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

Demand Side Management: An approach to peak load smoothing

Science.gov (United States)

Gupta, Prachi

A preliminary national-level analysis was conducted to determine whether Demand Side Management (DSM) programs introduced by electric utilities since 1992 have made any progress towards their stated goal of reducing peak load demand. Estimates implied that DSM has a very small effect on peak load reduction and there is substantial regional and end-user variability. A limited scholarly literature on DSM also provides evidence in support of a positive effect of demand response programs. Yet, none of these studies examine the question of how DSM affects peak load at the micro-level by influencing end-users' response to prices. After nearly three decades of experience with DSM, controversy remains over how effective these programs have been. This dissertation considers regional analyses that explore both demand-side solutions and supply-side interventions. On the demand side, models are estimated to provide in-depth evidence of end-user consumption patterns for each North American Electric Reliability Corporation (NERC) region, helping to identify sectors in regions that have made a substantial contribution to peak load reduction. The empirical evidence supports the initial hypothesis that there is substantial regional and end-user variability of reductions in peak demand. These results are quite robust in rapidly-urbanizing regions, where air conditioning and lighting load is substantially higher, and regions where the summer peak is more pronounced than the winter peak. It is also evident from the regional experiences that active government involvement, as shaped by state regulations in the last few years, has been successful in promoting DSM programs, and perhaps for the same reason we witness an uptick in peak load reductions in the years 2008 and 2009. On the supply side, we estimate the effectiveness of DSM programs by analyzing the growth of capacity margin with the introduction of DSM programs. The results indicate that DSM has been successful in offsetting the

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.

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

Development of reader for the demand data from compound demand meter for power supply/demand (CDM). Development of recommended tools for load leveling in existing works; Denryoku jukyuyo fukugo keiki kara no demand data yomitori sochi no kaihatsu. Kisetsu kojo no fuka heijunka suisho tool no kaihatsu

Energy Technology Data Exchange (ETDEWEB)

Sakamoto, S. [Kansai Electric Power Co. Inc., Osaka (Japan)

1997-10-10

Kansai Electric Power has developed a system which reads the demand data for 30min. stored in the compound demand meter for power supply/demand (CDM), and prints the load curves. It is for customers of high-voltage power of less than 500kW, where load management is less extensive than that in larger users, for initial consulting on improvement of load factor (recommendation of heat storage contracts). It is to be installed on the spot to display the load curves, to allow the expert visiting the site to issue initial proposals immediately. It displays `daily demands by time zone` instead of `monthly power consumption` previously provided, and makes the graph of demands by time zone. It is designed to be compact, light, and easily and safely handled. The field test results indicate that the system can be sufficiently practical with the major performance items. 4 figs., 1 tab.

Influential Factors for Accurate Load Prediction in a Demand Response Context

DEFF Research Database (Denmark)

Wollsen, Morten Gill; Kjærgaard, Mikkel Baun; Jørgensen, Bo Nørregaard

2016-01-01

Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the influence....... Next, the time of day that is being predicted greatly influence the prediction which is related to the weather pattern. By presenting these results we hope to improve the modeling of building loads and algorithms for Demand Response planning.......Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the influence...

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.

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

-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.......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...

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

Demand Response on domestic thermostatically controlled loads

DEFF Research Database (Denmark)

Lakshmanan, Venkatachalam

. 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......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....... In general, the electricity consumers are classified as industrial, commercial and domestic. In this dissertation, only the thermostatically controlled loads (TCLs) in the domestic segment are considered for the demand response study. The study is funded by Danish Council for Strategic Research (DCSR...

Demand modelling for central heating systems

Energy Technology Data Exchange (ETDEWEB)

Heller, A.

2000-07-01

Most researchers in the field of heat demand estimation have focussed on explaning the load for a given plant based on rather few measurements. This approach is simply the only one adaptable with the very limited data material and limited computer power. This way of dealing with the subject is here called the top-down approach, due to the fact that one tries to explain the load from the overall data. The results of such efforts are discussed in the report, leading to inspiration for own work. Also the significance of the findings to the causes for given heat loads are discussed and summarised. Contrary to the top-down approach applied in literature, a here-called bottom-up approach is applied in this work, describing the causes of a given partial load in detail and combining them to explain the total load for the system. Three partial load 'components' are discussed: 1) Space heating. 2) Hot-Water Consumption. 3) Heat losses in pipe networks. The report is aimed at giving an introduction to these subjects, but at the same time at collecting the previous work done by the author. Space heating is shortly discussed and loads are generated by an advanced simulation model. A hot water consumption model is presented and heat loads, generated by this model, utilised in the overall work. Heat loads due to heat losses in district heating a given a high priority in the current work. Hence a detailed presentation and overview of the subject is given to solar heating experts normally not dealing with district heating. Based on the 'partial' loads generated by the above-mentioned method, an overall load model is built in the computer simulation environment TRNSYS. The final tool is then employed for the generation of time series for heat demand, representing a district heating area. The results are compared to alternative methods for the generation of heat demand profiles. Results form this comparison will be presented. Computerised modelling of systems

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.

Least square regression based integrated multi-parameteric demand modeling for short term load forecasting

International Nuclear Information System (INIS)

Halepoto, I.A.; Uqaili, M.A.

2014-01-01

Nowadays, due to power crisis, electricity demand forecasting is deemed an important area for socioeconomic development and proper anticipation of the load forecasting is considered essential step towards efficient power system operation, scheduling and planning. In this paper, we present STLF (Short Term Load Forecasting) using multiple regression techniques (i.e. linear, multiple linear, quadratic and exponential) by considering hour by hour load model based on specific targeted day approach with temperature variant parameter. The proposed work forecasts the future load demand correlation with linear and non-linear parameters (i.e. considering temperature in our case) through different regression approaches. The overall load forecasting error is 2.98% which is very much acceptable. From proposed regression techniques, Quadratic Regression technique performs better compared to than other techniques because it can optimally fit broad range of functions and data sets. The work proposed in this paper, will pave a path to effectively forecast the specific day load with multiple variance factors in a way that optimal accuracy can be maintained. (author)

Simultaneous Provision of Flexible Ramping Product and Demand Relief by Interruptible Loads Considering Economic Incentives

Directory of Open Access Journals (Sweden)

Jiahua Hu

2017-12-01

Full Text Available To cope with the net load variability in real time, sufficient ramp capability from controllable resources is required. To address the issue of insufficient ramp capacity in real time operations, flexible ramping products (FRPs have been adopted by some Independent System Operators (ISOs in the USA as a new market design. The inherent variability and uncertainty caused by renewable energy sources (RESs call for new FRP providers apart from conventional generating units. The so-called interruptible load (IL has proved to be useful in maintaining the supply-demand balance by providing demand relief and can be a viable FRP provider in practice. Given this background, this work presents a stochastic real-time unit commitment model considering ramp requirement and simultaneous provision of IL for FRP and demand relief. Load serving entities (LSEs are included in the proposed model and act as mediators between the ISO and multiple ILs. In particular, incentive compatible contracts are designed to encourage customers to reveal their true outage costs. Case studies indicate both the system and LSEs can benefit by employing the proposed method and ILs can gain the highest profits by signing up a favorable contract.

Peak load demand forecasting using two-level discrete wavelet decomposition and neural network algorithm

Science.gov (United States)

Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

2010-02-01

This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.

Demand response driven load pattern elasticity analysis for smart households

NARCIS (Netherlands)

Paterakis, N.G.; Catalao, J.P.S.; Tascikaraoglu, A.; Bakirtzis, A.G.; Erdinc, O.

2015-01-01

The recent interest in smart grid vision enables several smart applications in different parts of the power grid structure, where specific importance should be given to the demand side. As a result, changes in load patterns due to demand response (DR) activities at end-user premises, such as smart

Optimizing electrical load pattern in Kuwait using grid connected photovoltaic systems

International Nuclear Information System (INIS)

Al-Hasan, A.Y.; Ghoneim, A.A.; Abdullah, A.H.

2004-01-01

Grid connected photovoltaic systems is one of the most promising applications of photovoltaic systems. These systems are employed in applications where utility service is already available. In this case, there is no need for battery storage because grid power may be used to supplement photovoltaic systems (PV) when the load exceeds available PV generation. The load receives electricity from both the photovoltaic array and the utility grid. In this system, the load is the total electrical energy consumption. The main objective of the present work is to optimize the electrical load pattern in Kuwait using grid connected PV systems. In this situation, the electric load demand can be satisfied from both the photovoltaic array and the utility grid. The performance of grid connected photovoltaic systems in the Kuwait climate has been evaluated. It was found that the peak load matches the maximum incident solar radiation in Kuwait, which would emphasize the role of using the PV station to minimize the electrical load demand. In addition, a significant reduction in peak load can be achieved with grid connected PV systems

Methodology of demand forecast by market analysis of electric power and load curves

International Nuclear Information System (INIS)

Barreiro, C.J.; Atmann, J.L.

1989-01-01

A methodology for demand forecast of consumer classes and their aggregation is presented. An analysis of the actual attended market can be done by appropriate measures and load curves studies. The suppositions for the future market behaviour by consumer classes (industrial, residential, commercial, others) are shown, and the actions for optimise this market are foreseen, obtained by load curves modulations. The process of future demand determination is obtained by the appropriate aggregation of this segmented demands. (C.G.C.)

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....

Evaluation of flexible demand-side load-following reserves in power systems with high wind generation penetration

NARCIS (Netherlands)

Paterakis, N.G.; Catalao, J.P.S.; Ntomaris, A.V.; Erdinc, O.

2015-01-01

In this study, a two-stage stochastic programming joint energy and reserve day-ahead market structure is proposed in order to procure the required load-following reserves to tackle with wind power production uncertainty. Reserves can be procured both from generation and demand-side. Responsive

Conceptual framework for load controlling : with demand reduction bidding & consumer retention

NARCIS (Netherlands)

Babar, M.; Ahamed, I.; Al-Ammar, E.A.

2013-01-01

Advancement in demand side management strategies enables smart grid to cope with the increasing energy demand and provide economic benefit to all of its stakeholders. Moreover, emerging concept of smart pricing and advances in load control and communication generate new business opportunities as a

System incremental cost calculations using the participation factor load-flow formulation

International Nuclear Information System (INIS)

Meisel, J.

1993-01-01

The load-flow problem is reformulated such that the use of a slack-bus generator is included only as a special case. This reformulation, known as the participation factor load-flow, includes a total mismatch variable and a defined participation vector, which, in general, distributes this mismatch to all system buses. The slack-bus constraint can still be obtained by defining a particular participation vector. In using the participation factor load-flow in the transpose Jacobian approach to the economic optimal dispatch problem, the paper shows that the value of the system-λ can be controlled such that this value represents the minimal incremental change in generation costs per unit change in system total demand with this demand distributed according to the specified participation vector. Methods using the conventional B-coefficient loss formulas or slack-bus load-flows give system-λ values whereby the unit change in demand must be placed on a fictitious single load-bus or on the slack-bus, respectively. Having a system-λ value which more accurately represents a proposed energy interchange between interconnected systems is very important in developing valid costs for each system. An extensive 28-bus, 8-generator system is included to illustrate these results

Evaluation of high temperature gas reactor for demanding cogeneration load follow

International Nuclear Information System (INIS)

Yan, Xing L.; Sato, Hiroyuki; Tachibana, Yukio; Kunitomi, Kazuhiko; Hino, Ryutaro

2012-01-01

Modular nuclear reactor systems are being developed around the world for new missions among which is cogeneration for industries and remote areas. Like existing fossil energy counterpart in these markets, a nuclear plant would need to demonstrate the feasibility of load follow including (1) the reliability to generate power and heat simultaneously and alone and (2) the flexibility to vary cogeneration rates concurrent to demand changes. This article reports the results of JAEA's evaluation on the high temperature gas reactor (HTGR) to perform these duties. The evaluation results in a plant design based on the materials and design codes developed with JAEA's operating test reactor and from additional equipment validation programs. The 600 MWt-HTGR plant generates electricity efficiently by gas turbine and 900degC heat by a topping heater. The heater couples via a heat transport loop to industrial facility that consumes the high temperature heat to yield heat product such as hydrogen fuel, steel, or chemical. Original control methods are proposed to automate transition between the load duties. Equipment challenges are addressed for severe operation conditions. Performance limits of cogeneration load following are quantified from the plant system simulation to a range of bounding events including a loss of either load and a rapid peaking of electricity. (author)

Community-driven demand creation for the use of routine viral load testing: a model to scale up routine viral load testing.

Science.gov (United States)

Killingo, Bactrin M; Taro, Trisa B; Mosime, Wame N

2017-11-01

HIV treatment outcomes are dependent on the use of viral load measurement. Despite global and national guidelines recommending the use of routine viral load testing, these policies alone have not translated into widespread implementation or sufficiently increased access for people living with HIV (PLHIV). Civil society and communities of PLHIV recognize the need to close this gap and to enable the scale up of routine viral load testing. The International Treatment Preparedness Coalition (ITPC) developed an approach to community-led demand creation for the use of routine viral load testing. Using this Community Demand Creation Model, implementers follow a step-wise process to capacitate and empower communities to address their most pressing needs. This includes utlizing a specific toolkit that includes conducting a baseline assessment, developing a treatment education toolkit, organizing mobilization workshops for knowledge building, provision of small grants to support advocacy work and conducting benchmark evaluations. The Community Demand Creation Model to increase demand for routine viral load testing services by PLHIV has been delivered in diverse contexts including in the sub-Saharan African, Asian, Latin American and the Caribbean regions. Between December 2015 and December 2016, ITPC trained more than 240 PLHIV activists, and disbursed US$90,000 to network partners in support of their national advocacy work. The latter efforts informed a regional, community-driven campaign calling for domestic investment in the expeditious implementation of national viral load testing guidelines. HIV treatment education and community mobilization are critical components of demand creation for access to optimal HIV treatment, especially for the use of routine viral load testing. ITPC's Community Demand Creation Model offers a novel approach to achieving this goal. © 2017 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of

Demand management through centralized control system using power line communication for existing buildings

International Nuclear Information System (INIS)

Al-Mulla, A.; ElSherbini, A.

2014-01-01

Highlights: • A pilot system was developed for demand management of equipment in buildings. • The networking was based on LonWorks platform and power line communication. • Demand strategies led to load reductions up to 74% and energy savings up to 25%. • The peak load reduction is expected to reach 3.44 GW by the year 2030. - Abstract: Managing peak demand efficiently is vital for maintaining uninterrupted supply of electrical power by utility providers. In this work, a pilot system was developed for managing and controlling the demand of major power consuming equipment in buildings from a central server, while relying mostly on existing infrastructure and maintaining consumer comfort. The system was successfully demonstrated on a selected group of buildings using the LonWorks networking platform. At the building level, the system utilized power line and twisted pair communication to control the thermostats of air-conditioning (A/C) units. The higher level communication was executed through extensible markup language (XML) and simple object access protocol (SOAP). The system provided control capabilities based on A/C unit priority, thermostat temperature, building type and geographic location. The development and execution of demand management strategies for selected buildings led to peak load reductions up to 74%, in addition to energy savings up to 25%. Implementing such a system at a national level in Kuwait is estimated to reduce peak demand by 3.44 GW, amounting to capital savings of $4.13 billion. The use of existing infrastructure reduced the cost and installation time of the system. Based on the successful testing of this pilot system, a larger-scale system is being developed

Deep Neural Network Based Demand Side Short Term Load Forecasting

Directory of Open Access Journals (Sweden)

Seunghyoung Ryu

2016-12-01

Full Text Available In the smart grid, one of the most important research areas is load forecasting; it spans from traditional time series analyses to recent machine learning approaches and mostly focuses on forecasting aggregated electricity consumption. However, the importance of demand side energy management, including individual load forecasting, is becoming critical. In this paper, we propose deep neural network (DNN-based load forecasting models and apply them to a demand side empirical load database. DNNs are trained in two different ways: a pre-training restricted Boltzmann machine and using the rectified linear unit without pre-training. DNN forecasting models are trained by individual customer’s electricity consumption data and regional meteorological elements. To verify the performance of DNNs, forecasting results are compared with a shallow neural network (SNN, a double seasonal Holt–Winters (DSHW model and the autoregressive integrated moving average (ARIMA. The mean absolute percentage error (MAPE and relative root mean square error (RRMSE are used for verification. Our results show that DNNs exhibit accurate and robust predictions compared to other forecasting models, e.g., MAPE and RRMSE are reduced by up to 17% and 22% compared to SNN and 9% and 29% compared to DSHW.

Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

Energy Technology Data Exchange (ETDEWEB)

Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.; Chassin, David P.; Djilali, Ned

2014-01-31

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.

Integration scenarios of Demand Response into electricity markets: Load shifting, financial savings and policy implications

International Nuclear Information System (INIS)

Feuerriegel, Stefan; Neumann, Dirk

2016-01-01

Demand Response allows for the management of demand side resources in real-time; i.e. shifting electricity demand according to fluctuating supply. When integrated into electricity markets, Demand Response can be used for load shifting and as a replacement for both control reserve and balancing energy. These three usage scenarios are compared based on historic German data from 2011 to determine that load shifting provides the highest benefit: its annual financial savings accumulate to €3.110 M for both households and the service sector. This equals to relative savings of 2.83% compared to a scenario without load shifting. To improve Demand Response integration, the proposed model suggests policy implications: reducing bid sizes, delivery periods and the time-lag between market transactions and delivery dates in electricity markets. - Highlights: •Comparison of 3 scenarios to integrate Demand Response into electricity markets. •These are: optimize procurement, offer as control reserve, avoid balancing energy. •Ex post simulation to quantify financial impact and policy implications. •Highest savings from load shifting with a cost reduction of 3%. •Model suggests reducing bid sizes, delivery periods and time lags as policy issues.

