the automated

  8. Bulk electric system reliability evaluation incorporating wind power and demand side management

    Science.gov (United States)

    Huang, Dange

    correlations and the interactive effects of wind power and load forecast uncertainty on system reliability are examined. The concept of the security cost associated with operating in the marginal state in the well-being framework is incorporated in the economic analyses associated with system expansion planning including wind power and load forecast uncertainty. Overall reliability cost/worth analyses including security cost concepts are applied to select an optimal wind power injection strategy in a bulk electric system. The effects of the various demand side management measures on system reliability are illustrated using the system, load point, and well-being indices, and the reliability index probability distributions. The reliability effects of demand side management procedures in a bulk electric system including wind power and load forecast uncertainty considerations are also investigated. The system reliability effects due to specific demand side management programs are quantified and examined in terms of their reliability benefits.

  9. Demand Response Potential for California SubLAPs and Local Capacity Planning Areas: An Addendum to the 2025 California Demand Response Potential Study – Phase 2

    Energy Technology Data Exchange (ETDEWEB)

    Alstone, Peter [Humboldt State Univ., Arcata, CA (United States). Schatz Energy Research Center; Potter, Jennifer [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Piette, Mary Ann [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Schwartz, Peter [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Berger, Michael A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Dunn, Laurel N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Smith, Sarah J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sohn, Michael D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Aghajanzadeh, Arian [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Stensson, Sofia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Szinai, Julia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-04-01

    The 2025 California Demand Response Potential Study Phase 2 Report1 was released on March 1, 2017, and described a range of pathways for Demand Response (DR) to support a clean, stable, and cost-effective electric grid for California. One of the Report’s key findings was that while there appears to be very low future value for untargeted DR Shed aimed at system-wide peak load conditions, there could be significant value for locally focused Shed resources. Although the dynamics of renewable capacity expansion have reduced the pressure to build new thermal generation in general, there are still transmission-constrained areas of the state where load growth needs to be managed with the addition of new local capacity, which could include DERs and/or DR. This Addendum to the Phase 2 Report presents a breakdown of the expected future “Local Shed” DR potential at a finer geographic resolution than what is available in the original report, with results summarized by SubLAP and Local Capacity Area (LCA).

  10. Reducing Energy Demand Using Wheel-Individual Electric Drives to Substitute EPS-Systems

    Directory of Open Access Journals (Sweden)

    Jürgen Römer

    2018-01-01

    Full Text Available The energy demand of vehicles is influenced, not only by the drive systems, but also by a number of add-on systems. Electric vehicles must satisfy this energy demand completely from the battery. Hence, the use of power steering systems directly result in a range reduction. The “e2-Lenk” joint project funded by the German Federal Ministry of Education and Research (BMBF involves a novel steering concept for electric vehicles to integrate the function of steering assistance into the drive-train. Specific distribution of driving torque at the steered axle allows the steering wheel torque to be influenced to support the steering force. This provides a potential for complete substitution of conventional power steering systems and reduces the vehicle’s energy demand. This paper shows the potential of wheel-individual drives influencing the driver’s steering torque using a control technique based on classical EPS control plans. Compared to conventional power-assisted steering systems, a reduced energy demand becomes evident over a wide range of operating conditions.

  11. Enabling Automated Dynamic Demand Response: From Theory to Practice

    Energy Technology Data Exchange (ETDEWEB)

    Frincu, Marc; Chelmis, Charalampos; Aman, Saima; Saeed, Rizwan; Zois, Vasileios; Prasanna, Viktor

    2015-07-14

    Demand response (DR) is a technique used in smart grids to shape customer load during peak hours. Automated DR offers utilities a fine grained control and a high degree of confidence in the outcome. However the impact on the customer's comfort means this technique is more suited for industrial and commercial settings than for residential homes. In this paper we propose a system for achieving automated controlled DR in a heterogeneous environment. We present some of the main issues arising in building such a system, including privacy, customer satisfiability, reliability, and fast decision turnaround, with emphasis on the solutions we proposed. Based on the lessons we learned from empirical results we describe an integrated automated system for controlled DR on the USC microgrid. Results show that while on a per building per event basis the accuracy of our prediction and customer selection techniques varies, it performs well on average when considering several events and buildings.

  12. Pilot Testing of Commercial Refrigeration-Based Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Hirsch, Adam [National Renewable Energy Lab. (NREL), Golden, CO (United States); Clark, Jordan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Deru, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Trenbath, Kim [National Renewable Energy Lab. (NREL), Golden, CO (United States); Doebber, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Studer, Daniel [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2015-10-08

    Supermarkets potentially offer a substantial demand response (DR) resource because of their high energy intensity and use patterns. This report describes a pilot project conducted to better estimate supermarket DR potential. Previous work has analyzed supermarket DR using heating, ventilating, and air conditioning (HVAC), lighting, and anti-condensate heaters. This project was concerned with evaluating DR using the refrigeration system and quantifying the DR potential inherent in supermarket refrigeration systems. Ancillary aims of the project were to identify practical barriers to the implementation of DR programs in supermarkets and to determine which high-level control strategies were most appropriate for achieving certain DR objectives. The scope of this project does not include detailed control strategy development for DR or development of a strategy for regional implementation of DR in supermarkets.

  13. Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel J.; Matson, Nance; Sohn, Michael D.; Rose, Cody; Dudley, Junqiao; Goli, Sasank; Kiliccote, Sila; Hummon, Marissa; Palchak, David; Denholm, Paul; Jorgenson, Jennie

    2013-09-09

    Demand response (DR) has the potential to improve electric grid reliability and reduce system operation costs. However, including DR in grid modeling can be difficult due to its variable and non-traditional response characteristics, compared to traditional generation. Therefore, efforts to value the participation of DR in procurement of grid services have been limited. In this report, we present methods and tools for predicting demand response availability profiles, representing their capability to participate in capacity, energy, and ancillary services. With the addition of response characteristics mimicking those of generation, the resulting profiles will help in the valuation of the participation of demand response through production cost modeling, which informs infrastructure and investment planning.

  14. Design of demand side response model in energy internet demonstration park

    Science.gov (United States)

    Zhang, Q.; Liu, D. N.

    2017-08-01

    The implementation of demand side response can bring a lot of benefits to the power system, users and society, but there are still many problems in the actual operation. Firstly, this paper analyses the current situation and problems of demand side response. On this basis, this paper analyses the advantages of implementing demand side response in the energy Internet demonstration park. Finally, the paper designs three kinds of feasible demand side response modes in the energy Internet demonstration park.

  15. Mass Market Demand Response and Variable Generation Integration Issues: A Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Cappers, Peter; Mills, Andrew; Goldman, Charles; Wiser, Ryan; Eto, Joseph H.

    2011-09-10

    This scoping study focuses on the policy issues inherent in the claims made by some Smart Grid proponents that the demand response potential of mass market customers which is enabled by widespread implementation of Advanced Metering Infrastructure (AMI) through the Smart Grid could be the “silver bullet” for mitigating variable generation integration issues. In terms of approach, we will: identify key issues associated with integrating large amounts of variable generation into the bulk power system; identify demand response opportunities made more readily available to mass market customers through widespread deployment of AMI systems and how they can affect the bulk power system; assess the extent to which these mass market Demand Response (DR) opportunities can mitigate Variable Generation (VG) integration issues in the near-term and what electricity market structures and regulatory practices could be changed to further expand the ability for DR to mitigate VG integration issues over the long term; and provide a qualitative comparison of DR and other approaches to mitigate VG integration issues.

  16. Contrasting Electricity Demand with Wind Power Supply: Case Study in Hungary

    Directory of Open Access Journals (Sweden)

    Imre M. Jánosi

    2009-09-01

    Full Text Available We compare the demand of a large electricity consumer with supply given by wind farms installed at two distant geographic locations. Obviously such situation is rather unrealistic, however our main goal is a quantitative characterization of the intermittency of wind electricity. The consumption pattern consists of marked daily and weekly cycles interrupted by periods of holidays. In contrast, wind electricity production has neither short-time nor seasonal periodicities. We show that wind power integration over a restricted area cannot provide a stable baseload supply, independently of the excess capacity. Further essential result is that the statistics are almost identical for a weekly periodic pattern of consumption and a constant load of the same average value. The length of both adequate supply and shortfall intervals exhibits a scale-free (power-law frequency distribution, possible consequences are shortly discussed.

  17. Cost-saving potentials using demand side management in households and electric mobility

    Energy Technology Data Exchange (ETDEWEB)

    Schinz, S.; Najib, H.; Steiner, L. [Darmstadt Univ. of Technology (Germany). Inst. for Renewable Energies

    2010-07-01

    The increasing share of renewable energies in the electricity production has an influence on the grid and on the electricity markets, where higher price fluctuations are expected. One way of integrating renewable energies is using demand side management (DSM). In this case online energy markets enable private households to participate with their loads in these markets. Especially their household appliances participate on the basis of hourly electricity prices. Thus these markets can provide DSM-services for the grid by means of aggregating household loads. To estimate the cost-savings of DSM for the purpose of reducing electricity costs in private households different gadget-models are developed and minimal costs are calculated by formulating linear optimization models. In private households especially refrigerators, freezers, washing machines, tumble- dryers and dishwashers can be considered as shiftable loads for DSM purposes. This application of DSM is examined in this paper precisely. Future developments regarding DSM are analyzed with scenarios for 2010 and 2030. The gadget-models have average specifications of gadgets in Europe and Germany. Their operation is optimized for minimal electricity cost over one year on the basis of electricity prices from the European Energy Exchange EEX in Leipzig, Germany. Finally DSM in Micro Grids is analyzed and different control options are considered to solve the voltage stability problem. (orig.)

  18. A Price-Based Demand Response Scheme for Discrete Manufacturing in Smart Grids

    Directory of Open Access Journals (Sweden)

    Zhe Luo

    2016-08-01

    Full Text Available Demand response (DR is a key technique in smart grid (SG technologies for reducing energy costs and maintaining the stability of electrical grids. Since manufacturing is one of the major consumers of electrical energy, implementing DR in factory energy management systems (FEMSs provides an effective way to manage energy in manufacturing processes. Although previous studies have investigated DR applications in process manufacturing, they were not conducted for discrete manufacturing. In this study, the state-task network (STN model is implemented to represent a discrete manufacturing system. On this basis, a DR scheme with a specific DR algorithm is applied to a typical discrete manufacturing—automobile manufacturing—and operational scenarios are established for the stamping process of the automobile production line. The DR scheme determines the optimal operating points for the stamping process using mixed integer linear programming (MILP. The results show that parts of the electricity demand can be shifted from peak to off-peak periods, reducing a significant overall energy costs without degrading production processes.

  19. Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

    Directory of Open Access Journals (Sweden)

    Jinchao Li

    2018-01-01

    Full Text Available Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have positive influences on electric grid investment demand, but the impact of population scale, social electricity consumption, and installed electrical capacity on electric grid investment is not remarkable. We divide different regions in China into the eastern region, central region, and western region to analyze influence factors of electric grid investment, finally obtaining key factors in the eastern, central, and western regions. In the end, according to the analysis of key factors, we make a prediction about China’s electric grid investment for 2020 in different scenarios. The results offer a certain understanding for the development trend of China’s electric grid investment and contribute to the future development of electric grid investment.

  20. Second life battery energy storage system for residential demand response service

    DEFF Research Database (Denmark)

    Saez-de-Ibarra, Andoni; Martinez-Laserna, Egoitz; Koch-Ciobotaru, Cosmin

    2015-01-01

    The integration of renewable energies and the usage of battery energy storage systems (BESS) into the residential buildings opens the possibility for minimizing the electricity bill for the end-user. This paper proposes the use of batteries that have already been aged while powering electric...... vehicles, during their main first life application, for providing residential demand response service. The paper considers the decayed characteristics of these batteries and optimizes the rating of such a second life battery energy storage system (SLBESS) for maximizing the economic benefits of the user......'s energy consumption during a period of one year. Furthermore, simulations were performed considering real data of PV generation, consumption, prices taken from the Spanish market and costs of battery and photovoltaic systems....

  1. Heat Pump Water Heaters: Controlled Field Research of Impact on Space Conditioning and Demand Response Characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Parker, Graham B.; Widder, Sarah H.; Eklund, Ken; Petersen, Joseph M.; Sullivan, Greg

    2015-10-05

    A new generation of heat pump water heaters (HPWH) has been introduced into the U.S. market that promises to provide significant energy savings for water heating. Many electric utilities are promoting their widespread adoption as a key technology for meeting energy conservation goals and reducing greenhouse gas emissions. There is, however, considerable uncertainty regarding the space conditioning impact of an HPWH installed in a conditioned space. There is also uncertainty regarding the potential for deployment of HPWHs in demand response (DR) programs to help manage and balance peak utility loads in a similar manner as conventional electric resistance water heaters (ERWH). To help answer these uncertainties, controlled experiments have been undertaken over 30 months in a matched pair of unoccupied Lab Homes located on the campus of the Pacific Northwest National Laboratory (PNNL) in Richland, Washington.

  2. Opportunities for Energy Efficiency and Open Automated Demand Response in Wastewater Treatment Facilities in California -- Phase I Report

    Energy Technology Data Exchange (ETDEWEB)

    Lekov, Alex; Thompson, Lisa; McKane, Aimee; Song, Katherine; Piette, Mary Ann

    2009-04-01

    This report summarizes the Lawrence Berkeley National Laboratory?s research to date in characterizing energy efficiency and automated demand response opportunities for wastewater treatment facilities in California. The report describes the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy use and demand, as well as details of the wastewater treatment process. It also discusses control systems and energy efficiency and automated demand response opportunities. In addition, several energy efficiency and load management case studies are provided for wastewater treatment facilities.This study shows that wastewater treatment facilities can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for automated demand response at little additional cost. These improved controls may prepare facilities to be more receptive to open automated demand response due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

  3. Public-policy responsibilities in a restructured electricity industry

    Energy Technology Data Exchange (ETDEWEB)

    Tonn, B.; Hirst, E.; Bauer, D.

    1995-06-01

    In this report, we identify and define the key public-policy values, objectives, and actions that the US electricity industry currently meets. We also discuss the opportunities for meeting these objectives in a restructured industry that relies primarily on market forces rather than on government mandates. And we discuss those functions that governments might undertake, presumably because they will not be fully met by a restructured industry on its own. These discussions are based on a variety of inputs. The most important inputs came from participants in an April 1995 workshop on Public-Policy Responsibilities and Electric Industry Restructuring: Shaping the Research Agenda. Other sources of information and insights include the reviews of a draft of this report by workshop participants and others and the rapidly growing literature on electric-industry restructuring and its implications. One of the major concerns about the future of the electricity industry is the fate of numerous social and environmental programs supported by today`s electric utilities. Many people worry that a market-driven industry may not meet the public-policy objectives that electric utilities have met in the past. Examples of potentially at-risk programs include demand-side management (DSM), renewable energy, low-income weatherization, and fuel diversity. Workshop participants represented electric utilities, public utility commissions (PUCs), state energy offices, public-interest groups, other energy providers, and the research community.

  4. Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

    Directory of Open Access Journals (Sweden)

    Gang Du

    2015-06-01

    Full Text Available Electricity intensity is an important indicator for measuring production efficiency. A comparative study could offer a new perspective on investigating determinants of electricity demand. The Japanese non-metallic mineral products industry is chosen as the object for comparison considering its representative position in production efficiency. By adopting the cointegration model, this paper examines influencing factors of electricity demand in Japanese and Chinese non-metallic mineral products industries under the same framework. Results indicate that although economic growth and industrial development stages are different between the two countries, major factors that affect the sectoral energy consumption are the same. Specifically, economic growth and industrial activity contribute to the growth of sectoral electricity consumption, while R&D intensity, per capita productivity and electricity price are contributors to the decline of sectoral electricity consumption. Finally, in order to further investigate the development trend of sectoral electricity demand, future electricity consumption and conservation potential are predicted under different scenarios. Electricity demand of the Chinese non-metallic mineral products industry is predicted to be 680.53 TWh (terawatt-hours in 2020 and the sectoral electricity conservation potentials are estimated to be 118.26 TWh and 216.25 TWh under the moderate and advanced electricity-saving scenarios, respectively.

  5. Development and Demonstration of the Open Automated Demand Response Standard for the Residential Sector

    Energy Technology Data Exchange (ETDEWEB)

    Herter, Karen; Rasin, Josh; Perry, Tim

    2009-11-30

    The goal of this study was to demonstrate a demand response system that can signal nearly every customer in all sectors through the integration of two widely available and non- proprietary communications technologies--Open Automated Demand Response (OpenADR) over lnternet protocol and Utility Messaging Channel (UMC) over FM radio. The outcomes of this project were as follows: (1) a software bridge to allow translation of pricing signals from OpenADR to UMC; and (2) a portable demonstration unit with an lnternet-connected notebook computer, a portfolio of DR-enabling technologies, and a model home. The demonstration unit provides visitors the opportunity to send electricity-pricing information over the lnternet (through OpenADR and UMC) and then watch as the model appliances and lighting respond to the signals. The integration of OpenADR and UMC completed and demonstrated in this study enables utilities to send hourly or sub-hourly electricity pricing information simultaneously to the residential, commercial and industrial sectors.

  6. Opportunities for Energy Efficiency and Demand Response in the California Cement Industry

    Energy Technology Data Exchange (ETDEWEB)

    Olsen, Daniel; Goli, Sasank; Faulkner, David; McKane, Aimee

    2010-12-22

    This study examines the characteristics of cement plants and their ability to shed or shift load to participate in demand response (DR). Relevant factors investigated include the various equipment and processes used to make cement, the operational limitations cement plants are subject to, and the quantities and sources of energy used in the cement-making process. Opportunities for energy efficiency improvements are also reviewed. The results suggest that cement plants are good candidates for DR participation. The cement industry consumes over 400 trillion Btu of energy annually in the United States, and consumes over 150 MW of electricity in California alone. The chemical reactions required to make cement occur only in the cement kiln, and intermediate products are routinely stored between processing stages without negative effects. Cement plants also operate continuously for months at a time between shutdowns, allowing flexibility in operational scheduling. In addition, several examples of cement plants altering their electricity consumption based on utility incentives are discussed. Further study is needed to determine the practical potential for automated demand response (Auto-DR) and to investigate the magnitude and shape of achievable sheds and shifts.

  7. Research on Simulation Requirements and Business Architecture of Automated Demand Response in Power Sales Side Market Liberalization

    Science.gov (United States)

    Liu, Yiqun; Zhou, Pengcheng; Zeng, Ming; Chen, Songsong

    2018-01-01

    With the gradual reform of the electricity market, the power sale side liberalization has become the focus of attention as the key task of reform. The open power market provides a good environment for DR (Demand Response). It is of great significance to research the simulation requirements and business architecture of ADR (Automatic Demand Response) in power sale side market liberalization. Firstly, this paper analyzes the simulation requirements of ADR. Secondly, it analyzes the influence factors that the business development of ADR from five aspects after power sale side market liberalization. Finally, Based on ADR technology support system, the business architecture of ADR after power sale side market liberalization is constructed.

  8. Operationally Responsive Spacecraft Using Electric Propulsion

    Science.gov (United States)

    2012-09-13

    OH, 1996 (ADA). Vallado, D. Fundamentals of Astrodynamics and Applications (2nd Edition). El Segundo CA: Microcosm Press, 2001. Vaughan, C. E...detailing the possible applications of the proposed responsive electric propulsion (EP) space system; however, none address the responsiveness achieved...5-37 5.8 Application ................................................................................................ 5-39 5.9 Conclusion

  9. Final Scientific Technical Report: INTEGRATED PREDICTIVE DEMAND RESPONSE CONTROLLER FOR COMMERCIAL BUILDINGS

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Mike

    2013-10-14

    This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.

  10. Short-term electricity demand forecasting using double seasonal exponential smoothing

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, J.W.

    2003-08-15

    This paper considers univariate online electricity demand forecasting for lead times from a half-hour-ahead to a day-ahead. A time series of demand recorded at half-hourly intervals contains more than one seasonal pattern. A within-day seasonal cycle is apparent from the similarity of the demand profile from one day to the next, and a within-week seasonal cycle is evident when one compares the demand on the corresponding day of adjacent weeks. There is strong appeal in using a forecasting method that is able to capture both seasonalities. The multiplicative seasonal ARIMA model has been adapted for this purpose. In this paper, we adapt the Holt-Winters exponential smoothing formulation so that it can accommodate two seasonalities. We correct for residual autocorrelation using a simple autoregressive model. The forecasts produced by the new double seasonal Holt-Winters method outperform those from traditional Holt-Winters and from a well-specified multiplicative double seasonal ARIMA model. (Author)

  11. Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

    Directory of Open Access Journals (Sweden)

    O. V. Russkov

    2015-01-01

    Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost

  12. Evaluation of the Demand Response Performance of Electric Water Heaters

    Energy Technology Data Exchange (ETDEWEB)

    Mayhorn, Ebony T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Widder, Sarah H. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Parker, Steven A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Pratt, Richard M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chassin, Forrest S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-03-17

    The purpose of this project is to verify or refute many of the concerns raised by utilities regarding the ability of large tank HPWHs to perform DR by measuring the performance of HPWHs compared to ERWHs in providing DR services. perform DR by measuring the performance of HPWHs compared to ERWHs in providing DR services. This project was divided into three phases. Phase 1 consisted of week-long laboratory experiments designed to demonstrate technical feasibility of individual large-tank HPWHs in providing DR services compared to large-tank ERWHs. In Phase 2, the individual behaviors of the water heaters were then extrapolated to a population by first calibrating readily available water heater models developed in GridLAB-D simulation software to experimental results obtained in Phase 1. These models were used to simulate a population of water heaters and generate annual load profiles to assess the impacts on system-level power and residential load curves. Such population modeling allows for the inherent and permanent load reduction accomplished by the more efficient HPWHs to be considered, in addition to the temporal DR services the water heater can provide by switching ON or OFF as needed by utilities. The economic and emissions impacts of using large-tank water heaters in DR programs are then analyzed from the utility and consumer perspective, based on National Impacts Analysis in Phase 3. Phase 1 is discussed in this report. Details on Phases 2 and 3 can be found in the companion report (Cooke et al. 2014).

  13. Measured electric hot water standby and demand loads from Pacific Northwest homes

    Energy Technology Data Exchange (ETDEWEB)

    Pratt, R.G.; Ross, B.A.

    1991-11-01

    The Bonneville Power Administration began the End-Use Load and Consumer Assessment Program (ELCAP) in 1983 to obtain metered hourly end-use consumption data for a large sample of new and existing residential and commercial buildings in the Pacific Northwest. Loads and load shapes from the first 3 years of data fro each of several ELCAP residential studies representing various segments of the housing population have been summarized by Pratt et al. The analysis reported here uses the ELCAP data to investigate in much greater detail the relationship of key occupant and tank characteristics to the consumption of electricity for water heating. The hourly data collected provides opportunities to understand electricity consumption for heating water and to examine assumptions about water heating that are critical to load forecasting and conservation resource assessments. Specific objectives of this analysis are to: (A) determine the current baseline for standby heat losses by determining the standby heat loss of each hot water tank in the sample, (B) examine key assumptions affecting standby heat losses such as hot water temperatures and tank sizes and locations, (C) estimate, where possible, impacts on standby heat losses by conservation measures such as insulating tank wraps, pipe wraps, anticonvection valves or traps, and insulating bottom boards, (D) estimate the EF-factors used by the federal efficiency standards and the nominal R-values of the tanks in the sample, (E) develop estimates of demand for hot water for each home in the sample by subtracting the standby load from the total hot water load, (F) examine the relationship between the ages and number of occupants and the hot water demand, (G) place the standby and demand components of water heating electricity consumption in perspective with the total hot water load and load shape.

  14. 76 FR 16657 - Demand Response Compensation in Organized Wholesale Energy Markets

    Science.gov (United States)

    2011-03-24

    ... wholesale energy markets and remove barriers to the participation of demand response resources, thus... meaningful demand-side participation.\\1\\ After nearly 3,800 pages of comments, a subsequent technical... energy markets by removing barriers to participation of demand response resources. For example, in Order...

  15. Real-Time Implementation of Demand Response Programs Based on Open ADR Technology

    OpenAIRE

    Omid Abrishambaf; Pedro Faria; Zita Vale

    2017-01-01

    In the Demand Response (DR) concepts, we witness several barriers that need to be addressed such as, data transferring from promoting entities to demand side. The Open Automated Demand Response (Open ADR) standard specification is a solution for overcoming these barriers. This PhD work proposes a real business model for DR implementation based on Open ADR technology.

  16. Survey of electric utility demand for coal. [1972-1992; by utility and state

    Energy Technology Data Exchange (ETDEWEB)

    Asbury, J.G.; Caruso, J.V.; Kouvalis, A.; Maslowski, C.S.

    1979-08-01

    This report presents the results of a survey of electric utility demand for coal in the United States. The sources of survey information are: (1) Federal Energy Regulatory Commission Form 423 data on utility coal purchases during the period July 1972 through December 1978 and (2) direct telephone survey data on utility coal-purchase intentions for power plants to be constructed by 1992. Price and quantity data for coal used in existing plants are presented to illustrate price and market-share trends in individual coal-consuming states during recent years. Coal source, quality, quantity, and transportation data are reported for existing and planned generating plants.

  17. Uganda Coffee Supply Response and Export Demand: An ...

    African Journals Online (AJOL)

    Econometric methods were used to estimate the supply and demand functions for Uganda's coffee using time series data for the period 1971-91. Eight major importing countries for Uganda's coffee: U.S., U.K., Japan, France, Italy, Spain, Germany, and the Netherlands were considered in export demand analysis.

  18. Fast demand response in support of the active distribution network

    NARCIS (Netherlands)

    MacDougall, P.; Heskes, P.; Crolla, P.; Burt, G.; Warmer, C.

    2013-01-01

    Demand side management has traditionally been investigated for "normal" operation services such as balancing and congestion management. However they potentially could be utilized for Distributed Network Operator (DNO) services. This paper investigates and validates the use of a supply and demand

  19. Reducing Residential Peak Electricity Demand with Mechanical Pre-Cooling of Building Thermal Mass

    Energy Technology Data Exchange (ETDEWEB)

    Turner, Will [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Walker, Iain [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Roux, Jordan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-08-01

    This study uses an advanced airflow, energy and humidity modelling tool to evaluate the potential for residential mechanical pre-cooling of building thermal mass to shift electricity loads away from the peak electricity demand period. The focus of this study is residential buildings with low thermal mass, such as timber-frame houses typical to the US. Simulations were performed for homes in 12 US DOE climate zones. The results show that the effectiveness of mechanical pre-cooling is highly dependent on climate zone and the selected pre-cooling strategy. The expected energy trade-off between cooling peak energy savings and increased off-peak energy use is also shown.