Load kick-back effects due to activation of demand response in view of distribution grid operation

DEFF Research Database (Denmark)

Han, Xue; Sossan, Fabrizio; Bindner, Henrik W.

2014-01-01

. The paper has shown how aggregated consumption dynamics introduce new peaks in the system due to the synchronous behaviors of a portfolio of homogeneous DSRs, which is instructed by the flexibility management system. This dynamic effect is recognized as load kick-back effect. The impact of load kick......-back effects onto the distribution grid is analysed in this paper by establishing scenarios based on the estimation of DSR penetration levels from the system operator. The results indicate some risks that the activation of demand response may create critical peaks in the local grid due to kick-back effects....

Improving demand response potential of a supermarket refrigeration system

DEFF Research Database (Denmark)

Pedersen, Rasmus; Schwensen, John; Biegel, Benjamin

2017-01-01

In a smart grid the load shifting capabilities of demand-side devices such as supermarkets are of high interest. In supermarkets this potential is represented by the ability to store energy in the thermal mass of refrigerated foodstuff. To harness the full load shifting potential we propose...... 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...... 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...

Control for large scale demand response of thermostatic loads

DEFF Research Database (Denmark)

Totu, Luminita Cristiana; Leth, John; Wisniewski, Rafal

2013-01-01

appliances with on/off operation. The objective is to reduce the consumption peak of a group of loads composed of both flexible and inflexible units. The power flexible units are the thermostat-based appliances. We discuss a centralized, model predictive approach and a distributed structure with a randomized......Demand response is an important Smart Grid concept that aims at facilitating the integration of volatile energy resources into the electricity grid. This paper considers a residential demand response scenario and specifically looks into the problem of managing a large number thermostatbased...

Two-stage discrete-continuous multi-objective load optimization: An industrial consumer utility approach to demand response

International Nuclear Information System (INIS)

Abdulaal, Ahmed; Moghaddass, Ramin; Asfour, Shihab

2017-01-01

Highlights: •Two-stage model links discrete-optimization to real-time system dynamics operation. •The solutions obtained are non-dominated Pareto optimal solutions. •Computationally efficient GA solver through customized chromosome coding. •Modest to considerable savings are achieved depending on the consumer’s preference. -- Abstract: In the wake of today’s highly dynamic and competitive energy markets, optimal dispatching of energy sources requires effective demand responsiveness. Suppliers have adopted a dynamic pricing strategy in efforts to control the downstream demand. This method however requires consumer awareness, flexibility, and timely responsiveness. While residential activities are more flexible and schedulable, larger commercial consumers remain an obstacle due to the impacts on industrial performance. This paper combines methods from quadratic, stochastic, and evolutionary programming with multi-objective optimization and continuous simulation, to propose a two-stage discrete-continuous multi-objective load optimization (DiCoMoLoOp) autonomous approach for industrial consumer demand response (DR). Stage 1 defines discrete-event load shifting targets. Accordingly, controllable loads are continuously optimized in stage 2 while considering the consumer’s utility. Utility functions, which measure the loads’ time value to the consumer, are derived and weights are assigned through an analytical hierarchy process (AHP). The method is demonstrated for an industrial building model using real data. The proposed method integrates with building energy management system and solves in real-time with autonomous and instantaneous load shifting in the hour-ahead energy price (HAP) market. The simulation shows the occasional existence of multiple load management options on the Pareto frontier. Finally, the computed savings, based on the simulation analysis with real consumption, climate, and price data, ranged from modest to considerable amounts

Load management for refrigeration systems: Potentials and barriers

Energy Technology Data Exchange (ETDEWEB)

Grein, Arne, E-mail: a.grein@tu-berlin.de [University of Technology Berlin, Institute for Energy Technology, Department of Energy Systems, Einsteinufer 25 (TA8), 10587 Berlin (Germany); Pehnt, Martin [Institute for Energy and Environmental Research Heidelberg (ifeu), Wilckensstr. 3, 69120 Heidelberg (Germany)

2011-09-15

As a strategy to deal with the increasing intermittent input of renewable energy sources in Germany, the adaptation of power consumption is complementary to power-plant regulation, grid expansion and physical energy storage. One demand sector that promises strong returns for load management efforts is cooling and refrigeration. In these processes, thermal inertia provides a temporal buffer for shifting and adjusting the power consumption of cooling systems. We have conducted an empirical investigation to obtain a detailed and time-resolved bottom-up analysis of load management for refrigeration systems in the city of Mannheim, Germany. We have extrapolated our results to general conditions in Germany. Several barriers inhibit the rapid adoption of load management strategies for cooling systems, including informational barriers, strict compliance with legal cooling requirements, liability issues, lack of technical experience, an inadequate rate of return and organizational barriers. Small commercial applications of refrigeration in the food-retailing and cold storage in hotels and restaurants are particularly promising starting points for intelligent load management. When our results are applied to Germany, suitable sectors for load management have theoretical and achievable potential values of 4.2 and 2.8 GW, respectively, amounting to about 4-6% of the maximum power demand in Germany. - Highlights: > Potential and barriers for implementation of load shifting for refrigeration. > Empirical investigation for time-resolved bottom-up analysis in Mannheim, Germany. > Suitable sectors and further recommendations for introducing load management.> Extrapolation of results from local to national level.

Load management for refrigeration systems: Potentials and barriers

International Nuclear Information System (INIS)

Grein, Arne; Pehnt, Martin

2011-01-01

As a strategy to deal with the increasing intermittent input of renewable energy sources in Germany, the adaptation of power consumption is complementary to power-plant regulation, grid expansion and physical energy storage. One demand sector that promises strong returns for load management efforts is cooling and refrigeration. In these processes, thermal inertia provides a temporal buffer for shifting and adjusting the power consumption of cooling systems. We have conducted an empirical investigation to obtain a detailed and time-resolved bottom-up analysis of load management for refrigeration systems in the city of Mannheim, Germany. We have extrapolated our results to general conditions in Germany. Several barriers inhibit the rapid adoption of load management strategies for cooling systems, including informational barriers, strict compliance with legal cooling requirements, liability issues, lack of technical experience, an inadequate rate of return and organizational barriers. Small commercial applications of refrigeration in the food-retailing and cold storage in hotels and restaurants are particularly promising starting points for intelligent load management. When our results are applied to Germany, suitable sectors for load management have theoretical and achievable potential values of 4.2 and 2.8 GW, respectively, amounting to about 4-6% of the maximum power demand in Germany. - Highlights: → Potential and barriers for implementation of load shifting for refrigeration. → Empirical investigation for time-resolved bottom-up analysis in Mannheim, Germany. → Suitable sectors and further recommendations for introducing load management.→ Extrapolation of results from local to national level.

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

Load building versus conservation as demand-side management objectives

International Nuclear Information System (INIS)

Kexel, D.T.

1994-01-01

This paper examines the economics of load building versus conservation as demand-side management objectives. Economic criteria to be used in evaluating each type of program from the perspectives of all impacted parties are provided. The impact of DSM programs on electric rates is shown to be a key focal point of a thorough evaluation

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.

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.

A novel microgrid demand-side management system for manufacturing facilities

Science.gov (United States)

Harper, Terance J.

Thirty-one percent of annual energy consumption in the United States occurs within the industrial sector, where manufacturing processes account for the largest amount of energy consumption and carbon emissions. For this reason, energy efficiency in manufacturing facilities is increasingly important for reducing operating costs and improving profits. Using microgrids to generate local sustainable power should reduce energy consumption from the main utility grid along with energy costs and carbon emissions. Also, microgrids have the potential to serve as reliable energy generators in international locations where the utility grid is often unstable. For this research, a manufacturing process that had approximately 20 kW of peak demand was matched with a solar photovoltaic array that had a peak output of approximately 3 KW. An innovative Demand-Side Management (DSM) strategy was developed to manage the process loads as part of this smart microgrid system. The DSM algorithm managed the intermittent nature of the microgrid and the instantaneous demand of the manufacturing process. The control algorithm required three input signals; one from the microgrid indicating the availability of renewable energy, another from the manufacturing process indicating energy use as a percent of peak production, and historical data for renewable sources and facility demand. Based on these inputs the algorithm had three modes of operation: normal (business as usual), curtailment (shutting off non-critical loads), and energy storage. The results show that a real-time management of a manufacturing process with a microgrid will reduce electrical consumption and peak demand. The renewable energy system for this research was rated to provide up to 13% of the total manufacturing capacity. With actively managing the process loads with the DSM program alone, electrical consumption from the utility grid was reduced by 17% on average. An additional 24% reduction was accomplished when the microgrid

Non-utility generation and demand management reliability of customer delivery systems

International Nuclear Information System (INIS)

Hamoud, G.A.; Wang, L.

1995-01-01

A probabilistic methodology for evaluating the impact of non-utility generation (NUG) and demand management programs (DMP) on supply reliability of customer delivery systems was presented. The proposed method was based on the criteria that the supply reliability to the customers on the delivery system should not be affected by the integration of either NUG or DMPs. The method considered station load profile, load forecast, and uncertainty in size and availability of the nuio. Impacts on system reliability were expressed in terms of possible delays of the in-service date for new facilities or in terms of an increase in the system load carrying capability. Examples to illustrate the proposed methodology were provided. 10 refs., 8 tabs., 2 figs

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.

Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system

International Nuclear Information System (INIS)

Jiang, Yibo; Xu, Jian; Sun, Yuanzhang; Wei, Congying; Wang, Jing; Ke, Deping; Li, Xiong; Yang, Jun; Peng, Xiaotao; Tang, Bowen

2017-01-01

Highlights: • Improving the utilization of wind power by the demand response of residential hybrid energy system. • An optimal scheduling of home energy management system integrating micro-CHP. • The scattered response capability of consumers is aggregated by demand bidding curve. • A stochastic day-ahead economic dispatch model considering demand response and wind power. - Abstract: As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.

Towards smart energy systems: application of kernel machine regression for medium term electricity load forecasting.

Science.gov (United States)

Alamaniotis, Miltiadis; Bargiotas, Dimitrios; Tsoukalas, Lefteri H

2016-01-01

Integration of energy systems with information technologies has facilitated the realization of smart energy systems that utilize information to optimize system operation. To that end, crucial in optimizing energy system operation is the accurate, ahead-of-time forecasting of load demand. In particular, load forecasting allows planning of system expansion, and decision making for enhancing system safety and reliability. In this paper, the application of two types of kernel machines for medium term load forecasting (MTLF) is presented and their performance is recorded based on a set of historical electricity load demand data. The two kernel machine models and more specifically Gaussian process regression (GPR) and relevance vector regression (RVR) are utilized for making predictions over future load demand. Both models, i.e., GPR and RVR, are equipped with a Gaussian kernel and are tested on daily predictions for a 30-day-ahead horizon taken from the New England Area. Furthermore, their performance is compared to the ARMA(2,2) model with respect to mean average percentage error and squared correlation coefficient. Results demonstrate the superiority of RVR over the other forecasting models in performing MTLF.

Data model for Demand Side Management

Directory of Open Access Journals (Sweden)

Simona-Vasilica OPREA

2017-08-01

Full Text Available Demand Side Management (DSM is a portfolio of measures to improve the energy system mainly at the consumption level. In this paper we propose a data model for DSM stating from the optimization methods approach in SMARTRADE project from different perspectives of several entities that include: Transmission System Operator (TSO/Distribution System Operators (DSOs perspectives in case of security/reliability concerns: minimum amount of load (or generation shedding; aggregators perspective in case of demand or generation shedding request: Which demand (or generators should be shed?; consumers perspective: load shifting (time-of-use (ToU tariffs and optimum contract strategies with the aggregators (also known as balancing responsible parties- BRP for load shedding.

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.

Impact of Demand Response Programs on Optimal Operation of Multi-Microgrid System

Directory of Open Access Journals (Sweden)

Anh-Duc Nguyen

2018-06-01

Full Text Available The increased penetration of renewables is beneficial for power systems but it poses several challenges, i.e., uncertainty in power supply, power quality issues, and other technical problems. Backup generators or storage system have been proposed to solve this problem but there are limitations remaining due to high installation and maintenance cost. Furthermore, peak load is also an issue in the power distribution system. Due to the adjustable characteristics of loads, strategies on demand side such as demand response (DR are more appropriate in order to deal with these challenges. Therefore, this paper studies how DR programs influence the operation of the multi-microgrid (MMG. The implementation is executed based on a hierarchical energy management system (HiEMS including microgrid EMSs (MG-EMSs responsible for local optimization in each MG and community EMS (C-EMS responsible for community optimization in the MMG. Mixed integer linear programming (MILP-based mathematical models are built for MMG optimal operation. Five scenarios consisting of single DR programs and DR groups are tested in an MMG test system to evaluate their impact on MMG operation. Among the five scenarios, some DR programs apply curtailing strategies, resulting in a study about the influence of base load value and curtailable load percentage on the amount of curtailed load and shifted load as well as the operation cost of the MMG. Furthermore, the impact of DR programs on the amount of external and internal trading power in the MMG is also examined. In summary, each individual DR program or group could be handy in certain situations depending on the interest of the MMG such as external trading, self-sufficiency or operation cost minimization.

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...

Data-Driven Optimization of Incentive-based Demand Response System with Uncertain Responses of Customers

Directory of Open Access Journals (Sweden)

Jimyung Kang

2017-10-01

Full Text Available Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of virtual generator, the amount of load reduction includes inevitable uncertainty, because it consists of a very large number of independent energy customers. While they may reduce energy today, they might not tomorrow. In this circumstance, a DSRP must choose a proper set of these uncertain customers to achieve the exact preferred amount of load curtailment. In this paper, the customer selection problem for a service provider that consists of uncertain responses of customers is defined and solved. The uncertainty of energy reduction is fully considered in the formulation with data-driven probability distribution modeling and stochastic programming technique. The proposed optimization method that utilizes only the observed load data provides a realistic and applicable solution to a demand response system. The performance of the proposed optimization is verified with real demand response event data in Korea, and the results show increased and stabilized performance from the service provider’s perspective.

Real-Time Load-Side Control of Electric Power Systems

Science.gov (United States)

Zhao, Changhong

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems. (1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with

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

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...... 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...

Projecting Electricity Demand in 2050

Energy Technology Data Exchange (ETDEWEB)

Hostick, Donna J. [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 C. W. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2014-07-01

This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% - 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly data for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.

Energy management for vehicle power net with flexible electric load demand

NARCIS (Netherlands)

Kessels, J.T.B.A.; Bosch, van den P.P.J.; Koot, M.W.T.; Jager, de A.G.

2005-01-01

The electric power demand in road vehicles increases rapidly and to supply all electric loads efficiently, energy management (EM) turns out to be a necessity. In general, EM exploits the storage capacity of a buffer connected to the vehicle's power net, such that energy is stored or retrieved at

Time-of-use based electricity demand response for sustainable manufacturing systems

International Nuclear Information System (INIS)

Wang, Yong; Li, Lin

2013-01-01

As required by the Energy Policy Act of 2005, utility companies across the U.S. are offering TOU (time-of-use) based electricity demand response programs. The TOU rate gives consumers opportunities to manage their electricity bill by shifting use from on-peak periods to mid-peak and off-peak periods. Reducing the amount of electricity needed during the peak load times makes it possible for the power grid to meet consumers' needs without building more costly backup infrastructures and help reduce GHG (greenhouse gas) emissions. Previous research on the applications of TOU and other electricity demand response programs has been mainly focused on residential and commercial buildings while largely neglected industrial manufacturing systems. This paper proposes a systems approach for TOU based electricity demand response for sustainable manufacturing systems under the production target constraint. Key features of this approach include: (i) the electricity related costs including both consumption and demand are integrated into production system modeling; (ii) energy-efficient and demand-responsive production scheduling problems are formulated and the solution technique is provided; and (iii) the effects of various factors on the near-optimal scheduling solutions are examined. The research outcome is expected to enhance the energy efficiency, electricity demand responsiveness, and cost effectiveness of modern manufacturing systems. - Highlights: • We propose a TOU based demand response approach for manufacturing systems. • Both electricity consumption and demand are integrated into the system modeling. • Energy-efficient and demand-responsive production scheduling problems are formulated. • The meta-heuristic solution technique is provided. • The effects of various factors on the scheduling solutions are examined

Plug-in Hybrid Electric Vehicles in the Smart Grid Environment: An Economic Model of Load Management by Demand Response

Directory of Open Access Journals (Sweden)

Poudineh R.

2012-10-01

Full Text Available Environmental concern regarding the consumption of fossil fuels is among the most serious challenges facing the world. As a result, utilisation of more renewable resources and promotion of a clean transport system such as the use of Plug in Hybrid Electric Vehicles (PHEVs became the forefront of the new energy policies. However, the breakthrough of PHEVs in the automotive fleet increases concerns around the stability of power system and in particular, the power network. This research simulates the aggregate load profile of the UK with presence of PHEVs based upon different price scenarios. The results show that under the fixed rate and time of use programmes in the current grid, the extra load of the electric vehicles intensifies the consumption profile and also creates new critical points. Thus, there should always be excess standby capacity to satisfy peak demand even for a short period of time. On the other hand, when the consumers do not pay the price based on the actual cost of supply, those who consume less in peak hours subsidise the ones who consume more and this cross subsidy raises a regulatory issue. On the contrary, a smart grid can accommodate PHEVs without creating technical and regulatory problems. This positive consequence is the result of demand response to the real time pricing. From a technical point of view, the biggest chunk of PHEVs' load will be shifted to the late evening and the hours of minimum demand. Besides, from a welfare analysis standpoint, real time pricing creates no deadweight losses and corresponding demand response will limit the ability of suppliers to increase the spot market clearing price above its equilibrium level.

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.

Micro-generation dispatch in a smart residential multi-carrier energy system considering demand forecast error

International Nuclear Information System (INIS)

Sanjari, M.J.; Karami, H.; Gooi, H.B.

2016-01-01

Highlights: • Combination of day-ahead and hour-ahead optimizations to design online controller. • Investigating the effect of load forecast error on the system operating cost. • Proposing effective method for hour-ahead resource re-dispatch. • Using the HSS algorithm as a powerful and effective optimization method. • Combining long-term and short-term strategies for optimal dispatch of resources. - Abstract: This paper deals with a residential hybrid thermal/electrical grid-connected home energy system incorporating real data for the load demand. A day-ahead scheduling (DAS) algorithm for dispatching different resources has been developed in previous studies to determine the optimal operation scheduling for the distributed energy resources at each time interval so that the operational cost of a smart house is minimized. However, demand of houses may be changed in each hour and cannot be exactly predicted one day ahead. System complexity caused by nonlinear dynamics of the fuel cell, as a combined heat and power device, and battery charging and discharging time make it difficult to find the optimal operating point of the system by using the optimization algorithms quickly in online applications. In this paper, the demand forecast error is studied and a near-optimal dispatch strategy by using artificial neural network (ANN) is proposed for the residential energy system when the demand changes are known one hour ahead with respect to the predicted day-ahead values. The day-ahead and hour-ahead optimizations are combined and ANN training inputs are adjusted according to the problem such that the economic dispatch of different energy resources can be achieved by the proposed method compared with previous studies. Using the model of the fuel cell extracted from experimental measurement and real data for the load demand makes the results more applicable in real residential energy systems.

Fuzzy Adaptive Particle Swarm Optimization for Power Loss Minimisation in Distribution Systems Using Optimal Load Response

DEFF Research Database (Denmark)

Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

2014-01-01

Consumers may decide to modify the profile of their demand from high price periods to low price periods in order to reduce their electricity costs. This optimal load response to electricity prices for demand side management generates different load profiles and provides an opportunity to achieve...... power loss minimization in distribution systems. In this paper, a new method to achieve power loss minimization in distribution systems by using a price signal to guide the demand side management is proposed. A fuzzy adaptive particle swarm optimization (FAPSO) is used as a tool for the power loss...

Optimal stochastic short-term thermal and electrical operation of fuel cell/photovoltaic/battery/grid hybrid energy system in the presence of demand response program

International Nuclear Information System (INIS)

Majidi, Majid; Nojavan, Sayyad; Zare, Kazem

2017-01-01

Highlights: • On-grid photovoltaic/battery/fuel cell system is considered as hybrid system. • Thermal and electrical operation of hybrid energy system is studied. • Hybrid energy system is used to reduce dependency on upstream grid for load serving. • Demand response program is proposed to manage the electrical load. • Demand response program is proposed to reduce hybrid energy system’s operation cost. - Abstract: In this paper, cost-efficient operation problem of photovoltaic/battery/fuel cell hybrid energy system has been evaluated in the presence of demand response program. Each load curve has off-peak, mid and peak time periods in which the energy prices are different. Demand response program transfers some amount of load from peak periods to other periods to flatten the load curve and minimize total cost. So, the main goal is to meet the energy demand and propose a cost-efficient approach to minimize system’s total cost including system’s electrical cost and thermal cost and the revenue from exporting power to the upstream grid. A battery has been utilized as an electrical energy storage system and a heat storage tank is used as a thermal energy storage system to save energy in off-peak and mid-peak hours and then supply load in peak hours which leads to reduction of cost. The proposed cost-efficient operation problem of photovoltaic/battery/fuel cell hybrid energy system is modeled by a mixed-integer linear program and solved by General algebraic modeling system optimization software under CPLEX solver. Two case studies are investigated to show the effects of demand response program on reduction of total cost.

Flexible demand in the GB domestic electricity sector in 2030

International Nuclear Information System (INIS)

Drysdale, Brian; Wu, Jianzhong; Jenkins, Nick

2015-01-01

Highlights: • Annual domestic demand by category and daily flexible load profiles are shown to 2030. • Valuable flexible demand requires loads to be identifiable, accessible, and useful. • The extent of flexible demand varies significantly on a diurnal and seasonal basis. • Barriers to accessing domestic demand include multiple low value loads and apathy. • Existing market structure a barrier to fully rewarding individual load flexibility. - Abstract: In order to meet greenhouse gas emissions targets the Great Britain (GB) future electricity supply will include a higher fraction of non-dispatchable generation, increasing opportunities for demand side management to maintain a supply/demand balance. This paper examines the extent of flexible domestic demand (FDD) in GB, its usefulness in system balancing and appropriate incentives to encourage consumers to participate. FDD, classified as electric space and water heating (ESWH), and cold and wet appliances, amounts to 59 TW h in 2012 (113 TW h total domestic demand) and is calculated to increase to 67 TW h in 2030. Summer and winter daily load profiles for flexible loads show significant seasonal and diurnal variations in the total flexible load and between load categories. Low levels of reflective consumer engagement with electricity consumption and a resistance to automation present barriers to effective access to FDD. A value of £1.97/household/year has been calculated for cold appliance loads used for frequency response in 2030, using 2013 market rates. The introduction of smart meters in GB by 2020 will allow access to FDD for system balancing. The low commercial value of individual domestic loads increases the attractiveness of non-financial incentives to fully exploit FDD. It was shown that appliance loads have different characteristics which can contribute to an efficient power system in different ways

Full scale investigation of the wind loads on a light-weight building-integrated photovoltaic system

NARCIS (Netherlands)

Geurts, C.P.W.; Bronkhorst, A.J.; Bentum, C.A. van

2017-01-01

The wind loads on solar energy systems are crucial for the engineering of the panels, substructure and fixings. There is a demand for aesthetically more acceptable solutions such as frameless solar systems. For these frameless systems, the wind loads are carried by the panels themselves. Combined

Simple models of district heating systems for load and demand side management and operational optimisation; Simple modeller for fjernvarmesystemer med henblik pae belastningsudjaevning og driftsoptimering

Energy Technology Data Exchange (ETDEWEB)

Boehm, B. [Technical Univ. of Denmark, Dept. of Mechanical Engineering, Kgs. Lyngby (Denmark); Larsen, H.V. [Risoe National Lab., System Analysis Dept., Roskilde (DK)

2004-12-01

The purpose of this research project has been to further develop and test simple (aggregated) models of district heating (DH) systems for simulation and operational optimization, and to investigate the influence of Load Management and Demand Side Management (DMS) on the total operational costs. The work is based on physical-mathematical modelling and simulation of DH systems, and is a continuation of previous EFP-96 work. In the present EFP-2001 project the goals have been to improve the Danish method of aggregation by addressing the problem of aggregation of pressure losses, and to test the methods on a much larger data set than in the EFP-1996 project. In order to verify the models it is crucial to have good data at disposal. Full information on the heat loads and temperatures not only at the DH plant but also at every consumer (building) is needed, and therefore only a few DH systems in Denmark can supply such data. (BA)

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

OpenAIRE

Cha, Hee-Jun; Won, Dong-Jun; Kim, Sang-Hyuk; Chung, Il-Yop; Han, Byung-Moon

2015-01-01

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...

Voltage Controlled Dynamic Demand Response

DEFF Research Database (Denmark)

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

2013-01-01

Future power system is expected to be characterized by increased penetration of intermittent sources. Random and rapid fluctuations in demands together with intermittency in generation impose new challenges for power balancing in the existing system. Conventional techniques of balancing by large...... 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...

Impact of Scheduling Flexibility on Demand Profile Flatness and User Inconvenience in Residential Smart Grid System

Directory of Open Access Journals (Sweden)

Naveed Ul Hassan

2013-12-01

Full Text Available The objective of this paper is to study the impact of scheduling flexibility on both demand profile flatness and user inconvenience in residential smart grid systems. Temporal variations in energy consumption by end users result in peaks and troughs in the aggregated demand profile. In a residential smart grid, some of these peaks and troughs can be eliminated through appropriate load balancing algorithms. However, load balancing requires user participation by allowing the grid to re-schedule some of their loads. In general, more scheduling flexibility can result in more demand profile flatness, however the resulting inconvenience to users would also increase. In this paper, our objective is to help the grid determine an appropriate amount of scheduling flexibility that it should demand from users, based on which, proper incentives can be designed. We consider three different types of scheduling flexibility (delay, advance scheduling and flexible re-scheduling in flexible loads and develop both optimal and sub-optimal scheduling algorithms. We discuss their implementation in centralized and distributed manners. We also identify the existence of a saturation point. Beyond this saturation point, any increase in scheduling flexibility does not significantly affect the flatness of the demand profile while user inconvenience continues to increase. Moreover, full participation of all the households is not required since increasing user participation only marginally increases demand profile flatness.

Load management potentials for the railway power system; Potenziale fuer das Lastmanagement im Bahnenergiesystem

Energy Technology Data Exchange (ETDEWEB)

Bosch, Julius; Aniceto, Josep M. [SBB AG Infrastruktur Energie, Zollikofen (Switzerland)

2013-02-15

The railway power supply system of the Schweizerische Bundesbahnen (SBB) is characterised by major load fluctuations that are expected to increase in the future. The available power that is generated must be kept at absolute load peak level which causes high costs. Simulations show that a load management is a practicable way of noticeably reducing load peaks in the SBB railway power supply system without having an adverse effect on railway operations or the energy demand.

Review of current Southern California edison load management programs and proposal for a new market-driven, mass-market, demand-response program

Energy Technology Data Exchange (ETDEWEB)

Weller, G.H.

2002-01-01

Utility load management programs, including direct load control and interruptible load programs, constitute a large installed base of controllable loads that are employed by utilities as system reliability resources. In response to energy supply shortfalls expected during the summer of 2001, the California Public Utilities Commission in spring 2001 authorized new utility load management programs as well as revisions to existing programs. This report provides an independent review of the designs of these new programs for a large utility (Southern California Edison) and suggests possible improvements to enhance the price responsiveness of the customer actions influenced by these programs. The report also proposes a new program to elicit a mass-market demand response to utility price signals.

A Closed-Loop Control Strategy for Air Conditioning Loads to Participate in Demand Response

Directory of Open Access Journals (Sweden)

Xiaoqing Hu

2015-08-01

Full Text Available Thermostatically controlled loads (TCLs, such as air conditioners (ACs, are important demand response resources—they have a certain heat storage capacity. A change in the operating status of an air conditioner in a small range will not noticeably affect the users’ comfort level. Load control of TCLs is considered to be equivalent to a power plant of the same capacity in effect, and it can significantly reduce the system pressure to peak load shift. The thermodynamic model of air conditioning can be used to study the aggregate power of a number of ACs that respond to the step signal of a temperature set point. This paper analyzes the influence of the parameters of each AC in the group to the indoor temperature and the total load, and derives a simplified control model based on the two order linear time invariant transfer function. Then, the stability of the model and designs its Proportional-Integral-Differential (PID controller based on the particle swarm optimization (PSO algorithm is also studied. The case study presented in this paper simulates both scenarios of constant ambient temperature and changing ambient temperature to verify the proposed transfer function model and control strategy can closely track the reference peak load shifting curves. The study also demonstrates minimal changes in the indoor temperature and the users’ comfort level.

A quantitative measure for degree of automation and its relation to system performance and mental load.

Science.gov (United States)

Wei, Z G; Macwan, A P; Wieringa, P A

1998-06-01

In this paper we quantitatively model degree of automation (DofA) in supervisory control as a function of the number and nature of tasks to be performed by the operator and automation. This model uses a task weighting scheme in which weighting factors are obtained from task demand load, task mental load, and task effect on system performance. The computation of DofA is demonstrated using an experimental system. Based on controlled experiments using operators, analyses of the task effect on system performance, the prediction and assessment of task demand load, and the prediction of mental load were performed. Each experiment had a different DofA. The effect of a change in DofA on system performance and mental load was investigated. It was found that system performance became less sensitive to changes in DofA at higher levels of DofA. The experimental data showed that when the operator controlled a partly automated system, perceived mental load could be predicted from the task mental load for each task component, as calculated by analyzing a situation in which all tasks were manually controlled. Actual or potential applications of this research include a methodology to balance and optimize the automation of complex industrial systems.

Load averaging system for co-generation plant; Jikayo hatsuden setsubi ni okeru fuka heijunka system

Energy Technology Data Exchange (ETDEWEB)

Ueno, Y. [Fuji Electric Co. Ltd., Tokyo (Japan)

1995-07-30

MAZDA Motor Corp. planed the construction of a 20.5MW co-generation plant in 1991 for responding to an increase in power demand due to expansion of the Hofu factory. On introduction of this co-generation plant, it was decided that the basic system would adopt the following. (1) A circulating fluidized bed boiler which can be operated by burning multiple kinds of fuels with minimum environmental pollution. (2) A heat accumulation system which can be operated through reception of a constant power from electric power company despite a sudden and wide range change in power demand. (3) A circulating-water exchange heat recovery system which recovers exhaust heat of the turbine plant as the hot water to be utilized for heating and air-conditioning of the factory mainly in winter. Power demand in MAZDA`s Hofu factory changes 15% per minute within a maximum range from 20MW to 8MW. This change is difficult to be followed even by an oil burning boiler excellent in load follow-up. The circulating Fluidized bed boiler employed this time is lower in the follow-up performance than the oil boiler. For the newly schemed plant, however, load averaging system named a heat accumulation system capable of responding fully to the above change has been developed. This co-generation plant satisfied the official inspection before commercial operation according the Ministerial Ordinance in 1993. Since then, with regard to the rapid load following, which was one of the initial targets, operation is now performed steadily. This paper introduces an outline of the system and operation conditions. 10 refs.

Demand side resource operation on the Irish power system with high wind power penetration

DEFF Research Database (Denmark)

Keane, A.; Tuohy, A.; Meibom, Peter

2011-01-01

part of the power system plant mix and contribute to the flexible operation of a power system. A model for demand side resources is proposed here that captures its key characteristics for commitment and dispatch calculations. The model is tested on the all island Irish power system, and the operation...... of the functions of conventional peaking plant. Demand side resources are also shown to be capable of improving the reliability of the system, with reserve capability identified as a key requirement in this respect....... of the model is simulated over one year in both a stochastic and deterministic mode, to illustrate the impact of wind and load uncertainty. The results illustrate that demand side resources can contribute to the efficient, flexible operation of systems with high penetrations of wind by replacing some...

Optimal control of a fuel cell/wind/PV/grid hybrid system with thermal heat pump load

CSIR Research Space (South Africa)

Sichilalu, S

2016-10-01

Full Text Available This paper presents an optimal energy management strategy for a grid-tied photovoltaic–wind-fuel cell hybrid power supply system. The hybrid system meets the load demand consisting of an electrical load and a heat pump water heater supplying thermal...

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).

Implementation and Assessment of a Decentralized Load Frequency Control: Application to Power Systems with High Wind Energy Penetration

Directory of Open Access Journals (Sweden)

Irene Muñoz-Benavente

2017-01-01

Full Text Available This paper describes and assesses a decentralized solution based on a wireless sensor-actuator network to provide primary frequency control from demand response in power systems with high wind energy penetration and, subsequently, with relevant frequency excursions. The proposed system is able to modify the electrical power demand of a variety of thermostatically-controlled loads, maintaining minimum comfort levels and minimizing both infrastructure requirements and primary reserves from the supply side. This low-cost hardware solution avoids any additional wiring, extending the wireless sensor-actuator network technology towards small customers, which account for over a 30% share of the current power demand. Frequency excursions are collected by each individual load controller, considering not only the magnitude of the frequency deviation, but also their evolution over time. Based on these time-frequency excursion characteristics, controllers are capable of modifying the power consumption of thermostatically-controlled loads by switching them off and on, thus contributing to primary frequency control in power systems with higher generation unit oscillations as a consequence of relevant wind power integration. Field tests have been carried out in a laboratory environment to assess the load controller performance, as well as to evaluate the electrical and thermal response of individual loads under frequency deviations. These frequency deviations are estimated from power systems with a high penetration of wind energy, which are more sensitive to frequency oscillations and where demand response can significantly contribute to mitigate these frequency excursions. The results, also included in the paper, evaluate the suitability of the proposed load controllers and their suitability to decrease frequency excursions from the demand side in a decentralized manner.