  20. Impacts of electric demand-side management programs on fuel choice: A case study

    Energy Technology Data Exchange (ETDEWEB)

    Lee, A.D.; Kavanaugh, D.C.; Sandahl, L.J. [Pacific Northwest Lab., Richland, WA (United States); Vinnard, A.B. [USDOE Bonneville Power Administration, Portland, OR (United States)

    1994-04-01

    Information, rebates, and technical assistance associated with utility demand-side management (DSM) programs can alter consumer behavior. Such programs may unintentionally affect consumer fuel choices. This study addresses fuel choice effects of a unique Pacific Northwest DSM program: (1) it is directed at new manufactured homes only, (2) it is an acquisition program -- utilities make $2,500 payments directly to manufacturers for each electrically heated, energy-efficient home built, (3) it has rapidly penetrated nearly 100% of the potential market, and (4) over 90% of the affected homes in the participating region have traditionally used electricity for space heating. Heating equipment data for all manufactured homes built in the region since 1987 were sampled and regression analysis was used to examine the relationship between the DSM program and fuel shares. The quantitative data were supplemented with interview data to better understand the relationship between the program and fuel choice. The results should be useful for program design and evaluation.

  1. Natural graphite demand and supply - Implications for electric vehicle battery requirements

    Science.gov (United States)

    Olson, Donald W.; Virta, Robert L.; Mahdavi, Mahbood; Sangine, Elizabeth S.; Fortier, Steven M.

    2016-01-01

    Electric vehicles have been promoted to reduce greenhouse gas emissions and lessen U.S. dependence on petroleum for transportation. Growth in U.S. sales of electric vehicles has been hindered by technical difficulties and the high cost of the lithium-ion batteries used to power many electric vehicles (more than 50% of the vehicle cost). Groundbreaking has begun for a lithium-ion battery factory in Nevada that, at capacity, could manufacture enough batteries to power 500,000 electric vehicles of various types and provide economies of scale to reduce the cost of batteries. Currently, primary synthetic graphite derived from petroleum coke is used in the anode of most lithium-ion batteries. An alternate may be the use of natural flake graphite, which would result in estimated graphite cost reductions of more than US$400 per vehicle at 2013 prices. Most natural flake graphite is sourced from China, the world's leading graphite producer. Sourcing natural flake graphite from deposits in North America could reduce raw material transportation costs and, given China's growing internal demand for flake graphite for its industries and ongoing environmental, labor, and mining issues, may ensure a more reliable and environmentally conscious supply of graphite. North America has flake graphite resources, and Canada is currently a producer, but most new mining projects in the United States require more than 10 yr to reach production, and demand could exceed supplies of flake graphite. Natural flake graphite may serve only to supplement synthetic graphite, at least for the short-term outlook.

  2. Research on industrialization of electric vehicles with its demand forecast using exponential smoothing method

    Directory of Open Access Journals (Sweden)

    Zhanglin Peng

    2015-04-01

    Full Text Available Purpose: Electric vehicles industry has gotten a rapid development in the world, especially in the developed countries, but still has a gap among different countries or regions. The advanced industrialization experiences of the EVs in the developed countries will have a great helpful for the development of EVs industrialization in the developing countries. This paper seeks to research the industrialization path & prospect of American EVs by forecasting electric vehicles demand and its proportion to the whole car sales based on the historical 37 EVs monthly sales and Cars monthly sales spanning from Dec. 2010 to Dec. 2013, and find out the key measurements to help Chinese government and automobile enterprises to promote Chinese EVs industrialization. Design/methodology: Compared with Single Exponential Smoothing method and Double Exponential Smoothing method, Triple exponential smoothing method is improved and applied in this study. Findings: The research results show that:  American EVs industry will keep a sustained growth in the next 3 months.  Price of the EVs, price of fossil oil, number of charging station, EVs technology and the government market & taxation polices have a different influence to EVs sales. So EVs manufacturers and policy-makers can adjust or reformulate some technology tactics and market measurements according to the forecast results. China can learn from American EVs polices and measurements to develop Chinese EVs industry. Originality/value: The main contribution of this paper is to use the triple exponential smoothing method to forecast the electric vehicles demand and its proportion to the whole automobile sales, and analyze the industrial development of Chinese electric vehicles by American EVs industry.

  3. Market and policy barriers for demand response providing ancillary services in U.S. markets

    Energy Technology Data Exchange (ETDEWEB)

    Cappers, Peter [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); MacDonald, Jason [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Goldman, Charles [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

    2013-03-01

    This study provides an examination of various market and policy barriers to demand response providing ancillary services in both ISO/RTO and non-ISO/RTO regions, especially at the program provider level. It is useful to classify barriers in order to create a holistic understanding and identify parties that could be responsible for their removal. This study develops a typology of barriers focusing on smaller customers that must rely on a program provider (i.e., electric investor owned utility or IOU, ARC) to create an aggregated DR resource in order to bring ancillary services to the balancing authority. The barriers were identified through examinations of regulatory structures, market environments, and product offerings; and discussions with industry stakeholders and regulators. In order to help illustrate the differences in barriers among various wholesale market designs and their constituent retail environments, four regions were chosen to use as case studies: Colorado, Texas, Wisconsin, and New Jersey.

  4. The battery designer's challenge — satisfying the ever-increasing demands of vehicle electrical systems

    Science.gov (United States)

    Pierson, John R.; Johnson, Richard T.

    The automotive battery designer of the 1990s and beyond will encounter an unprecedented array of complex challenges imposed by consumer desires, governmental mandates, and vehicle manufacturers' specifications. It is predicted that enhanced feature content in the areas of safety, convenience, performance, and guidance will result in a three- to six-fold increase in electrical power consumption in vehicles by the year 2000. In the absence of major break-throughs in vehicle electrical systems, these new loads will significantly modify the duty cycle to which the battery is subjected. The micro- and macro-environment in which the battery must survive will significantly impact the product's design and material specifications. Severe weight and size limits will be imposed on batteries in an attempt to meet mandated Corporate Average Fuel Economy (CAFE) requirements and additional pre-start electrical loads may be introduced to reduce objectionable emissions. Finally, quality and reliability levels of vehicles and their component parts must undergo continuous improvement. In order to respond to these diverse and sometimes contradictory demands, the battery designer must participate as an integral part of the vehicle electrical system development team. Design considerations for the future must include elevated and multiple voltages, multiple batteries per vehicle designed for specific functions, and further improvements in power and energy density, as well as cycle-life.

  5. Electricity Demand Projection Using a Path-Coefficient Analysis and BAG-SA Approach: A Case Study of China

    Directory of Open Access Journals (Sweden)

    Qunli Wu

    2017-01-01

    Full Text Available Path-coefficient analysis is utilized to investigate the direct and indirect effects of economic growth, population growth, urbanization rate, industrialization level, and carbon intensity on electricity demand of China. To improve the projection accuracy of electricity demand, this study proposes a hybrid bat algorithm, Gaussian perturbations, and simulated annealing (BAG-SA optimization method. The proposed BAG-SA algorithm not only inherits the simplicity and efficiency of the standard BA with a capability of searching for global optimality but also enhances local search ability and speeds up the global convergence rate. The BAG-SA algorithm is employed to optimize the coefficients of the multiple linear and quadratic forms of electricity demand estimation model. Results indicate that the proposed algorithm has higher precision and reliability than the coefficients optimized by other single-optimization methods, such as genetic algorithm, particle swarm optimization algorithm, or bat algorithm. And the quadratic form of BAG-SA electricity demand estimation model has better fitting ability compared with the multiple linear form of the model. Therefore, the quadratic form of the model is applied to estimate electricity demand of China from 2016 to 2030. The findings of this study demonstrate that China’s electricity demand will reach 14925200 million KWh in 2030.

  6. Coordination of Retail Demand Response with Midwest ISO Markets

    Energy Technology Data Exchange (ETDEWEB)

    Bharvirkar, Ranjit; Bharvirkar, Ranjit; Goldman, Charles; Heffner, Grayson; Sedano, Richard

    2008-05-27

    The Organization of Midwest ISO States (OMS) launched the Midwest Demand Resource Initiative (MWDRI) in 2007 to identify barriers to deploying demand response (DR) resources in the Midwest Independent System Operator (MISO) region and develop policies to overcome them. The MWDRI stakeholders decided that a useful initial activity would be to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This additional detail could then be used to assess any"seams issues" affecting coordination and integration of retail DR resources with MISO's wholesale markets. Working with state regulatory agencies, we conducted a detailed survey of existing DR programs, dynamic pricing tariffs, and their features in MISO states. Utilities were asked to provide information on advance notice requirements to customers, operational triggers used to call events (e.g. system emergencies, market conditions, local emergencies), use of these DR resources to meet planning reserves requirements, DR resource availability (e.g., seasonal, annual), participant incentive structures, and monitoring and verification (M&V) protocols. This report describes the results of this comprehensive survey and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into organized wholesale markets. Survey responses from 37 MISO members and 4 non-members provided information on 141 DR programs and dynamic pricing tariffs with a peak load reduction potential of 4,727 MW of retail DR resource. Major findings of this study area:- About 72percent of available DR is from interruptible rate tariffs offered to large commercial and industrial customers, while direct load control (DLC) programs account for ~;;18percent. Almost 90percent of the DR resources included in this survey are provided by investor-owned utilities. - Approximately, 90percent of the DR resources are available with less than

  7. Nonlinear cell response to strong electric fields

    Science.gov (United States)

    Bardos, D. C.; Thompson, C. J.; Yang, Y. S.; Joyner, K. H.

    2000-07-01

    The response of living cells to externally applied electric fields is of widespread interest. In particular, the intensification of electric fields across cell membranes is believed to be responsible, through membrane rupture and reversible membrane breakdown processes, for certain types of tissue damage in electrical trauma cases which cannot be attributed to Joule heating. Large elongated cells such as skeletal muscle fibres are particularly vulnerable to such damage. Previous theoretical studies of field intensification across cell membranes in such cells have assumed the membrane current to be linear in the applied field (Ohmic membrane conductivity) and were limited to sinusoidal applied fields. In this paper, we investigate a simple model of a long cylindrical cell, corresponding to nerve or skeletal muscle cells. Employing the electroquasistatic approximation, a system of coupled first-order differential equations for the membrane electric field is derived which incorporates arbitrary time dependence in the external field and nonlinear membrane response (non-Ohmic conductivity). The behaviour of this model is investigated for a variety of applied fields in both the linear and highly nonlinear regimes. We find that peak membrane fields predicted by the nonlinear model are approximately twice as intense, for low-frequency electrical trauma conditions, as those of the linear theory.

  8. Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

    Directory of Open Access Journals (Sweden)

    Hee-Jun Cha

    2015-12-01

    Full Text Available The microgrid and demand response (DR are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR. The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

  9. On-demand nanodevice with electrical and neuromorphic multifunction realized by local ion migration.

    Science.gov (United States)

    Yang, Rui; Terabe, Kazuya; Liu, Guangqiang; Tsuruoka, Tohru; Hasegawa, Tsuyoshi; Gimzewski, James K; Aono, Masakazu

    2012-11-27

    A potential route to extend Moore's law beyond the physical limits of existing materials and device architectures is to achieve nanotechnology breakthroughs in materials and device concepts. Here, we discuss an on-demand WO(3-x)-based nanoionic device where electrical and neuromorphic multifunctions are realized through externally induced local migration of oxygen ions. The device is found to possess a wide range of time scales of memorization, resistance switching, and rectification varying from volatile to permanent in a single device, and these can furthermore be realizable in both two- or three-terminal systems. The gradually changing volatile and nonvolatile resistance states are experimentally demonstrated to mimic the human brain's forgetting process for short-term memory and long-term memory.We propose this nanoionic device with its on-demand electrical and neuromorphic multifunction has a unique paradigm shifting potential for the fabrication of configurable circuits, analog memories, digital-neural fused networks, and more in one device architecture.

  10. Modeling the Capacity and Emissions Impacts of Reduced Electricity Demand. Part 1. Methodology and Preliminary Results

    Energy Technology Data Exchange (ETDEWEB)

    Coughlin, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Shen, Hongxia [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Chan, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; McDevitt, Brian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division; Sturges, Andrew [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division

    2013-02-07

    Policies aimed at energy conservation and efficiency have broad environmental and economic impacts. Even if these impacts are relatively small, they may be significant compared to the cost of implementing the policy. Methodologies that quantify the marginal impacts of reduced demand for energy have an important role to play in developing accurate measures of both the benefits and costs of a given policy choice. This report presents a methodology for estimating the impacts of reduced demand for electricity on the electric power sector as a whole. The approach uses the National Energy Modeling System (NEMS), a mid-range energy forecast model developed and maintained by the U.S. Department of Energy, Energy Information Administration (EIA)(DOE EIA 2013). The report is organized as follows: In the rest of this section the traditional NEMS-BT approach is reviewed and an outline of the new reduced form NEMS methodology is presented. Section 2 provides an overview of how the NEMS model works, and describes the set of NEMS-BT runs that are used as input to the reduced form approach. Section 3 presents our NEMS-BT simulation results and post-processing methods. In Section 4 we show how the NEMS-BT output can be generalized to apply to a broader set of end-uses. In Section 5 we disuss the application of this approach to policy analysis, and summarize some of the issues that will be further investigated in Part 2 of this study.

  11. An analysis of the factors influencing demand-side management activity in the electric utility industry

    Science.gov (United States)

    Bock, Mark Joseph

    Demand-side management (DSM), defined as the "planning, implementation, and monitoring of utility activities designed to encourage consumers to modify their pattern of electricity usage, including the timing and level of electricity demand," is a relatively new concept in the U.S. electric power industry. Nevertheless, in twenty years since it was first introduced, utility expenditures on DSM programs, as well as the number of such programs, have grown rapidly. At first glance, it may seem peculiar that a firm would actively attempt to reduce demand for its primary product. There are two primary explanations as to why a utility might pursue DSM: regulatory mandate, and self-interest. The purpose of this dissertation is to determine the impact these influences have on the amount of DSM undertaken by utilities. This research is important for two reasons. First, it provides insight into whether DSM will continue to exist as competition becomes more prevalent in the industry. Secondly, it is important because no one has taken a comprehensive look at firm-level DSM activity on an industry-wide basis. The primary data set used in this dissertation is the U.S. Department of Energy's Annual Electric Utility Report, Form EIA-861, which represents the most comprehensive data set available for analyzing DSM activity in the U.S. There are four measures of DSM activity in this data set: (1) utility expenditures on DSM programs; (2) energy savings by DSM program participants; and (3) the actual and (4) the potential reductions in peak load resulting from utility DSM measures. Each is used as the dependent variable in an econometric analysis where independent variables include various utility characteristics, regulatory characteristics, and service territory and customer characteristics. In general, the results from the econometric analysis suggest that in 1993, DSM activity was primarily the result of regulatory pressure. All of the evidence suggests that if DSM continues to

  12. Development of a Decision Making Model for the Assessment of Electricity Demand Side Management in the State of Kuwait

    OpenAIRE

    Al-Ajmi, Abdullah A.

    2014-01-01

    Kuwait’s per capita electrical energy consumption is among the largest in the world, reaching 13,663 kWh per person in 2011. The electricity demand in Kuwait is increasing, which requires additional investments in power generation. A particular challenge in Kuwait is the peak demand in summer, when extreme heat increases air conditioning loads. Peak demand reached 11,220 MW in 2011, with a fast growth rate averaging 5.6% over the last decade and a maximum production capacity of around 14,720 ...

  13. Anal sphincter responses after perianal electrical stimulation

    DEFF Research Database (Denmark)

    Pedersen, Ejnar; Klemar, B; Schrøder, H D

    1982-01-01

    By perianal electrical stimulation and EMG recording from the external anal sphincter three responses were found with latencies of 2-8, 13-18 and 30-60 ms, respectively. The two first responses were recorded in most cases. They were characterised by constant latency and uniform pattern, were...... stimulation to a minimum of 30-60 ms. This response represented the clinical observable spinal reflex, "the classical anal reflex". The latencies of the two first responses were so short that they probably do not represent spinal reflexes. This was further supported by the effect of epidural anaesthesia which...... left the first responses unaffected but abolished the classical anal reflex. The origin of the two first responses is discussed and models involving antidromal impulse propagation in the efferent fibre as the afferent limbs of the responses are proposed....

  14. Determinants of electricity demand for newly electrified low-income African households

    Energy Technology Data Exchange (ETDEWEB)

    Louw, Kate [Energy Research Centre, University of Cape Town, Cape Town, Private Bag, Rondebosch 7701 (South Africa); Conradie, Beatrice [School of Economics, University of Cape Town (South Africa); Howells, Mark [Planning and Economic Studies Section (PESS), International Atomic Energy Agency, Vienna (Austria); Dekenah, Marcus [Marcus Dekenah Consulting, Centurion (South Africa)

    2008-08-15

    Access to clean, affordable and appropriate energy is an important enabler of development. Energy allows households to meet their most basic subsistence needs; it is a central feature of all the millennium development goals (MDGs) and, while a lack of access to energy may not be a cause of poverty, addressing the energy needs of the impoverished lets them access services which in turn address the causes of poverty. While much is known about the factors affecting the decisions made when choosing between fuel types within a household, few quantitative studies have been carried out in South Africa to determine the extent to which these factors affect energy choice decisions. It is assumed that the factors traditionally included in economic demand such as price and income of the household affect choice; tastes and preferences as well as external factors such as distance to fuel suppliers are expected to influence preferences. This study follows two typical low-income rural sites in South Africa, Antioch and Garagapola, where the Electricity Basic Services Support Tariff (EBSST) was piloted in 2002. The EBSST is set at 50 kWh/month per household for low domestic consumers; this is worth approximately R20 ({+-}US$3). This subsidy is a lifeline tariff, where households receive the set amount of units per month, free of charge irrespective of whether more units are purchased. These data (collected in 2001 and 2002), recently collated with detailed electricity consumption data, allow us to determine the drivers of electricity consumption within these households. The sample analysed is taken from the initial phase of the study, when no FBE had been introduced to the households. This enabled the study presented here to make use of the well-populated datasets to assess what affects the electricity use decision in these households. This paper attempts to assess which factors affected the decision-making process for electricity consumption within these households. A brief

  15. Dynamic Pricing for Demand Response Considering Market Price Uncertainty

    National Research Council Canada - National Science Library

    Mohammad Ali Fotouhi Ghazvini; João Soares; Hugo Morais; Rui Castro; Zita Vale

    2017-01-01

    ...) units to avoid financial losses in the volatile electricity markets. In this paper, the problem of setting dynamic retail sales price by a REP is addressed with a robust optimization technique...

  16. Assessing the influence of manufacturing sectors on electricity demand. A cross-country input-output approach

    Energy Technology Data Exchange (ETDEWEB)

    Tarancon, Miguel Angel; Callejas Albinana, Fernando [Faculty of Law and Social Sciences, Universidad de Castilla - La Mancha, Ronda de Toledo s/n, 13071 Ciudad Real (Spain); Del Rio, Pablo [Institute for Public Policies and Goods (IPP), Centro de Ciencias Humanas y Sociales, CSIC, C/Albasanz 26-28, 28037 Madrid (Spain)

    2010-04-15

    The production and consumption of electricity is a major source of CO{sub 2} emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input-output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price. (author)

  17. Assessment of Industrial Load for Demand Response across U.S. Regions of the Western Interconnect

    Energy Technology Data Exchange (ETDEWEB)

    Starke, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Alkadi, Nasr [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ma, Ookie [USDOE Office of Energy Efficiency and Renewable Energy (EERE), Washington, DC (United States)

    2013-09-01

    Demand response has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles for demand response that can provide more regional understanding and can be inserted into analysis software for further study.

  18. Supply-side-demand-side optimization and cost-environment trade offs for China`s coal and electricity system

    Energy Technology Data Exchange (ETDEWEB)

    Xie Zhijun; Kuby, M. [Boston University, Boston, MA (United States). Dept. of Geography, Center for Energy and Environmental Studies

    1997-02-01

    The authors simultaneously optimize supply-side and demand-size investments for satisfying China`s coal and electricity needs over a 15 year time horizon. The results are compared to equivalent results from a supply-side only optimization assuming a business-as-usual demand scenario. It is estimated that, by shifting investment from energy production and transportation to energy efficiency improvement, China could meet the same energy service demand in 2000 for 7% less cost and 120 million tons (mt) less coal. Alternatively, for greater environmental protection, China could satisfy the same demands at the same cost using 275 mt coal. 27 refs., 6 figs.

  19. Demand Response Design and Use Based on Network Locational Marginal Prices

    DEFF Research Database (Denmark)

    Morais, Hugo; Faria, Pedro; Vale, Zita

    2014-01-01

    Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation...... (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper...... proposes a methodology to support VPPs in the DR programs’ management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific...

  20. Estimating Large-Customer Demand Response Market Potential:Integrating Price and Customer Behavior

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Cappers, Peter

    2007-06-01

    ABSTRACT=Demand response (DR) is increasingly recognized asan essential ingredient to well-functioning electricity markets. DRmarket potential studies can answer questions about the amount of DRavailable in a given area, from which market segments. Several recent DRmarket potential studies have been conducted, most adapting techniquesused to estimate energy-efficiency (EE) potential. In this scoping study,we: reviewed and categorized seven recent DR market potential studies;recommended a methodology for estimating DR market potential for large,non-residential utility customers that uses price elasticities to accountfor behavior and prices; compiled participation rates and elasticityvalues from six DR options offered to large customers in recent years,and demonstrated our recommended methodology with large customer marketpotential scenarios at an illustrative Northeastern utility. We recommendan elasticity approach for large-customer DR options that rely oncusto!

  1. The Response of Abortion Demand to Changes in Abortion Costs

    Science.gov (United States)

    Medoff, Marshall H.

    2008-01-01

    This study uses pooled cross-section time-series data, over the years 1982, 1992 and 2000, to estimate the impact of various restrictive abortion laws on the demand for abortion. This study complements and extends prior research by explicitly including the price of obtaining an abortion in the estimation. The empirical results show that the real…

  2. The adaptative response of jaw muscles to varying functional demands

    NARCIS (Netherlands)

    Grünheid, T.; Langenbach, G.E.J.; Korfage, J.A.M.; Zentner, A.; van Eijden, T.M.G.J.

    2009-01-01

    Jaw muscles are versatile entities that are able to adapt their anatomical characteristics, such as size, cross-sectional area, and fibre properties, to altered functional demands. The dynamic nature of muscle fibres allows them to change their phenotype to optimize the required contractile function

  3. Implementation and Test of Demand Response using Behaviour Descriptions

    DEFF Research Database (Denmark)

    Kullmann, Daniel; Gehrke, Oliver; Bindner, Henrik W.

    2011-01-01

    The term Smart Grid describes the effort to enable the integration of large numbers of renewable distributed energy resources into the power grid. The fluctuations inherent in renewable energy resources imply the need to also integrate the demand side actively into the control of the power system...

  4. Demand Response Spinning Reserve Demonstration -- Phase 2 Findings from the Summer of 2008

    Energy Technology Data Exchange (ETDEWEB)

    Eto, Joseph H.; Nelson-Hoffman, Janine; Parker, Eric; Bernier, Clark; Young, Paul; Sheehan, Dave; Kueck, John; Kirby, Brendan

    2009-04-30

    The Demand Response Spinning Reserve project is a pioneering demonstration showing that existing utility load-management assets can provide an important electricity system reliability resource known as spinning reserve. Using aggregated demand-side resources to provide spinning reserve as demonstrated in this project will give grid operators at the California Independent System Operator (CA ISO) and Southern California Edison (SCE) a powerful new tool to improve reliability, prevent rolling blackouts, and lower grid operating costs.In the first phase of this demonstration project, we target marketed SCE?s air-conditioning (AC) load-cycling program, called the Summer Discount Plan (SDP), to customers on a single SCE distribution feederand developed an external website with real-time telemetry for the aggregated loads on this feeder and conducted a large number of short-duration curtailments of participating customers? air-conditioning units to simulate provision of spinning reserve. In this second phase of the demonstration project, we explored four major elements that would be critical for this demonstration to make the transition to a commercial activity:1. We conducted load curtailments within four geographically distinct feeders to determine the transferability of target marketing approaches and better understand the performance of SCE?s load management dispatch system as well as variations in the AC use of SCE?s participating customers;2. We deployed specialized, near-real-time AC monitoring devices to improve our understanding of the aggregated load curtailments we observe on the feeders;3. We integrated information provided by the AC monitoring devices with information from SCE?s load management dispatch system to measure the time required for each step in the curtailment process; and4. We established connectivity with the CA ISO to explore the steps involved in responding to CA ISO-initiated requests for dispatch of spinning reserve.The major findings from

  5. Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Hang T.; Nabney, Ian T. [Non-linearity and Complexity Research Group, School of Engineering and Applied Science, Aston University, Aston Triangle, Birmingham B4 7ET (United Kingdom)

    2010-09-15

    This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their NMSEs are 0.02314 and 0.15384 respectively. (author)

  6. Spatial analysis of electricity demand patterns in Greece: Application of a GIS-based methodological framework

    Science.gov (United States)

    Tyralis, Hristos; Mamassis, Nikos; Photis, Yorgos N.

    2016-04-01

    We investigate various uses of electricity demand in Greece (agricultural, commercial, domestic, industrial use as well as use for public and municipal authorities and street lightning) and we examine their relation with variables such as population, total area, population density and the Gross Domestic Product. The analysis is performed on data which span from 2008 to 2012 and have annual temporal resolution and spatial resolution down to the level of prefecture. We both visualize the results of the analysis and we perform cluster and outlier analysis using the Anselin local Moran's I statistic as well as hot spot analysis using the Getis-Ord Gi* statistic. The definition of the spatial patterns and relationships of the aforementioned variables in a GIS environment provides meaningful insight and better understanding of the regional development model in Greece and justifies the basis for an energy demand forecasting methodology. Acknowledgement: This research has been partly financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARISTEIA II: Reinforcement of the interdisciplinary and/ or inter-institutional research and innovation (CRESSENDO project; grant number 5145).

  7. Performance Assessment of Aggregation Control Services for Demand Response

    DEFF Research Database (Denmark)

    Bondy, Daniel Esteban Morales; Costanzo, Giuseppe Tommaso; Heussen, Kai

    2014-01-01

    . This paper formulates performance measures and an index to evaluate in hind sight the quality of service delivery by an aggregator, both with respect to ancillary service and asset management service. The index is based on requirements formulated in service contracts and provides an overall assessment......Aggregation algorithms that provide services to the grid via demand side management are moving from research ideas to the market. With the diversity of the technology delivering such services, it becomes essential to establish transparent performance standards from a service delivery perspective...... of the quality of service provided by an aggregation control algorithm. By a detailed case study we present and an application of the index, comparing the performance of two different control architectures for demand side management delivering a distribution grid service....

  8. Dynamic Pricing: An Efficient Solution for True Demand Response Enabling

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2017-01-01

    , to provide a reliable reference point based on mathematical models, this paper utilizes well-known economics theories and mathematical formulations to prove the impact of RTP on true enabling of DR actions in electricity markets. Based on the theory of saving under uncertainty, it is shown that the use...