Power systems balancing with high penetration renewables: The potential of demand response in Hawaii

International Nuclear Information System (INIS)

Critz, D. Karl; Busche, Sarah; Connors, Stephen

2013-01-01

Highlights: • Demand response for Oahu results in system cost savings. • Demand response improves thermal power plant operations. • Increased use of wind generation possible with demand response. • WILMAR model used to simulate various levels and prices of demand response. - Abstract: The State of Hawaii’s Clean Energy policies call for 40% of the state’s electricity to be supplied by renewable sources by 2030. A recent study focusing on the island of Oahu showed that meeting large amounts of the island’s electricity needs with wind and solar introduced significant operational challenges, especially when renewable generation varies from forecasts. This paper focuses on the potential of demand response in balancing supply and demand on an hourly basis. Using the WILMAR model, various levels and prices of demand response were simulated. Results indicate that demand response has the potential to smooth overall power system operation, with production cost savings arising from both improved thermal power plant operations and increased wind production. Demand response program design and cost structure is then discussed drawing from industry experience in direct load control programs

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)

Managing Sustainable Demand-side Infrastructure for Power System Ancillary Services

Science.gov (United States)

Parkinson, Simon Christopher

Widespread access to renewable electricity is seen as a viable method to mitigate carbon emissions, although problematic are the issues associated with the integration of the generation systems within current power system configurations. Wind power plants are the primary large-scale renewable generation technology applied globally, but display considerable short-term supply variability that is difficult to predict. Power systems are currently not designed to operate under these conditions, and results in the need to increase operating reserve in order to guarantee stability. Often, operating conventional generation as reserve is both technically and economically inefficient, which can overshadow positive benefits associated with renewable energy exploitation. The purpose of this thesis is to introduce and assess an alternative method of enhancing power system operations through the control of electric loads. In particular, this thesis focuses on managing highly-distributed sustainable demand-side infrastructure, in the form of heat pumps, electric vehicles, and electrolyzers, as dispatchable short-term energy balancing resources. The main contribution of the thesis is an optimal control strategy capable of simultaneously balancing grid- and demand-side objectives. The viability of the load control strategy is assessed through model-based simulations that explicitly track end-use functionality of responsive devices within a power systems analysis typically implemented to observe the effects of integrated wind energy systems. Results indicate that there is great potential for the proposed method to displace the need for increased reserve capacity in systems considering a high penetration of wind energy, thereby allowing conventional generation to operate more efficiently and avoid the need for possible capacity expansions.

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.

Nodal price volatility reduction and reliability enhancement of restructured power systems considering demand-price elasticity

International Nuclear Information System (INIS)

Goel, L.; Wu, Qiuwei; Wang, Peng

2008-01-01

With the development of restructured power systems, the conventional 'same for all customers' electricity price is getting replaced by nodal prices. Electricity prices will fluctuate with time and nodes. In restructured power systems, electricity demands will interact mutually with prices. Customers may shift some of their electricity consumption from time slots of high electricity prices to those of low electricity prices if there is a commensurate price incentive. The demand side load shift will influence nodal prices in return. This interaction between demand and price can be depicted using demand-price elasticity. This paper proposes an evaluation technique incorporating the impact of the demand-price elasticity on nodal prices, system reliability and nodal reliabilities of restructured power systems. In this technique, demand and price correlations are represented using the demand-price elasticity matrix which consists of self/cross-elasticity coefficients. Nodal prices are determined using optimal power flow (OPF). The OPF and customer damage functions (CDFs) are combined in the proposed reliability evaluation technique to assess the reliability enhancement of restructured power systems considering demand-price elasticity. The IEEE reliability test system (RTS) is simulated to illustrate the developed techniques. The simulation results show that demand-price elasticity reduces the nodal price volatility and improves both the system reliability and nodal reliabilities of restructured power systems. Demand-price elasticity can therefore be utilized as a possible efficient tool to reduce price volatility and to enhance the reliability of restructured power systems. (author)

An effective Load shedding technique for micro-grids using artificial neural network and adaptive neuro-fuzzy inference system

Directory of Open Access Journals (Sweden)

Foday Conteh

2017-09-01

Full Text Available In recent years, the use of renewable energy sources in micro-grids has become an effectivemeans of power decentralization especially in remote areas where the extension of the main power gridis an impediment. Despite the huge deposit of natural resources in Africa, the continent still remains inenergy poverty. Majority of the African countries could not meet the electricity demand of their people.Therefore, the power system is prone to frequent black out as a result of either excess load to the systemor generation failure. The imbalance of power generation and load demand has been a major factor inmaintaining the stability of the power systems and is usually responsible for the under frequency andunder voltage in power systems. Currently, load shedding is the most widely used method to balancebetween load and demand in order to prevent the system from collapsing. But the conventional methodof under frequency or under voltage load shedding faces many challenges and may not perform asexpected. This may lead to over shedding or under shedding, causing system blackout or equipmentdamage. To prevent system cascade or equipment damage, appropriate amount of load must beintentionally and automatically curtailed during instability. In this paper, an effective load sheddingtechnique for micro-grids using artificial neural network and adaptive neuro-fuzzy inference system isproposed. The combined techniques take into account the actual system state and the exact amount ofload needs to be curtailed at a faster rate as compared to the conventional method. Also, this methodis able to carry out optimal load shedding for any input range other than the trained data. Simulationresults obtained from this work, corroborate the merit of this algorithm.

Impacts of Demand-Side Management on Electrical Power Systems: A Review

Directory of Open Access Journals (Sweden)

Hussein Jumma Jabir

2018-04-01

Full Text Available Electricity demand has grown over the past few years and will continue to grow in the future. The increase in electricity demand is mainly due to industrialization and the shift from a conventional to a smart-grid paradigm. The number of microgrids, renewable energy sources, plug-in electric vehicles and energy storage systems have also risen in recent years. As a result, future electricity grids have to be revamped and adapt to increasing load levels. Thus, new complications associated with future electrical power systems and technologies must be considered. Demand-side management (DSM programs offer promising solutions to these issues and can considerably improve the reliability and financial performances of electrical power systems. This paper presents a review of various initiatives, techniques, impacts and recent developments of the DSM of electrical power systems. The potential benefits derived by implementing DSM in electrical power networks are presented. An extensive literature survey on the impacts of DSM on the reliability of electrical power systems is also provided for the first time. The research gaps within the broad field of DSM are also identified to provide directions for future work.

Current status of and problems in ice heat storage systems contributing to improving load rates. Strengthening works intended for leveling the electric power load; Fukaritsu kaizen ni kokensuru kori chikunetsu system no genjo to kadai. Denryoku fuka heikinka ni muketa torikumi no kyoka

Energy Technology Data Exchange (ETDEWEB)

Yamada, T. [Agency of Natural Resources and Energy, Tokyo (Japan)

1998-02-01

This paper introduces improvement in annual load rate in power supply in Japan, and the measures to proliferate and expand the use of ice heat storage systems. The annual load rate in power supply has dropped to about 55% today from the level of about 70% in 1965. This has been caused by the following reasons: the maximum power demand having become sharper in summer due to rapid increase in demand for air conditioning for room cooling, increase in weight of business operation department associated with progress of service economy, and change in the industrial structure from the material type industry to the processing and assembling type industry in the industrial department. In order to achieve load shift in the room cooling demand, which accounts largely for consumer demand during the peak time in summer, and is the main cause for reduced load rate, it is important that a heat storage type air conditioning system and a gas room cooling system be used more widely. The heat storage air conditioning and gas room cooling systems have a bottleneck in their proliferation that their facility cost is more expensive than existing air conditioning systems of non-heat regeneration type. It is necessary to review legal institutions and electric power charge systems for the purpose of proliferation and expanded use of the heat regeneration air conditioning and gas room cooling systems. 2 figs.

Solar + Storage Synergies for Managing Commercial-Customer Demand Charges

Energy Technology Data Exchange (ETDEWEB)

Gagnon, P. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Govindarajan, A. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bird, L. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Barbose, G. L. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Darghouth, N. R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mills, A. D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2017-10-18

Demand charges, which are based on a customer’s maximum demand in kilowatts (kW), are a common element of electricity rate structures for commercial customers. Customer-sited solar photovoltaic (PV) systems can potentially reduce demand charges, but the level of savings is difficult to predict, given variations in demand charge designs, customer loads, and PV generation profiles. Lawrence Berkeley National Laboratory (Berkeley Lab) and the National Renewable Energy Laboratory (NREL) are collaborating on a series of studies to understand how solar PV can impact demand charges. Prior studies in the series examined demand charge reductions from solar on a stand-alone basis for residential and commercial customers. Those earlier analyses found that solar, alone, has limited ability to reduce demand charges depending on the specific design of the demand charge and on the shape of the customer’s load profile. This latest analysis estimates demand charge savings from solar in commercial buildings when co-deployed with behind-the-meter storage, highlighting the complementary roles of the two technologies. The analysis is based on simulated loads, solar generation, and storage dispatch across a wide variety of building types, locations, system configurations, and demand charge designs.

Demand response from the non-domestic sector: Early UK experiences and future opportunities

International Nuclear Information System (INIS)

Grünewald, Philipp; Torriti, Jacopo

2013-01-01

Demand response is believed by some to become a major contributor towards system balancing in future electricity networks. Shifting or reducing demand at critical moments can reduce the need for generation capacity, help with the integration of renewables, support more efficient system operation and thereby potentially lead to cost and carbon reductions for the entire energy system. In this paper we review the nature of the response resource of consumers from different non-domestic sectors in the UK, based on extensive half hourly demand profiles and observed demand responses. We further explore the potential to increase the demand response capacity through changes in the regulatory and market environment. The analysis suggests that present demand response measures tend to stimulate stand-by generation capacity in preference to load shifting and we propose that extended response times may favour load based demand response, especially in sectors with significant thermal loads. - Highlights: • Empirical demand response data from non-domestic sector evaluated. • Load profiles suggest strong sector dependence on availability response at system peak. • Majority of aggregated demand response still stems from stand-by generation, not from demand turn down. • Scope for substantial increase in demand response capacity if response times were extended

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.

Study of a conceptual nuclear energy center at Green River, Utah. Power demand, load center assessment and transmission

Energy Technology Data Exchange (ETDEWEB)

Smith, D.R.; Thaik, A.; Pingel, P.

1982-02-01

This document constitutes a segment of a feasibility study investigating the ramification of constructing a nuclear energy center in an arid western region. In this phase of the study. The projected power demands and load center locations were reviewed and assessed. Alternative transmission systems were analysed and a conceptual transmission for bulk power transportation is proposed with potential line routes. Environmental impacts of the proposed transmission were also identified.

Study of a conceptual nuclear energy center at Green River, Utah. Power demand, load center assessment and transmission

International Nuclear Information System (INIS)

Smith, D.R.; Thaik, A.; Pingel, P.

1982-02-01

This document constitutes a segment of a feasibility study investigating the ramification of constructing a nuclear energy center in an arid western region. In this phase of the study. The projected power demands and load center locations were reviewed and assessed. Alternative transmission systems were analysed and a conceptual transmission for bulk power transportation is proposed with potential line routes. Environmental impacts of the proposed transmission were also identified

Load control services in the management of power system security costs

International Nuclear Information System (INIS)

Jayantilal, A.; Strbac, G.

1999-01-01

The new climate of deregulation in the electricity industry is creating a need for a more transparent cost structure and within this framework the cost of system security has been a subject of considerable interest. Traditionally power system security has been supplied by out-of-merit generation, in the short term, and transmission reinforcement, in the long term. This paper presents a method of analysing the role of load-demand in the management of power system security costs by utilising load control services (LCS). It also proposes a competitive market to enable bidding from various participants within the electricity industry to supply system security. (author)

Online AMR Domestic Load Profile Characteristic Change Monitor to Support Ancillary Demand Services

DEFF Research Database (Denmark)

Stephen, Bruce; Isleifsson, Fridrik Rafn; Galloway, Stuart

2014-01-01

of small loads is presented. This would allow them to be assessed for their availability to provide demand services to the grid. In the method presented, significant changes in behavior are detected using Bayesian changepoint analysis which tracks a multivariate Gaussian representation of a residential...... in remote rural communities, are currently modeled with homogenous and coarse load profiles developed from aggregated data. An objective of AMR deployment is to clarify the nature and variability of the residential LV customer. In this paper, an algorithm for tracking the consistency of the behavior...

Modeling of demand response in electricity markets : effects of price elasticity

International Nuclear Information System (INIS)

Banda, E.C.; Tuan, L.A.

2007-01-01

A design mechanism for the optimal participation of customer load in electricity markets was presented. In particular, this paper presented a modified market model for the optimal procurement of interruptible loads participating in day-ahead electricity markets. The proposed model considers the effect of price elasticity and demand-response functions. The objective was to determine the role that price elasticity plays in electricity markets. The simulation model can help the Independent System Operator (ISO) identify customers offering the lowest price of interruptible loads and load flow patterns that avoid problems associated with transmission congestion and transmission losses. Various issues associated with procurement of demand-response offerings such as advance notification, locational aspect of load, and power factor of the loads, were considered. It was shown that demand response can mitigate price volatility by allowing the ISO to maintain operating reserves during peak load periods. It was noted that the potential benefits of the demand response program would be reduced when price elasticity of demand is taken into account. This would most likely occur in actual developed open electricity markets, such as Nordpool. This study was based on the CIGRE 32-bus system, which represents the Swedish high voltage power system. It was modified for this study to include a broad range of customer characteristics. 18 refs., 2 tabs., 14 figs

Demand side resource operation on the Irish power system with high wind power penetration

International Nuclear Information System (INIS)

Keane, A.; Tuohy, A.; Meibom, P.; Denny, E.; Flynn, D.; Mullane, A.; O'Malley, M.

2011-01-01

The utilisation of demand side resources is set to increase over the coming years with the advent of advanced metering infrastructure, home area networks and the promotion of increased energy efficiency. Demand side resources are proposed as an energy resource that, through aggregation, can form part of the power system plant mix and contribute to the flexible operation of a power system. A model for demand side resources is proposed here that captures its key characteristics for commitment and dispatch calculations. The model is tested on the all island Irish power system, and the operation of the model is simulated over one year in both a stochastic and deterministic mode, to illustrate the impact of wind and load uncertainty. The results illustrate that demand side resources can contribute to the efficient, flexible operation of systems with high penetrations of wind by replacing some of the functions of conventional peaking plant. Demand side resources are also shown to be capable of improving the reliability of the system, with reserve capability identified as a key requirement in this respect. - Highlights: → Demand side resource model presented for use in unit commitment and dispatch calculations. → Benefits of demand side aggregation demonstrated specifically as a peaking unit and provider of reserve. → Potential to displace or defer construction of conventional peaking units.

Security Policies for Mitigating the Risk of Load Altering Attacks on Smart Grid Systems

Energy Technology Data Exchange (ETDEWEB)

Ryutov, Tatyana; AlMajali, Anas; Neuman, Clifford

2015-04-01

While demand response programs implement energy efficiency and power quality objectives, they bring potential security threats to the Smart Grid. The ability to influence load in a system enables attackers to cause system failures and impacts the quality and integrity of power delivered to customers. This paper presents a security mechanism to monitor and control load according to a set of security policies during normal system operation. The mechanism monitors, detects, and responds to load altering attacks. We examined the security requirements of Smart Grid stakeholders and constructed a set of load control policies enforced by the mechanism. We implemented a proof of concept prototype and tested it using the simulation environment. By enforcing the proposed policies in this prototype, the system is maintained in a safe state in the presence of load drop attacks.

Flexible Transmission Network Expansion Planning Considering Uncertain Renewable Generation and Load Demand Based on Hybrid Clustering Analysis

Directory of Open Access Journals (Sweden)

Yun-Hao Li

2015-12-01

Full Text Available This paper presents a flexible transmission network expansion planning (TNEP approach considering uncertainty. A novel hybrid clustering technique, which integrates the graph partitioning method and rough fuzzy clustering, is proposed to cope with uncertain renewable generation and load demand. The proposed clustering method is capable of recognizing the actual cluster distribution of complex datasets and providing high-quality clustering results. By clustering the hourly data for renewable generation and load demand, a multi-scenario model is proposed to consider the corresponding uncertainties in TNEP. Furthermore, due to the peak distribution characteristics of renewable generation and heavy investment in transmission, the traditional TNEP, which caters to rated renewable power output, is usually uneconomic. To improve the economic efficiency, the multi-objective optimization is incorporated into the multi-scenario TNEP model, while the curtailment of renewable generation is considered as one of the optimization objectives. The solution framework applies a modified NSGA-II algorithm to obtain a set of Pareto optimal planning schemes with different levels of investment costs and renewable generation curtailments. Numerical results on the IEEE RTS-24 system demonstrated the robustness and effectiveness of the proposed approach.

Impact of plug-in hybrid electric vehicles on power systems with demand response and wind power

International Nuclear Information System (INIS)

Wang Jianhui; Liu Cong; Ton, Dan; Zhou Yan; Kim, Jinho; Vyas, Anantray

2011-01-01

This paper uses a new unit commitment model which can simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). Four PHEV charging scenarios are simulated for the Illinois power system: (1) unconstrained charging, (2) 3-hour delayed constrained charging, (3) smart charging, and (4) smart charging with DR. The PHEV charging is assumed to be optimally controlled by the system operator in the latter two scenarios, along with load shifting and shaving enabled by DR programs. The simulation results show that optimally dispatching the PHEV charging load can significantly reduce the total operating cost of the system. With DR programs in place, the operating cost can be further reduced. - Research highlights: → A unit commitment model is used to simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). → Different PHEV charging scenarios are simulated on the Illinois power system → Load shifting and shaving enabled by DR programs are also modeled. → The simulation results show that the operating cost can be reduced with DR and optimal PHEV charging.

Design And Modeling An Automated Digsilent Power System For Optimal New Load Locations

Directory of Open Access Journals (Sweden)

Mohamed Saad

2015-08-01

Full Text Available Abstract The electric power utilities seek to take advantage of novel approaches to meet growing energy demand. Utilities are under pressure to evolve their classical topologies to increase the usage of distributed generation. Currently the electrical power engineers in many regions of the world are implementing manual methods to measure power consumption for farther assessment of voltage violation. Such process proved to be time consuming costly and inaccurate. Also demand response is a grid management technique where retail or wholesale customers are requested either electronically or manually to reduce their load. Therefore this paper aims to design and model an automated power system for optimal new load locations using DPL DIgSILENT Programming Language. This study is a diagnostic approach that assists system operator about any voltage violation cases that would happen during adding new load to the grid. The process of identifying the optimal bus bar location involves a complicated calculation of the power consumptions at each load bus As a result the DPL program would consider all the IEEE 30 bus internal networks data then a load flow simulation will be executed. To add the new load to the first bus in the network. Therefore the developed model will simulate the new load at each available bus bar in the network and generate three analytical reports for each case that captures the overunder voltage and the loading elements among the grid.

Comparison of Deterministic and Probabilistic Radial Distribution Systems Load Flow

Science.gov (United States)

Gupta, Atma Ram; Kumar, Ashwani

2017-12-01

Distribution system network today is facing the challenge of meeting increased load demands from the industrial, commercial and residential sectors. The pattern of load is highly dependent on consumer behavior and temporal factors such as season of the year, day of the week or time of the day. For deterministic radial distribution load flow studies load is taken as constant. But, load varies continually with a high degree of uncertainty. So, there is a need to model probable realistic load. Monte-Carlo Simulation is used to model the probable realistic load by generating random values of active and reactive power load from the mean and standard deviation of the load and for solving a Deterministic Radial Load Flow with these values. The probabilistic solution is reconstructed from deterministic data obtained for each simulation. The main contribution of the work is: Finding impact of probable realistic ZIP load modeling on balanced radial distribution load flow. Finding impact of probable realistic ZIP load modeling on unbalanced radial distribution load flow. Compare the voltage profile and losses with probable realistic ZIP load modeling for balanced and unbalanced radial distribution load flow.

System behaviour modelling for demand response provision in a smart grid

International Nuclear Information System (INIS)

Dave, Saraansh; Sooriyabandara, Mahesh; Yearworth, Mike

2013-01-01

While pilot projects in the smart grid domain have abounded through public and private efforts, there is still uncertainty in identifying effective business models for the smart grid. In this paper we take the view of a new entrant in this market acting as a third party provider of demand response. New entrants are a key player in emerging technological domains but simulation and policy analysis from this perspective have not been forthcoming. We present a novel approach for evaluating business models within a regulatory context and avoid committing to specific technical solutions but instead embark on a parameter exploration through simple yet insightful agent-based models. Our simulations analyse the impact of system performance by three key variables; participant population size, household flexibility in terms of the maximum number of DR events allowed and size of load shifting/shedding available. The simulations indicate that benefits of avoided capital investment leads to valuing a participating household at approximately £1800 over a 20 year period. These results show how mandated infrastructure influenced by policy can affect the value proposition of a demand response service and provide a useful reference for system level parameter requirements. With weak business models, policy decisions can be crucial in providing the impetus needed to spur growth in this market. - Author-Highlights: • We model a demand response (DR) system to analyse interdependence of parameters. • Parameters analysed are number and flexibility of households and size of load shedding. • Challenges in providing a reliable DR service are explored. • A novel approach to evaluate business models for a DR service provider is presented. • The approach simultaneously evaluates business models in a regulatory context

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.

A load predictive energy management system for supercapacitor-battery hybrid energy storage system in solar application using the Support Vector Machine

International Nuclear Information System (INIS)

Chia, Yen Yee; Lee, Lam Hong; Shafiabady, Niusha; Isa, Dino

2015-01-01

Highlights: • A novel energy management system (EMS) for supercapacitor-battery hybrid energy storage system is implemented. • It is a load predictive EMS which is implemented using Support Vector Machine (SVM). • An optimum SVM load prediction model is obtained, which yields 100% accuracy in 0.004866 s of training time. • The implemented load predictive EMS is compared with the conventional sequential programming control. • This methodology reduces the number of power electronics used and prolong battery lifespan. - Abstract: This paper presents the use of a Support Vector Machine load predictive energy management system to control the energy flow between a solar energy source, a supercapacitor-battery hybrid energy storage combination and the load. The supercapacitor-battery hybrid energy storage system is deployed in a solar energy system to improve the reliability of delivered power. The combination of batteries and supercapacitors makes use of complementary characteristic that allow the overlapping of a battery’s high energy density with a supercapacitors’ high power density. This hybrid system produces a straightforward benefit over either individual system, by taking advantage of each characteristic. When the supercapacitor caters for the instantaneous peak power which prolongs the battery lifespan, it also minimizes the system cost and ensures a greener system by reducing the number of batteries. The resulting performance is highly dependent on the energy controls implemented in the system to exploit the strengths of the energy storage devices and minimize its weaknesses. It is crucial to use energy from the supercapacitor and therefore minimize jeopardizing the power system reliability especially when there is a sudden peak power demand. This study has been divided into two stages. The first stage is to obtain the optimum SVM load prediction model, and the second stage carries out the performance comparison of the proposed SVM-load predictive

Optimal Sizing of Hybrid Renewable Energy Systems: An Application for Real Demand in Qatar Remote Area

Science.gov (United States)

Alyafei, Nora

Renewable energy (RE) sources are becoming popular for power generations due to advances in renewable energy technologies and their ability to reduce the problem of global warming. However, their supply varies in availability (as sun and wind) and the required load demand fluctuates. Thus, to overcome the uncertainty issues of RE power sources, they can be combined with storage devices and conventional energy sources in a Hybrid Power Systems (HPS) to satisfy the demand load at any time. Recently, RE systems received high interest to take advantage of their positive benefits such as renewable availability and CO2 emissions reductions. The optimal design of a hybrid renewable energy system is mostly defined by economic criteria, but there are also technical and environmental criteria to be considered to improve decision making. In this study three main renewable sources of the system: photovoltaic arrays (PV), wind turbine generators (WG) and waste boilers (WB) are integrated with diesel generators and batteries to design a hybrid system that supplies the required demand of a remote area in Qatar using heuristic approach. The method utilizes typical year data to calculate hourly output power of PV, WG and WB throughout the year. Then, different combinations of renewable energy sources with battery storage are proposed to match hourly demand during the year. The design which satisfies the desired level of loss of power supply, CO 2 emissions and minimum costs is considered as best design.

User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jin, Xin [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Baker, Kyri A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Christensen, Dane T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Isley, Steven C. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-21

This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

Data-Driven Predictive Direct Load Control of Refrigeration Systems

DEFF Research Database (Denmark)

Shafiei, Seyed Ehsan; Knudsen, Torben; Wisniewski, Rafal

2015-01-01

A predictive control using subspace identification is applied for the smart grid integration of refrigeration systems under a direct load control scheme. A realistic demand response scenario based on regulation of the electrical power consumption is considered. A receding horizon optimal control...... is proposed to fulfil two important objectives: to secure high coefficient of performance and to participate in power consumption management. Moreover, a new method for design of input signals for system identification is put forward. The control method is fully data driven without an explicit use of model...... against real data. The performance improvement results in a 22% reduction in the energy consumption. A comparative simulation is accomplished showing the superiority of the method over the existing approaches in terms of the load following performance....

Heat demand profiles of energy conservation measures in buildings and their impact on a district heating system

International Nuclear Information System (INIS)

Lundström, Lukas; Wallin, Fredrik

2016-01-01

Highlights: • Energy savings impact on an low CO 2 emitting district heating system. • Heat profiles of eight building energy conservation measures. • Exhaust air heat pump, heat recovery ventilation, electricity savings etc. • Heat load weather normalisation with segmented multivariable linear regression. - Abstract: This study highlights the forthcoming problem with diminishing environmental benefits from heat demand reducing energy conservation measures (ECM) of buildings within district heating systems (DHS), as the supply side is becoming “greener” and more primary energy efficient. In this study heat demand profiles and annual electricity-to-heat factors of ECMs in buildings are computed and their impact on system efficiency and greenhouse gas emissions of a Swedish biomass fuelled and combined heat and power utilising DHS are assessed. A weather normalising method for the DHS heat load is developed, combining segmented multivariable linear regressions with typical meteorological year weather data to enable the DHS model and the buildings model to work under the same weather conditions. Improving the buildings’ envelope insulation level and thereby levelling out the DHS heat load curve reduces greenhouse gas emissions and improves primary energy efficiency. Reducing household electricity use proves to be highly beneficial, partly because it increases heat demand, allowing for more cogeneration of electricity. However the other ECMs considered may cause increased greenhouse gas emissions, mainly because of their adverse impact on the cogeneration of electricity. If biomass fuels are considered as residuals, and thus assigned low primary energy factors, primary energy efficiency decreases when implementing ECMs that lower heat demand.

A stochastic method for battery sizing with uninterruptible-power and demand shift capabilities in PV (photovoltaic) systems

International Nuclear Information System (INIS)

Tan, Chee Wei; Green, Tim C.; Hernandez-Aramburo, Carlos A.

2010-01-01

This paper presents a stochastic simulation using Monte Carlo technique to size a battery to meet dual objectives of demand shift at peak electricity cost times and outage protection in BIPV (building integrated photovoltaic) systems. Both functions require battery storage and the sizing of battery using numerical optimization is popularly used. However, the weather conditions, outage events and demand peaks are not deterministic in nature. Therefore, the sizing of battery storage capacity should also be based on a probabilistic approach. The Monte Carlo simulation is a rigorous method to sizing BIPV system as it takes into account a real building load profiles, the weather information and the local historical outage distribution. The simulation is split into seasonal basis for the analysis of demand shifting and outage events in order to match the seasonal weather conditions and load profiles. Five configurations of PV (photovoltaic) are assessed that cover different areas and orientations. The simulation output includes the predicted PV energy yield, the amount of energy required for demand management and outage event. Therefore, consumers can base sizing decisions on the historical data and local risk of outage statistics and the success rate of meeting the demand shift required. Finally, the economic evaluations together with the sensitivity analysis and the assessment of customers' outage cost are discussed.

Demand side management in South Africa at industrial residence water heating systems using in line water heating methodology

International Nuclear Information System (INIS)

Rankin, R.; Rousseau, P.G.

2008-01-01

The South African electrical utility, ESKOM, currently focuses its demand side management (DSM) initiatives on controlling electrical load between 18:00 and 20:00 each day, which is the utility's peak demand period. Funding is provided to energy service companies (ESCo's) to implement projects that can achieve load shifting out of this period. This paper describes how an improved in line water heating concept developed in previous studies was implemented into several real life industrial sanitary water heating systems to obtain the DSM load shift required by ESKOM. Measurements from a selection of these plants are provided to illustrate the significant load reductions that are being achieved during 18:00-20:00. The measured results also show that the peak load reduction is achieved without adversely affecting the availability of sufficient hot water to the persons using the showering and washing facilities served by the water heating system. A very good correlation also exists between these measured results and simulations that were done beforehand to predict the DSM potential of the project. The in line water heater concept provides an improved solution for DSM at sanitary water heating systems due to the stratified manner in which hot water is supplied to the tanks. This provides an improved hot water supply to users when compared to conventional in tank heating systems, even with load shifting being done. It also improves the storage efficiency of a plant, thereby allowing the available storage capacity of a plant to be utilized to its full extent for load shifting purposes

Demand differentiation in inventory systems

NARCIS (Netherlands)

Kleijn, M.J.

1998-01-01

This book deals with inventory systems where customer demand is categorised into different classes. Most inventory systems do not take into account individual customer preferences for a given product, and therefore handle all demand in a similar way. Nowadays, market segmentation has become a

A New Strategy for Short-Term Load Forecasting

Directory of Open Access Journals (Sweden)

Yi Yang

2013-01-01

Full Text Available Electricity is a special energy which is hard to store, so the electricity demand forecasting remains an important problem. Accurate short-term load forecasting (STLF plays a vital role in power systems because it is the essential part of power system planning and operation, and it is also fundamental in many applications. Considering that an individual forecasting model usually cannot work very well for STLF, a hybrid model based on the seasonal ARIMA model and BP neural network is presented in this paper to improve the forecasting accuracy. Firstly the seasonal ARIMA model is adopted to forecast the electric load demand day ahead; then, by using the residual load demand series obtained in this forecasting process as the original series, the follow-up residual series is forecasted by BP neural network; finally, by summing up the forecasted residual series and the forecasted load demand series got by seasonal ARIMA model, the final load demand forecasting series is obtained. Case studies show that the new strategy is quite useful to improve the accuracy of STLF.

Development of a web-based remote load supervision and control system

Energy Technology Data Exchange (ETDEWEB)

Chang, Wei-Fu; Wu, Yu-Chi; Chiu, Chui-Wen [National United University, Miao-Li (Taiwan). Department of Electrical Engineering

2006-07-15

The ability to remotely acquire information and even to control appliances/devices at fingertips over the Internet is becoming desirable to the general public as well as professionals. In this paper, a web-based remote electric load supervision and control (WBRELSAC) system with automatic meter reading and demand control via programmable logic controllers (PLCs) is presented. For both utilities and industrial/commercial customers, the electric load supervision and control (ELSAC) system is a critical function to their load management. However, most high voltage customers do not have enough capital to build a regular-scale supervisory control and data acquisition system as the one for utilities. Therefore, we adopt the industrial-widely-used PLCs in WBRELSAC. In order to make a non-web-based PLC become web-controllable, we develop a graphical-control interface and utilize Internet techniques to implement our system. Based on the performance test conducted under the Laboratory environment, the proposed WBRELSAC architecture is cost-effective and suitable for industrial applications. (author)

Stochastic risk-constrained short-term scheduling of industrial cogeneration systems in the presence of demand response programs

International Nuclear Information System (INIS)

Alipour, Manijeh; Mohammadi-Ivatloo, Behnam; Zare, Kazem

2014-01-01

Highlights: • Short-term self-scheduling problem of customers with CHP units is conducted. • Power demand and pool prices are forecasted using ARIMA models. • Risk management problem is conducted by implementing CVaR methodology. • The demand response program is implemented in self-scheduling problem of CHP units. • Non-convex feasible operation region in different types of CHP units is modeled. - Abstract: This paper presents a stochastic programming framework for solving the scheduling problem faced by an industrial customer with cogeneration facilities, conventional power production system, and heat only units. The power and heat demands of the customer are supplied considering demand response (DR) programs. In the proposed DR program, the responsive load can vary in different time intervals. In the paper, the heat-power dual dependency characteristic in different types of CHP units is taken into account. In addition, a heat buffer tank, with the ability of heat storage, has been incorporated in the proposed framework. The impact of the market and load uncertainties on the scheduling problem is characterized through a stochastic programming formulation. Autoregressive integrated moving average (ARIMA) technique is used to generate the electricity price and the customer demand scenarios. The daily and weekly seasonalities of demand and market prices are taken into account in the scenario generation procedure. The conditional value-at-risk (CVaR) methodology is implemented in order to limit the risk of expected profit due to market price and load forecast volatilities

Multiobjective CVaR Optimization Model and Solving Method for Hydrothermal System Considering Uncertain Load Demand

Directory of Open Access Journals (Sweden)

Zhongfu Tan

2015-01-01

Full Text Available In order to solve the influence of load uncertainty on hydrothermal power system operation and achieve the optimal objectives of system power generation consumption, pollutant emissions, and first-stage hydropower station storage capacity, this paper introduced CVaR method and built a multiobjective optimization model and its solving method. In the optimization model, load demand’s actual values and deviation values are regarded as random variables, scheduling objective is redefined to meet confidence level requirement and system operation constraints and loss function constraints are taken into consideration. To solve the proposed model, this paper linearized nonlinear constraints, applied fuzzy satisfaction, fuzzy entropy, and weighted multiobjective function theories to build a fuzzy entropy multiobjective CVaR model. The model is a mixed integer linear programming problem. Then, six thermal power plants and three cascade hydropower stations are taken as the hydrothermal system for numerical simulation. The results verified that multiobjective CVaR method is applicable to solve hydrothermal scheduling problems. It can better reflect risk level of the scheduling result. The fuzzy entropy satisfaction degree solving algorithm can simplify solving difficulty and get the optimum operation scheduling scheme.

Effects of demand elasticity and price variation on load profile

NARCIS (Netherlands)

Maqbool, S.D.; Babar, M.; Al-Ammar, E.A.