  9. A Methodology for Estimating Large-Customer Demand Response MarketPotential

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Charles; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Cappers,Peter

    2007-08-01

    Demand response (DR) is increasingly recognized as an essential ingredient to well-functioning electricity markets. DR market potential studies can answer questions about the amount of DR available in a given area and from which market segments. Several recent DR market potential studies have been conducted, most adapting techniques used to estimate energy-efficiency (EE) potential. In this scoping study, we: reviewed and categorized seven recent DR market potential studies; recommended a methodology for estimating DR market potential for large, non-residential utility customers that uses price elasticities to account for behavior and prices; compiled participation rates and elasticity values from six DR options offered to large customers in recent years, and demonstrated our recommended methodology with large customer market potential scenarios at an illustrative Northeastern utility. We observe that EE and DR have several important differences that argue for an elasticity approach for large-customer DR options that rely on customer-initiated response to prices, rather than the engineering approaches typical of EE potential studies. Base-case estimates suggest that offering DR options to large, non-residential customers results in 1-3% reductions in their class peak demand in response to prices or incentive payments of $500/MWh. Participation rates (i.e., enrollment in voluntary DR programs or acceptance of default hourly pricing) have the greatest influence on DR impacts of all factors studied, yet are the least well understood. Elasticity refinements to reflect the impact of enabling technologies and response at high prices provide more accurate market potential estimates, particularly when arc elasticities (rather than substitution elasticities) are estimated.

  10. Optimal Ozone Control with Inclusion of Spatiotemporal Marginal Damages and Electricity Demand.

    Science.gov (United States)

    Mesbah, S Morteza; Hakami, Amir; Schott, Stephan

    2015-07-07

    Marginal damage (MD), or damage per ton of emission, is a policy metric used for effective pollution control and reducing the corresponding adverse health impacts. However, for a pollutant such as NOx, the MD varies by the time and location of the emissions, a complication that is not adequately accounted for in the currently implemented economic instruments. Policies accounting for MD information would aim to encourage emitters with large MDs to reduce their emissions. An optimization framework is implemented to account for NOx spatiotemporal MDs calculated through adjoint sensitivity analysis and to simulate power plants' behavior under emission and simplified electricity constraints. The results from a case study of U.S. power plants indicate that time-specific MDs are high around noon and low in the evening. Furthermore, an emissions reduction of about 40% and a net benefit of about $1200 million can be gained for this subset of power plants if a larger fraction of the electricity demand is supplied by power plants at low-damage times and in low-damage locations. The results also indicate that the consideration of temporal effects in NOx control policies results in a comparable net benefit to the consideration of spatial or spatiotemporal effects, thus providing a promising option for policy development.

  11. Demand Response in Low Voltage Distribution Networks with High PV Penetration

    DEFF Research Database (Denmark)

    Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    . Simulation results show that the proposed method is effective for calculating the optimum demand response. From the test scenarios, it is inferred that absorption of renewable energy from PV increased by 38% applying optimum demand response during the evaluation period in the studied distribution network....

  12. Implementation of a building energy management system for residential demand response

    DEFF Research Database (Denmark)

    Rotger Griful, Sergi; Welling, Ubbe; Jacobsen, Rune Hylsberg

    2017-01-01

    Demand response is proposed as a solution to handle the fluctuations in the power supply in a scenario with higher penetration of renewable energy sources. Although demand response already offers a positive business case in certain domains, it still lacks maturity in other areas, especially in th...

  13. Optimal Control of Distributed Energy Resources and Demand Response under Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Siddiqui, Afzal; Stadler, Michael; Marnay, Chris; Lai, Judy

    2010-06-01

    We take the perspective of a microgrid that has installed distribution energy resources (DER) in the form of distributed generation with combined heat and power applications. Given uncertain electricity and fuel prices, the microgrid minimizes its expected annual energy bill for various capacity sizes. In almost all cases, there is an economic and environmental advantage to using DER in conjunction with demand response (DR): the expected annualized energy bill is reduced by 9percent while CO2 emissions decline by 25percent. Furthermore, the microgrid's risk is diminished as DER may be deployed depending on prevailing market conditions and local demand. In order to test a policy measure that would place a weight on CO2 emissions, we use a multi-criteria objective function that minimizes a weighted average of expected costs and emissions. We find that greater emphasis on CO2 emissions has a beneficial environmental impact only if DR is available and enough reserve generation capacity exists. Finally, greater uncertainty results in higher expected costs and risk exposure, the effects of which may be mitigated by selecting a larger capacity.

  14. Why Electricity Demand Is Highly Income-Elastic in Spain: A Cross-Country Comparison Based on an Index-Decomposition Analysis

    Directory of Open Access Journals (Sweden)

    Julián Pérez-García

    2017-03-01

    Full Text Available Since 1990, Spain has had one of the highest elasticities of electricity demand in the European Union. We provide an in-depth analysis into the causes of this high elasticity, and we examine how these same causes influence electricity demand in other European countries. To this end, we present an index-decomposition analysis of growth in electricity demand which allows us to identify three key factors in the relationship between gross domestic product (GDP and electricity demand: (i structural change; (ii GDP growth; and (iii intensity of electricity use. Our findings show that the main differences in electricity demand elasticities across countries and time are accounted for by the fast convergence in residential per capita electricity consumption. This convergence has almost concluded, and we expect the Spanish energy demand elasticity to converge to European standards in the near future.

  15. Bayesian Learning of Consumer Preferences for Residential Demand Response

    OpenAIRE

    Goubko, Mikhail V.; Kuznetsov, Sergey O.; Neznanov, Alexey A.; Ignatov, Dmitry I.

    2017-01-01

    In coming years residential consumers will face real-time electricity tariffs with energy prices varying day to day, and effective energy saving will require automation - a recommender system, which learns consumer's preferences from her actions. A consumer chooses a scenario of home appliance use to balance her comfort level and the energy bill. We propose a Bayesian learning algorithm to estimate the comfort level function from the history of appliance use. In numeric experiments with datas...

  16. INDIA’S ELECTRICITY DEMAND FORECAST USING REGRESSION ANALYSIS AND ARTIFICIAL NEURAL NETWORKS BASED ON PRINCIPAL COMPONENTS

    Directory of Open Access Journals (Sweden)

    S. Saravanan

    2012-07-01

    Full Text Available Power System planning starts with Electric load (demand forecasting. Accurate electricity load forecasting is one of the most important challenges in managing supply and demand of the electricity, since the electricity demand is volatile in nature; it cannot be stored and has to be consumed instantly. The aim of this study deals with electricity consumption in India, to forecast future projection of demand for a period of 19 years from 2012 to 2030. The eleven input variables used are Amount of CO2 emission, Population, Per capita GDP, Per capita gross national income, Gross Domestic savings, Industry, Consumer price index, Wholesale price index, Imports, Exports and Per capita power consumption. A new methodology based on Artificial Neural Networks (ANNs using principal components is also used. Data of 29 years used for training and data of 10 years used for testing the ANNs. Comparison made with multiple linear regression (based on original data and the principal components and ANNs with original data as input variables. The results show that the use of ANNs with principal components (PC is more effective.

  17. Analysis of residential, industrial and commercial sector responses to potential electricity supply constraints in the 1990s

    Energy Technology Data Exchange (ETDEWEB)

    Fisher, Z.J.; Fang, J.M.; Lyke, A.J.; Krudener, J.R.

    1986-09-01

    There is considerable debate over the ability of electric generation capacity to meet the growing needs of the US economy in the 1990s. This study provides new perspective on that debate and examines the possibility of power outages resulting from electricity supply constraints. Previous studies have focused on electricity supply growth, demand growth, and on the linkages between electricity and economic growth. This study assumes the occurrence of electricity supply shortfalls in the 1990s and examines the steps that homeowners, businesses, manufacturers, and other electricity users might take in response to electricity outages.

  18. Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Yi Yu

    2018-02-01

    Full Text Available The integration of renewables is fast-growing, in light of smart grid technology development. As a result, the uncertain nature of renewables and load demand poses significant technical challenges to distribution network (DN daily operation. To alleviate such issues, price-sensitive demand response and distributed generators can be coordinated to accommodate the renewable energy. However, the investment cost for demand response facilities, i.e., load control switch and advanced metering infrastructure, cannot be ignored, especially when the responsive demand is large. In this paper, an optimal coordinated investment for distributed generator and demand response facilities is proposed, based on a linearized, price-elastic demand response model. To hedge against the uncertainties of renewables and load demand, a two-stage robust investment scheme is proposed, where the investment decisions are optimized in the first stage, and the demand response participation with the coordination of distributed generators is adjusted in the second stage. Simulations on the modified IEEE 33-node and 123-node DN demonstrate the effectiveness of the proposed model.

  19. Agricultural sectoral demand and crop productivity response across the world

    Science.gov (United States)

    Johnston, M.; Ray, D. K.; Cassidy, E. S.; Foley, J. A.

    2013-12-01

    With an increasing and increasingly affluent population, humans will need to roughly double agricultural production by 2050. Continued yield growth forms the foundation of all future strategies aiming to increase agricultural production while slowing or eliminating cropland expansion. However, a recent analysis by one of our co-authors has shown that yield trends in many important maize, wheat and rice growing regions have begun stagnating or declining from the highs seen during the green revolution (Ray et al. 2013). Additional research by our group has shown that nearly 50% of new agricultural production since the 1960s has gone not to direct human consumption, but instead to animal feed and other industrial uses. Our analysis for GLP looks at the convergence of these two trends by examining time series utilization data for 16 of the biggest crops to determine how demand from different sectors has shaped our land-use and intensification strategies around the world. Before rushing headlong into the next agricultural doubling, it would be prudent to first consult our recent agricultural history to better understand what was driving past changes in production. Using newly developed time series dataset - a fusion of cropland maps with historic agricultural census data gathered from around the world - we can examine yield and harvested area trends over the last half century for 16 top crops. We combine this data with utilization rates from the FAO Food Balance Sheet to see how demand from different sectors - food, feed, and other - has influenced long-term growth trends from the green revolution forward. We will show how intensification trends over time and across regions have grown or contracted depending on what is driving the change in production capacity. Ray DK, Mueller ND, West PC, Foley JA (2013) Yield Trends Are Insufficient to Double Global Crop Production by 2050. PLoS ONE 8(6): e66428. doi:10.1371/journal.pone.0066428

  20. Process-based modelling of regional water demand for electricity, industry and municipal sectors in Integrated Assessment Models.

    Science.gov (United States)

    Bijl, David L.; Bogaart, Patrick W.; Kram, Tom; De Vries, Bert J. M.; Van Vuuren, Detlef P.

    2014-05-01

    Integrated Assessment Models (IAMs) are a prime tool for studying global scale interactions between the human and natural earth systems. Our research contributes to this field by modelling water, food and energy demand as outcomes of more physical processes and by adding links between them. As part of this ambition, we here describe a model for water demand in the electricity generation, industrial and municipal sectors, going beyond previous modelling efforts. For instance, by coupling water demand to energy inputs, the model directly couples water efficiency to fuel efficiency of power plants. We present electricity, industry and municipal water demand models and develop water demand projections for the new Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) for climate research. Our regional-level demand models contribute to understanding the extent of crossing planetary boundaries and the scope for solutions such as virtual water trade or efficiency improvements. We also discuss how we plan to link demand and supply models, and how the usefulness for policy makers can be increased.

  1. Religiosity, attitude and the demand for socially responsible products

    NARCIS (Netherlands)

    Graafland, Johan

    In this paper, we examine the relationship between various Christian denominations and attitude and behavior regarding consumption of socially responsible (SR) products. Literature on the relationship between religiosity and pro-social behavior has shown that religiosity strengthens positive

  2. Simulation of demand-response power management in smart city

    Science.gov (United States)

    Kadam, Kshitija

    Smart Grids manage energy efficiently through intelligent monitoring and control of all the components connected to the electrical grid. Advanced digital technology, combined with sensors and power electronics, can greatly improve transmission line efficiency. This thesis proposed a model of a deregulated grid which supplied power to diverse set of consumers and allowed them to participate in decision making process through two-way communication. The deregulated market encourages competition at the generation and distribution levels through communication with the central system operator. A software platform was developed and executed to manage the communication, as well for energy management of the overall system. It also demonstrated self-healing property of the system in case a fault occurs, resulting in an outage. The system not only recovered from the fault but managed to do so in a short time with no/minimum human involvement.

  3. Field Testing of Telemetry for Demand Response Control of Small Loads

    Energy Technology Data Exchange (ETDEWEB)

    Lanzisera, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Weber, Adam [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Liao, Anna [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Schetrit, Oren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2018-01-30

    The electricity system in California, from generation through loads, must be prepared for high renewable penetration and increased electrification of end uses while providing increased resilience and lower operating cost. California has an aggressive renewable portfolio standard that is complemented by world-leading greenhouse gas goals. The goal of this project was to evaluate methods of enabling fast demand response (DR) signaling to small loads for low-cost site enablement. We used OpenADR 2.0 to meet telemetry requirements for providing ancillary services, and we used a variety of low-cost devices coupled with open-source software to enable an end-to-end fast DR. The devices, architecture, implementation, and testing of the system is discussed in this report. We demonstrate that the emerging Internet of Things (IoT) and Smart Home movements provide an opportunity for diverse small loads to provide fast, low-cost demand response. We used Internet-connected lights, thermostats, load interruption devices, and water heaters to demonstrate an ecosystem of controllable devices. The system demonstrated is capable of providing fast load shed for between 20 dollars and $300 per kilowatt (kW) of available load. The wide range results from some loads may have very low cost but also very little shed capability (a 10 watt [W] LED light can only shed a maximum of 10 W) while some loads (e.g., water heaters or air conditioners) can shed several kilowatts but have a higher initial cost. These costs, however, compare well with other fast demand response costs, with typically are over $100/kilowatt of shed. We contend these loads are even more attractive than their price suggests because many of them will be installed for energy efficiency or non-energy benefits (e.g., improved lighting quality or controllability), and the ability to use them for fast DR is a secondary benefit. Therefore the cost of enabling them for DR may approach zero if a software-only solution can be

  4. Web-based energy information systems for energy management and demand response in commercial buildings

    Energy Technology Data Exchange (ETDEWEB)

    Motegi, Naoya; Piette, Mary Ann; Kinney, Satkartar; Herter, Karen

    2003-04-18

    Energy Information Systems (EIS) for buildings are becoming widespread in the U.S., with more companies offering EIS products every year. As a result, customers are often overwhelmed by the quickly expanding portfolio of EIS feature and application options, which have not been clearly identified for consumers. The object of this report is to provide a technical overview of currently available EIS products. In particular, this report focuses on web-based EIS products for large commercial buildings, which allow data access and control capabilities over the Internet. EIS products combine software, data acquisition hardware, and communication systems to collect, analyze and display building information to aid commercial building energy managers, facility managers, financial managers and electric utilities in reducing energy use and costs in buildings. Data types commonly processed by EIS include energy consumption data; building characteristics; building system data, such as heating, ventilation, and air-conditioning (HVAC) and lighting data; weather data; energy price signals; and energy demand-response event information. This project involved an extensive review of research and trade literature to understand the motivation for EIS technology development. This study also gathered information on currently commercialized EIS. This review is not an exhaustive analysis of all EIS products; rather, it is a technical framework and review of current products on the market. This report summarizes key features available in today's EIS, along with a categorization framework to understand the relationship between EIS, Energy Management and Control Systems (EMCSs), and similar technologies. Four EIS types are described: Basic Energy Information Systems (Basic-EIS); Demand Response Systems (DRS); Enterprise Energy Management (EEM); and Web-based Energy Management and Control Systems (Web-EMCS). Within the context of these four categories, the following characteristics of EIS

  5. Management and control of the electrical energy demand; Administracion y control de la demanda de la energia electrica

    Energy Technology Data Exchange (ETDEWEB)

    Johnson Controls [Comision Federal de Electricidad (Mexico)

    2005-07-01

    Administrative measures allow a reduction in the energy consumption, but not always in the electrical demand. Control measures allow a reduction in the billing of the electrical demand, but not always in the energy consumption. This is why it is explained in this document what management and control of the electrical demand is, as well as its control strategies, the control alternatives, the billing demand and at the same time graphical representations along with three practical cases on the management of demand in air compressors, air conditioning equipment and in corporative buildings are presented. [Spanish] La aplicacion de las medidas administrativas permite reducir el consumo de energia, pero no siempre la demanda electrica. La aplicacion de medidas de control permiten reducir la demanda electrica facturable, pero no siempre el consumo de energia. Es por eso que en este documento se explica que es la administracion y el control de la demanda electrica, sus estrategias de control, las alternativas de control, la demanda facturable, representaciones graficas y tres casos practicos sobre la administracion de demanda en compresores de aire, la administracion de demanda en aire acondicionado y la administracion de demanda en un edificio corporativo.

  6. Strategic Demand-Side Response to Wind Power Integration

    DEFF Research Database (Denmark)

    Daraeepour, Ali; Kazempour, Seyyedjalal; Patiño-Echeverri, Dalia

    2016-01-01

    This paper explores the effects of allowing large, price-responsive consumers to provide reserves in a power system with significant penetration of wind energy. A bilevel optimization model represents the utility maximization problem of a large consumer, subject to a stochastic day-ahead co-optim...

  7. Market and Policy Barriers for Demand Response Providing Ancillary Services in U.S. Markets

    Energy Technology Data Exchange (ETDEWEB)

    Cappers, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); MacDonald, Jason [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goldman, Charles [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-03-01

    In this study, we attempt to provide a comprehensive examination of various market and policy barriers to demand response providing ancillary services in both ISO/RTO and non-ISO/RTO regions, especially at the program provider level. It is useful to classify barriers in order to create a holistic understanding and identify parties that could be responsible for their removal. This study develops a typology of barriers focusing on smaller customers that must rely on a program provider (i.e., electric investor owned utility or IOU, ARC) to create an aggregated DR resource in order to bring ancillary services to the balancing authority.ii The barriers were identified through examinations of regulatory structures, market environments, and product offerings; and discussions with industry stakeholders and regulators. In order to help illustrate the differences in barriers among various wholesale market designs and their constituent retail environments, four regions were chosen to use as case studies: Colorado, Texas, Wisconsin, and New Jersey. We highlight the experience in each area as it relates to the identified barriers.

  8. Fatigued and dissatisfied or fatigued but satisfied? Goal orientations and responses to high job demands.

    NARCIS (Netherlands)

    Van Yperen, N.W.; Janssen, O.

    2002-01-01

    The present study tested dispositional goal orientation as an explanation for variation in responses to high job demands. Survey data from 322 university employees demonstrated that job demands were positively related to fatigue, for all combinations of goal orientation. In line with our main

  9. Cardiac responsiveness to attention-demanding tasks in socially maladaptive children

    NARCIS (Netherlands)

    Althaus, M; Aarnoudse, CC; Minderaa, RB; Mulder, Gysbertus; Mulder, Lambertus

    Cardiac responsiveness to attention-demanding tasks in socially maladaptive children A psychofysiological study of the cardiac adaptivity to attention-demanding reaction time tasks demonstrated that children with a lesser variant of the pervasive developmental disorder (DSM-IV: PDDNOS) exhibit less

  10. How task demands shape brain responses to visual food cues.

    Science.gov (United States)

    Pohl, Tanja Maria; Tempelmann, Claus; Noesselt, Toemme

    2017-06-01

    Several previous imaging studies have aimed at identifying the neural basis of visual food cue processing in humans. However, there is little consistency of the functional magnetic resonance imaging (fMRI) results across studies. Here, we tested the hypothesis that this variability across studies might - at least in part - be caused by the different tasks employed. In particular, we assessed directly the influence of task set on brain responses to food stimuli with fMRI using two tasks (colour vs. edibility judgement, between-subjects design). When participants judged colour, the left insula, the left inferior parietal lobule, occipital areas, the left orbitofrontal cortex and other frontal areas expressed enhanced fMRI responses to food relative to non-food pictures. However, when judging edibility, enhanced fMRI responses to food pictures were observed in the superior and middle frontal gyrus and in medial frontal areas including the pregenual anterior cingulate cortex and ventromedial prefrontal cortex. This pattern of results indicates that task sets can significantly alter the neural underpinnings of food cue processing. We propose that judging low-level visual stimulus characteristics - such as colour - triggers stimulus-related representations in the visual and even in gustatory cortex (insula), whereas discriminating abstract stimulus categories activates higher order representations in both the anterior cingulate and prefrontal cortex. Hum Brain Mapp 38:2897-2912, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  11. Prosumer with demand response - Distribution network impact and mitigation

    Energy Technology Data Exchange (ETDEWEB)

    Ackeby, S.; Bollen, M.; Munkhammar, J.

    2013-05-15

    This report is the result from a project funded by ELFORSK done by STRI. The project is studying the effects the introduction of so called 'prosumers' (customers with own production) and electrical vehicles will have on different types of networks. Four different cases are studied covering urban and rural areas with different types of customers. In the urban areas the power through the transformer will be the limiting factor. The major impact in the cases studied is from the introduction of production from photovoltaics at the customer-side of the meter. This will result in an introduction of surplus due to production which in one case led to an increase of the absolute power through the transformer with more than 30 %, which resulted in transformer overloading. In the rural areas the voltage drop or rise will be the limiting factor. The cases studied had already high voltage drops even in the base cases. In the case studies it was seen that the voltage drop could be slightly reduced when introducing more local production, but the production also led to that voltage rise could appear. As a result the interval of the voltage variations was increased, which in turn leads to difficulties with designing the network such that neither overvoltage nor undervoltage occurs. Introducing control algorithms had a very positive effect on reducing the net production from the photovoltaics. Using both hard and soft curtailment made it possible to remove all overcurrents or overvoltages. Using hard curtailment, where all production is turned off during overcurrent or overvoltage, leads however to a large reduction in energy from renewable energy sources. Therefore soft curtailment should as much as possible be used. The control algorithms studied for reducing the net consumption had a more limited effect and even resulted in an increase of the maximum net consumption. When trying to reduce the net consumption during an overload, the reason of the overload could only be

  12. Water demands for electricity generation in the U.S.: Modeling different scenarios for the water–energy nexus

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Lu; Hejazi, Mohamad I.; Patel, Pralit L.; Kyle, G. Page; Davies, Evan; Zhou, Yuyu; Clarke, Leon E.; Edmonds, James A.

    2015-05-01

    Water withdrawal for electricity generation in the United States accounts for approximately half the total freshwater withdrawal. With steadily growing electricity demands, a changing climate, and limited water supplies in many water-scarce states, meeting future energy and water demands poses a significant socio-economic challenge. Employing an integrated modeling approach that can capture the energy-water interactions at regional and national scales is essential to improve our understanding of the key drivers that govern those interactions and the role of national policies. In this study, the Global Change Assessment Model (GCAM), a technologically-detailed integrated model of the economy, energy, agriculture and land use, water, and climate systems, was extended to model the electricity and water systems at the state level in the U.S. (GCAM-USA). GCAM-USA was employed to estimate future state-level electricity generation and consumption, and their associated water withdrawals and consumption under a set of six scenarios with extensive details on the generation fuel portfolio, cooling technology mix, and their associated water use intensities. Six scenarios of future water demands of the U.S. electric-sector were explored to investigate the implications of socioeconomics development and growing electricity demands, climate mitigation policy, the transition of cooling systems, electricity trade, and water saving technologies. Our findings include: 1) decreasing water withdrawals and substantially increasing water consumption from both climate mitigation and the conversion from open-loop to closed-loop cooling systems; 2) open trading of electricity benefiting energy scarce yet demand intensive states; 3) within state variability under different driving forces while across state homogeneity under certain driving force ; 4) a clear trade-off between water consumption and withdrawal for the electricity sector in the U.S. The paper discusses this withdrawal

  13. Demand Profile Study of Battery Electric Vehicle under Different Charging Options

    DEFF Research Database (Denmark)

    Marra, Francesco; Yang, Guang Ya; Træholt, Chresten

    2012-01-01

    An increased research on electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) deals with their flexible use in electric power grids. Several research projects on smart grids and electric mobility are now looking into realistic models representing the behavior of an EV during charging...

  14. Hierarchical Control Architecture for Demand Response in Smart Grid Scenario

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte; Mahat, Pukar

    2013-01-01

    , a number of issues, including DR enabling technologies, control strategy, and control architecture, are still under discussion. This paper outlines novel control requirements based on the categorization of existing DR techniques. More specifically, the roles and responsibilities of smart grid actors...... effective tool for optimum asset utilization and to avoid or delay the need for new infrastructure investment. Furthermore, most of the power networks are under the process of reconfiguration to realize the concept of smart grid and are at the transforming stage to support various forms of DR. However...

  15. How price responsive is the demand for specialty care?

    Science.gov (United States)

    Maciejewski, Matthew L; Liu, Chuan-Fen; Kavee, Andrew L; Olsen, Maren K

    2012-08-01

    Outpatient visit co-payments have increased in recent years. We estimate the patient response to a price change for specialty care, based on a co-payment increase from $15 to $50 per visit for veterans with hypertension. A retrospective cohort of veterans required to pay co-payments was compared with veterans exempt from co-payments whose nonequivalence was reduced via propensity score matching. Specialty care expenditures in 2000-2003 were estimated via a two-part mixed model to account for the correlation of the use and level outcomes over time, and results from this correlated two-part model were compared with an uncorrelated two-part model and a correlated random intercept two-part mixed model. A $35 specialty visit co-payment increase had no impact on the likelihood of seeking specialty care but induced lower specialty expenditures over time among users who were required to pay co-payments. The log ratio of price responsiveness (semi-elasticity) for specialty care increased from -0.25 to -0.31 after the co-payment increase. Estimates were similar across the three models. A significant increase in specialty visit co-payments reduced specialty expenditures among patients obtaining medications at the Veterans Affairs medical centers. Longitudinal expenditure analysis may be improved using recent advances in two-part model methods. Published 2011. This article is a US Government work and is in the public domain in the USA.

  16. Modelling a demand driven biogas system for production of electricity at peak demand and for production of biomethane at other times.

    Science.gov (United States)

    O'Shea, R; Wall, D; Murphy, J D

    2016-09-01

    Four feedstocks were assessed for use in a demand driven biogas system. Biomethane potential (BMP) assays were conducted for grass silage, food waste, Laminaria digitata and dairy cow slurry. Semi-continuous trials were undertaken for all feedstocks, assessing biogas and biomethane production. Three kinetic models of the semi-continuous trials were compared. A first order model most accurately correlated with gas production in the pulse fed semi-continuous system. This model was developed for production of electricity on demand, and biomethane upgrading. The model examined a theoretical grass silage digester that would produce 435kWe in a continuous fed system. Adaptation to demand driven biogas required 187min to produce sufficient methane to run a 2MWe combined heat and power (CHP) unit for 60min. The upgrading system was dispatched 71min following CHP shutdown. Of the biogas produced 21% was used in the CHP and 79% was used in the upgrading system. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. On the Trade-off Between Real-time Pricing and the Social Acceptability Costs of Demand Response

    DEFF Research Database (Denmark)

    da Silva, Hendrigo Batista; Santiago, Leonardo

    2018-01-01

    Dynamic tariff policies have become an essential feature of modern electric grid design. The successful implementation of such policies usually depends on overcoming the resistance of end-users to real-time pricing and its political implications. In this paper, we review the literature...... on the social acceptability costs of implementing demand response programs, and we discuss the key features of implementing a real-time price to energy. Although the literature acknowledges the existence of a social acceptability cost, it does not propose an explicit approach to dealing with this issue. A model...