2011-01-01

Optimizing the operation of power generation systems is one of the core objectives of Smart Grid. The area of Smart Grid focuses on this issue is Demand Response (DR). DR is an essential tool to limit the demand to flatten spikes. This can reduce the need of peak power generation units which

Demand for power in Calcutta Electricity Supply Corporation area

Energy Technology Data Exchange (ETDEWEB)

Banerjee, N

1980-07-01

Since the early 1970's there has been a continuous crisis of power supply to the Calcutta industrial region. Historical records show that only the peak demand has grown and has a potential for growth, which, with an unchanging base demand, results in a low load factor and consequently inefficient power system operation. Attempts to shift industrial loads by operating industrial plants during non-peak hours are described. Adverse economic conditions eliminated the need for extra working shifts. It is concluded that the power system supplying the Calcutta region has an insufficient peak load generating capacity and an uneconomic load curve and that stricter hourly schedules for power use by industries should be adhered to in order to minimize these problems. (LCL)

Aggregate modeling of fast-acting demand response and control under real-time pricing

International Nuclear Information System (INIS)

Chassin, David P.; Rondeau, Daniel

2016-01-01

Highlights: • Demand elasticity for fast-acting demand response load under real-time pricing. • Validated first-principles logistic demand curve matches random utility model. • Logistic demand curve suitable for diversified aggregate loads market-based transactive control systems. - Abstract: This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop a more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.

Assessment of demand-response-driven load pattern elasticity using a combined approach for smart households

NARCIS (Netherlands)

Paterakis, N.G.; Tascikaraoglu, A.; Erdinç, O.; Bakirtzis, A.G.; Catalaõ, J.P.S.

2016-01-01

The recent interest in the smart grid vision and the technological advancement in the communication and control infrastructure enable several smart applications at different levels of the power grid structure, while specific importance is given to the demand side. As a result, changes in load

The integration of Price Responsive Demand into Regional Transmission Organization (RTO) wholesale power markets and system operations

International Nuclear Information System (INIS)

Centolella, Paul

2010-01-01

A number of states and utilities are pursuing demand response based on dynamic and time-differentiated retail prices and utility investments in Advanced Metering Infrastructure (AMI), often as part of Smart Grid initiatives. These developments could produce large amounts of Price Responsive Demand, demand that predictably responds to changes in wholesale prices. Price Responsive Demand could provide significant reliability and economic benefits. However, existing RTO tariffs present potential barriers to the development of Price Responsive Demand. Effectively integrating Price Responsive Demand into RTO markets and operations will require changes in demand forecasting, scarcity pricing reform, synchronization of scarcity pricing with capacity markets, tracking voluntary hedging by price responsive loads, and a non-discriminatory approach in curtailments in capacity emergencies. The article describes changes in RTO policies and systems needed incorporate Price Responsive Demand. (author)

An Economic Evalution of Demand-side Energy Storage Systems by using a Multi-agent based Electricity Market

Science.gov (United States)

Furusawa, Ken; Sugihara, Hideharu; Tsuji, Kiichiro

Opened wholesale electric power market in April 2005, deregulation of electric power industry in Japan has faced a new competitive environment. In the new environment, Independent Power Producer (: IPP), Power Producer and Supplier (: PPS), Load Service Entity (: LSE) and electric utility can trade electric energy through both bilateral contracts and single-price auction at the electricity market. In general, the market clearing price (: MCP) is largely changed by amount of total load demand in the market. The influence may cause price spike, and consequently the volatility of MCP will make LSEs and their customers to face a risk of revenue and cost. DSM is attracted as a means of load leveling, and has effect on decreasing MCP at peak load period. Introducing Energy Storage systems (: ES) is one of DSM in order to change demand profile at customer-side. In case that customers decrease their own demand at jumped MCP, a bidding strategy of generating companies may be changed their strategy. As a result, MCP is changed through such complex mechanism. In this paper the authors evaluate MCP by multi-agent. It is considered that customer-side ES has an effect on MCP fluctuation. Through numerical examples, this paper evaluates the influence on MCP by controlling customer-side ES corresponding to variation of MCP.

Impact of thermostatically controlled loads' demand response activation on aggregated power: A field experiment

DEFF Research Database (Denmark)

Lakshmanan, Venkatachalam; Marinelli, Mattia; Kosek, Anna Magdalena

2015-01-01

activation. The outcome of this experimental study quantifies the actual flexibility of household TCLs and the consequence for the different parties with respect to power behaviour. Each DR activation method adopts different scenarios to meet the power reduction, and has different impacts on the parameters......This paper describes the impacts of different types of DR (demand response) activation on TCLs' (thermostatically controlled loads) aggregated power. The different parties: power system operators, DR service providers (or aggregators) and consumers, have different objectives in relation to DR....... The experiments are conducted with real domestic refrigerators representing TCL. Activating refrigerators for DR with a delay reduces the ISE (integral square error) in power limitation by 28.46%, overshoot by 7.69%. The delay in refrigerator activation causes reduction in power ramp down rate by 39.90%, ramp up...

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...... price is proposed. A 17-bus power system with high wind power penetrations, which resembles the Eastern 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 small signal stability of power...... 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...

Demand response policies for the implementation of smart grids

NARCIS (Netherlands)

Koliou, E.

2016-01-01

With the grasp of a smart grid in sight, discussions have shifted the focus of system security measures away from generation capacity; apart from modifying the supply side, demand may also be exploited to keep the system in balance. Specifically, Demand Response (DR) is the concept of consumer load

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.

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.

A Study of Demand Response Effect of Thermal Storage Air-Conditioning Systems in Consideration of Electricity Market Prices

Science.gov (United States)

Omagari, Yuko; Sugihara, Hideharu; Tsuji, Kiichiro

This paper evaluates the economic impact of the introduction of customer-owned Thermal Storage Air-conditioning (TSA) systems, in an electricity market, from the viewpoint of the load service entity. We perform simulations on the condition that several thousand customers install TSA systems and shift peak demand in an electricity market by one percent. Our numerical results indicate that the purchase cost of the LSE was reduced through load management of customers with TSA systems. The introduction of TSA systems also reduced the volatility of market clearing price and reduced the whole-trade cost in an electricity market.

Load demand profile for a large charging station of a fleet of all-electric plug-in buses

Directory of Open Access Journals (Sweden)

Mario A. Rios

2014-08-01

Full Text Available This study proposes a general procedure to compute the load demand profile from a parking lot where a fleet of buses with electric propulsion mechanisms are charged. Such procedure is divided in three different stages, the first one models the daily energy utilisation of the batteries based on Monte Carlo simulations and route characteristics. The second one models the process in the charging station based on discrete event simulation of queues of buses served by a lot of available chargers. The third step computes the final demand profile in the parking lot because of the charging process based on the power consumption of batteries’ chargers and the utilisation of the available charges. The proposed procedure allows the computation of the number of required batteries’ chargers to be installed in a charging station placed at a parking lot in order to satisfy and ensure the operation of the fleet, the computation of the power demand profile and the peak load and the computation of the general characteristics of electrical infrastructure to supply the power to the station.

Preliminary guidelines for electricity distributor conservation and demand management activities : a guide for conservation and demand management investment

International Nuclear Information System (INIS)

2004-01-01

In May 2004, electricity distributors in Ontario were asked to submit deferral accounts to the Ontario Energy Board to track expenditures on conservation and demand management initiatives. The deferral accounts must be established before the distributor could recover the costs through the next installment of the allowable return on equity in March 2004. The Board will determine the appropriateness of the actual expenditures. These guidelines offer short-term assistance to distributors in establishing conservation and demand management plans and initiatives. The following specific measures may be supported by the Board: energy efficiency; operational changes to smart control systems; load management measures which facilitate interruptible and dispatchable loads, dual fuel applications, thermal storage and demand response; fuel switching measures; programs targeted to low income and hard to reach consumers; and, distributed energy options such as tri-generation, cogeneration, ground source heat pumps, wind and biomass systems. These guidelines described the regulatory treatment of conservation and demand management investments along with cost effectiveness, allocation of costs, monitoring, evaluation, and implementation. 1 appendix

Demand response in energy markets

International Nuclear Information System (INIS)

Skytte, K.; Birk Mortensen, J.

2004-11-01

Improving the ability of energy demand to respond to wholesale prices during critical periods of the spot market can reduce the total costs of reliably meeting demand, and the level and volatility of the prices. This fact has lead to a growing interest in the short-run demand response. There has especially been a growing interest in the electricity market where peak-load periods with high spot prices and occasional local blackouts have recently been seen. Market concentration at the supply side can result in even higher peak-load prices. Demand response by shifting demand from peak to base-load periods can counteract the market power in the peak-load. However, demand response has so far been modest since the current short-term price elasticity seems to be small. This is also the case for related markets, for example, green certificates where the demand is determined as a percentage of the power demand, or for heat and natural gas markets. This raises a number of interesting research issues: 1) Demand response in different energy markets, 2) Estimation of price elasticity and flexibility, 3) Stimulation of demand response, 4) Regulation, policy and modelling aspects, 5) Demand response and market power at the supply side, 6) Energy security of supply, 7) Demand response in forward, spot, ancillary service, balance and capacity markets, 8) Demand response in deviated markets, e.g., emission, futures, and green certificate markets, 9) Value of increased demand response, 10) Flexible households. (BA)

Domestic demand-side management (DSM): Role of heat pumps and thermal energy storage (TES) systems

International Nuclear Information System (INIS)

Arteconi, A.; Hewitt, N.J.; Polonara, F.

2013-01-01

Heat pumps are seen as a promising technology for load management in the built environment, in combination with the smart grid concept. They can be coupled with thermal energy storage (TES) systems to shift electrical loads from high-peak to off-peak hours, thus serving as a powerful tool in demand-side management (DSM). This paper analyzes heat pumps with radiators or underfloor heating distribution systems coupled with TES with a view to showing how a heat pump system behaves and how it influences the building occupants' thermal comfort under a DSM strategy designed to flatten the shape of the electricity load curve by switching off the heat pump during peak hours (16:00–19:00). The reference scenario for the analysis was Northern Ireland (UK). The results showed that the heat pump is a good tool for the purposes of DSM, also thanks to the use of TES systems, in particular with heating distribution systems that have a low thermal inertia, e.g. radiators. It proved possible to achieve a good control of the indoor temperature, even if the heat pump was turned off for 3 h, and to reduce the electricity bill if a “time of use” tariff structure was adopted. -- Highlights: ► Heat pump heating systems with thermal energy storage are considered. ► System behavior is investigated during a DSM strategy for reducing peak energy demand. ► Heat pump heating systems demonstrate to be able to have an active role in DSM programs. ► A TES system must be coupled with the heat pump in presence of low thermal inertia heating distribution systems. ► Central role played by incentives schemes to promote this technology

Forecasting Monthly Electricity Demands by Wavelet Neuro-Fuzzy System Optimized by Heuristic Algorithms

Directory of Open Access Journals (Sweden)

Jeng-Fung Chen

2018-02-01

Full Text Available Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate planning and prediction of electricity load are therefore vital. In this study, a novel approach for forecasting monthly electricity demands by wavelet transform and a neuro-fuzzy system is proposed. Firstly, the most appropriate inputs are selected and a dataset is constructed. Then, Haar wavelet transform is utilized to decompose the load data and eliminate noise. In the model, a hierarchical adaptive neuro-fuzzy inference system (HANFIS is suggested to solve the curse-of-dimensionality problem. Several heuristic algorithms including Gravitational Search Algorithm (GSA, Cuckoo Optimization Algorithm (COA, and Cuckoo Search (CS are utilized to optimize the clustering parameters which help form the rule base, and adaptive neuro-fuzzy inference system (ANFIS optimize the parameters in the antecedent and consequent parts of each sub-model. The proposed approach was applied to forecast the electricity load of Hanoi, Vietnam. The constructed models have shown high forecasting performances based on the performance indices calculated. The results demonstrate the validity of the approach. The obtained results were also compared with those of several other well-known methods including autoregressive integrated moving average (ARIMA and multiple linear regression (MLR. In our study, the wavelet CS-HANFIS model outperformed the others and provided more accurate forecasting.

Integrated load distribution and production planning in series-parallel multi-state systems with failure rate depending on load

International Nuclear Information System (INIS)

Nourelfath, Mustapha; Yalaoui, Farouk

2012-01-01

A production system containing a set of machines (also called components) arranged according to a series-parallel configuration is addressed. A set of products must be produced in lots on this production system during a specified finite planning horizon. This paper presents a method for integrating load distribution decisions, and tactical production planning considering the costs of capacity change and the costs of unused capacity. The objective is to minimize the sum of capacity change costs, unused capacity costs, setup costs, holding costs, backorder costs, and production costs. The main constraints consist in satisfying the demand for all products over the entire horizon, and in not exceeding available repair resource. The production series-parallel system is modeled as a multi-state system with binary-state components. The proposed model takes into account the dependence of machines' failure rates on their load. Universal generating function technique can be used in the optimization algorithm for evaluating the expected system production rate in each period. We show how the formulated problem can be solved by comparing the results of several multi-product lot-sizing problems with capacity associated costs. The importance of integrating load distribution decisions and production planning is illustrated through numerical examples.

Demand side management for remote area power supply systems incorporating solar irradiance model

International Nuclear Information System (INIS)

Al-Alawi, A.; Islam, S.M.

2004-01-01

This paper presents a technique for generating the daily electricity load profile for remote areas in the Middle East from first principles, using diversified demand. The generated load profile includes the energy required to run a small desalination unit to provide the necessary freshwater. Demand side management (DSM) is used in this study to smooth out the daily peaks and fill valleys in the load curve to make the most efficient use of energy resources. Finally, the load profile is compared with real data for six houses collected from Safri area in the Sultanate of Oman. These data may be used as the basis to obtain load profiles of other remote areas of the Middle East since the weather and social factors are similar. The modified hourly variation factor based on weather and economic and social factors of the Middle East is obtained. (author)

Improving electrical power systems reliability through locally controlled distributed curtailable load

Science.gov (United States)

Dehbozorgi, Mohammad Reza

2000-10-01

Improvements in power system reliability have always been of interest to both power companies and customers. Since there are no sizable electrical energy storage elements in electrical power systems, the generated power should match the load demand at any given time. Failure to meet this balance may cause severe system problems, including loss of generation and system blackouts. This thesis proposes a methodology which can respond to either loss of generation or loss of load. It is based on switching of electric water heaters using power system frequency as the controlling signal. The proposed methodology encounters, and the thesis has addressed, the following associated problems. The controller must be interfaced with the existing thermostat control. When necessary to switch on loads, the water in the tank should not be overheated. Rapid switching of blocks of load, or chattering, has been considered. The contributions of the thesis are: (A) A system has been proposed which makes a significant portion of the distributed loads connected to a power system to behave in a predetermined manner to improve the power system response during disturbances. (B) The action of the proposed system is transparent to the customers. (C) The thesis proposes a simple analysis for determining the amount of such loads which might be switched and relates this amount to the size of the disturbances which can occur in the utility. (D) The proposed system acts without any formal communication links, solely using the embedded information present system-wide. (E) The methodology of the thesis proposes switching of water heater loads based on a simple, localized frequency set-point controller. The thesis has identified the consequent problem of rapid switching of distributed loads, which is referred to as chattering. (F) Two approaches have been proposed to reduce chattering to tolerable levels. (G) A frequency controller has been designed and built according to the specifications required to

DeMand: A tool for evaluating and comparing device-level demand and supply forecast models

DEFF Research Database (Denmark)

Neupane, Bijay; Siksnys, Laurynas; Pedersen, Torben Bach

2016-01-01

Fine-grained device-level predictions of both shiftable and non-shiftable energy demand and supply is vital in order to take advantage of Demand Response (DR) for efficient utilization of Renewable Energy Sources. The selection of an effective device-level load forecast model is a challenging task......, mainly due to the diversity of the models and the lack of proper tools and datasets that can be used to validate them. In this paper, we introduce the DeMand system for fine-tuning, analyzing, and validating the device-level forecast models. The system offers several built-in device-level measurement...... datasets, forecast models, features, and errors measures, thus semi-automating most of the steps of the forecast model selection and validation process. This paper presents the architecture and data model of the DeMand system; and provides a use-case example on how one particular forecast model...

Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models

Energy Technology Data Exchange (ETDEWEB)

Pappas, S.S. [Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi, 83 200 Samos (Greece); Ekonomou, L.; Chatzarakis, G.E. [Department of Electrical Engineering Educators, ASPETE - School of Pedagogical and Technological Education, N. Heraklion, 141 21 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24100 Kalamata (Greece); Katsikas, S.K. [Department of Technology Education and Digital Systems, University of Piraeus, 150 Androutsou Srt., 18 532 Piraeus (Greece); Liatsis, P. [Division of Electrical Electronic and Information Engineering, School of Engineering and Mathematical Sciences, Information and Biomedical Engineering Centre, City University, Northampton Square, London EC1V 0HB (United Kingdom)

2008-09-15

This study addresses the problem of modeling the electricity demand loads in Greece. The provided actual load data is deseasonilized and an AutoRegressive Moving Average (ARMA) model is fitted on the data off-line, using the Akaike Corrected Information Criterion (AICC). The developed model fits the data in a successful manner. Difficulties occur when the provided data includes noise or errors and also when an on-line/adaptive modeling is required. In both cases and under the assumption that the provided data can be represented by an ARMA model, simultaneous order and parameter estimation of ARMA models under the presence of noise are performed. The produced results indicate that the proposed method, which is based on the multi-model partitioning theory, tackles successfully the studied problem. For validation purposes the produced results are compared with three other established order selection criteria, namely AICC, Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The developed model could be useful in the studies that concern electricity consumption and electricity prices forecasts. (author)

Impact of optimal load response to real-time electricity price on power system constraints 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. The optimal load response to a real-time electricity price...... and may represent the future of electricity markets in some ways, is chosen as the studied power system in this paper. A distribution system where wind power capacity is 126% of maximum loads is chosen as the study case. This paper presents a nonlinear load optimization method to real-time power price...... for demand side management in order to save the energy costs as much as possible. Simulation results show that the optimal load response to a real-time electricity price has some good impacts on power system constraints in a distribution system with high wind power penetrations....