  18. Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system

    Science.gov (United States)

    Koskinas, Aristotelis; Zacharopoulou, Eleni; Pouliasis, George; Engonopoulos, Ioannis; Mavroyeoryos, Konstantinos; Deligiannis, Ilias; Karakatsanis, Georgios; Dimitriadis, Panayiotis; Iliopoulou, Theano; Koutsoyiannis, Demetris; Tyralis, Hristos

    2017-04-01

    We simulate the electrical energy demand in the remote island of Astypalaia. To this end we first obtain information regarding the local socioeconomic conditions and energy demand. Secondly, the available hourly demand data are analysed at various time scales (hourly, weekly, daily, seasonal). The cross-correlations between the electrical energy demand and the mean daily temperature as well as other climatic variables for the same time period are computed. Also, we investigate the cross-correlation between those climatic variables and other variables related to renewable energy resources from numerous observations around the globe in order to assess the impact of each one to a hybrid renewable energy system. An exploratory data analysis including all variables is performed with the purpose to find hidden relationships. Finally, the demand is simulated considering all the periodicities found in the analysis. The simulation time series will be used in the development of a framework for planning of a hybrid renewable energy system in Astypalaia. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

  19. Assessment of Restrained demand of Electricity, Natural Gas and Alcohol into Clean Development Context at Aracatuba Administrative Region

    Energy Technology Data Exchange (ETDEWEB)

    Heideier, Raphael B.; Ueocka, Marcos Z.; Udaeda, Miguel E.M. [Escola Politecnica da Universidade de Sao Paulo, Dep. de Engenharia de Energia, Sao Paulo (Brazil); Bernal, Jonathas [Instituto de Eletrotecnica e Energia da Universidade de Sao Paulo, Sao Paulo (Brazil)

    2009-07-01

    This paper assesses the restrained market of electricity, natural gas and alcohol in the Aracatuba Administrative Region (RAA) comparing the consumption with the average consumption of Sao Paulo State, Brazil, and Florida State, USA. Projections are made for the attendance of these demands in the context of clean development in a hypothetical set. Results show that the total restrained electric demand in the RAA was estimated in 22,467 MWh monthly in respect to Sao Paulo and 477,052 MWh monthly in respect to Florida, it means more power than the whole production of the region today and 3 times the demand nowadays. And the restrained vehicle demand in relation to the average of the state of Sao Paulo was low, about 5%, resulting in a restrained demand of less than 10 million liters per year (alcohol and gasoline). As the current production is about 2 billion liters of alcohol per year, one conclusion is that the RAA has potential to supply its necessity and export using only 10% of its territory in planted area of sugarcane.

  20. Analysis of PG&E`s residential end-use metered data to improve electricity demand forecasts -- final report

    Energy Technology Data Exchange (ETDEWEB)

    Eto, J.H.; Moezzi, M.M.

    1993-12-01

    This report summarizes findings from a unique project to improve the end-use electricity load shape and peak demand forecasts made by the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). First, the direct incorporation of end-use metered data into electricity demand forecasting models is a new approach that has only been made possible by recent end-use metering projects. Second, and perhaps more importantly, the joint-sponsorship of this analysis has led to the development of consistent sets of forecasting model inputs. That is, the ability to use a common data base and similar data treatment conventions for some of the forecasting inputs frees forecasters to concentrate on those differences (between their competing forecasts) that stem from real differences of opinion, rather than differences that can be readily resolved with better data. The focus of the analysis is residential space cooling, which represents a large and growing demand in the PG&E service territory. Using five years of end-use metered, central air conditioner data collected by PG&E from over 300 residences, we developed consistent sets of new inputs for both PG&E`s and CEC`s end-use load shape forecasting models. We compared the performance of the new inputs both to the inputs previously used by PG&E and CEC, and to a second set of new inputs developed to take advantage of a recently added modeling option to the forecasting model. The testing criteria included ability to forecast total daily energy use, daily peak demand, and demand at 4 P.M. (the most frequent hour of PG&E`s system peak demand). We also tested the new inputs with the weather data used by PG&E and CEC in preparing their forecasts.

  1. Development of a “Current Energy Mix Scenario” and a “Electricity as Main Energy Source Scenario” for electricity demand up to 2100

    Directory of Open Access Journals (Sweden)

    Mário J. S. Brito

    2014-06-01

    Full Text Available In this work, we develop a model to forecast world electricity production up to 2100. We analyze historical data for electricity production, population and GDP per Capita for the period 1900–2008. We show that electricity production follows general trends. First, there is an electricity intensity target of 0.20-0.25 kWh per unit of GDP (US$2012 as economies mature, except in countries traditionally relying heavily on renewable electricity (hydroelectricity, for whom this target ranges between 0.50 to 0.80 kWh per unit GDP. Also, countries that belong to the same region tend to follow the evolution of electricity production and GDP/Capita of a regional “modelcountry”. Equations that describe the behavior of these model countries are used to forecast electricity production per capita up to 2100 under a low and a high scenario for the evolution of GDP per Capita. For electricity production two main scenarios were set: “Current Energy MixScenario” and “Electricity as Main Energy Source Scenario”, with two additional sub scenarios considering slightly different electric intensities. Forecasts up to 2100 yield a demand forelectricity production 3.5 to 5 times higher than the current production for the “Current EnergyMix Scenario” and about 9 to 14 times for the “Electricity as Main Energy Source Scenario”. Forecasts for the “Current Energy Mix Scenario” matched well with forecasts from IEA/EIA (International Energy Agency/ Energy Information Administration while the forecasts for the“Electricity as the Main Energy Source Scenario” are much higher than current predictions.

  2. Distribution transformer lifetime analysis in the presence of demand response and rooftop PV integration

    Directory of Open Access Journals (Sweden)

    Behi Behnaz

    2017-01-01

    Full Text Available Many distribution transformers have already exceeded half of their expected service life of 35 years in the infrastructure of Western Power, the electric distribution company supplying southwest of Western Australia, Australia. Therefore, it is anticipated that a high investment on transformer replacement happens in the near future. However, high renewable integration and demand response (DR are promising resources to defer the investment on infrastructure upgrade and extend the lifetime of transformers. This paper investigates the impact of rooftop photovoltaic (PV integration and customer engagement through DR on the lifetime of transformers in electric distribution networks. To this aim, first, a time series modelling of load, DR and PV is utilised for each year over a planning period. This load model is applied to a typical distribution transformer for which the hot-spot temperature rise is modelled based on the relevant standard. Using this calculation platform, the loss of life and the actual age of distribution transformer are obtained. Then, various scenarios including different levels of PV penetration and DR contribution are examined, and their impacts on the age of transformer are reported. Finally, the equivalent loss of net present value of distribution transformer is formulated and discussed. This formulation gives major benefits to the distribution network planners for analysing the contribution of PV and DR on lifetime extension of the distribution transformer. In addition, the provided model can be utilised in optimal investment analysis to find the best time for the transformer replacement and the associated cost considering PV penetration and DR. The simulation results show that integration of PV and DR within a feeder can significantly extend the lifetime of transformers.

  3. Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias; Zhang, Jianhua; Li, Zhigang; Shafie-Khah, Miadreza; Catalao, Joao P. S.

    2017-11-01

    A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and upper bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.

  4. The impact of ICT investment and energy price on industrial electricity demand: Dynamic growth model approach

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Youngsang; Lee, Jongsu; Kim, Tai-Yoo [Technology Management, Economics and Policy Program, College of Engineering, Seoul National University, Shillim-Dong San56-1, Gwanak-Ku, Seoul 151-742 (Korea)

    2007-09-15

    The authors investigate the effects of information and communications technology (ICT) investment, electricity price, and oil price on the consumption of electricity in South Korea's industries using a logistic growth model. The concept electricity intensity is used to explain electricity consumption patterns. An empirical analysis implies that ICT investment in manufacturing industries that normally consume relatively large amounts of electricity promotes input factor substitution away from the labor intensive to the electricity intensive. Moreover, results also suggest that ICT investment in some specific manufacturing sectors is conducive to the reduction of electricity consumption, whereas ICT investment in the service sector and most manufacturing sectors increases electricity consumption. It is concluded that electricity prices critically affect electricity consumption in half of South Korea's industrial sectors, but not in the other half, a finding that differs somewhat from previous research results. Reasons are suggested to explain why the South Korean case is so different. Policymakers may find this study useful, as it answers the question of whether ICT investment can ultimately reduce energy consumption and may aid in planning the capacity of South Korea's national electric power. (author)

  5. Demand effects on positive response distortion by police officer applicants on the Revised NEO Personality Inventory.

    Science.gov (United States)

    Detrick, Paul; Chibnall, John T; Call, Cynthia

    2010-09-01

    Understanding and detecting response distortion is important in the high-demand circumstances of personnel selection. In this article, we describe positive response distortion on the Revised NEO Personality Inventory (NEO PI-R; Costa & McCrae, 1992) among police officer applicants under high and low demand conditions. Positive response distortion primarily reflected denial/minimization of Neuroticism and accentuation of traits associated with moralistic bias (Agreeableness and Conscientiousness). Validity of the NEO PI-R research validity scale, Positive Presentation Management, was weakly supported with respect to the Neuroticism domain only. Results will be useful in interpreting personality inventory results in the police personnel selection process.

  6. Water and Climate Impacts on Power System Operations: The Importance of Cooling Systems and Demand Response Measures

    Energy Technology Data Exchange (ETDEWEB)

    Macknick, Jordan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Zhou, Ella [National Renewable Energy Lab. (NREL), Golden, CO (United States); O' Connell, Matthew [National Renewable Energy Lab. (NREL), Golden, CO (United States); Brinkman, Gregory [National Renewable Energy Lab. (NREL), Golden, CO (United States); Miara, Ariel [City College of New York, NY (United States); Ibanez, Eduardo [GE Energy Connections, Atlanta, GA (United States); Hummon, Marissa [Tendril, Denver, CO (United States)

    2016-12-01

    The U.S. electricity sector is highly dependent upon water resources; changes in water temperatures and water availability can affect operational costs and the reliability of power systems. Despite the importance of water for power system operations, the effects of changes in water characteristics on multiple generators in a system are generally not modeled. Moreover, demand response measures, which can change the magnitude and timing of loads and can have beneficial impacts on power system operations, have not yet been evaluated in the context of water-related power vulnerabilities. This effort provides a first comprehensive vulnerability and cost analysis of water-related impacts on a modeled power system and the potential for demand response measures to address vulnerability and cost concerns. This study uniquely combines outputs and inputs of a water and power plant system model, production cost, model, and relative capacity value model to look at variations in cooling systems, policy-related thermal curtailments, and demand response measures to characterize costs and vulnerability for a test system. Twenty-five scenarios over the course of one year are considered: a baseline scenario as well as a suite of scenarios to evaluate six cooling system combinations, the inclusion or exclusion of policy-related thermal curtailments, and the inclusion or exclusion of demand response measures. A water and power plant system model is utilized to identify changes in power plant efficiencies resulting from ambient conditions, a production cost model operating at an hourly scale is used to calculate generation technology dispatch and costs, and a relative capacity value model is used to evaluate expected loss of carrying capacity for the test system.

  7. Analysis of the electricity demand of Greece for optimal planning of a large-scale hybrid renewable energy system

    Science.gov (United States)

    Tyralis, Hristos; Karakatsanis, Georgios; Tzouka, Katerina; Mamassis, Nikos

    2015-04-01

    The Greek electricity system is examined for the period 2002-2014. The demand load data are analysed at various time scales (hourly, daily, seasonal and annual) and they are related to the mean daily temperature and the gross domestic product (GDP) of Greece for the same time period. The prediction of energy demand, a product of the Greek Independent Power Transmission Operator, is also compared with the demand load. Interesting results about the change of the electricity demand scheme after the year 2010 are derived. This change is related to the decrease of the GDP, during the period 2010-2014. The results of the analysis will be used in the development of an energy forecasting system which will be a part of a framework for optimal planning of a large-scale hybrid renewable energy system in which hydropower plays the dominant role. Acknowledgement: This research was funded by the Greek General Secretariat for Research and Technology through the research project Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO; grant number 5145)

  8. Small Signal Stability Improvement of Power Systems Using Optimal Load Responses in Competitive Electricity Markets

    DEFF Research Database (Denmark)

    Hu, Weihao; Su, Chi; Chen, Zhe

    2011-01-01

    Since the hourly spot market price is available one day ahead in Denmark, the price could be transferred to the consumers and they may shift some of their loads from high price periods to the low price periods in order to save their energy costs. The optimal load response to an electricity price...... for demand side management generates different load profiles and may provide an opportunity to improve the small signal stability of power systems with high wind power penetrations. In this paper, the idea of power system small signal stability improvement by using optimal load response to the electricity...

  9. Profiling of Prosumers for the Needs of Electric Energy Demand Estimation in Microgrids

    OpenAIRE

    Karol Fabisz; Agata Filipowska; Tymoteusz Hossa

    2015-01-01

    Nowadays, a lot of attention regarding smart grids' development is devoted to delivery of methods for estimation of the energy demand taking into account the behavior of network participants (being single prosumers or groups of prosumers). These methods take an advantage from an analysis of the ex-post data on energy consumption, usually with no additional data about profiles of prosumers. The goal of this paper is to present and validate a method for an energy demand forecasting based on pro...

  10. High Electricity Demand in the Northeast U.S.: PJM Reliability Network and Peaking Unit Impacts on Air Quality.

    Science.gov (United States)

    Farkas, Caroline M; Moeller, Michael D; Felder, Frank A; Henderson, Barron H; Carlton, Annmarie G

    2016-08-02

    On high electricity demand days, when air quality is often poor, regional transmission organizations (RTOs), such as PJM Interconnection, ensure reliability of the grid by employing peak-use electric generating units (EGUs). These "peaking units" are exempt from some federal and state air quality rules. We identify RTO assignment and peaking unit classification for EGUs in the Eastern U.S. and estimate air quality for four emission scenarios with the Community Multiscale Air Quality (CMAQ) model during the July 2006 heat wave. Further, we population-weight ambient values as a surrogate for potential population exposure. Emissions from electricity reliability networks negatively impact air quality in their own region and in neighboring geographic areas. Monitored and controlled PJM peaking units are generally located in economically depressed areas and can contribute up to 87% of hourly maximum PM2.5 mass locally. Potential population exposure to peaking unit PM2.5 mass is highest in the model domain's most populated cities. Average daily temperature and national gross domestic product steer peaking unit heat input. Air quality planning that capitalizes on a priori knowledge of local electricity demand and economics may provide a more holistic approach to protect human health within the context of growing energy needs in a changing world.

  11. Reductions in electricity consumption and power demand in case of the mass use of compact fluorescent lamps

    Energy Technology Data Exchange (ETDEWEB)

    Trifunovic, J.; Mikulovic, J.; Djurisic, Z.; Djuric, M.; Kostic, M. [Faculty of Electrical Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, 11000 Belgrade (RS)

    2009-09-15

    The paper presents a general methodology for the evaluation of the reduction in electricity consumption and its market value, as well as the reduction of the peak power demand in case of the mass use of compact fluorescent lamps (CFLs), illustrated on the Serbian power system. The evaluation was based on the assumption that the two most used incandescent lamps in each of 25-50% of the total number of dwellings in Serbia will be replaced with adequate CFLs, and that the same total number of lamps will be replaced in residential and non-residential sectors. The daily diagrams of the total electrical power demand in Serbia for days with the maximum and minimum yearly peak loads are presented and compared with the corresponding daily diagrams which took into account the planned lamp replacement and the coincidence factors (CFs) for the observed lamps, which in case of the residential sector are obtained by on-site monitoring of 344 dwellings. It was shown that, in order to precisely calculate the cost-effectiveness of the planned action, decrease of electricity consumption has to be calculated for each hour, because the electricity cost rate (ECR) usually changes on an hourly basis. (author)

  12. Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

    Energy Technology Data Exchange (ETDEWEB)

    DeForest, Nicholas; Mendes, Goncalo; Stadler, Michael; Feng, Wei; Lai, Judy; Marnay, Chris

    2013-06-02

    In much of the developed world, air-conditioning in buildings is the dominant driver of summer peak electricity demand. In the developing world a steadily increasing utilization of air-conditioning places additional strain on already-congested grids. This common thread represents a large and growing threat to the reliable delivery of electricity around the world, requiring capital-intensive expansion of capacity and draining available investment resources. Thermal energy storage (TES), in the form of ice or chilled water, may be one of the few technologies currently capable of mitigating this problem cost effectively and at scale. The installation of TES capacity allows a building to meet its on-peak air conditioning load without interruption using electricity purchased off-peak and operating with improved thermodynamic efficiency. In this way, TES has the potential to fundamentally alter consumption dynamics and reduce impacts of air conditioning. This investigation presents a simulation study of a large office building in four distinct geographical contexts: Miami, Lisbon, Shanghai, and Mumbai. The optimization tool DER-CAM (Distributed Energy Resources Customer Adoption Model) is applied to optimally size TES systems for each location. Summer load profiles are investigated to assess the effectiveness and consistency in reducing peak electricity demand. Additionally, annual energy requirements are used to determine system cost feasibility, payback periods and customer savings under local utility tariffs.

  13. Short-Term Multiple Forecasting of Electric Energy Loads for Sustainable Demand Planning in Smart Grids for Smart Homes

    Directory of Open Access Journals (Sweden)

    Adeshina Y. Alani

    2017-10-01

    Full Text Available Energy consumption in the form of fuel or electricity is ubiquitous globally. Among energy types, electricity is crucial to human life in terms of cooking, warming and cooling of shelters, powering of electronic devices as well as commercial and industrial operations. Users of electronic devices sometimes consume fluctuating amounts of electricity generated from smart-grid infrastructure owned by the government or private investors. However, frequent imbalance is noticed between the demand and supply of electricity, hence effective planning is required to facilitate its distribution among consumers. Such effective planning is stimulated by the need to predict future consumption within a short period. Although several interesting classical techniques have been used for such predictions, they still require improvement for the purpose of reducing significant predictive errors when used for short-term load forecasting. This research develops a near-zero cooperative probabilistic scenario analysis and decision tree (PSA-DT model to address the lacuna of enormous predictive error faced by the state-of-the-art models. The PSA-DT is based on a probabilistic technique in view of the uncertain nature of electricity consumption, complemented by a DT to reinforce the collaboration of the two techniques. Based on detailed experimental analytics on residential, commercial and industrial data loads, the PSA-DT model outperforms the state-of-the-art models in terms of accuracy to a near-zero error rate. This implies that its deployment for electricity demand planning will be of great benefit to various smart-grid operators and homes.

  14. Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids

    Directory of Open Access Journals (Sweden)

    Claudia Pop

    2018-01-01

    Full Text Available In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.. In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

  15. Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids.

    Science.gov (United States)

    Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo

    2018-01-09

    In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

  16. 2008-2010 Research Summary: Analysis of Demand Response Opportunities in California Industry

    Energy Technology Data Exchange (ETDEWEB)

    Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Olsen, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McKane, Aimee [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2011-08-01

    This report describes the work of the Industrial Demand Response (DR) Team of Lawrence Berkeley National Laboratory’s Demand Response Research Center (DRRC) from 2008-2010, in the context of its mandate to conduct and disseminate research that broadens the knowledge base of DR strategies, with a focus on the Industrial-Agricultural-Water (IAW) sector. Through research and case studies of industrial sectors and entities, the DRRC-IAW Team continued to assimilate knowledge on the feasibility of industrial DR strategies with an emphasis on technical and economic evaluation and worked to encourage implementation of these strategies.

  17. Electric Vehicles in Colorado: Anticipating Consumer Demand for Direct Current Fast Charging

    Energy Technology Data Exchange (ETDEWEB)

    Wood, Eric W. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Rames, Clement L. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-07-01

    To support the State of Colorado in planning for growth in direct current fast charging (DCFC) for electric vehicles, the National Renewable Energy Laboratory (NREL) has partnered with the Regional Air Quality Council (RAQC) and the Colorado Department of Transportation (CDOT) to analyze a number of DCFC investment scenarios. NREL analyzed existing electric vehicle registration data from IHS Markit (IHS) to highlight early trends in the electric vehicle market, which were compared with sales forecasts predicting large growth in the Colorado electric vehicle market. Electric vehicle forecasts were then used to develop future DCFC scenarios to be evaluated in a simulation environment to estimate consumer benefits of the hypothetical DCFC networks in terms of increased driving range and electric vehicle miles traveled (eVMT). Simulated utilization of the hypothetical DCFC networks was analyzed for geographic trends, particularly for correlations with vehicle electric range. Finally, a subset of simulations is presented for consumers with potentially inconsistent access to charging at their home location and presumably greater reliance on public DCFC infrastructure.

  18. Demand response impacts on off-grid hybrid photovoltaic-diesel generator microgrids

    Directory of Open Access Journals (Sweden)

    Aaron St. Leger

    2015-08-01

    Full Text Available Hybrid microgrids consisting of diesel generator set(s and converter based power sources, such as solar photovoltaic or wind sources, offer an alternative to generator based off-grid power systems. The hybrid approach has been shown to be economical in many off-grid applications and can result in reduced generator operation, fuel requirements, and maintenance. However, the intermittent nature of demand and renewable energy sources typically require energy storage, such as batteries, to properly operate the hybrid microgrid. These batteries increase the system cost, require proper operation and maintenance, and have been shown to be unreliable in case studies on hybrid microgrids. This work examines the impacts of leveraging demand response in a hybrid microgrid in lieu of energy storage. The study is performed by simulating two different hybrid diesel generator—PV microgrid topologies, one with a single diesel generator and one with multiple paralleled diesel generators, for a small residential neighborhood with varying levels of demand response. Various system designs are considered and the optimal design, based on cost of energy, is presented for each level of demand response. The solar resources, performance of solar PV source, performance of diesel generators, costs of system components, maintenance, and operation are modeled and simulated at a time interval of ten minutes over a twenty-five year period for both microgrid topologies. Results are quantified through cost of energy, diesel fuel requirements, and utilization of the energy sources under varying levels of demand response. The results indicate that a moderate level of demand response can have significant positive impacts to the operation of hybrid microgrids through reduced energy cost, fuel consumption, and increased utilization of PV sources.

  19. Short-Term Measurements of Household Electricity Demand During Hot Weather in Kuala Lumpur

    National Research Council Canada - National Science Library

    Nassir Ranjbar; Sheikh Ahmad Zaki; Nelidya Md Yusoff; Fitri Yakub; Aya Hagishima

    2017-01-01

    .... The measurements included total and air conditioner (AC) electricity consumption of 10 households in an apartment building as well as outdoor air temperatures, which were collected from March to May 2016...

  20. MARKET SUPPLY RESPONSE AND DEMAND FOR LOCAL RICE IN NIGERIA: IMPLICATIONS FOR SELF-SUFFICIENCY POLICY

    Directory of Open Access Journals (Sweden)

    M RAHJI

    2009-03-01

    Full Text Available This study examined the supply response and demand for local rice in Nigeria between 1960 and 2004. A system of equations using secondary data was estimated by OLS and 2SLS techniques. Area planted with local rice is mainly affected by expected price of output, agriculture wage rate and by the partial adjustment coefficient. The short-run response elasticity is 0.077. The implied long-run response elasticity is 1.578. The partial adjustment measure is 0.049. This, points to the difficulty of supply response to changing economic conditions. The price elasticity of demand obtained is 0.841. The demand for local rice is thus price inelastic. Rice income elasticity is 0.3378. It is also inelastic. The ban on rice importation in Nigeria could be said to be a step in the right direction. This policy should be continued and policed. However, price, output and non-price incentives that can exert significant influence on rice supply response and demand are required if the self-sufficiency goal is to be achieved.

  1. Direct Electricity from Heat: A Solution to Assist Aircraft Power Demands

    Science.gov (United States)

    Goldsby, Jon C.

    2010-01-01

    A thermionic device produces an electrical current with the application of a thermal gradient whereby the temperature at one electrode provides enough thermal energy to eject electrons. The system is totally predicated on the thermal gradient and the work function of the electrode collector relative to the emitter electrode. Combined with a standard thermoelectric device high efficiencies may result, capable of providing electrical energy from the waste heat of gas turbine engines.

  2. The Boom of Electricity Demand in the Residential Sector in the Developing World and the Potential for Energy Efficiency

    Energy Technology Data Exchange (ETDEWEB)

    Letschert, Virginie; McNeil, Michael A.

    2008-05-13

    With the emergence of China as the world's largest energy consumer, the awareness of developing country energy consumption has risen. According to common economic scenarios, the rest of the developing world will probably see an economic expansion as well. With this growth will surely come continued rapid growth in energy demand. This paper explores the dynamics of that demand growth for electricity in the residential sector and the realistic potential for coping with it through efficiency. In 2000, only 66% of developing world households had access to electricity. Appliance ownership rates remain low, but with better access to electricity and a higher income one can expect that households will see their electricity consumption rise significantly. This paper forecasts developing country appliance growth using econometric modeling. Products considered explicitly - refrigerators, air conditioners, lighting, washing machines, fans, televisions, stand-by power, water heating and space heating - represent the bulk of household electricity consumption in developing countries. The resulting diffusion model determines the trend and dynamics of demand growth at a level of detail not accessible by models of a more aggregate nature. In addition, the paper presents scenarios for reducing residential consumption through cost-effective and/or best practice efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, which allows for a realistic assessment of efficiency opportunities at the national or regional level. The past decades have seen some of the developing world moving towards a standard of living previously reserved for industrialized countries. Rapid economic development, combined with large populations has led to first China and now India to emerging as &apos

  3. Study the Effect of Value-Added of Services Sector on Forecasting of Electricity Demand in Services Sector due to Price Reform

    Directory of Open Access Journals (Sweden)

    Sayed Mahdi Mostafavi

    2016-07-01

    Full Text Available Electrical energy is as one of the important effective factors on economic growth and development. In recent decades, numerous studies in different countries to estimate and forecast electricity demand in different parts of the economy have been made. In this paper, using the method ARDL, estimation and forecasting of electricity demand in the services sector of Iran are determined for the time period from 1983 to 2012. Estimated equations show that the added value of the services sector and a significant positive impact on the demand for electricity in this sector. The price elasticity for services sector is smaller than 1 due to low electricity prices and subsidized electricity. Hence, electricity prices have little impact on the demand for electricity. The results of the estimate represents a long-term relationship between the variables in the services sector. In this paper, based on amendments to the law on subsidies and estimated values, anticipated electricity demand until the end of the fifth development plan was carried out. The results indicate an increase in power consumption in the services sector.

  4. Research of the elasticity of electric energy tariff demand on competitive market of unified energy system of the Ural

    Directory of Open Access Journals (Sweden)

    Mokhov V.G.

    2017-01-01

    Full Text Available The aim of the study is to analyze the youngest in the world competitive market of electric energy and power of Russia. The hypothesis that there is a significant time lag between the launch date regulated competitive energy market and the actual state of its transition to a stationary operation. To test the hypothesis covered the electric energy consumer’s reaction on tariffs changes in the UES of the Ural in the period of time after restructuring RJSC “UES of Russian Federation”. Factual data of UES of Russia’s System operator shows how indicator values of electric energy consumption elasticity changes: consuming turns from elastic to inelastic according to price. Proved that in 2014 the energy demand matches to a competitive market. As a methodical research tool used 5 types of regression analysis equations for time series of electricity consumption, in addiction by the rate of the day-ahead market for 2009-2014. The research found that the transition to a competitive market of electricity production in Russia in fact was didn’t carried out in 2008, but was carried in 2014. Research proved that the electricity market regression analysis applied in predicting short periods of time (day-ahead market, because by increasing the time interval of forecasting accuracy of the forecast is decreases. The research results have great practical significance for the power industry subjects, especially those with high energy intensity of production, as the increase in the accuracy of forecasting reduces fines and total costs for electricity.