Cognitive Load and Attentional Demands during Objects' Position Change in Real and Digital Environments

Science.gov (United States)

Zacharis, Georgios K.; Mikropoulos, Tassos Anastasios; Kalyvioti, Katerina

2016-01-01

Studies showed that two-dimensional (2D) and three-dimensional (3D) educational content contributes to learning. Although there were many studies with 3D stereoscopic learning environments, only a few studies reported on the differences between real, 2D, and 3D scenes, as far as cognitive load and attentional demands were concerned. We used…

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.

Load leveling total system. Part 2. Development of load leveling logic for residential customer; Fuka heijunka total system. 2. Kateiyo juyoka wo taisho to shita heijunka ronri no kaihatsu

Energy Technology Data Exchange (ETDEWEB)

Asari, M.; Nanahara, T. [Central Research Institute of Electric Power Industry, Tokyo (Japan)

1995-05-01

It is essential, in order to meet steadily increasing demands for electrical power, to develop techniques for effective utilization of energy and load leveling. Described herein is development, by the aid of linear programming, of logic for daily management of charge/discharge of load conditioners and reverse power flow, for predicted loads and patterns of power generated by photovoltaic cells installed at individual customers. It is aimed at minimizing power rate and leveling of load at distribution systems. Predicted loads, outputs by photovoltaic cell units and different power rates by time zone for the next day are inputted, to determine the charge/discharge schedules and power supply/reverse flow patterns for that day, in order to minimize power rates and level loads at higher hierarchical levels. The logic-aided daily simulation for various districts confirms the operational patterns that realize improved utilization of pole-mounted transformers while reducing costs at customers, and effects of prediction errors. 4 refs., 14 figs.

Responsive demand to mitigate slow recovery voltage sags

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; da Silva, Luiz Carlos Pereira; Xu, Zhao

2012-01-01

, and reactive power reserve for peak load management through price responsive methods and also as energy providers through embedded generation technologies. This article introduces a new technology, called demand as voltagecontrolled reserve, which can help mitigation of momentary voltage sags. The technology...... faults. This article presents detailed models, discussion, and simulation tests to demonstrate the technical viability and effectiveness of the demand as voltage-controlled reserve technology for mitigating voltage sags....... can be provided by thermostatically controlled loads as well as other types of load. This technology has proven to be effective in distribution systems with a large composition of induction motors, when voltage sags present slow recovery characteristics because of the deceleration of the motors during...

Electricity Crisis and Load Management in Bangladesh

Directory of Open Access Journals (Sweden)

Rajib Kanti Das

2012-09-01

Full Text Available Bangladesh is a densely populated country. Only a small part of her area is electrified which cover around 18% of total population. The people who are in the electrified area are suffering from severe load shedding. A systematic load management procedure related to demand side may improve the situation is the research problem. The major objectives serve by the research are to analyze contemporary electricity status with a view to drawing inference about demand supply gap and extracting benefits from load management. Data supplied by the Bangladesh Power Development Board, World Bank and outcome of survey are analyzed with some simple statistical tools to test the hypothesis. Analysis discloses that with properly managed uses of electricity with load switch and rotation week-end can improve the concurrent condition of electricity. Moreover, introducing smart distribution system, reducing system loss, shifting load to off-peak, large scale use of prepaid mete, observing energy week and using energy efficient home and office appliance are recommended to improve load through demand side management. Some other recommendations such as introducing alternative energy, public private partnership and using renewable energy development and producing energy locally are made for load management from the supply side.

Identifying interactive effects of task demands in lifting on estimates of in vivo low back joint loads.

Science.gov (United States)

Gooyers, Chad E; Beach, Tyson A C; Frost, David M; Howarth, Samuel J; Callaghan, Jack P

2018-02-01

This investigation examined interactions between the magnitude of external load, movement speed and (a)symmetry of load placement on estimates of in vivo joint loading in the lumbar spine during simulated occupational lifting. Thirty-two participants with manual materials handling experience were included in the study. Three-dimensional motion data, ground reaction forces, and activation of six bilateral trunk muscle groups were captured while participants performed lifts with two loads at two movement speeds and using two load locations. L4-L5 joint compression and shear force-time histories were estimated using an EMG-assisted musculoskeletal model of the lumbar spine. Results from this investigation provide strong evidence that known mechanical low back injury risk factors should not be viewed in isolation. Rather, injury prevention efforts need to consider the complex interactions that exist between external task demands and their combined influence on internal joint loading. Copyright © 2017 Elsevier Ltd. All rights reserved.

Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets

Science.gov (United States)

Surender Reddy, S.; Abhyankar, A. R.; Bijwe, P. R.

2015-04-01

This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.

Ontario demand response scenarios

International Nuclear Information System (INIS)

Rowlands, I.H.

2005-09-01

Strategies for demand management in Ontario were examined via 2 scenarios for a commercial/institutional building with a normal summertime peak load of 300 kW between 14:00 and 18:00 during a period of high electricity demand and high electricity prices. The first scenario involved the deployment of a 150 kW on-site generator fuelled by either diesel or natural gas. The second scenario involved curtailing load by 60 kW during the same periods. Costs and benefits of both scenarios were evaluated for 3 groups: consumers, system operators and society. Benefits included electricity cost savings, deferred transmission capacity development, lower system prices for electricity, as well as environmental changes, economic development, and a greater sense of corporate social responsibility. It was noted that while significant benefits were observed for all 3 groups, they were not substantial enough to encourage action, as the savings arising from deferred generation capacity development do not accrue to individual players. The largest potential benefit was identified as lower prices, spread across all users of electricity in Ontario. It was recommended that representative bodies cooperate so that the system-wide benefits can be reaped. It was noted that if 10 municipal utilities were able to have 250 commercial or institutional customers engaged in distributed response, then a total peak demand reduction of 375 MW could be achieved, representing more than 25 per cent of Ontario's target for energy conservation. It was concluded that demand response often involves the investment of capital and new on-site procedures, which may affect reactions to various incentives. 78 refs., 10 tabs., 5 figs

Demand controlled ventilation for multi-family dwellings

DEFF Research Database (Denmark)

Mortensen, Dorthe Kragsig

for centrally balanced DCV systems with heat recovery. A design expected to fulfill this requirement was investigated in detail with regard to its electricity consumption by evaluating a control strategy that resets the static pressure set point at part load. The results showed that this control strategy can......The present thesis “Demand controlled ventilation for multi-family dwellings” constitutes the summary of a three year project period during which demand specification and system design of demand controlled ventilation for residential buildings were studied. Most standards and buildings codes...... can be reduced compared to a system with constant air flow. A literature study on indoor pollutants in homes, their sources and their impact on humans formed the basis for the demand specification. Emission of pollutants in residential buildings roughly fall into constantly emitted background sources...

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

Modelling changes to electricity demand load duration curves as a consequence of predicted climate change for Australia

International Nuclear Information System (INIS)

Thatcher, Marcus J.

2007-01-01

In this paper, we describe a method for constructing regional electricity demand data sets at 30 min intervals, which are consistent with climate change scenarios. Specifically, we modify a commonly used linear regression model between regional electricity demand and climate to also describe intraday variability in demand so that regional load duration curves (LDCs) can be predicted. The model is evaluated for four different Australian states that are participants in the Australian National Electricity Market (NEM) and the resultant data sets are found to reproduce each state's LDCs with reasonable accuracy. We also apply the demand model to CSIRO's Mk 3 global climate model data sets that have been downscaled to 60 km resolution using CSIRO's conformal-cubic atmospheric model to estimate how LDCs change as a consequence of a 1 C increase in the average temperature of Australian state capital cities. These regional electricity demand data sets are then useful for economic modelling of electricity markets such as the NEM. (author)

A bi-level integrated generation-transmission planning model incorporating the impacts of demand response by operation simulation

International Nuclear Information System (INIS)

Zhang, Ning; Hu, Zhaoguang; Springer, Cecilia; Li, Yanning; Shen, Bo

2016-01-01

Highlights: • We put forward a novel bi-level integrated power system planning model. • Generation expansion planning and transmission expansion planning are combined. • The effects of two sorts of demand response in reducing peak load are considered. • Operation simulation is conducted to reflect the actual effects of demand response. • The interactions between the two levels can guarantee a reasonably optimal result. - Abstract: If all the resources in power supply side, transmission part, and power demand side are considered together, the optimal expansion scheme from the perspective of the whole system can be achieved. In this paper, generation expansion planning and transmission expansion planning are combined into one model. Moreover, the effects of demand response in reducing peak load are taken into account in the planning model, which can cut back the generation expansion capacity and transmission expansion capacity. Existing approaches to considering demand response for planning tend to overestimate the impacts of demand response on peak load reduction. These approaches usually focus on power reduction at the moment of peak load without considering the situations in which load demand at another moment may unexpectedly become the new peak load due to demand response. These situations are analyzed in this paper. Accordingly, a novel approach to incorporating demand response in a planning model is proposed. A modified unit commitment model with demand response is utilized. The planning model is thereby a bi-level model with interactions between generation-transmission expansion planning and operation simulation to reflect the actual effects of demand response and find the reasonably optimal planning result.

Social implications of residential demand response in cool temperate climates

International Nuclear Information System (INIS)

Darby, Sarah J.; McKenna, Eoghan

2012-01-01

Residential electrical demand response (DR) offers the prospect of reducing the environmental impact of electricity use, and also the supply costs. However, the relatively small loads and numerous actors imply a large effort: response ratio. Residential DR may be an essential part of future smart grids, but how viable is it in the short to medium term? This paper reviews some DR concepts, then evaluates the propositions that households in cool temperate climates will be in a position to contribute to grid flexibility within the next decade, and that that they will allow some automated load control. Examples of demand response from around the world are discussed in order to assess the main considerations for cool climates. Different tariff types and forms of control are assessed in terms of what is being asked of electricity users, with a focus on real-time pricing and direct load control in energy systems with increasingly distributed resources. The literature points to the significance of thermal loads, supply mix, demand-side infrastructure, market regulation, and the framing of risks and opportunities associated with DR. In concentrating on social aspects of residential demand response, the paper complements the body of work on technical and economic potential. - Highlights: ► Demand response implies major change in governance of electricity systems. ► Households in cool temperate climates can be flexible, mainly with thermal loads. ► DR requires simple tariffs, appropriate enabling technology, education, and feedback. ► Need to test consumer acceptance of DR in specific conditions. ► Introduce tariffs with technologies e.g., TOU tariff plus DLC with electric vehicles.

Optimization Design Method and Experimental Validation of a Solar PVT Cogeneration System Based on Building Energy Demand

Directory of Open Access Journals (Sweden)

Chao Zhou

2017-08-01

Full Text Available Photovoltaic-thermal (PVT technology refers to the integration of a photovoltaic (PV and a conventional solar thermal collector, representing the deep exploitation and utilization of solar energy. In this paper, we evaluate the performance of a solar PVT cogeneration system based on specific building energy demand using theoretical modeling and experimental study. Through calculation and simulation, the dynamic heating load and electricity load is obtained as the basis of the system design. An analytical expression for the connection of PVT collector array is derived by using basic energy balance equations and thermal models. Based on analytical results, an optimized design method was carried out for the system. In addition, the fuzzy control method of frequency conversion circulating water pumps and pipeline switching by electromagnetic valves is introduced in this paper to maintain the system at an optimal working point. Meanwhile, an experimental setup is established, which includes 36 PVT collectors with every 6 PVT collectors connected in series. The thermal energy generation, thermal efficiency, power generation and photovoltaic efficiency have been given in this paper. The results demonstrate that the demonstration solar PVT cogeneration system can meet the building energy demand in the daytime in the heating season.

An Optimization Model for Large–Scale Wind Power Grid Connection Considering Demand Response and Energy Storage Systems

Directory of Open Access Journals (Sweden)

Zhongfu Tan

2014-11-01

Full Text Available To reduce the influence of wind power output uncertainty on power system stability, demand response (DRPs and energy storage systems (ESSs are introduced while solving scheduling optimization problems. To simulate wind power scenarios, this paper uses Latin Hypercube Sampling (LHS to generate the initial scenario set and constructs a scenario reduction strategy based on Kantorovich distance. Since DRPs and ESSs can influence the distribution of demand load, this paper constructs a joint scheduling optimization model for wind power, ESSs and DRPs under the objective of minimizing total coal cost, and constraints of power demand and supply balance, users’ demand elasticity, thermal units’ startup-shutdown, thermal units’ output power climbing and wind power backup service. To analyze the influences of ESSs and DRPs on system wind power consumption capacity, example simulation is made in a 10 thermal units system with a 1000 MW wind farm and 400 MW energy storage systems under four simulation scenarios. The simulation results show that the introduction of DRPs and ESSs could promote system wind power consumption capacity with significantly economic and environment benefits, which include less coal consumption and less pollutant emission; and the optimization effect reaches the optimum when DRPs and ESSs are both introduced.

A fuzzy inference model for short-term load forecasting

International Nuclear Information System (INIS)

Mamlook, Rustum; Badran, Omar; Abdulhadi, Emad

2009-01-01

This paper is concerned with the short-term load forecasting (STLF) in power system operations. It provides load prediction for generation scheduling and unit commitment decisions, and therefore precise load forecasting plays an important role in reducing the generation cost and the spinning reserve capacity. Short-term electricity demand forecasting (i.e., the prediction of hourly loads (demand)) is one of the most important tools by which an electric utility/company plans, dispatches the loading of generating units in order to meet system demand. The accuracy of the dispatching system, which is derived from the accuracy of the forecasting algorithm used, will determine the economics of the operation of the power system. The inaccuracy or large error in the forecast simply means that load matching is not optimized and consequently the generation and transmission systems are not being operated in an efficient manner. In the present study, a proposed methodology has been introduced to decrease the forecasted error and the processing time by using fuzzy logic controller on an hourly base. Therefore, it predicts the effect of different conditional parameters (i.e., weather, time, historical data, and random disturbances) on load forecasting in terms of fuzzy sets during the generation process. These parameters are chosen with respect to their priority and importance. The forecasted values obtained by fuzzy method were compared with the conventionally forecasted ones. The results showed that the STLF of the fuzzy implementation have more accuracy and better outcomes

Application of Linear Quadratic Gaussian and Coefficient Diagram Techniques to Distributed Load Frequency Control of Power Systems

Directory of Open Access Journals (Sweden)

Tarek Hassan Mohamed

2015-12-01

Full Text Available This paper presented both the linear quadratic Gaussian technique (LQG and the coefficient diagram method (CDM as load frequency controllers in a multi-area power system to deal with the problem of variations in system parameters and load demand change. The full states of the system including the area frequency deviation have been estimated using the Kalman filter technique. The efficiency of the proposed control method has been checked using a digital simulation. Simulation results indicated that, with the proposed CDM + LQG technique, the system is robust in the face of parameter uncertainties and load disturbances. A comparison between the proposed technique and other schemes is carried out, confirming the superiority of the proposed CDM + LQG technique.

Optimization of a polygeneration system for energy demands of a livestock farm

Directory of Open Access Journals (Sweden)

Mančić Marko V.

2016-01-01

Full Text Available A polygeneration system is an energy system capable of providing multiple utility outputs to meet local demands by application of process integration. This paper addresses the problem of pinpointing the optimal polygeneration energy supply system for the local energy demands of a livestock farm in terms of optimal system configuration and optimal system capacity. The optimization problem is presented and solved for a case study of a pig farm in the paper. Energy demands of the farm, as well as the super-structure of the polygeneration system were modelled using TRNSYS software. Based on the locally available resources, the following polygeneration modules were chosen for the case study analysis: a biogas fired internal combustion engine co-generation module, a gas boiler, a chiller, a ground water source heat pump, solar thermal collectors, photovoltaic collectors, and heat and cold storage. Capacities of the polygeneration modules were used as optimization variables for the TRNSYS-GenOpt optimization, whereas net present value, system primary energy consumption, and CO2 emissions were used as goal functions for optimization. A hybrid system composed of biogas fired internal combustion engine based co-generation system, adsorption chiller solar thermal and photovoltaic collectors, and heat storage is found to be the best option. Optimal heating capacity of the biogas co-generation and adsorption units was found equal to the design loads, whereas the optimal surface of the solar thermal array is equal to the south office roof area, and the optimal surface of the PV array corresponds to the south facing animal housing building rooftop area. [Projekat Ministarstva nauke Republike Srbije, br. III 42006: Research and development of energy and environmentally highly effective polygeneration systems based on using renewable energy sources

Probabilistic Quantification of Potentially Flexible Residential Demand

DEFF Research Database (Denmark)

Kouzelis, Konstantinos; Mendaza, Iker Diaz de Cerio; Bak-Jensen, Birgitte

2014-01-01

The balancing of power systems with high penetration of renewable energy is a serious challenge to be faced in the near future. One of the possible solutions, recently capturing a lot of attention, is demand response. Demand response can only be achieved by power consumers holding loads which allow...... them to modify their normal power consumption pattern, namely flexible consumers. However flexibility, despite being constantly mentioned, is usually not properly defined and even rarer quantified. This manuscript introduces a methodology to identify and quantify potentially flexible demand...

Decentralized/stand-alone hybrid Wind-Diesel power systems to meet residential loads of hot coastal regions

International Nuclear Information System (INIS)

Elhadidy, M.A.; Shaahid, S.M.