  5. Describing Long-Term Electricity Demand Scenarios in the Telecommunications Industry: A Case Study of Japan

    Directory of Open Access Journals (Sweden)

    Yusuke Kishita

    2016-01-01

    Full Text Available Due to the rapid expansion of information and communication technology (ICT usage, the telecommunications industry is faced with a challenge to promote green ICT toward achieving a low-carbon society. One critical obstacle in planning long-term strategies for green ICT is the uncertainty of various external factors, such as consumers’ lifestyle and technological advancement. To tackle this issue, this paper employs a scenario planning method to analyze electricity consumption in the telecommunications industry, where both changes in various external factors and energy-saving measures are assumed. We propose a model to estimate future electricity consumption of the telecommunications industry using a statistical approach. In a case study, we describe four scenarios that differ in the diffusion of ICT and the technological advancement of ICT equipment in order to analyze the electricity consumption in Japan’s telecommunications industry to 2030. The results reveal that the electricity consumption in 2030 becomes 0.7–1.6-times larger than the 2012 level (10.7 TWh/year. It is also shown that the most effective measures to reduce the electricity consumption include improving the energy efficiency of IP (Internet Protocol communication equipment and mobile communication equipment.

  6. Residential Demand Response of Thermostatically Controlled Loads Using Batch Reinforcement Learning

    NARCIS (Netherlands)

    Ruelens, F; Claessens, BJ; Vandael, S; De Schutter, B.H.K.; Babuska, R.; Belmans, R

    2017-01-01

    Driven by recent advances in batch Reinforcement Learning (RL), this paper contributes to the application of batch RL to demand response. In contrast to conventional model-based approaches, batch RL techniques do not require a system identification step, making them more suitable for a large-scale

  7. Universities Response to Oil and Gas Industry Demands in South Texas (USA) and Tamaulipas (Mexico)

    Science.gov (United States)

    Navarro, Marco Aurelio

    2016-01-01

    Given the importance of hydrocarbons for this area, the purpose of this paper is to explore the response of universities to cope with new demands in the south of Texas and Tamaulipas, especially in relation to gas plays of Eagle Ford (Texas side) and Burgos Basin (Mexican side). To accomplish this task, in the first section of the paper a broad…

  8. 75 FR 47499 - Demand Response Compensation in Organized Wholesale Energy Markets

    Science.gov (United States)

    2010-08-06

    ... (RTOs) \\2\\ with tariff provisions allowing demand response \\3\\ resources \\4\\ to participate in wholesale... (March 29, 2010), 130 FERC ] 61,213 (March 18, 2010). \\2\\ The following RTOs and ISOs have organized... energy markets, i.e., the day-ahead and real-time markets administered by ISOs and RTOs. Under the...

  9. Impact of Competition on Quality of Service in Demand Responsive Transit

    NARCIS (Netherlands)

    Grootenboers, F.; De Weerdt, M.M.; Zargayouna, M.

    2010-01-01

    Demand responsive transportation has the potential to provide efficient public door-to-door transport with a high quality. In currently implemented systems in the Netherlands, however, we observe a decrease in the quality of service (QoS), expressed in longer travel times for the customers.

  10. 75 FR 15362 - Demand Response Compensation in Organized Wholesale Energy Markets

    Science.gov (United States)

    2010-03-29

    ... ] 61,253, at P 19 and n.23 (2009) (``The Smart Grid concept envisions a power system architecture that... compensation structures, the Commission is concerned that some existing, inadequate compensation structures... pricing structures, before they will make an investment in demand response.'' \\31\\ Some participants have...

  11. Design and Co-simulation of Hierarchical Architecture for Demand Response Control and Coordination

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad; Lévesque, Martin; Bak-Jensen, Birgitte

    2017-01-01

    Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this study, we propose a hierarchical DR architecture (HDRA) to control an...

  12. Demands on Attention and the Role of Response Priming in Visual Discrimination of Feature Conjunctions

    Science.gov (United States)

    Fournier, Lisa R.; Herbert, Rhonda J.; Farris, Carrie

    2004-01-01

    This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less…

  13. 49 CFR 37.189 - Service requirement for OTRB demand-responsive systems.

    Science.gov (United States)

    2010-10-01

    ... SERVICES FOR INDIVIDUALS WITH DISABILITIES (ADA) Over-the-Road Buses (OTRBs) § 37.189 Service requirement... business of transporting people, whose operations affect commerce, and that provide demand-responsive OTRB... who needs an accessible bus, or someone who later buys a seat in the block of seats the group has...

  14. Residential Demand Response Behaviour Modeling applied to Cyber-physical Intrusion Detection

    DEFF Research Database (Denmark)

    Heussen, Kai; Tyge, Emil; Kosek, Anna Magdalena

    2017-01-01

    be identified and how the characterization can be updated continuously. Finally, we propose an approach to apply this behaviour characterization to the identification of anomalous and potentially malicious behaviour modifications as part of a cyber-physical intrusion detection mechanism.......A real-time demand response system can be viewed as a cyber-physical system, with physical systems dependent on cyber infrastructure for coordination and control, which may be vulnerable to cyber-attacks. The time domain dynamic behaviour of individual residential demand responses is governed...... by a mix of physical system parameters, exogenous influences, user behaviour and preferences, which can be characterized by unstructured models such as a time-varying finite impulse response. In this study, which is based on field data, it is shown how this characteristic response behaviours can...

  15. Measured electric hot water standby and demand loads from Pacific Northwest homes. End-Use Load and Consumer Assessment Program

    Energy Technology Data Exchange (ETDEWEB)

    Pratt, R.G.; Ross, B.A.

    1991-11-01

    The Bonneville Power Administration began the End-Use Load and Consumer Assessment Program (ELCAP) in 1983 to obtain metered hourly end-use consumption data for a large sample of new and existing residential and commercial buildings in the Pacific Northwest. Loads and load shapes from the first 3 years of data fro each of several ELCAP residential studies representing various segments of the housing population have been summarized by Pratt et al. The analysis reported here uses the ELCAP data to investigate in much greater detail the relationship of key occupant and tank characteristics to the consumption of electricity for water heating. The hourly data collected provides opportunities to understand electricity consumption for heating water and to examine assumptions about water heating that are critical to load forecasting and conservation resource assessments. Specific objectives of this analysis are to: (A) determine the current baseline for standby heat losses by determining the standby heat loss of each hot water tank in the sample, (B) examine key assumptions affecting standby heat losses such as hot water temperatures and tank sizes and locations, (C) estimate, where possible, impacts on standby heat losses by conservation measures such as insulating tank wraps, pipe wraps, anticonvection valves or traps, and insulating bottom boards, (D) estimate the EF-factors used by the federal efficiency standards and the nominal R-values of the tanks in the sample, (E) develop estimates of demand for hot water for each home in the sample by subtracting the standby load from the total hot water load, (F) examine the relationship between the ages and number of occupants and the hot water demand, (G) place the standby and demand components of water heating electricity consumption in perspective with the total hot water load and load shape.

  16. Impact of Competition on Quality of Service in Demand Responsive Transit

    OpenAIRE

    Grootenboers, F.; De Weerdt, M.M.; ZARGAYOUNA, M

    2010-01-01

    International audience; Demand responsive transportation has the potential to provide efficient public door-to-door transport with a high quality. In currently implemented systems in the Netherlands, however, we observe a decrease in the quality of service (QoS), expressed in longer travel times for the customers. Currently, generally one transport company is responsible for transporting all customers located in a specified geographic zone. In general it is known that when multiple companies ...

  17. Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States

    Science.gov (United States)

    Auffhammer, Maximilian; Baylis, Patrick; Hausman, Catherine H.

    2017-01-01

    It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today’s technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual. PMID:28167756

  18. Electricity Demand of PHEVs Operated by Private Households and Commercial Fleets: Effects of Driving and Charging Behavior

    Energy Technology Data Exchange (ETDEWEB)

    John Smart; Matthew Shirk; Ken Kurani; Casey Quinn; Jamie Davies

    2010-11-01

    Automotive and energy researchers have made considerable efforts to predict the impact of plug-in hybrid vehicle (PHEV) charging on the electrical grid. This work has been done primarily through computer modeling and simulation. The US Department of Energy’s (DOE) Advanced Vehicle Testing Activity (AVTA), in partnership with the University of California at Davis’s Institute for Transportation Stuides, have been collecting data from a diverse fleet of PHEVs. The AVTA is conducted by the Idaho National Laboratory for DOE’s Vehicle Technologies Program. This work provides the opportunity to quantify the petroleum displacement potential of early PHEV models, and also observe, rather than simulate, the charging behavior of vehicle users. This paper presents actual charging behavior and the resulting electricity demand from these PHEVs operating in undirected, real-world conditions. Charging patterns are examined for both commercial-use and personal-use vehicles. Underlying reasons for charging behavior in both groups are also presented.

  19. The role of energy and investment literacy for residential electricity demand and end-use efficiency

    NARCIS (Netherlands)

    Blasch, J.E.; Boogen, Nina; Filippini, Massimo; Kumar, Nilkanth

    2017-01-01

    This paper estimates the level of transient and persistent efficiency in the use of electricity in Swiss households using the newly developed generalized true random effects model (GTREM). An unbalanced panel dataset of 1, 994 Swiss households from 2010 to 2014 collected via a household survey is

  20. The bright side of snow cover effects on PV production - How to lower the seasonal mismatch between electricity supply and demand in a fully renewable Switzerland

    Science.gov (United States)

    Kahl, Annelen; Dujardin, Jérôme; Dupuis, Sonia; Lehning, Michael

    2017-04-01

    One of the major problems with solar PV in the context of a fully renewable electricity production at mid-latitudes is the trend of higher production in summer and lower production in winter. This trend is most often exactly opposite to demand patterns, causing a seasonal mismatch that requires extensive balancing power from other production sources or large storage capacities. Which possibilities do we have to bring PV production into closer correlation with demand? This question motivated our research and in response we investigated the effects of placing PV panels at different tilt angles in regions with extensive snow cover to increase winter production from ground reflected short wave radiation. The aim of this project is therefore to quantify the effect of varying snow cover duration (SCD) and of panel tilt angle on the annual total production and on production during winter months when electricity is most needed. We chose Switzerland as ideal test site, because it has a wide range of snow cover conditions and a high potential for renewable electricity production. But methods can be applied to other regions of comparable conditions for snow cover and irradiance. Our analysis can be separated into two steps: 1. A systematic, GIS and satellite-based analysis for all of Switzerland: We use time series of satellite-derived irradiance, and snow cover characteristics together with land surface cover types and elevation information to quantify the environmental conditions and to estimate potential production and ideal tilt angles. 2. A scenario-based analysis that contrasts the production patterns of different placement scenarios for PV panels in urban, rural and mountainous areas. We invoke a model of a fully renewable electricity system (including Switzerland's large hydropower system) at national level to compute the electricity import and storage capacity that will be required to balance the remaining mismatch between production and demand to further illuminate

  1. Magnetic and electric response in multiferroic manganites

    NARCIS (Netherlands)

    Mufti, Nandang

    2008-01-01

    Multiferroics are materials that display spontaneous ferroelectric and magnetic ordering at the same time. Magnetoelectrics are materials in which an electric polarization can be induced by an applied magnetic field. The cross-coupling between the magnetism and ferroelectricity can potentially be

  2. Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission

    Directory of Open Access Journals (Sweden)

    Yi Liang

    2016-11-01

    Full Text Available The power industry is the main battlefield of CO2 emission reduction, which plays an important role in the implementation and development of the low carbon economy. The forecasting of electricity demand can provide a scientific basis for the country to formulate a power industry development strategy and further promote the sustained, healthy and rapid development of the national economy. Under the goal of low-carbon economy, medium and long term electricity demand forecasting will have very important practical significance. In this paper, a new hybrid electricity demand model framework is characterized as follows: firstly, integration of grey relation degree (GRD with induced ordered weighted harmonic averaging operator (IOWHA to propose a new weight determination method of hybrid forecasting model on basis of forecasting accuracy as induced variables is presented; secondly, utilization of the proposed weight determination method to construct the optimal hybrid forecasting model based on extreme learning machine (ELM forecasting model and multiple regression (MR model; thirdly, three scenarios in line with the level of realization of various carbon emission targets and dynamic simulation of effect of low-carbon economy on future electricity demand are discussed. The resulting findings show that, the proposed model outperformed and concentrated some monomial forecasting models, especially in boosting the overall instability dramatically. In addition, the development of a low-carbon economy will increase the demand for electricity, and have an impact on the adjustment of the electricity demand structure.

  3. Stochastic Unit Commitment of Wind-Integrated Power System Considering Air-Conditioning Loads for Demand Response

    Directory of Open Access Journals (Sweden)

    Xiao Han

    2017-11-01

    Full Text Available As a result of extensive penetration of wind farms into electricity grids, power systems face enormous challenges in daily operation because of the intermittent characteristics of wind energy. In particular, the load peak-valley gap has been dramatically widened in wind energy-integrated power systems. How to quickly and efficiently meet the peak-load demand has become an issue to practitioners. Previous literature has illustrated that the demand response (DR is an important mechanism to direct customer usage behaviors and reduce the peak load at critical times. This paper introduces air-conditioning loads (ACLs as a load shedding measure in the DR project. On the basis of the equivalent thermal parameter model for ACLs and the state-queue control method, a compensation cost calculation method for the ACL to shift peak load is proposed. As a result of the fluctuation and uncertainty of wind energy, a two-stage stochastic unit commitment (UC model is developed to analyze the ACL users’ response in the wind-integrated power system. A simulation study on residential and commercial ACLs has been performed on a 10-generator test system. The results illustrate the feasibility of the proposed stochastic programming strategy and that the system peak load can be effectively reduced through the participation of ACL users in DR projects.

  4. Balancing Renewable Electricity Energy Storage, Demand Side Management, and Network Extension from an Interdisciplinary Perspective

    CERN Document Server

    Droste-Franke, Bert; Rehtanz, Christian; Sauer, Dirk Uwe; Schneider, Jens-Peter; Schreurs, Miranda; Ziesemer, Thomas

    2012-01-01

    A significant problem of integrating renewable energies into the electricity system is the temporally fluctuating energy production by wind and solar power plants. Thus, in order to meet the ambitious long-term targets on CO2 emission reduction, long-term viable low-carbon options for balancing electricity will be needed. This interdisciplinary study analyses published future energy scenarios in order to get an impression of the required balancing capacities and shows which framework conditions should be modified to support their realisation. The authors combine their perspectives from energy engineering, technology assessment, political science, economical science and jurisprudence and address science, politics, actors in the energy sector and the interested public. Respectively, requirements for the balancing systems are analysed, considering the case of Germany as a large country with high ambitions to reduce greenhouse gas emissions. Additionally, an approach to investigate the optimal design of the techn...

  5. Light a Spark! Addressing Barriers and Enablers to Increase Demand of Electric Vehicles in Southeast Sweden

    OpenAIRE

    Nordström, Lina; Runesson, Lars; Warnecke, Helena

    2015-01-01

    The Personal Transportation System safeguards peoples’ cultural understanding of freedom: to move individually without being dependent on others. However, the increasing number of private vehicles driven on fossil fuels contributes to unsustainability and one of the most urgent issues, climate change. The authors explored electric vehicles as an alternative to fossil fuel driven vehicles as a way of moving strategically towards sustainability in the Personal Transportation System. In order to...

  6. Effect of Response Reduction Factor on Peak Floor Acceleration Demand in Mid-Rise RC Buildings

    Science.gov (United States)

    Surana, Mitesh; Singh, Yogendra; Lang, Dominik H.

    2017-06-01

    Estimation of Peak Floor Acceleration (PFA) demand along the height of a building is crucial for the seismic safety of nonstructural components. The effect of the level of inelasticity, controlled by the response reduction factor (strength ratio), is studied using incremental dynamic analysis. A total of 1120 nonlinear dynamic analyses, using a suite of 30 recorded ground motion time histories, are performed on mid-rise reinforced-concrete (RC) moment-resisting frame buildings covering a wide range in terms of their periods of vibration. The obtained PFA demands are compared with some of the major national seismic design and retrofit codes (IS 1893 draft version, ASCE 41, EN 1998, and NZS 1170.4). It is observed that the PFA demand at the building's roof level decreases with increasing period of vibration as well as with strength ratio. However, current seismic building codes do not account for these effects thereby producing very conservative estimates of PFA demands. Based on the identified parameters affecting the PFA demand, a model to obtain the PFA distribution along the height of a building is proposed. The proposed model is validated with spectrum-compatible time history analyses of the considered buildings with different strength ratios.

  7. Real-time pricing strategy of micro-grid energy centre considering price-based demand response

    Science.gov (United States)

    Xu, Zhiheng; Zhang, Yongjun; Wang, Gan

    2017-07-01

    With the development of energy conversion technology such as power to gas (P2G), fuel cell and so on, the coupling between energy sources becomes more and more closely. Centralized dispatch among electricity, natural gas and heat will become a trend. With the goal of maximizing the system revenue, this paper establishes the model of micro-grid energy centre based on energy hub. According to the proposed model, the real-time pricing strategy taking into account price-based demand response of load is developed. And the influence of real-time pricing strategy on the peak load shifting is discussed. In addition, the impact of wind power predicted inaccuracy on real-time pricing strategy is analysed.

  8. Demands For Solar Electricity From The BRICS Countries In The Future

    Science.gov (United States)

    Fan, Y.

    2015-12-01

    BRICS countries are presently among the leading the economic powers globally, but their increasing demands for energy and sustainable future requires renewed technical progress on implementation of renewable energy (e.g., solar energy) and a sustainable solution rather than extracting finite natural resources. BRICS countries (Brazil, Russia, India, China and South Africa) face both social and environmental pressures as their economy keeps growing. The rapid development of technology in BRICS inevitably altered their culture and behavior, as reflected by education, gender equality, health, and other demographic/socio-economic indicators. These changes coupled with land use/land cover change have altered ecosystem services, as reflected by NEE (Net Ecosystem Exchange of CO2) and NDVI (Normalized Difference Vegetation Index). Global climatic changes also drives the demand for sustainable energy. With a focus on solar energy, we analyzed time series of energy consuming behaviors, government policies, and the ecosystem services. Structural equation modeling was applied to confirm the relationships among societal transition, ecosystem services, and climate change. We compared the energy consumption patterns for the five countries and forecasted the changes through 2025. We found that government policies significantly influenced energy consumption behaviors for BRICS and that solar energy usage would continue to increase to 2025 and beyond.

  9. Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks

    Directory of Open Access Journals (Sweden)

    Pol Olivella-Rosell

    2015-05-01

    Full Text Available Electric Vehicles (EVs have seen significant growth in sales recently and it is not clear how power systems will support the charging of a great number of vehicles. This paper proposes a methodology which allows the aggregated EV charging demand to be determined. The methodology applied to obtain the model is based on an agent-based approach to calculate the EV charging demand in a certain area. This model simulates each EV driver to consider its EV model characteristics, mobility needs, and charging processes required to reach its destination. This methodology also permits to consider social and economic variables. Furthermore, the model is stochastic, in order to consider the random pattern of some variables. The model is applied to Barcelona’s (Spain mobility pattern and uses the 37-node IEEE test feeder adapted to common distribution grid characteristics from Barcelona. The corresponding grid impact is analyzed in terms of voltage drop and four charging strategies are compared. The case study indicates that the variability in scenarios without control is relevant, but not in scenarios with control. Moreover, the voltages do not reach the minimum voltage allowed, but the MV/LV substations could exceed their capacities. Finally, it is determined that all EVs can charge during the valley without any negative effect on the distribution grid. In conclusion, it is determined that the methodology presented allows the EV charging demand to be calculated, considering different variables, to obtain better accuracy in the results.

  10. A Study of the Relationship between Weather Variables and Electric Power Demand inside a Smart Grid/Smart World Framework

    Directory of Open Access Journals (Sweden)

    David Chinarro

    2012-08-01

    Full Text Available One of the main challenges of today’s society is the need to fulfill at the same time the two sides of the dichotomy between the growing energy demand and the need to look after the environment. Smart Grids are one of the answers: intelligent energy grids which retrieve data about the environment through extensive sensor networks and react accordingly to optimize resource consumption. In order to do this, the Smart Grids need to understand the existing relationship between energy demand and a set of relevant climatic variables. All smart “systems” (buildings, cities, homes, consumers, etc. have the potential to employ their intelligence for self-adaptation to climate conditions. After introducing the Smart World, a global framework for the collaboration of these smart systems, this paper presents the relationship found at experimental level between a range of relevant weather variables and electric power demand patterns, presenting a case study using an agent-based system, and emphasizing the need to consider this relationship in certain Smart World (and specifically Smart Grid and microgrid applications.

  11. A Study of the Relationship between Weather Variables and Electric Power Demand inside a Smart Grid/Smart World Framework

    Science.gov (United States)

    Hernández, Luis; Baladrón, Carlos; Aguiar, Javier M.; Calavia, Lorena; Carro, Belén; Sánchez-Esguevillas, Antonio; Cook, Diane J.; Chinarro, David; Gómez, Jorge

    2012-01-01

    One of the main challenges of today's society is the need to fulfill at the same time the two sides of the dichotomy between the growing energy demand and the need to look after the environment. Smart Grids are one of the answers: intelligent energy grids which retrieve data about the environment through extensive sensor networks and react accordingly to optimize resource consumption. In order to do this, the Smart Grids need to understand the existing relationship between energy demand and a set of relevant climatic variables. All smart “systems” (buildings, cities, homes, consumers, etc.) have the potential to employ their intelligence for self-adaptation to climate conditions. After introducing the Smart World, a global framework for the collaboration of these smart systems, this paper presents the relationship found at experimental level between a range of relevant weather variables and electric power demand patterns, presenting a case study using an agent-based system, and emphasizing the need to consider this relationship in certain Smart World (and specifically Smart Grid and microgrid) applications.

  12. Solving a Location, Allocation, and Capacity Planning Problem with Dynamic Demand and Response Time Service Level

    Directory of Open Access Journals (Sweden)

    Carrie Ka Yuk Lin

    2014-01-01

    Full Text Available Logistic systems with uncertain demand, travel time, and on-site processing time are studied here where sequential trip travel is allowed. The relationship between three levels of decisions: facility location, demand allocation, and resource capacity (number of service units, satisfying the response time requirement, is analysed. The problem is formulated as a stochastic mixed integer program. A simulation-based hybrid heuristic is developed to solve the dynamic problem under different response time service level. An initial solution is obtained from solving static location-allocation models, followed by iterative improvement of the three levels of decisions by ejection, reinsertion procedure with memory of feasible and infeasible service regions. Results indicate that a higher response time service level could be achieved by allocating a given resource under an appropriate decentralized policy. Given a response time requirement, the general trend is that the minimum total capacity initially decreases with more facilities. During this stage, variability in travel time has more impact on capacity than variability in demand arrivals. Thereafter, the total capacity remains stable and then gradually increases. When service level requirement is high, the dynamic dispatch based on first-come-first-serve rule requires smaller capacity than the one by nearest-neighbour rule.

  13. Response Analysis of Electro-Optic Electric Field Sensor

    Directory of Open Access Journals (Sweden)

    Dawood Najem Saleh

    2013-05-01

    Full Text Available In this paper an electric field sensor based on the electro-optical effect in Lithium Niobate crystal is studied. The electro-optically induced polarization modification in crystal has been described and the response analyzed for different crystal lengths and light source wave lengths. The study shows that as the crystal length increased the required electric field to produce a phase-shift equal p is decreased. The responsivity of the sensor for different ranges of the electric field to be measured has been calculated and it is found that the rate of change of the half of the phase shift with respect to the electric field d(f/2/dE is equal to the responsivity of the sensor at the mid-point of the linear part of the light intensity response curve.

  14. The Impact of Hybrid Electric Vehicles Incentives on Demand and the Determinants of Hybrid-Vehicle Adoption

    Science.gov (United States)

    Riggieri, Alison

    According to the Energy Information Administration, transportation currently accounts for over 60% of U.S. oil demand (E.I.A. 2010). Improving automobile energy efficiency could therefore reduce oil consumption and the negative environmental effects of automobile use. Subsidies for energy-efficient technologies such as hybrid-electric vehicles have gained political popularity since their introduction into the market and therefore have been implemented with increasing frequency. After the introduction of hybrid-electric vehicles into the U.S. market, the federal government initially implemented a 2000 federal tax deduction for these vehicles (later increased to a 3500 credit). Many states followed, offering various exemptions, such as high-occupancy vehicle (HOV) lane use, and excise-tax, sales-tax, and income-tax exemptions. Because not all states have implemented these subsidies, this policy topic is an ideal candidate for an outcome evaluation using an observational study postulation. States adopt incentives for different reasons based on factors that make adoption more attractive, however, so it is first necessary to identify these differences that predict policy adoption. This allows for the evaluative work to control for self selection bias. Three classes of internal determinants of policy adoption, political context, problem severity, and institutional support, and one type of external diffusion factor, are tested using logistic regression. Results suggest that the number of neighboring states that have already adopted incentives are consistently a determinant of diffusion for all three types of incentives test, HOV lane exemptions, sales-tax exemptions, and income-tax exemptions. In terms of internal factors, constituent support, a type of political context, predicts, sale-tax, income-tax, and HOV lane exemptions, but that the other two classes of determinants, problem severity and institutional support, were not universally significant across types of

  15. The Activity Demands and Physiological Responses Encountered During Basketball Match-Play: A Systematic Review.

    Science.gov (United States)

    Stojanović, Emilija; Stojiljković, Nenad; Scanlan, Aaron T; Dalbo, Vincent J; Berkelmans, Daniel M; Milanović, Zoran

    2018-01-01

    Basketball is a popular, court-based team sport that has been extensively studied over the last decade. The purpose of this article was to provide a systematic review regarding the activity demands and physiological responses experienced during basketball match-play according to playing period, playing position, playing level, geographical location, and sex. An electronic database search of relevant articles published prior to 30 September 2016 was performed with PubMed, MEDLINE, ERIC, Google Scholar, SCIndex, and ScienceDirect. Studies that measured activity demands and/or physiological responses during basketball match-play were included. Following screening, 25 articles remained for review. During live playing time across 40-min matches, male and female basketball players travel 5-6 km at average physiological intensities above lactate threshold and 85% of maximal heart rate (HR). Temporal comparisons show a reduction in vigorous activities in the fourth quarter, likely contributing to lower blood lactate concentrations and HR responses evident towards the end of matches. Guards tend to perform a higher percentage of live playing time sprinting and performing high-intensity shuffling compared with forwards and centers. Guards also perform less standing and walking during match-play compared with forwards and centers. Variations in activity demands likely account for the higher blood lactate concentrations and HR responses observed for guards compared with forwards and centers. Furthermore, higher-level players perform a greater intermittent workload than lower-level players. Moreover, geographical differences may exist in the activity demands (distance and frequency) and physiological responses between Australian, African, and European basketball players, whereby Australian players sustain greater workloads. While activity demands and physiological data vary across playing positions, playing levels, and geographical locations, male and female players competing

  16. Modeling of Electric Demand for Sustainable Energy and Management in India Using Spatio-Temporal DMSP-OLS Night-Time Data.

    Science.gov (United States)

    Tripathy, Bismay Ranjan; Sajjad, Haroon; Elvidge, Christopher D; Ting, Yu; Pandey, Prem Chandra; Rani, Meenu; Kumar, Pavan

    2017-12-27

    Changes in the pattern of electric power consumption in India have influenced energy utilization processes and socio-economic development to greater extent during the last few decades. Assessment of spatial distribution of electricity consumption is, thus, essential for projecting availability of energy resource and planning its infrastructure. This paper makes an attempt to model the future electricity demand for sustainable energy and its management in India. The nighttime light database provides a good approximation of availability of energy. We utilized defense meteorological satellite program-operational line-scan system (DMSP-OLS) nighttime satellite data, electricity consumption (1993-2013), gross domestic product (GDP) and population growth to construct the model. We also attempted to examine the sensitiveness of electricity consumption to GDP and population growth. The results revealed that the calibrated DMSP and model has provided realistic information on the electric demand with respect to GDP and population, with a better accuracy of r 2  = 0.91. The electric demand was found to be more sensitive to GDP (r = 0.96) than population growth (r = 0.76) as envisaged through correlation analysis. Hence, the model proved to be useful tool in predicting electric demand for its sustainable use and management.

  17. Optimal Load Response to Time-of-Use Power Price for Demand Side Management in Denmark

    DEFF Research Database (Denmark)

    Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

    2010-01-01

    Since the hourly spot market price is available one day ahead in Denmark, the price could be transferred to the consumers and they may shift their loads from high price periods to the low price periods in order to save their energy costs. This paper presents a load optimization method to time......-of-use power price for demand side management in order to save the energy costs as much as possible. 3 typical different kinds of loads (industrial load, residential load and commercial load) in Denmark are chosen as study cases. The energy costs decrease up to 9.6% with optimal load response to time......-of-use power price for different loads. Simulation results show that the optimal load response to time-of-use power price for demand side management generates different load profiles and reduces the load peaks. This kind of load patterns may also have significant effects on the power system normal operation....

  18. Hierarchical control framework for integrated coordination between distributed energy resources and demand response

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Di; Lian, Jianming; Sun, Yannan; Yang, Tao; Hansen, Jacob

    2017-09-01

    Demand response is representing a significant but largely untapped resource that can greatly enhance the flexibility and reliability of power systems. In this paper, a hierarchical control framework is proposed to facilitate the integrated coordination between distributed energy resources and demand response. The proposed framework consists of coordination and device layers. In the coordination layer, various resource aggregations are optimally coordinated in a distributed manner to achieve the system-level objectives. In the device layer, individual resources are controlled in real time to follow the optimal power generation or consumption dispatched from the coordination layer. For the purpose of practical applications, a method is presented to determine the utility functions of controllable loads by taking into account the real-time load dynamics and the preferences of individual customers. The effectiveness of the proposed framework is validated by detailed simulation studies.

  19. Demand Response Management For Power Throttling Air Conditioning Loads In Residential Smart Grids

    OpenAIRE

    Khalid, Yawar Ismail; Hassan, Naveed Ul; Yuen, Chau; Huang, Shisheng

    2014-01-01

    In this paper we develop an algorithm for peak load reduction to reduce the impact of increased air conditioner usage in a residential smart grid community. We develop Demand Response Management (DRM) plans that clearly spell out the maximum duration as well as maximum severity of inconvenience. We model the air conditioner as a power throttling device and for any given DRM plan we study the impact of increasing the number of power states on the resulting peak load reduction. Through simulati...

  20. Analysis of Open Automated Demand Response Deployments in California and Guidelines to Transition to Industry Standards

    Energy Technology Data Exchange (ETDEWEB)

    Ghatikar, Girish; Riess, David; Piette, Mary Ann

    2014-01-02

    This report reviews the Open Automated Demand Response (OpenADR) deployments within the territories serviced by California?s investor-owned utilities (IOUs) and the transition from the OpenADR 1.0 specification to the formal standard?OpenADR 2.0. As demand response service providers and customers start adopting OpenADR 2.0, it is necessary to ensure that the existing Automated Demand Response (AutoDR) infrastructure investment continues to be useful and takes advantage of the formal standard and its many benefits. This study focused on OpenADR deployments and systems used by the California IOUs and included a summary of the OpenADR deployment from the U.S. Department of Energy-funded demonstration conducted by the Sacramento Municipal Utility District (SMUD). Lawrence Berkeley National Laboratory collected and analyzed data about OpenADR 1.0 deployments, categorized architectures, developed a data model mapping to understand the technical compatibility of each version, and compared the capabilities and features of the two specifications. The findings, for the first time, provided evidence of the total enabled load shed and average first cost for system enablement in the IOU and SMUD service territories. The OpenADR 2.0a profile specification semantically supports AutoDR system architectures and data propagation with a testing and certification program that promotes interoperability, scaled deployments by multiple vendors, and provides additional features that support future services.

  1. Investigation of electrical responses to acupuncture stimulation: the effect of electrical grounding and insulation conditions.

    Science.gov (United States)

    Lee, Yong-Heum; Ryu, Yeon-Hang; Jung, Byungjo

    2009-03-01

    Acupuncture in Oriental medicine has been widely used as a core therapeutic method due to its minimal side-effects and therapeutic efficacy. However, the electrical response to acupuncture stimulation (ERAS) has not been clearly studied under acupuncture conditions that might affect the efficacy of acupuncture therapy. In this study, the ERAS was objectively investigated by measuring meridian electric potentials (MEPs) when the electrical grounding conditions of the operator and subject were varied, and when the insulation conditions of acupuncture needle were varied. MEPs between Sang-geoheo (ST37) and Ha-geoheo (ST39) of the Stomach Meridian (ST) were measured by stimulating Jok-samni (ST36) with an acupuncture needle. For non-insulated acupuncture stimulation (NIAS), the average MEP peak was 148.6 +/- 20.6 when neither the operator nor the subject were electrically grounded, 23.1 +/- 8.8 when the subject only was electrically grounded, 348 +/- 76.8 when the operator only was electrically grounded, and 19.9 +/- 4.7 when both the operator and the subject were electrically grounded. The MEPs presented various magnitudes and patterns depending on the electrical grounding conditions. The MEP pattern was very similar to that of the charge and discharge of a capacitor. For insulated acupuncture stimulation (IAS), the average MEP peak was 20 +/- 4 in all electrical grounding conditions, which is not a significant electric response for acupuncture stimulation. In terms of electricity, this study verified that acupuncture therapy might be affected by acupuncture conditions such as (1) the electrical grounding condition of the operator and the subject and (2) the insulation condition of the acupuncture needle.

  2. Fast Demand Forecast of Electric Vehicle Charging Stations for Cell Phone Application

    Energy Technology Data Exchange (ETDEWEB)

    Majidpour, Mostafa; Qiu, Charlie; Chung, Ching-Yen; Chu, Peter; Gadh, Rajit; Pota, Hemanshu R.

    2014-07-31

    This paper describes the core cellphone application algorithm which has been implemented for the prediction of energy consumption at Electric Vehicle (EV) Charging Stations at UCLA. For this interactive user application, the total time of accessing database, processing the data and making the prediction, needs to be within a few seconds. We analyze four relatively fast Machine Learning based time series prediction algorithms for our prediction engine: Historical Average, kNearest Neighbor, Weighted k-Nearest Neighbor, and Lazy Learning. The Nearest Neighbor algorithm (k Nearest Neighbor with k=1) shows better performance and is selected to be the prediction algorithm implemented for the cellphone application. Two applications have been designed on top of the prediction algorithm: one predicts the expected available energy at the station and the other one predicts the expected charging finishing time. The total time, including accessing the database, data processing, and prediction is about one second for both applications.

  3. DISCOVERING AND LABELLING OF TEMPORAL GRANULARITY PATTERNS IN ELECTRIC POWER DEMAND WITH A BRAZILIAN CASE STUDY

    Directory of Open Access Journals (Sweden)

    Gabriela Servidone

    Full Text Available ABSTRACT Clustering is commonly used to group data in order to represent the behaviour of a system as accurately as possible by obtaining patterns and profiles. In this paper, clustering is applied with partitioning-clustering techniques, specifically, Partitioning around Medoids (PAM to analyse load curves from a city of South-eastern Brazil in São Paulo state. A top-down approach in time granularity is performed to detect and to label profiles which could be affected by seasonal trends and daily/hourly time blocks. Time-granularity patterns are useful to support the improvement of activities related to distribution, transmission and scheduling of energy supply. Results indicated four main patterns which were post-processed in hourly blocks by using shades of grey to help final-user to understand demand thresholds according to the meaning of dark grey, light grey and white colours. A particular and different behaviour of load curve was identified for the studied city if it is compared to the classical behaviour of urban cities.

  4. Analysis of the key factors of the change in the demand of electrical energy in Neuquén

    Directory of Open Access Journals (Sweden)

    Griselda Domeett

    2015-12-01

    Full Text Available The electrical energy is a basic input of high diffusion, derived from its capacity to satisfy all type of necessities. It shows that seasonal alterations in the consumptions are motivated by the level of economic activity, climatic changes and demographic dynamics. Since this is an essential good that cannot be stored, it determines the configuration, planning, operation and organization of the electrical energy systems. Its particular feature is forced to perform a multidimensional coverage: technological, economic, political, legal and environmental. The analysis of the factors that determine the levels and structures of the electric energy consumption it allows to identify the supplying problems, and the actions and policies that promote the sustainable usage of the service.Accordingly, the current work tries to make a preliminary analysis of these changes in the capital city of Neuquén, since the 90s until recent years. In order to do this, information from the Population Census, Provincial Registers, Household Surveys, Consumption and Invoicing sector, has been used.                                                                                          Keywords: Electrical energy, demand evolution key factors

  5. Modeling plug-in electric vehicle charging demand with BEAM: the framework for behavior energy autonomy mobility

    Energy Technology Data Exchange (ETDEWEB)

    Sheppard, Colin; Waraich, Rashid; Campbell, Andrew; Pozdnukov, Alexei; Gopal, Anand R.

    2017-05-01

    This report summarizes the BEAM modeling framework (Behavior, Energy, Mobility, and Autonomy) and its application to simulating plug-in electric vehicle (PEV) mobility, energy consumption, and spatiotemporal charging demand. BEAM is an agent-based model of PEV mobility and charging behavior designed as an extension to MATSim (the Multi-Agent Transportation Simulation model). We apply BEAM to the San Francisco Bay Area and conduct a preliminary calibration and validation of its prediction of charging load based on observed charging infrastructure utilization for the region in 2016. We then explore the impact of a variety of common modeling assumptions in the literature regarding charging infrastructure availability and driver behavior. We find that accurately reproducing observed charging patterns requires an explicit representation of spatially disaggregated charging infrastructure as well as a more nuanced model of the decision to charge that balances tradeoffs people make with regards to time, cost, convenience, and range anxiety.

  6. Physiological demands of women's rugby union: time-motion analysis and heart rate response.

    Science.gov (United States)

    Virr, Jody Lynn; Game, Alex; Bell, Gordon John; Syrotuik, Daniel

    2014-01-01

    The aim of this study was to determine the physical demands of women's rugby union match play using time-motion analysis and heart rate (HR) response. Thirty-eight premier club level female rugby players, ages 18-34 years were videotaped and HRs monitored for a full match. Performances were coded into 12 different movement categories: 5 speeds of locomotion (standing, walking, jogging, striding, sprinting), 4 forms of intensive non-running exertion (ruck/maul/tackle, pack down, scrum, lift) and 3 discrete activities (kick, jump, open field tackle). The main results revealed that backs spend significantly more time sprinting and walking whereas forwards spend more time in intensive non-running exertion and jogging. Forwards also had a significantly higher total work frequency compared to the backs, but a higher total rest frequency compared to the backs. In terms of HR responses, forwards displayed higher mean HRs throughout the match and more time above 80% of their maximum HR than backs. In summary, women's rugby union is characterised by intermittent bursts of high-intensity activity, where forwards and backs have similar anaerobic energy demands, but different specific match demands.

  7. Turnkey Heating, Ventilating, and Air Conditioning and Lighting Retrofit Solution Combining Energy Efficiency and Demand Response Benefits

    Energy Technology Data Exchange (ETDEWEB)

    Doebber, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States); Deru, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Trenbath, Kim [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-04-12

    NREL worked with the Bonneville Power Administration's Technology Innovation Office to demonstrate a turnkey, retrofit technology that combines demand response (DR) and energy efficiency (EE) benefits for HVAC and lighting in retail buildings. As a secondary benefit, we also controlled various plug loads and electric hot water heaters (EHWH). The technology demonstrated was Transformative Wave's eIQ Building Management System (BMS) automatically responding to DR signals. The BMS controlled the HVAC rooftop units (RTU) using the CATALYST retrofit solution also developed by Transformative Wave. The non-HVAC loads were controlled using both hardwired and ZigBee wireless communication. The wireless controllers, manufactured by Autani, were used when the building's electrical layout was too disorganized to leverage less expensive hardwired control. The six demonstration locations are within the Seattle metro area. Based on the assets curtailed by the BMS at each location, we projected the DR resource. We were targeting a 1.7 W/ft2 shed for the summer Day-Ahead events and a 0.7 W/ft2 shed for the winter events. While summarized in Table ES-1, only one summer DR event was conducted at Casino #2.

  8. A model of auditory nerve responses to electrical stimulation

    DEFF Research Database (Denmark)

    Joshi, Suyash Narendra; Dau, Torsten; Epp, Bastian

    , fail to correctly predict responses to anodic stimulation. This study presents a model that simulates AN responses to anodic and cathodic stimulation. The main goal was to account for the data obtained with monophasic electrical stimulation in cat AN. The model is based on an exponential integrate...... to neutralize the charge induced during the cathodic phase. Single-neuron recordings in cat auditory nerve using monophasic electrical stimulation show, however, that both phases in isolation can generate an AP. The site of AP generation differs for both phases, being more central for the anodic phase and more...... perception of CI listeners, a model needs to incorporate the correct responsiveness of the AN to anodic and cathodic polarity. Previous models of electrical stimulation have been developed based on AN responses to symmetric biphasic stimulation or to monophasic cathodic stimulation. These models, however...

  9. Opportunities for Open Automated Demand Response in Wastewater Treatment Facilities in California - Phase II Report. San Luis Rey Wastewater Treatment Plant Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, Lisa; Lekov, Alex; McKane, Aimee; Piette, Mary Ann

    2010-08-20

    This case study enhances the understanding of open automated demand response opportunities in municipal wastewater treatment facilities. The report summarizes the findings of a 100 day submetering project at the San Luis Rey Wastewater Treatment Plant, a municipal wastewater treatment facility in Oceanside, California. The report reveals that key energy-intensive equipment such as pumps and centrifuges can be targeted for large load reductions. Demand response tests on the effluent pumps resulted a 300 kW load reduction and tests on centrifuges resulted in a 40 kW load reduction. Although tests on the facility?s blowers resulted in peak period load reductions of 78 kW sharp, short-lived increases in the turbidity of the wastewater effluent were experienced within 24 hours of the test. The results of these tests, which were conducted on blowers without variable speed drive capability, would not be acceptable and warrant further study. This study finds that wastewater treatment facilities have significant open automated demand response potential. However, limiting factors to implementing demand response are the reaction of effluent turbidity to reduced aeration load, along with the cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities.

  10. Demand Response Control in Low Voltage Grids for Technical and Commercial Aggregation Services

    DEFF Research Database (Denmark)

    Diaz de Cerio Mendaza, Iker; Szczesny, Ireneusz; Pillai, Jayakrishnan Radhakrishna

    2016-01-01

    . In this way, a system operator playing a role of an aggregator not only could trade flexible demand in the power markets but also materialize its energy agreements while ensuring the local network security and reliability. To verify the effectiveness of this extended method, a Danish low voltage networks...... hand, some of those represent a source of flexibility which can be used to satisfy different technical and commercial purposes. This paper introduces an upgraded hierarchical structure which aims to serve as a platform for activating and controlling the demand response in low voltage networks...... is considered. The results show that it is possible to fulfill energy commitments in energy markets such as the regulation power market while respecting the proper network operation. However, the activation of the flexibility offered might be limited depending on the network characteristics and the season...

  11. An Integrated Multiperiod OPF Model with Demand Response and Renewable Generation Uncertainty

    DEFF Research Database (Denmark)

    Bukhsh, Waqquas Ahmed; Zhang, Chunyu; Pinson, Pierre

    2015-01-01

    Renewable energy sources such as wind and solar have received much attention in recent years, and large amount of renewable generation is being integrated to the electricity networks. A fundamental challenge in a power system operation is to handle the intermittent nature of the renewable...... generation. In this paper we present a stochastic programming approach to solve a multiperiod optimal power flow problem under renewable generation uncertainty. The proposed approach consists of two stages. In the first stage, operating points for the conventional power plants are determined. The second...... stage realizes generation from the renewable resources and optimally accommodates it by relying on the demand-side flexibilities and limited available flexibilities from the conventional generating units. The proposed model is illustrated on a 4-bus and a 39- bus system. Numerical results show...

  12. Optimal consumer response for electricity spot pricing

    Energy Technology Data Exchange (ETDEWEB)

    David, A.K.

    1988-09-01

    Techniques to optimise consumer response are essential to maximising the overall benefits to consumers and utilities in any short-range marginal tariff scheme. The theory of categorising consumer load types, is developed and appropriate optimisation methods for the different types are proposed and methods of practical implementation are considered. Potentialities and problems of consumers of various sizes, including small consumers with microcomputing facilities only are discussed.

  13. Electric Field-Responsive Mesoporous Suspensions: A Review

    Directory of Open Access Journals (Sweden)

    Seung Hyuk Kwon

    2015-12-01

    Full Text Available This paper briefly reviews the fabrication and electrorheological (ER characteristics of mesoporous materials and their nanocomposites with conducting polymers under an applied electric field when dispersed in an insulating liquid. Smart fluids of electrically-polarizable particles exhibit a reversible and tunable phase transition from a liquid-like to solid-like state in response to an external electric field of various strengths, and have potential applications in a variety of active control systems. The ER properties of these mesoporous suspensions are explained further according to their dielectric spectra in terms of the flow curve, dynamic moduli, and yield stress.

  14. A sustainable development of a city electrical grid via a non-contractual Demand-Side Management

    Science.gov (United States)

    Samoylenko, Vladislav O.; Pazderin, Andrew V.

    2017-06-01

    An increasing energy consumption of large cities as well as an extreme high density of city electrical loads leads to the necessity to search for an alternative approaches to city grid development. The ongoing implementation of the energy accounting tariffs with differentiated rates depending upon the market conditions and changing in a short-term perspective, provide the possibility to use it as a financial incentive base of a Demand-Side Management (DSM). Modern hi-technology energy metering and accounting systems with a large number of functions and consumer feedback are supposed to be the good means of DSM. Existing systems of Smart Metering (SM) billing usually provide general information about consumption curve, bills and compared data, but not the advanced statistics about the correspondence of financial and electric parameters. Also, consumer feedback is usually not fully used. So, the efforts to combine the market principle, Smart Metering and a consumer feedback for an active non-contractual load control are essential. The paper presents the rating-based multi-purpose system of mathematical statistics and algorithms of DSM efficiency estimation useful for both the consumers and the energy companies. The estimation is performed by SM Data processing systems. The system is aimed for load peak shaving and load curve smoothing. It is focused primarily on a retail market support. The system contributes to the energy efficiency and a distribution process improvement by the manual management or by the automated Smart Appliances interaction.

  15. Demand Estimation

    OpenAIRE

    Elliot E. Combs

    2017-01-01

    Price elasticity shows the responsiveness of demand to changes in price. Negative price elasticity of demand (PED) signifies the inverse relationship between price and demand. According to the equation, PED is -1.19 for widgets, which means that an increase in price of $1 would result in a contraction of demand of $1.19. Since the change in price corresponds with a more than proportionate change in demand, PED is said to be elastic. As a result, an increase in price would discourage consumers...

  16. Demands on project management of comprehensive modernization projects in the electrical systems area. Example of modernization of electrical systems of Kozloduy NPP Unit 5 and 6

    Energy Technology Data Exchange (ETDEWEB)

    Stinshoff, Helmut; Weber, Patrick [Framatome ANP GmbH, P.O. Box 3220, Freyeslebenstrasse 1, D-91050 Erlangen (Germany)

    2006-07-01

    In nuclear power plants, station supply with electric energy must be guaranteed any time. This applies in particular also during the implementation of complex electrical systems modernization projects. Highest demands on the project management, extensive experience and system knowledge are required. In the frame of the Modernization Program for the nuclear power plant Kozloduy unit 5 and 6 in Bulgaria Framatome ANP has approved its ability to implement a large scope of modernization measures during the refueling outages of the years 2003 to 2005. The Contract of the Modernization Program for the European Consortium Kozloduy (Framatome ANP, Atomenergoexport) was signed in July 1999 and became effective in June 2001. The project will be finished by May 2006, with the approval of the Updated Final Safety Analysis Report. The scope of hardware work has been implemented within 6 plant outages during the years 2002 to 2005. The focus of the Modernization Program is mainly oriented to nuclear safety aspects, with the aim of upgrading of the Units to a high safety level in compliance with international practice. A further section of the project is dedicated to upgrading of operational equipment. Framatome ANP personnel have shown that besides the technical challenges which had to be faced, also the intercultural and language barriers were successfully overcome. The good teamwork between the partners of the Consortium ECK, its Bulgarian subcontractors and with Kozloduy plant personnel has been an important success factor. (authors)

  17. Response demands and the recruitment of heuristic strategies in syllogistic reasoning.

    Science.gov (United States)

    Reverberi, Carlo; Rusconi, Patrice; Paulesu, Eraldo; Cherubini, Paolo

    2009-03-01

    Two experiments investigated whether dealing with a homogeneous subset of syllogisms with time-constrained responses encouraged participants to develop and use heuristics for abstract (Experiment 1) and thematic (Experiment 2) syllogisms. An atmosphere-based heuristic accounted for most responses with both abstract and thematic syllogisms. With thematic syllogisms, a weaker effect of a belief heuristic was also observed, mainly where the correct response was inconsistent with the atmosphere of the premises. Analytic processes appear to have played little role in the time-constrained condition, whereas their involvement increased in a self-paced, unconstrained condition. From a dual-process perspective, the results further specify how task demands affect the recruitment of heuristic and analytic systems of reasoning. Because the syllogisms and experimental procedure were the same as those used in a previous neuroimaging study by Goel, Buchel, Frith, and Dolan (2000), the result also deepen our understanding of the cognitive processes investigated by that study.

  18. Day-Ahead Scheduling Considering Demand Response as a Frequency Control Resource

    Directory of Open Access Journals (Sweden)

    Yu-Qing Bao

    2017-01-01

    Full Text Available The development of advanced metering technologies makes demand response (DR able to provide fast response services, e.g., primary frequency control. It is recognized that DR can contribute to the primary frequency control like thermal generators. This paper proposes a day-ahead scheduling method that considers DR as a frequency control resource, so that the DR resources can be dispatched properly with other resources. In the proposed method, the objective of frequency control is realized by defining a frequency limit equation under a supposed contingency. The frequency response model is used to model the dynamics of system frequency. The nonlinear frequency limit equation is transformed to a linear arithmetic equation by piecewise linearization, so that the problem can be solved by mixed integer linear programming (MILP. Finally, the proposed method is verified on numerical examples.

  19. Small Business Demand Response with Communicating Thermostats: SMUD's Summer Solutions Research Pilot

    Energy Technology Data Exchange (ETDEWEB)

    Herter, Karen; Wayland, Seth; Rasin, Josh

    2009-09-25

    This report documents a field study of 78 small commercial customers in the Sacramento Municipal Utility District service territory who volunteered for an integrated energy-efficiency/demand-response (EE-DR) program in the summer of 2008. The original objective for the pilot was to provide a better understanding of demand response issues in the small commercial sector. Early findings justified a focus on offering small businesses (1) help with the energy efficiency of their buildings in exchange for occasional load shed, and (2) a portfolio of options to meet the needs of a diverse customer sector. To meet these expressed needs, the research pilot provided on-site energy efficiency advice and offered participants several program options, including the choice of either a dynamic rate or monthly payment for air-conditioning setpoint control. An analysis of hourly load data indicates that the offices and retail stores in our sample provided significant demand response, while the restaurants did not. Thermostat data provides further evidence that restaurants attempted to precool and reduce AC service during event hours, but were unable to because their air-conditioning units were undersized. On a 100 F reference day, load impacts of all participants during events averaged 14%, while load impacts of office and retail buildings (excluding restaurants) reached 20%. Overall, pilot participants including restaurants had 2007-2008 summer energy savings of 20% and bill savings of 30%. About 80% of participants said that the program met or surpassed their expectations, and three-quarters said they would probably or definitely participate again without the $120 participation incentive. These results provide evidence that energy efficiency programs, dynamic rates and load control programs can be used concurrently and effectively in the small business sector, and that communicating thermostats are a reliable tool for providing air-conditioning load shed and enhancing the ability

  20. Effects of Granular Control on Customers’ Perspective and Behavior with Automated Demand Response Systems

    Energy Technology Data Exchange (ETDEWEB)

    Schetrit, Oren; Kim, Joyce; Yin, Rongxin; Kiliccote, Sila

    2014-08-01

    Automated demand response (Auto-DR) is expected to close the loop between buildings and the grid by providing machine-to-machine communications to curtail loads without the need for human intervention. Hence, it can offer more reliable and repeatable demand response results to the grid than the manual approach and make demand response participation a hassle-free experience for customers. However, many building operators misunderstand Auto-DR and are afraid of losing control over their building operation. To ease the transition from manual to Auto-DR, we designed and implemented granular control of Auto-DR systems so that building operators could modify or opt out of individual load-shed strategies whenever they wanted. This paper reports the research findings from this effort demonstrated through a field study in large commercial buildings located in New York City. We focused on (1) understanding how providing granular control affects building operators’ perspective on Auto-DR, and (2) evaluating the usefulness of granular control by examining their interaction with the Auto-DR user interface during test events. Through trend log analysis, interviews, and surveys, we found that: (1) the opt-out capability during Auto-DR events can remove the feeling of being forced into load curtailments and increase their willingness to adopt Auto-DR; (2) being able to modify individual load-shed strategies allows flexible Auto-DR participation that meets the building’s changing operational requirements; (3) a clear display of automation strategies helps building operators easily identify how Auto-DR is functioning and can build trust in Auto-DR systems.

  1. A Data-Driven Bidding Model for a Cluster of Price-Responsive Consumers of Electricity

    DEFF Research Database (Denmark)

    Saez Gallego, Javier; Morales González, Juan Miguel; Zugno, Marco

    2016-01-01

    This paper deals with the market-bidding problem of a cluster of price-responsive consumers of electricity. We develop an inverse optimization scheme that, recast as a bilevel programming problem, uses price-consumption data to estimate the complex market bid that best captures the price......-response of the cluster. The complex market bid is defined as a series of marginal utility functions plus some constraints on demand, such as maximum pick-up and drop-off rates. The proposed modeling approach also leverages information on exogenous factors that may influence the consumption behavior of the cluster, e...... can be largely captured in the form of a complex market bid, so that this could be ultimately used for the cluster to participate in the wholesale electricity market....

  2. Development of the Optimum Operation Scheduling Model of Domestic Electric Appliances for the Supply-Demand Adjustment in a Power System

    Science.gov (United States)

    Ikegami, Takashi; Iwafune, Yumiko; Ogimoto, Kazuhiko

    The high penetration of variable renewable generation such as Photovoltaic (PV) systems will cause the issue of supply-demand imbalance in a whole power system. The activation of the residential power usage, storage and generation by sophisticated scheduling and control using the Home Energy Management System (HEMS) will be needed to balance power supply and demand in the near future. In order to evaluate the applicability of the HEMS as a distributed controller for local and system-wide supply-demand balances, we developed an optimum operation scheduling model of domestic electric appliances using the mixed integer linear programming. Applying this model to several houses with dynamic electricity prices reflecting the power balance of the total power system, it was found that the adequate changes in electricity prices bring about the shift of residential power usages to control the amount of the reverse power flow due to excess PV generation.

  3. Technical Resource Potential of Non-disruptive Residential Demand Response in Denmark

    DEFF Research Database (Denmark)

    Mathieu, Johanna; Rasmussen, Theis Bo; Sørensen, Mads

    2014-01-01

    Denmark has one of the most aggressive renewable energy strategies in the world; however, large penetrations of fluctuating renewable energy resources will pose new problems in the Danish power system. Demand response (DR) has the potential to mitigate these problems by providing a new source...... of flexibility. This paper estimates the technical resource potential of residential DR in Denmark. We focus on DR that is non-disruptive to the consumer, meaning that DR actions harness inherent load flexibility and are not noticeable by the consumer. We build on existing methodologies for computing DR...

  4. Reduced dielectric response in spatially varying electric fields

    DEFF Research Database (Denmark)

    Hansen, Jesper Schmidt

    2015-01-01

    In this paper, the dynamical equation for polarization is derived. From this the dielectric response to a spatially varying electric field is analyzed showing a reduced response due to flux of polarization in the material. This flux is modeled as a diffusive process through linear constitutive...... relations between the flux and the gradient of the polarization. Comparison between the theory and molecular dynamics simulations confirms this effect. The effect is significant for small length scale electric field variations and the inclusion of the flux is thus important in nanoscale modeling...

  5. Modeling auditory-nerve responses to electrical stimulation

    DEFF Research Database (Denmark)

    Joshi, Suyash Narendra; Dau, Torsten; Epp, Bastian

    2014-01-01

    large enough to affect the temporal coding of sounds and hence, potentially, the communication abilities of the CI listener. In the present study, two recently proposed models of electric stimulationof the AN [1, 2, 3] were considered in terms of their efficacy to predict the spike timing for anodic...... andcathodic stimulation of the AN of cat [4]. The models' responses to the electrical pulses of variousshapes [5] were also analyzed. It was found that, while the models can account for the ring rates inresponse to various biphasic pulse shapes, they fail to correctly describe the timing of AP in response...

  6. Serum brain-derived neurotrophic factor and interleukin-6 response to high-volume mechanically demanding exercise.

    Science.gov (United States)

    Verbickas, Vaidas; Kamandulis, Sigitas; Snieckus, Audrius; Venckunas, Tomas; Baranauskiene, Neringa; Brazaitis, Marius; Satkunskiene, Danguole; Unikauskas, Alvydas; Skurvydas, Albertas

    2018-01-01

    The aim of this study was to follow circulating brain-derived neurotrophic factor (BDNF) and interleukin-6 (IL-6) levels in response to severe muscle-damaging exercise. Young healthy men (N = 10) performed a bout of mechanically demanding stretch-shortening cycle exercise consisting of 200 drop jumps. Voluntary and electrically induced knee extension torque, serum BDNF levels, and IL-6 levels were measured before and for up to 7 days after exercise. Muscle force decreased by up to 40% and did not recover by 24 hours after exercise. Serum BDNF was decreased 1 hour and 24 hours after exercise, whereas IL-6 increased immediately and 1 hour after but recovered to baseline by 24 hours after exercise. IL-6 and 100-Hz stimulation torque were correlated (r = -0.64, P < 0.05) 24 hours after exercise. In response to acute, severe muscle-damaging exercise, serum BDNF levels decrease, whereas IL-6 levels increase and are associated with peripheral fatigue. Muscle Nerve 57: E46-E51, 2018. © 2017 Wiley Periodicals, Inc.

  7. Prediction and control of neural responses to pulsatile electrical stimulation

    Science.gov (United States)

    Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

    2012-04-01

    This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

  8. A Comparison of Sales Response Predictions From Demand Models Applied to Store-Level versus Panel Data

    NARCIS (Netherlands)

    Andrews, Rick L.; Currim, Imran S.; Leeflang, Peter S. H.

    In order to generate sales promotion response predictions, marketing analysts estimate demand models using either disaggregated (consumer-level) or aggregated (store-level) scanner data. Comparison of predictions from these demand models is complicated by the fact that models may accommodate

  9. Response of juvenile scalloped hammerhead sharks to electric stimuli.

    Science.gov (United States)

    Kajiura, Stephen M; Fitzgerald, Timothy P

    2009-01-01

    Sharks can use their electrosensory system to detect electric fields in their environment. Measurements of their electrosensitivity are often derived by calculating the voltage gradient from a model of the charge distribution for an ideal dipole. This study measures the charge distribution around a dipole in seawater and confirms the close correspondence with the model. From this, it is possible to predict how the sharks will respond to dipolar electric fields comprised of differing parameters. We tested these predictions by exposing sharks to different sized dipoles and levels of applied current that simulated the bioelectric fields of their natural prey items. The sharks initiated responses from a significantly greater distance with larger dipole sizes and also from a significantly greater distance with increasing levels of electric current. This study is the first to provide empirical evidence supporting a popular theoretical model and test predictions about how sharks will respond to a variety of different electric stimuli.

  10. Predicting the Response of Electricity Load to Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, Patrick [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Colman, Jesse [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kalendra, Eric [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2015-07-28

    Our purpose is to develop a methodology to quantify the impact of climate change on electric loads in the United States. We perform simple linear regression, assisted by geospatial smoothing, on paired temperature and load time-series to estimate the heating- and coolinginduced sensitivity to temperature across 300 transmission zones and 16 seasonal and diurnal time periods. The estimated load sensitivities can be coupled with climate scenarios to quantify the potential impact of climate change on load, with a primary application being long-term electricity scenarios. The method allows regional and seasonal differences in climate and load response to be reflected in the electricity scenarios. While the immediate product of this analysis was designed to mesh with the spatial and temporal resolution of a specific electricity model to enable climate change scenarios and analysis with that model, we also propose that the process could be applied for other models and purposes.

  11. Reversibly pH-responsive polyurethane membranes for on-demand intravaginal drug delivery.

    Science.gov (United States)

    Kim, Seungil; Chen, Yufei; Ho, Emmanuel A; Liu, Song

    2017-01-01

    To provide better protection for women against sexually transmitted infections, on-demand intravaginal drug delivery was attempted by synthesizing reversibly pH-sensitive polyether-polyurethane copolymers using poly(ethylene glycol) (PEG) and 1,4-bis(2-hydroxyethyl)piperazine (HEP). Chemical structure and thermo-characteristics of the synthesized polyurethanes were confirmed by attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), 1H-nuclear magnetic resonance (1H-NMR), and melting point testing. Membranes were cast by solvent evaporation method using the prepared pH-sensitive polyurethanes. The impact of varying pH on membrane swelling and surface morphology was evaluated via swelling ratio change and scanning electron microscopy (SEM). The prepared pH-responsive membranes showed two times higher swelling ratio at pH 4 than pH 7 and pH-triggered switchable surface morphology change. The anionic anti-inflammatory drug diclofenac sodium (NaDF) was used as a model compound for release studies. The prepared pH-responsive polyurethane membranes allowed continuous NaDF release for 24h and around 20% release of total NaDF within 3h at pH 7 but little-to-no drug release at pH 4.5. NaDF permeation across the prepared membranes demonstrated a reversible pH-responsiveness. The pH-responsive polyurethane membranes did not show any noticeable negative impact on vaginal epithelial cell viability or induction of pro-inflammatory cytokine production compared to controls. Overall, the non-cytotoxic HEP-based pH-responsive polyurethane demonstrated its potential to be used in membrane-based implants such as intravaginal rings to achieve on-demand "on-and-off" intravaginal drug delivery. A reversible and sharp switch between "off" and "on" drug release is achieved for the first time through new pH-sensitive polyurethane membranes, which can serve as window membranes in reservoir-type intravaginal rings for on-demand drug delivery to prevent sexually

  12. Demand Response Advanced Controls Framework and Assessment of Enabling Technology Costs

    Energy Technology Data Exchange (ETDEWEB)

    Potter, Jennifer; Cappers, Peter

    2017-08-28

    The Demand Response Advanced Controls Framework and Assessment of Enabling Technology Costs research describe a variety of DR opportunities and the various bulk power system services they can provide. The bulk power system services are mapped to a generalized taxonomy of DR “service types”, which allows us to discuss DR opportunities and bulk power system services in fewer yet broader categories that share similar technological requirements which mainly drive DR enablement costs. The research presents a framework for the costs to automate DR and provides descriptions of the various elements that drive enablement costs. The report introduces the various DR enabling technologies and end-uses, identifies the various services that each can provide to the grid and provides the cost assessment for each enabling technology. In addition to a report, this research includes a Demand Response Advanced Controls Database and User Manual. They are intended to provide users with the data that underlies this research and instructions for how to use that database more effectively and efficiently.

  13. Emergency response network design for hazardous materials transportation with uncertain demand

    Directory of Open Access Journals (Sweden)

    Kamran Shahanaghi

    2012-10-01

    Full Text Available Transportation of hazardous materials play an essential role on keeping a friendly environment. Every day, a substantial amount of hazardous materials (hazmats, such as flammable liquids and poisonous gases, need to be transferred prior to consumption or disposal. Such transportation may result in unsuitable events for people and environment. Emergency response network is designed for this reason where specialist responding teams resolve any issue as quickly as possible. This study proposes a new multi-objective model to locate emergency response centers for transporting the hazardous materials. Since many real-world applications are faced with uncertainty in input parameters, the proposed model of this paper also assumes that reference and demand to such centre is subject to uncertainty, where demand is fuzzy random. The resulted problem formulation is modelled as nonlinear non-convex mixed integer programming and we used NSGAII method to solve the resulted problem. The performance of the proposed model is examined with several examples using various probability distribution and they are compared with the performance of other existing method.

  14. Adaptive support and pressure support ventilation behavior in response to increased ventilatory demand.

    Science.gov (United States)

    Jaber, Samir; Sebbane, Mustapha; Verzilli, Daniel; Matecki, Stefan; Wysocki, Marc; Eledjam, Jean-Jacques; Brochard, Laurent

    2009-03-01

    Dual-control modes of ventilation adapt the pressure delivery to keep a volume target in response to changes in respiratory mechanics, but they may respond poorly to changes in ventilatory demand. Adaptive support ventilation (ASV), a complex minute volume-targeted pressure-regulated ventilation, was compared to adaptive pressure ventilation (APV), a dual-mode in which the pressure level is adjusted to deliver a preset tidal volume, and to pressure support ventilation (PSV) when facing an increase in ventilatory demand. A total of 14 intensive care unit patients being weaned off mechanical ventilation were included in this randomized crossover study. The effect of adding a heat-and-moisture exchanger to augment circuit dead space was assessed with a same fixed level of ASV, PSV, and APV. Arterial blood gases, ventilator response, and patient respiratory effort parameters were evaluated at the end of the six periods. Adding dead space significantly increased minute ventilation and PaCO2 values with the three modes. Indexes of respiratory effort (pressure-time index of respiratory muscles and work of breathing) increased with all ventilatory modes after dead-space augmentation. This increase was significantly greater with APV than with PSV or ASV (P ventilator.

  15. Water Demands with Two Adaptation Responses to Climate Change in a Mexican Irrigation District

    Science.gov (United States)

    Ojeda, W.; Iñiguez-Covarrubias, M.; Rojano, A.

    2012-12-01

    It is well documented that climate change is inevitable and that farmers need to adapt to changes in projected climate. Changes in water demands for a Mexican irrigation district were assessed using an irrigation scheduling model. The impact of two adaptations actions on water demands were estimated and compared with a baseline scenario. Wet and dry cropping plans were selected from the last 15 water years with actual climatology (1961-1990) taken as reference and three A1B climate change projection periods P1, P2 and P3 (2011-2040, 2041-2070, and 2071-2098). Projected precipitation and air temperature (medium, maximum and minimum) data were obtained through weighted averages of the best CGCM projections for Mexico, available at the IPCC data distribution center, using the Reliability Ensemble Averaging method (REA). Two adaptation farmers' responses were analyzed: use of longer season varieties and reduction of planting dates toward colder season as warming intensifies in the future. An annual accumulated ETo value of 1554 mm was estimated for the base period P0. Cumulative and Daily irrigations demands were generated for each agricultural season using the four climate projection series and considering adaptations actions. Figure 1 integrates in a unique net flow curve for the Fall-Winter season under selected adaptations actions. The simulation results indicated that for mid century (Period P2), the use of longer-season cultivars (AV) will have more pronounced effect in daily net flow based than the reduction of planting season (APS) as climate change intensifies during present century. Without adaptation (WA), the increase in temperature will shorten the growing season of all annual crops, generating a peak shift with respect to reference case (WA-P0). Combined adoptions of adaptation actions (AP+V) can generate higher, peak and cumulative, crop water requirements than actual values as Figure 1 shows. There are clear trends that without adaptations, water

  16. Controlling Electricity Consumption by Forecasting its Response to Varying Prices

    DEFF Research Database (Denmark)

    Corradi, Olivier; Ochsenfeld, Henning Peter; Madsen, Henrik

    2013-01-01

    In a real-time electricity pricing context where consumers are sensitive to varying prices, having the ability to anticipate their response to a price change is valuable. This paper proposes models for the dynamics of such price-response, and shows how these dynamics can be used to control...... electricity consumption using a one-way price signal. Estimation of the price-response is based on data measurable at grid level, removing the need to install sensors and communication devices between each individual consumer and the price-generating entity. An application for price-responsive heating systems...... is studied based on real data, before conducting a control by price experiment using a mixture of real and synthetic data. With the control objective of following a constant consumption reference, peak heating consumption is reduced by nearly 5%, and 11% of the mean daily heating consumption is shifted....

  17. Modelling the Aggregated Dynamic Response of Electric Vehicles

    DEFF Research Database (Denmark)

    Ziras, Charalampos; Hu, Junjie; You, Shi

    2017-01-01

    There is an increasing interest in the use of electric vehicles (EVs) for providing fast frequency reserves due to their large installed capacity and their very fast response. Most works focus on scheduling and optimization and usually neglect their aggregated dynamic response, which is particula......There is an increasing interest in the use of electric vehicles (EVs) for providing fast frequency reserves due to their large installed capacity and their very fast response. Most works focus on scheduling and optimization and usually neglect their aggregated dynamic response, which....... Such approximations can be used in power system studies, in order to capture the dynamics of an EV population more accurately. Finally, we compare our approach to the most widely used in the literature, i.e. the averaging method where all EVs are represented with the population’s average values, and discuss the key...

  18. Joint Planning Of Energy Storage and Transmission Considering Wind-Storage Combined System and Demand Side Response

    Science.gov (United States)

    Huang, Y.; Liu, B. Z.; Wang, K. Y.; Ai, X.

    2017-12-01

    In response to the new requirements of the operation mode of wind-storage combined system and demand side response for transmission network planning, this paper presents a joint planning of energy storage and transmission considering wind-storage combined system and demand side response. Firstly, the charge-discharge strategy of energy storage system equipped at the outlet of wind farm and demand side response strategy are analysed to achieve the best comprehensive benefits through the coordination of the two. Secondly, in the general transmission network planning model with wind power, both energy storage cost and demand side response cost are added to the objective function. Not only energy storage operation constraints and but also demand side response constraints are introduced into the constraint condition. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of the charge-discharge strategy of energy storage system equipped at the outlet of the wind farm and demand side response strategy, which belongs to a typical mixed integer linear programming model that can be solved by mature optimization software. The case study based on the Garver-6 bus system shows that the validity of the proposed model is verified by comparison with general transmission network planning model. Furthermore, the results demonstrate that the joint planning model can gain more economic benefits through setting up different cases.

  19. Progress towards Managing Residential Electricity Demand: Impacts of Standards and Labeling for Refrigerators and Air Conditioners in India

    Energy Technology Data Exchange (ETDEWEB)

    McNeil, Michael A.; Iyer, Maithili

    2009-05-30

    The development of Energy Efficiency Standards and Labeling (EES&L) began in earnest in India in 2001 with the Energy Conservation Act and the establishment of the Indian Bureau of Energy Efficiency (BEE). The first main residential appliance to be targeted was refrigerators, soon to be followed by room air conditioners. Both of these appliances are of critical importance to India's residential electricity demand. About 15percent of Indian households own a refrigerator, and sales total about 4 million per year, but are growing. At the same time, the Indian refrigerator market has seen a strong trend towards larger and more consumptive frost-free units. Room air conditioners in India have traditionally been sold to commercial sector customers, but an increasing number are going to the residential sector. Room air conditioner sales growth in India peaked in the last few years at 20percent per year. In this paper, we perform an engineering-based analysis using data specific to Indian appliances. We evaluate costs and benefits to residential and commercial sector consumers from increased equipment costs and utility bill savings. The analysis finds that, while the BEE scheme presents net benefits to consumers, there remain opportunities for efficiency improvement that would optimize consumer benefits, according to Life Cycle Cost analysis. Due to the large and growing market for refrigerators and air conditioners in India, we forecast large impacts from the standards and labeling program as scheduled. By 2030, this program, if fully implemented would reduce Indian residential electricity consumption by 55 TWh. Overall savings through 2030 totals 385 TWh. Finally, while efficiency levels have been set for several years for refrigerators, labels and MEPS for these products remain voluntary. We therefore consider the negative impact of this delay of implementation to energy and financial savings achievable by 2030.

  20. Technological solutions of decentralized generation of hydroelectricity for those demands that cannot be attended by conventional electric with centralized generation

    Energy Technology Data Exchange (ETDEWEB)

    Signoretti, Valdir Tesche; Veras, Carlos Alberto Gurgel Rudi; Els, Henri Van [Universidade de Brasilia, Brasilia, DF (Brazil). Faculdade de Tecnologia. Dept. de Engenharia Mecanica], e-mail: gurgel@unb.br

    2010-07-01

    A source of energy stable and reliable and of acceptable cost is a basic requisite for the development of a given region can give-if full. Access to energy is important basis of human existence, essential to the satisfaction of basic needs such as food, clothing, and housing and also of mobility and communication. However, the dependency world burning of fossil fuels for energy generation and supply of a demand constantly increasing, both in industrialized countries and those in development, already threatening the ecological stability of the Earth. At the same time, conflicts by distribution of the last reserves these resources non-renewable threaten significantly to civil society. Adding to the breakneck speed in which humanity consumes the energetic sources and the obvious devastation of nature has an unequal distribution in consumption and access to energy. Renewable sources and energy efficiency are viable and necessary, especially because they can be the key to reduce wastefulness and extend the access to energy. In this way, there is a significant influence on economic and social inclusion of population excluded, generating employment and income with costs local and global environmental reduced compared to traditional forms and unsustainable generation and use of energy. This work is a study involving issues related to rural electrification from hydroelectricity, especially related to those isolated communities of the Amazon region that are lacking this form of energy, presented a general review since the origins of hydroelectricity in Brazil, as well as a national panorama electric exclusion as well as a scenario Amazon's supply of electricity. Finally presenting-if the main technologies available for hydroelectric generation for these isolated communities. (author)

  1. Electrical field stimulation-induced excitatory responses of ...

    African Journals Online (AJOL)

    The aim of the present study was to investigate the effect of the endothelium on electrical field stimulation (EFS)-induced excitatory responses of pulmonary artery segments from pulmonary hypertensive rats. Methods: Pulmonary hypertension was induced in rats with a single dose of monocrotaline (60 mg/kg) and 21 days ...

  2. The Integration of Energy Efficiency, Renewable Energy, DemandResponse and Climate Change: Challenges and Opportunities for Evaluatorsand Planners

    Energy Technology Data Exchange (ETDEWEB)

    Vine, Edward

    2007-05-29

    This paper explores the feasibility of integrating energyefficiency program evaluation with the emerging need for the evaluationof programs from different "energy cultures" (demand response, renewableenergy, and climate change). The paper reviews key features andinformation needs of the energy cultures and critically reviews theopportunities and challenges associated with integrating these withenergy efficiency program evaluation. There is a need to integrate thedifferent policy arenas where energy efficiency, demand response, andclimate change programs are developed, and there are positive signs thatthis integration is starting to occur.

  3. An ILP based Algorithm for Optimal Customer Selection for Demand Response in SmartGrids

    Energy Technology Data Exchange (ETDEWEB)

    Kuppannagari, Sanmukh R. [Univ. of Southern California, Los Angeles, CA (United States); Kannan, Rajgopal [Louisiana State Univ., Baton Rouge, LA (United States); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

    2015-12-07

    Demand Response (DR) events are initiated by utilities during peak demand periods to curtail consumption. They ensure system reliability and minimize the utility’s expenditure. Selection of the right customers and strategies is critical for a DR event. An effective DR scheduling algorithm minimizes the curtailment error which is the absolute difference between the achieved curtailment value and the target. State-of-the-art heuristics exist for customer selection, however their curtailment errors are unbounded and can be as high as 70%. In this work, we develop an Integer Linear Programming (ILP) formulation for optimally selecting customers and curtailment strategies that minimize the curtailment error during DR events in SmartGrids. We perform experiments on real world data obtained from the University of Southern California’s SmartGrid and show that our algorithm achieves near exact curtailment values with errors in the range of 10-7 to 10-5, which are within the range of numerical errors. We compare our results against the state-of-the-art heuristic being deployed in practice in the USC SmartGrid. We show that for the same set of available customer strategy pairs our algorithm performs 103 to 107 times better in terms of the curtailment errors incurred.

  4. A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, C. Lindsay [Cornell Univ., Ithaca, NY (United States); Zéphyr, Luckny [Cornell Univ., Ithaca, NY (United States); Liu, Jialin [Cornell Univ., Ithaca, NY (United States); Cardell, Judith B. [Smith College, Northampton MA (United States)

    2017-01-07

    The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewables and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.

  5. Multi-Objective Low-Carbon Economic Dispatch Considering Demand Response with Wind Power Integrated Systems

    Directory of Open Access Journals (Sweden)

    Liu Wenjuan

    2017-01-01

    Full Text Available The generation cost, carbon emissions and customers’ satisfaction are considered in this paper. On the basis of this, the multi-objective and low-carbon economic dispatch model with wind farm, this considers demand response, is established. The model user stochastic programming theory to describe the uncertainty of the wind power and converts it into an equivalent deterministic model by using distribution function of wind power output, optimizes demand side resources to adjust the next day load curve and to improve load rate and absorptive capacity of wind power, introduce customers’ satisfaction to ensure that the scheduling scheme satisfies customer and integrate the resources of source and load to unify coordination wind farm access to network and to meet the requirements of energy saving and emission reduction. The search process of artificial fish school algorithm introducing Tabu search and more targeted search mechanism, an multi-objective improved artificial fish school algorithm is proposed to solve this model. Using the technique for order preference by similarity to ideal solution (TOPSIS to sort the Pareto frontier, the optimal scheduling scheme is determined. Simulation results verify the rationality and validity of the proposed model and algorithm.

  6. Data-Driven Baseline Estimation of Residential Buildings for Demand Response

    Directory of Open Access Journals (Sweden)

    Saehong Park

    2015-09-01

    Full Text Available The advent of advanced metering infrastructure (AMI generates a large volume of data related with energy service. This paper exploits data mining approach for customer baseline load (CBL estimation in demand response (DR management. CBL plays a significant role in measurement and verification process, which quantifies the amount of demand reduction and authenticates the performance. The proposed data-driven baseline modeling is based on the unsupervised learning technique. Specifically we leverage both the self organizing map (SOM and K-means clustering for accurate estimation. This two-level approach efficiently reduces the large data set into representative weight vectors in SOM, and then these weight vectors are clustered by K-means clustering to find the load pattern that would be similar to the potential load pattern of the DR event day. To verify the proposed method, we conduct nationwide scale experiments where three major cities’ residential consumption is monitored by smart meters. Our evaluation compares the proposed solution with the various types of day matching techniques, showing that our approach outperforms the existing methods by up to a 68.5% lower error rate.

  7. Aggregation Potentials for Buildings - Business Models of Demand Response and Virtual Power Plants

    DEFF Research Database (Denmark)

    Ma, Zheng; Billanes, Joy Dalmacio; Jørgensen, Bo Nørregaard

    2017-01-01

    Buildings as prosumers have an important role in the energy aggregation market due to their potential flexible energy consumption and distributed energy resources. However, energy flexibility provided by buildings can be very complex and depend on many factors. The immaturity of the current...... in the energy aggregation market: (1) buildings participate in the implicit Demand Response (DR) program via retailers; (2) buildings with small energy consumption participate in the explicit DR via aggregators; (3) buildings directly access the explicit DR program; (4) buildings access energy market via...... aggregation market with unclear incentives is still a challenge for buildings to participate in the aggregation market. However, few studies have investigated business models for building participation in the aggregation market. Therefore, this paper develops four business models for buildings to participate...

  8. A Time-Varying Potential-Based Demand Response Method for Mitigating the Impacts of Wind Power Forecasting Errors

    Directory of Open Access Journals (Sweden)

    Jia Ning

    2017-11-01

    Full Text Available The uncertainty of wind power results in wind power forecasting errors (WPFE which lead to difficulties in formulating dispatching strategies to maintain the power balance. Demand response (DR is a promising tool to balance power by alleviating the impact of WPFE. This paper offers a control method of combining DR and automatic generation control (AGC units to smooth the system’s imbalance, considering the real-time DR potential (DRP and security constraints. A schematic diagram is proposed from the perspective of a dispatching center that manages smart appliances including air conditioner (AC, water heater (WH, electric vehicle (EV loads, and AGC units to maximize the wind accommodation. The presented model schedules the AC, WH, and EV loads without compromising the consumers’ comfort preferences. Meanwhile, the ramp constraint of generators and power flow transmission constraint are considered to guarantee the safety and stability of the power system. To demonstrate the performance of the proposed approach, simulations are performed in an IEEE 24-node system. The results indicate that considerable benefits can be realized by coordinating the DR and AGC units to mitigate the WPFE impacts.

  9. Demand response strategy management with active and reactive power incentive in the smart grid: a two-level optimization approach

    Directory of Open Access Journals (Sweden)

    Ryuto Shigenobu

    2017-05-01

    Full Text Available High penetration of distributed generators (DGs using renewable energy sources (RESs is raising some important issues in the operation of modern po­wer system. The output power of RESs fluctuates very steeply, and that include uncertainty with weather conditions. This situation causes voltage deviation and reverse power flow. Several methods have been proposed for solving these problems. Fundamentally, these methods involve reactive power control for voltage deviation and/or the installation of large battery energy storage system (BESS at the interconnection point for reverse power flow. In order to reduce the installation cost of static var compensator (SVC, Distribution Company (DisCo gives reactive power incentive to the cooperating customers. On the other hand, photovoltaic (PV generator, energy storage and electric vehicle (EV are introduced in customer side with the aim of achieving zero net energy homes (ZEHs. This paper proposes not only reactive power control but also active power flow control using house BESS and EV. Moreover, incentive method is proposed to promote participation of customers in the control operation. Demand response (DR system is verified with several DR menu. To create profit for both side of DisCo and customer, two level optimization approach is executed in this research. Mathematical modeling of price elasticity and detailed simulations are executed by case study. The effectiveness of the proposed incentive menu is demonstrated by using heuristic optimization method.

  10. Capacity Evaluation of Several Types of DG Systems in Micro-grid using Load Demand Analysis and Frequency Response of DG Systems

    Science.gov (United States)

    Shimoda, Eisuke; Numata, Shigeo; Baba, Jumpei; Nitta, Tanzo; Masada, Eisuke

    The micro-grid has been operating at institute of technology of Shimizu Corporation since July, 2006. Main generators are two gas engine CHP systems which capacity are 350kW and 90kW. Two power storage devices, secondary battery and electric double layer capacitor, are also installed to compensate rapid load fluctuation. In this paper, load demand is analyzed by using frequency analysis and this sampling interval is decided by probability distribution of power transition. DG systems' characteristics such as frequency response, fuel efficiency and frequency stabilization capability are also assessed. Capacity of DG Systems in the Micro-grid is evaluated by results of load demand analysis and DG systems' characteristics assessment.

  11. Magnetic and electric fields induce directional responses in Steinernema carpocapsae.

    Science.gov (United States)

    Ilan, Teva; Kim-Shapiro, Daniel B; Bock, Clive H; Shapiro-Ilan, David I

    2013-09-01

    Entomopathogenic nematode species respond directionally to various cues including electrical stimuli. For example, in prior research Steinernema carpocapsae was shown to be attracted to an electrical current that was applied to an agar dish. Thus, we hypothesised that these nematodes may use electromagnetic reception to assist in navigating through the soil and finding a host. In this study we discovered that S. carpocapsae also responds to electrical fields (without current) and to magnetic fields; to our knowledge this is the first report of nematode directional movement in response to a magnetic field. Our research expands on the range of known stimuli that entomopathogenic nematodes respond to. The findings may have implications for foraging behavior. Published by Elsevier Ltd.

  12. Optimizing Industrial Consumer Demand Response Through Disaggregation, Hour-Ahead Pricing, and Momentary Autonomous Control

    Science.gov (United States)

    Abdulaal, Ahmed

    The work in this study addresses the current limitations of the price-driven demand response (DR) approach. Mainly, the dependability on consumers to respond in an energy aware conduct, the response timeliness, the difficulty of applying DR in a busy industrial environment, and the problem of load synchronization are of utmost concern. In order to conduct a simulation study, realistic price simulation model and consumers' building load models are created using real data. DR action is optimized using an autonomous control method, which eliminates the dependency on frequent consumer engagement. Since load scheduling and long-term planning approaches are infeasible in the industrial environment, the proposed method utilizes instantaneous DR in response to hour-ahead price signals (RTP-HA). Preliminary simulation results concluded savings at the consumer-side at the cost of increased supplier-side burden due to the aggregate effect of the universal DR policies. Therefore, a consumer disaggregation strategy is briefly discussed. Finally, a refined discrete-continuous control system is presented, which utilizes multi-objective Pareto optimization, evolutionary programming, utility functions, and bidirectional loads. Demonstrated through a virtual testbed fit with real data, the new system achieves momentary optimized DR in real-time while maximizing the consumer's wellbeing.

  13. Do the rotator cuff tendons of young athletic subjects hypertrophy in response to increased loading demands?

    Science.gov (United States)

    Milgrom, Charles; Moran, Daniel S; Safran, Ori; Finsestone, Aharon S

    2012-11-01

    The rotator cuff is composed of muscle and tendon units. Although muscle has been shown to adapt to mechanical loads, the response of human tendon is not well defined. We hypothesized that increased loading demands on the rotator cuff of young trainees would cause an adaptive muscle response but not an adaptive hypertrophic tendon response. The hypertrophic response of the rotator cuff tendon, shoulder strength, aerobic fitness, and the lean body weight of 70 young male recruits were studied before and after a 1-year course of elite infantry training. Shoulder strength was assessed by the maximum number of pull-ups done and the rotator cuff thickness by ultrasound measurement of the supraspinatus thickness. Aerobic physical fitness was assessed by maximum oxygen consumption (Vo(2) max). Lean body weight was measured by skin-fold thickness. The mean number of pull-ups done increased from 17.5 to 21.7 (P = .01), but the supraspinatus thickness at the beginning of training (6.1 mm) was unchanged at the end of the training. Vo(2) max increased from 57 to 64 mL/kg/min (P = .0001). Lean body weight increased from 58.3 to 64.7 kg (P = .0001). As a result of increased loading, the strength of the rotator cuff muscles of young trainees increased, but by the parameter of hypertrophy, no evidence was found of a parallel adaptive response of the rotator cuff tendon. Copyright © 2012 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Mosby, Inc. All rights reserved.

  14. Experimental Sleep Restriction Facilitates Pain and Electrically Induced Cortical Responses.

    Science.gov (United States)

    Matre, Dagfinn; Hu, Li; Viken, Leif A; Hjelle, Ingri B; Wigemyr, Monica; Knardahl, Stein; Sand, Trond; Nilsen, Kristian Bernhard

    2015-10-01

    Sleep restriction (SR) has been hypothesized to sensitize the pain system. The current study determined whether experimental sleep restriction had an effect on experimentally induced pain and pain-elicited electroencephalographic (EEG) responses. A paired crossover study. Pain testing was performed after 2 nights of 50% SR and after 2 nights with habitual sleep (HS). Laboratory experiment at research center. Self-reported healthy volunteers (n = 21, age range: 18-31 y). Brief high-density electrical stimuli to the forearm skin produced pinprick-like pain. Subjective pain ratings increased after SR, but only in response to the highest stimulus intensity (P = 0.018). SR increased the magnitude of the pain-elicited EEG response analyzed in the time-frequency domain (P = 0.021). Habituation across blocks did not differ between HS and SR. Event-related desynchronization (ERD) was reduced after SR (P = 0.039). Pressure pain threshold of the trapezius muscle region also decreased after SR (P = 0.017). Sleep restriction (SR) increased the sensitivity to pressure pain and to electrically induced pain of moderate, but not low, intensity. The increased electrical pain could not be explained by a difference in habituation. Increased response magnitude is possibly related to reduced processing within the somatosensory cortex after partial SR. © 2015 Associated Professional Sleep Societies, LLC.

  15. Experimental Sleep Restriction Facilitates Pain and Electrically Induced Cortical Responses

    Science.gov (United States)

    Matre, Dagfinn; Hu, Li; Viken, Leif A.; Hjelle, Ingri B.; Wigemyr, Monica; Knardahl, Stein; Sand, Trond; Nilsen, Kristian Bernhard

    2015-01-01

    Study Objectives: Sleep restriction (SR) has been hypothesized to sensitize the pain system. The current study determined whether experimental sleep restriction had an effect on experimentally induced pain and pain-elicited electroencephalographic (EEG) responses. Design: A paired crossover study. Intervention: Pain testing was performed after 2 nights of 50% SR and after 2 nights with habitual sleep (HS). Setting: Laboratory experiment at research center. Participants: Self-reported healthy volunteers (n = 21, age range: 18–31 y). Measurements and Results: Brief high-density electrical stimuli to the forearm skin produced pinprick-like pain. Subjective pain ratings increased after SR, but only in response to the highest stimulus intensity (P = 0.018). SR increased the magnitude of the pain-elicited EEG response analyzed in the time-frequency domain (P = 0.021). Habituation across blocks did not differ between HS and SR. Event-related desynchronization (ERD) was reduced after SR (P = 0.039). Pressure pain threshold of the trapezius muscle region also decreased after SR (P = 0.017). Conclusion: Sleep restriction (SR) increased the sensitivity to pressure pain and to electrically induced pain of moderate, but not low, intensity. The increased electrical pain could not be explained by a difference in habituation. Increased response magnitude is possibly related to reduced processing within the somatosensory cortex after partial SR. Citation: Matre D, Hu L, Viken LA, Hjelle IB, Wigemyr M, Knardahl S, Sand T, Nilsen KB. Experimental sleep restriction facilitates pain and electrically induced cortical responses. SLEEP 2015;38(10):1607–1617. PMID:26194577

  16. Modeling auditory-nerve responses to electrical stimulation

    DEFF Research Database (Denmark)

    Joshi, Suyash Narendra; Dau, Torsten; Epp, Bastian

    Cochlear implants (CI) directly stimulate the auditory nerve (AN), bypassing the mechano-electrical transduction in the inner ear. Trains of biphasic, charge balanced pulses (anodic and cathodic) are used as stimuli to avoid damage of the tissue. The pulses of either polarity are capable of produ......Cochlear implants (CI) directly stimulate the auditory nerve (AN), bypassing the mechano-electrical transduction in the inner ear. Trains of biphasic, charge balanced pulses (anodic and cathodic) are used as stimuli to avoid damage of the tissue. The pulses of either polarity are capable......μs, which is large enough to affect the temporal coding of sounds and hence, potentially, the communication abilities of the CI listener. In the present study, two recently proposed models of electric stimulation of the AN [1,2] were considered in terms of their efficacy to predict the spike timing...... for anodic and cathodic stimulation of the AN of cat [3]. The models’ responses to the electrical pulses of various shapes [4,5,6] were also analyzed. It was found that, while the models can account for the firing rates in response to various biphasic pulse shapes, they fail to correctly describe the timing...

  17. Development of a “Current Energy Mix Scenario” and a “Electricity as Main Energy Source Scenario” for electricity demand up to 2100

    OpenAIRE

    Mário J. S. Brito; Tânia Sousa

    2014-01-01

    In this work, we develop a model to forecast world electricity production up to 2100. We analyze historical data for electricity production, population and GDP per Capita for the period 1900–2008. We show that electricity production follows general trends. First, there is an electricity intensity target of 0.20-0.25 kWh per unit of GDP (US$2012) as economies mature, except in countries traditionally relying heavily on renewable electricity (hydroelectricity), for whom this target ranges betwe...

  18. Photoacoustic microscopy of microvascular responses to cortical electrical stimulation

    Science.gov (United States)

    Tsytsarev, Vassiliy; Hu, Song; Yao, Junjie; Maslov, Konstantin; Barbour, Dennis L.; Wang, Lihong V.

    2011-07-01

    Advances in the functional imaging of cortical hemodynamics have greatly facilitated the understanding of neurovascular coupling. In this study, label-free optical-resolution photoacoustic microscopy (OR-PAM) was used to monitor microvascular responses to direct electrical stimulations of the mouse somatosensory cortex through a cranial opening. The responses appeared in two forms: vasoconstriction and vasodilatation. The transition between these two forms of response was observed in single vessels by varying the stimulation intensity. Marked correlation was found between the current-dependent responses of two daughter vessels bifurcating from the same parent vessel. Statistical analysis of twenty-seven vessels from three different animals further characterized the spatial-temporal features and the current dependence of the microvascular response. Our results demonstrate that OR-PAM is a valuable tool to study neurovascular coupling at the microscopic level.

  19. Design of Fast Response Smart Electric Vehicle Charging Infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Ching-Yen; Chynoweth, Joshua; Qiu, Charlie; Chu, Chi-Cheng; Gadh, Rajit

    2013-11-25

    The response time of the smart electrical vehicle (EV) charging infrastructure is the key index of the system performance. The traffic between the smart EV charging station and the control center dominates the response time of the smart charging stations. To accelerate the response of the smart EV charging station, there is a need for a technology that collects the information locally and relays it to the control center periodically. To reduce the traffic between the smart EV charger and the control center, a Power Information Collector (PIC), capable of collecting all the meters power information in the charging station, is proposed and implemented in this paper. The response time is further reduced by pushing the power information to the control center. Thus, a fast response smart EV charging infrastructure is achieved to handle the shortage of energy in the local grid.

  20. Cardiorespiratory demand of acute voluntary cycling with functional electrical stimulation in individuals with multiple sclerosis with severe mobility impairment.

    Science.gov (United States)

    Edwards, Thomas; Motl, Robert W; Pilutti, Lara A

    2018-01-01

    Exercise training is one strategy for improving cardiorespiratory fitness (CRF) in multiple sclerosis (MS); however, few modalities are accessible for those with severe mobility impairment. Functional electrical stimulation (FES) cycling is an adapted exercise modality with the potential for improving CRF in people with severe MS. The objective of this study was to characterize the cardiorespiratory response of acute voluntary cycling with FES in people with MS with severe mobility impairment, and to compare this response to passive leg cycling. Eleven participants with MS that required assistance for ambulation completed a single bout of voluntary cycling with FES or passive leg cycling. Oxygen consumption, heart rate (HR), work rate (WR), and ratings of perceived exertion (RPE) were recorded throughout the session. For the FES group, mean exercising oxygen consumption was 8.7 ± 1.8 mL/(kg·min) -1 , or 63.5% of peak oxygen consumption. Mean HR was 102 ± 9.7 bpm, approximately 76.4% of peak HR. Mean WR was 27.0 ± 9.2 W, or 57.3% of peak WR, and median RPE was 13.5 (interquartile range = 5.5). Active cycling with FES was significantly (p cycling based on oxygen consumption, HR, WR, and RPE during exercise. In conclusion, voluntary cycling with FES elicited an acute response that corresponded with moderate-to vigorous-intensity activity, suggesting that active cycling with FES can elicit a sufficient stimulus for improving CRF.

  1. Using climate response functions in analyzing electricity production variables. A case study from Norway.

    Science.gov (United States)

    Tøfte, Lena S.; Martino, Sara; Mo, Birger

    2016-04-01

    representation of hydropower is included and total hydro power production for each area is calculated, and the production is distributed among all available plants within each area. During simulation, the demand is affected by prices and temperatures. 6 different infrastructure scenarios of wind and power line development are analyzed. The analyses are done by running EMPS calibrated for today's situation for 11*11*8 different combinations of altered weather variables (temperature, precipitation and wind) describing different climate change scenarios, finding the climate response function for every EMPS-variable according the electricity production, such as prices and income, energy balances (supply, consumption and trade), overflow losses, probability of curtailment etc .

  2. Electric and magnetic response of hot QCD matter

    Energy Technology Data Exchange (ETDEWEB)

    Steinert, Thorsten; Cassing, Wolfgang [Institut fuer Theoretische Physik, Universitaet Giessen, 35392 Giessen (Germany)

    2014-07-01

    We study the electric conductivity as well as the magnetic response of hot QCD matter at various temperatures T and chemical potentials μ{sub q} within the off-shell Parton-Hadron-String Dynamics (PHSD) transport approach for interacting partonic systems in a finite box with periodic boundary conditions. The response of the strongly-interacting system in equilibrium to an external electric field defines the electric conductivity σ{sub 0} whereas the response to a moderate external magnetic field defines the induced diamagnetic moment μ{sub L} (T, μ{sub q}) as well as the spin susceptibility χ{sub S}(T, μ{sub q}). We find a sizeable temperature dependence of the dimensionless ratio σ{sub 0}/T well in line with calculations in a relaxation time approach for T{sub c} < T < 2.5 T{sub c} as well as an increase of σ{sub 0} with μ{sub q}{sup 2}/T{sup 2}. Furthermore, the frequency dependence of the electric conductivity σ(Ω) shows a simple functional form well in line with results from the Dynamical QuasiParticle Model (DQPM). The spin susceptibility χ{sub S}(T,μ{sub q}) is found to increase with temperature T and to rise ∝ μ{sub q}{sup 2}/T{sup 2}, too. The actual values for the magnetic response of the QGP in the temperature range below 250 MeV show that the QGP should respond diamagnetically in actual ultra-relativistic heavy-ion collisions since the maximal magnetic fields created in these collisions are smaller than B{sub c}(T) which defines a boundary between diamagnetism and paramagnetism.

  3. Social Responsibility of the University of Cotopaxi Facing the Demands of the Development in the Ecuador

    Directory of Open Access Journals (Sweden)

    MSc. Ángel Francisco Esquivel-Valverde

    2015-10-01

    Full Text Available The social responsibility of the universities is to guarantee the access to knowledge of high level, new methods and development forms, as well as to technology of last generation, having the moral obligation and ethics of increasing the quality of its systems through the improvement of the administration of the university processes. For it the implementation of a model of administration of the knowledge in the State University of Cotopaxi (UTC that propitiates the recognition from the society to the results that the university generates it constitutes a necessity and a priority for the institution and its authorities that its gives answer to the demands that the society generates and the execution of the responsibility social university. In this address ours thinks about the necessity of a theoretical reflection on the contradictions that impact in the relevancy of the superior education and the list of the UTC in the Ecuadorian context of development.Keywords:  knowledge, university impact, university relevancy, social commitment, generation knowledge.

  4. Field Testing and Modeling of Supermarket Refrigeration Systems as a Demand Response Resource

    Energy Technology Data Exchange (ETDEWEB)

    Deru, Michael; Hirsch, Adam; Clark, Jordan; Anthony, Jamie

    2016-08-26

    Supermarkets offer a substantial demand response (DR) resource because of their high energy intensity and use patterns; however, refrigeration as the largest load has been challenging to access. Previous work has analyzed supermarket DR using heating, ventilating, and air conditioning; lighting; and anti-sweat heaters. This project evaluated and quantified the DR potential inherent in supermarket refrigeration systems in the Bonneville Power Administration service territory. DR events were carried out and results measured in an operational 45,590-ft2 supermarket located in Hillsboro, Oregon. Key results from the project include the rate of temperature increase in freezer reach-in cases and walk-ins when refrigeration is suspended, the load shed amount for DR tests, and the development of calibrated models to quantify available DR resources. Simulations showed that demand savings of 15 to 20 kilowatts (kW) are available for 1.5 hours for a typical store without precooling and for about 2.5 hours with precooling using only the low-temperature, non-ice cream cases. This represents an aggregated potential of 20 megawatts within BPA's service territory. Inability to shed loads for medium-temperature (MT) products because of the tighter temperature requirements is a significant barrier to realizing larger DR for supermarkets. Store owners are reluctant to allow MT case set point changes, and laboratory tests of MT case DR strategies are needed so that owners become comfortable testing, and implementing, MT case DR. The next-largest barrier is the lack of proper controls in most supermarket displays over ancillary equipment, such as anti-sweat heaters, lights, and fans.

  5. Electricity for groundwater use: constraints and opportunities for adaptive response to climate change

    Science.gov (United States)

    Scott, Christopher A.

    2013-09-01

    Globally, groundwater use is intensifying to meet demands for irrigation, urban supply, industrialization, and, in some instances, electrical power generation. In response to hydroclimatic variability, surface water is being substituted with groundwater, which must be viewed as a strategic resource for climate adaptation. In this sense, the supply of electricity for pumping is an adaptation policy tool. Additionally, planning for climate-change mitigation must consider CO2 emissions resulting from pumping. This paper examines the influence of electricity supply and pricing on groundwater irrigation and resulting emissions, with specific reference to Mexico—a climate-water-energy ‘perfect storm’. Night-time power supply at tariffs below the already-subsidized rates for agricultural groundwater use has caused Mexican farmers to increase pumping, reversing important water and electricity conservation gains achieved. Indiscriminate groundwater pumping, including for virtual water exports of agricultural produce, threatens the long-term sustainability of aquifers, non-agricultural water uses, and stream-aquifer interactions that sustain riparian ecosystems. Emissions resulting from agricultural groundwater pumping in Mexico are estimated to be 3.6% of total national emissions and are equivalent to emissions from transporting the same agricultural produce to market. The paper concludes with an assessment of energy, water, and climate trends coupled with policy futures to address these challenges.

  6. Essays on measurement and evaluation of demand side management programs in the electricity industry, and impacts of firm strategy on stock price in the biotechnology industry

    Science.gov (United States)

    Bandres Motola, Miguel A.

    Essay one estimates changes in small business customer energy consumption (kWh) patterns resulting from a seasonally differentiated pricing structure. Econometric analysis leverages cross-sectional time series data across the entire population of affected customers, from 2007 through the present. Observations include: monthly energy usage (kWh), relevant customer segmentations, local daily temperature, energy price, and region-specific economic conditions, among other variables. The study identifies the determinants of responsiveness to seasonal price differentiation. In addition, estimated energy consumption changes occurring during the 2010 summer season are reported for the average customer and in aggregate grouped by relevant customer segments, climate zone, and total customer base. Essay two develops an econometric modeling methodology to evaluate load impacts for short duration demand response events. The study analyzes time series data from a season of direct load control program tests aimed at integrating demand response into the wholesale electricity market. I have combined "fuzzy logic" with binary variables to create "fuzzy indicator variables" that allow for measurement of short duration events while using industry standard model specifications. Typically, binary variables for every hour are applied in load impact analysis of programs dispatched in hourly intervals. As programs evolve towards integration with the wholesale market, event durations become irregular and often occur for periods of only a few minutes. This methodology is innovative in that it conserves the degrees of freedom in the model while allowing for analysis of high frequency data using fixed effects. Essay three examines the effects of strategies, intangibles, and FDA news on the stocks of young biopharmaceutical firms. An event study methodology is used to explore those effects. This study investigates 20,839 announcements from 1990 to 2005. Announcements on drug development

  7. Responders to Wide-Pulse, High-Frequency Neuromuscular Electrical Stimulation Show Reduced Metabolic Demand: A 31P-MRS Study in Humans.

    Directory of Open Access Journals (Sweden)

    Jennifer Wegrzyk

    Full Text Available Conventional (CONV neuromuscular electrical stimulation (NMES (i.e., short pulse duration, low frequencies induces a higher energetic response as compared to voluntary contractions (VOL. In contrast, wide-pulse, high-frequency (WPHF NMES might elicit--at least in some subjects (i.e., responders--a different motor unit recruitment compared to CONV that resembles the physiological muscle activation pattern of VOL. We therefore hypothesized that for these responder subjects, the metabolic demand of WPHF would be lower than CONV and comparable to VOL. 18 healthy subjects performed isometric plantar flexions at 10% of their maximal voluntary contraction force for CONV (25 Hz, 0.05 ms, WPHF (100 Hz, 1 ms and VOL protocols. For each protocol, force time integral (FTI was quantified and subjects were classified as responders and non-responders to WPHF based on k-means clustering analysis. Furthermore, a fatigue index based on FTI loss at the end of each protocol compared with the beginning of the protocol was calculated. Phosphocreatine depletion (ΔPCr was assessed using 31P magnetic resonance spectroscopy. Responders developed four times higher FTI's during WPHF (99 ± 37 × 10(3 N.s than non-responders (26 ± 12 × 10(3 N.s. For both responders and non-responders, CONV was metabolically more demanding than VOL when ΔPCr was expressed relative to the FTI. Only for the responder group, the ∆PCr/FTI ratio of WPHF (0.74 ± 0.19 M/N.s was significantly lower compared to CONV (1.48 ± 0.46 M/N.s but similar to VOL (0.65 ± 0.21 M/N.s. Moreover, the fatigue index was not different between WPHF (-16% and CONV (-25% for the responders. WPHF could therefore be considered as the less demanding NMES modality--at least in this subgroup of subjects--by possibly exhibiting a muscle activation pattern similar to VOL contractions.

  8. Electricity decision-making: New techniques for calculating statewide economic impacts from new power supply and demand-side management programs

    Science.gov (United States)

    Tegen, Suzanne Isabel Helmholz

    This dissertation introduces new techniques for calculating and comparing statewide economic impacts from new coal, natural gas and wind power plants, as well as from demand-side management programs. The impetus for this work was two-fold. First, reviews of current literature and projects revealed that there was no standard way to estimate statewide economic impacts from new supply- and demand-side electricity options. Second, decision-makers who were interviewed stated that they were overwhelmed with data in general, but also lacked enough specific information about economic development impacts to their states from electricity, to make informed choices. This dissertation includes chapters on electricity decision-making and on economic impacts from supply and demand. The supply chapter compares different electricity options in three states which vary in natural resource content: Arizona, Colorado and Michigan. To account for differing capacity factors, resources are compared on a per-megawatt-hour basis. The calculations of economic impacts from new supply include: materials and labor for construction, operations, maintenance, fuel extraction, fuel transport, as well as property tax, financing and landowner revenues. The demand-side chapter compares residential, commercial and industrial programs in Iowa. Impact calculations include: incremental labor and materials for program planning, installation and operations, as well as sales taxes and electricity saved. Results from supply-side calculations in the three states analyzed indicate that adding new wind power can have a greater impact to a state's economy than adding new gas or coal power due to resource location, taxes and infrastructure. Additionally, demand-side management programs have a higher relative percentage of in-state dollar flow than supply-side solutions, though demand-side programs typically involve fewer MWh and dollars than supply-side generation. Methods for this dissertation include researching

  9. Households under the impression of the energy turnaround. Development of electricity demand and load profiles; Die Haushalte im Zeichen der Energiewende. Entwicklung der Stromnachfrage und Lastprofile

    Energy Technology Data Exchange (ETDEWEB)

    Elsland, Rainer; Bossmann, Tobias; Gnann, Till; Wietschel, Martin [Fraunhofer-Institut fuer System- und Innovationsforschung (ISI), Karlsruhe (Germany); Hartel, Rupert; Fichtner, Wolf [Karlsruher Institut fuer Technologie (KIT), Karlsruhe (Germany). Inst. fuer Industriebetriebslehre und Industrielle Produktion (IIP)

    2013-01-15

    One of the central components of the energy turnaround is the improvement of energy efficiency. Households play a key role in this connection, not only due to their high potentials for saving energy and shifting loads, but also because of the growing importance of electricity as an energy carrier. This makes it interesting to explore how the continuing dissemination of efficient energy applications, electromobility and decentralised electricity production through photovoltaics will impact on load and electricity production profiles in the German household sector until the year 2040. The results show that with ambitious energy policy goals it will be possible to lower the electricity demand of households by 30%. However, this decrease could be more than undone by electromobility.

  10. A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm

    DEFF Research Database (Denmark)

    Kong, Fanrong; Jiang, Jianhui; Ding, Zhigang

    2017-01-01

    . Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may...... not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner's historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make......To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs) have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost...

  11. Public policy responsibilities in a restructured electric industry: An analysis of values, objectives, and approaches

    Energy Technology Data Exchange (ETDEWEB)

    Tonn, B.E.; Schweitzer, M.

    1996-03-01

    Discussions and decisions in states as diverse as California, Wisconsin, and Rhode Island are focusing on moving the United States electric industry from one dominated by vertically-integrated and highly regulated utility-based electricity monopolies to one characterized by largely divested and independent generation, transmission, and distribution sectors and by vigorous wholesale and retail competition. Numerous issues must be solved for this transition to be successful. Three of the most important are how to deal with stranded investments, how to provide open access to transmission systems, and how to deal with potentially stranded benefits, which is the current term being used to describe environmental and social programs such as demand-side management, low income programs, and renewable energy. This report explores how to meet public policy responsibilities, which are growing more acute, in a proactive fashion in a restructured United States electric industry. The specific goals of this report are to (1) assess trade-offs in the short-term in meeting public policy responsibilities associated with stranded benefits and (2) introduce a series of new ideas that, if enacted, could substantially satisfy important public policy considerations.