2005-01-01

In view of rising costs, pollution and fears of exhaustion of oil and coal, governments around the world are encouraging to seek energy from renewable/sustainable energy sources such as wind. The utilization of energy from wind (since the oil embargo of the 1970s) is being widely disseminated for displacement of fossil fuel produced energy and to reduce atmospheric degradation. A system that consists of a wind turbine and Diesel genset is called a Wind-Diesel power system.The literature indicates that the commercial/residential buildings in Saudi Arabia consume an estimated 10-40% of the total electric energy generated. In the present study, the hourly mean wind-speed data of the period 1986-1997 recorded at the solar radiation and meteorological station, Dhahran (26 deg. 32'N, 50 deg. 13'E in the Eastern Coastal Region of Saudi Arabia), has been analyzed to investigate the potential of utilizing hybrid (Wind-Diesel) energy conversion systems to meet the load requirements of a hundred typical two bedroom residential buildings (with annual electrical energy demand of 3512 MWh). The long term monthly average wind speeds for Dhahran range from 4.2 to 6.4 m/s. The hybrid systems considered in the present case study consist of different combinations/clusters of 150 kW commercial wind machines supplemented with battery storage and Diesel back-up. The deficit energy generated by the Diesel generator (for different battery capacities) and the number of operational hours of the Diesel system to meet a specific annual electrical energy demand of 3512 MWh have also been presented. The evaluation of the hybrid system shows that with seven 150 kW wind energy conversion system (WECS) and one day of battery storage, the Diesel back-up system has to provide 21.6% of the load demand. Furthermore, with three days of battery storage, the Diesel back-up system has to provide 17.5% of the load demand. However, in the absence of battery storage, about 37% of the load needs to be

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.

Survey of energy load leveling system in Europe; Energy fuka heijunka taisaku ni kansuru Europe chosa

Energy Technology Data Exchange (ETDEWEB)

Suzuki, Y. [Setsunan University, Osaka (Japan). Faculty of Engineering

1998-05-05

This paper describes the survey of energy load leveling systems in Europe. In Denmark, especially regional heating is remarkably diffused, and they have 350 plants. With extending the service areas, the energy load leveling has been promoted. For the cogeneration plants of SK Power, the largest electric power company, they have hot water heat storage tanks for regional heat supply with a total capacity 2,200 MWh. The regional heating system in Goeteborg City of Sweden supplies 80% of the total heat demand of the city. Unused energy sources derived from petroleum refining, sewage treatment, and garbage burning are utilized. In Uppsala, they have seasonal heat storage systems using solar heat. The Vienna Regional Heat Supply Corporation supplies heat equivalent to 5,000 GWh a year. Cogeneration plants and garbage burning plants are used as heat sources, and 25% of the total heating in the city is supplied. In Austria, they have an electric power demand with a peak in winter, and they have a pumped-storage power station in Kaprun for the annual load leveling using dump power in summer. This paper also introduces a compressed air storage gas turbine plant at Huntorf of Germany, and a large-scale underground natural gas storage of Gaz de France. 6 figs.

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...... this simulation, real power system data from the Danish island of Bornholm is introduced and methods to quantify an aggregated load is developed. These methods can be used for real-time operation and to support investment decisions. More specifically, they can be used to forecast the response to electricity...... 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...

Introduction effect of a load levelling system in an electric power system with a photovoltaic and wind system; Taiyoko/furyoku hatsuden wo donyu shita denryoku keito ni okeru fuka heijunka shisutemu no donyu koka

Energy Technology Data Exchange (ETDEWEB)

Kenmoku, Y.; Sakakibara, T. [Toyohashi University of Technology, Aichi (Japan); Nakagawa, S. [Maizuru College of Technology, Kyoto (Japan); Kawamoto, T. [Shizuoka University, Shizuoka (Japan)

1998-12-05

Introduction effect of load levelling system by a battery in an electric power system by a battery in an electric power system with a PV and wind system is investigated. Charge and discharge power of the battery are determined from a load curve and every hour data of PV and wind output. Annual cost of the power system is calculated from the generating power and the capacity of each source via the installed utility capacity and the capacity factor. It is found that (1) the battery system reduces the maximum demand and improves the load factor, (2) the cost effect of the battery system when introducing the PV system is higher than that when introducing the wind system. (author)

Evaluation of automated residential demand response with flat and dynamic pricing

International Nuclear Information System (INIS)

Swisher, Joel; Wang, Kitty; Stewart, Stewart

2005-01-01

This paper reviews the performance of two recent automated load management programs for residential customers of electric utilities in two American states. Both pilot programs have been run with about 200 participant houses each, and both programs have control populations of similar customers without the technology or program treatment. In both cases, the technology used in the pilot is GoodWatts, an advanced, two-way, real-time, comprehensive home energy management system. The purpose of each pilot is to determine the household kW reduction in coincident peak electric load from the energy management technology. Nevada Power has conducted a pilot program for Air-Conditioning Load Management (ACLM), in which customers are sent an electronic curtailment signal for three-hour intervals during times of maximum peak demand. The participating customers receive an annual incentive payment, but otherwise they are on a conventional utility tariff. In California, three major utilities are jointly conducting a pilot demonstration of an Automated Demand Response System (ADRS). Customers are on a time-of-use (ToU) tariff, which includes a critical peak pricing (CPP) element. During times of maximum peak demand, customers are sent an electronic price signal that is three times higher than the normal on-peak price. Houses with the automated GoodWatts technology reduced their demand in both the ACLM and the ADRS programs by about 50% consistently across the summer curtailment or super peak events, relative to homes without the technology or any load management program or tariff in place. The absolute savings were greater in the ACLM program, due to the higher baseline air conditioning loads in the hotter Las Vegas climate. The results suggest that either automated technology or dynamic pricing can deliver significant demand response in low-consumption houses. However, for high-consumption houses, automated technology can reduce load by a greater absolute kWh difference. Targeting

Interdependent demands, regulatory constraint, and peak-load pricing. [Assessment of Bailey's model

Energy Technology Data Exchange (ETDEWEB)

Nguyen, D T; Macgregor-Reid, G J

1977-06-01

A model of a regulated firm which includes an analysis of peak-load pricing has been formulated by E. E. Bailey in which three alternative modes of regulation on a profit-maximizing firm are considered. The main conclusion reached is that under a regulation limiting the rate of return on capital investment, price reductions are received solely by peak-users and that when regulation limiting the profit per unit of output or the return on costs is imposed, there are price reductions for all users. Bailey has expressly assumed that the demands in different periods are interdependent but has somehow failed to derive the correct price and welfare implications of this empirically highly relevant assumption. Her conclusions would have been perfectly correct for marginal revenues but are quite incorrect for prices, even if her assumption that price exceeds marginal revenues in every period holds. This present paper derives fully and rigorously the implications of regulation for prices, outputs, capacity, and social welfare for a profit-maximizing firm with interdependent demands. In section II, Bailey's model is reproduced and the optimal conditions are given. In section III, it is demonstrated that under the conditions of interdependent demands assumed by Bailey herself, her often-quoted conclusion concerning the effects of the return-on-investment regulation on the off-peak price is invalid. In section IV, the effects of the return-on-investment regulation on the optimal prices, outputs, capacity, and social welfare both for the case in which the demands in different periods are substitutes and for the case in which they are complements are examined. In section V, the pricing and welfare implications of the return-on-investment regulation are compared with the two other modes of regulation considered by Bailey. Section VI is a summary of all sections. (MCW)

Integration of V2H/V2G Hybrid System for Demand Response in Distribution Network

Energy Technology Data Exchange (ETDEWEB)

Wang, Yubo; Sheikh, Omar; Hu, Boyang; Chu, Chi-Cheng; Gadh, Rajit

2014-11-03

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities for distributed storage and generation in distribution network. With the introduction of Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G), EVs can help stabilize the operation of power grid. This paper proposed and implemented a hybrid V2H/V2G system with commercialized EVs, which is able to support both islanded AC/DC load and the power grid with one single platform. Standard industrial communication protocols are implemented for a seamless respond to remote Demand Respond (DR) signals. Simulation and implementation are carried out to validate the proposed design. Simulation and implementation results showed that the hybrid system is capable of support critical islanded DC/AC load and quickly respond to the remote DR signal for V2G within 1.5kW of power range.

Demand as Frequency-controlled Reserve

DEFF Research Database (Denmark)

Bang, Christian; Rasmussen, Christian Brandt; Østergaard, Jacob

with great enthusiasm from all DFR project members who have shown a memorable dedication to their work. Active control of electricity demand is a key technology when creating a more dynamic, wind power friendly energy system. In this demonstration project, we have developed and tested devices, which use...... electric loads to provide frequency controlled primary reserves. The devices collected data from domestic households and industrial loads covering i.e. circulation pumps, electrical domestic heating, bottle coolers, a wastewater treatment plant etc., that have been analysed and used for the papers...

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

Thermodynamic analysis of load-leveling hyper energy converting and utilization system

International Nuclear Information System (INIS)

Kiani, Behdad; Akisawa, Atsushi; Kashiwagi, Takao

2008-01-01

Load-leveling hyper energy converting and utilization system (LHECUS) is a hybrid cycle which utilizes ammonia-water mixture as the working fluid in a combined power generation and refrigeration cycle. The power generation cycle functions as a Kalina cycle and an absorption refrigeration cycle is combined with it as a bottoming cycle. LHECUS is designed to utilize the waste heat from industry to produce cooling and power simultaneously. The refrigeration effect can be either transported to end-use sectors by means of a solution transportation absorption chiller (STA) as solution concentration difference or stored for demand load leveling. This paper shows a simulation of the LHECUS cycle. A computer model was written to balance the cycle and key parameters for optimizing the cycle were identified

Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers

International Nuclear Information System (INIS)

Jang, Dongsik; Eom, Jiyong; Jae Park, Min; Jeung Rho, Jae

2016-01-01

To the extent that demand response represents an intentional electricity usage adjustment to price changes or incentive payments, consumers who exhibit more-variable load patterns on normal days may be capable of altering their loads more significantly in response to dynamic pricing plans. This study investigates the variation in the pre-enrollment load patterns of Korean commercial and industrial electricity customers and their impact on event-day loads during a critical peak pricing experiment in the winter of 2013. Contrary to conventional approaches to profiling electricity loads, this study proposes a new clustering technique based on variability indices that collectively represent the potential demand–response resource that these customers would supply. Our analysis reveals that variability in pre-enrollment load patterns does indeed have great predictive power for estimating their impact on demand–response loads. Customers in relatively low-variability clusters provided limited or no response, whereas customers in relatively high-variability clusters consistently presented large load impacts, accounting for most of the program-level peak reductions. This study suggests that dynamic pricing programs themselves may not offer adequate motivation for meaningful adjustments in load patterns, particularly for customers in low-variability clusters. - Highlights: • A method of clustering customers by variability indices is developed. • Customers in high-variability clusters provide substantial peak reductions. • Low-variability clusters exhibit limited reductions. • For low-variability customers, alternative policy instruments is well advised. • A model of discerning customer's demand response potential is suggested.

Optimal real time cost-benefit based demand response with intermittent resources

International Nuclear Information System (INIS)

Zareen, N.; Mustafa, M.W.; Sultana, U.; Nadia, R.; Khattak, M.A.

2015-01-01

Ever-increasing price of conventional energy resources and related environmental concern enforced to explore alternative energy sources. Inherent uncertainty of power generation and demand being strongly influenced by the electricity market has posed severe challenges for DRPs (Demand Response Programs). Definitely, the success of such uncertain energy systems under new market structures is critically decided by the advancement of innovative technical and financial tools. Recent exponential growth of DG (distributed generations) demanded both the grid reliability and financial cost–benefits analysis for deregulated electricity market stakeholders. Based on the SGT (signaling game theory), the paper presents a novel user-aware demand-management approach where the price are colligated with grid condition uncertainties to manage the peak residential loads. The degree of information disturbances are considered as a key factor for evaluating electricity bidding mechanisms in the presence of independent multi-generation resources and price-elastic demand. A correlation between the cost–benefit price and variable reliability of grid is established under uncertain generation and demand conditions. Impacts of the strategies on load shape, benefit of customers and the reduction of energy consumption are inspected and compared with Time-of-Used based DRPs. Simulation results show that the proposed DRP can significantly reduce or even eliminate peak-hour energy consumption, leading to a substantial raise of revenues with 18% increase in the load reduction and a considerable improvement in system reliability is evidenced. - Highlights: • Proposed an optimal real time cost-benefit based demand response model. • Used signaling game theory for the information disturbances in deregulated market. • Introduced a correlation between the cost–benefit price and variable grid reliability. • Derive robust bidding strategies for utility/customers successful participation. �

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.

A tri-generation system based on polymer electrolyte fuel cell and desiccant wheel – Part A: Fuel cell system modelling and partial load analysis

International Nuclear Information System (INIS)

Najafi, Behzad; De Antonellis, Stefano; Intini, Manuel; Zago, Matteo; Rinaldi, Fabio; Casalegno, Andrea

2015-01-01

Highlights: • A mathematical model for a PEMFC based cogeneration system is developed. • Developed model is validated using the available experimental data. • Performance of the plant at full load conditions is investigated. • Performance indices while applying two different modifications are determined. • System’s performance with and without modifications at partial loads is investigated. - Abstract: Polymer Electrolyte Membrane Fuel Cell (PEMFC) based systems have recently received increasing attention as a viable alternative for meeting the residential electrical and thermal demands. However, as the intermittent demand profiles of a building can only be addressed by a tri-generative unit which can operate at partial loads, the variation of performance of the system at partial loads might affect its corresponding potential benefits significantly. Nonetheless, no previous study has been carried out on assessing the performance of this type of tri-generative systems in such conditions. The present paper is the first of a two part study dedicated to the investigation of the performance of a tri-generative system in which a PEMFC based system is coupled with a desiccant wheel unit. This study is focused on evaluating the performance of the PEMFC subsystem while operating at partial loads. Accordingly, a detailed mathematical model of the fuel cell subsystem is first developed and validated using the experimental data obtained from the plant’s and the fuel cell stack’s manufacturer. Next, in order to increase the performance of the plant, two modifications have been proposed and the resulting performance at partial load have been determined. The obtained results demonstrate that applying both modifications results in increasing the electrical efficiency of the plant by 5.5%. It is also shown that, while operating at partial loads, the electrical efficiency of the plant does not significantly change; the fact which corresponds to the trade-off between

Streamlining On-Demand Access to Joint Polar Satellite System (JPSS) Data Products for Weather Forecasting

Science.gov (United States)

Evans, J. D.; Tislin, D.

2017-12-01

Observations from the Joint Polar Satellite System (JPSS) support National Weather Service (NWS) forecasters, whose Advanced Weather Interactive Processing System (AWIPS) Data Delivery (DD) will access JPSS data products on demand from the National Environmental Satellite, Data, and Information Service (NESDIS) Product Distribution and Access (PDA) service. Based on the Open Geospatial Consortium (OGC) Web Coverage Service, this on-demand service promises broad interoperability and frugal use of data networks by serving only the data that a user needs. But the volume, velocity, and variety of JPSS data products impose several challenges to such a service. It must be efficient to handle large volumes of complex, frequently updated data, and to fulfill many concurrent requests. It must offer flexible data handling and delivery, to work with a diverse and changing collection of data, and to tailor its outputs into products that users need, with minimal coordination between provider and user communities. It must support 24x7 operation, with no pauses in incoming data or user demand; and it must scale to rapid changes in data volume, variety, and demand as new satellites launch, more products come online, and users rely increasingly on the service. We are addressing these challenges in order to build an efficient and effective on-demand JPSS data service. For example, on-demand subsetting by many users at once may overload a server's processing capacity or its disk bandwidth - unless alleviated by spatial indexing, geolocation transforms, or pre-tiling and caching. Filtering by variable (/ band / layer) may also alleviate network loads, and provide fine-grained variable selection; to that end we are investigating how best to provide random access into the variety of spatiotemporal JPSS data products. Finally, producing tailored products (derivatives, aggregations) can boost flexibility for end users; but some tailoring operations may impose significant server loads

A coupled nuclear reactor thermal energy storage system for enhanced load following operation

International Nuclear Information System (INIS)

Alameri, Saeed A.; King, Jeffrey C.

2013-01-01

Nuclear power plants operate most economically at a constant power level, providing base load electric power. In an energy grid containing a high fraction of renewable power sources, nuclear reactors may be subject to significantly variable power demands. These variable power demands can negatively impact the effective capacity factor of the reactor and result in severe economic penalties. Coupling a nuclear reactor to a large thermal energy storage block will allow the reactor to better respond to variable power demands. In the system described in this paper, a Prismatic core Advanced High Temperature Reactor supplies constant power to a lithium chloride molten salt thermal energy storage block that provides thermal power as needed to a closed Brayton cycle energy conversion system. During normal operation, the thermal energy storage block stores thermal energy during the night for use in the times of peak demand during the day. In this case, the nuclear reactor stays at a constant thermal power level. After a loss of forced circulation, the reactor reaches a shut down state in less than half an hour and the average fuel, graphite and coolant temperatures remain well within the design limits over the duration of the transient, demonstrating the inherent safety of the coupled system. (author)

Experimental analysis of flexibility change with different levels of power reduction by demand response activation on thermostat controlled loads

DEFF Research Database (Denmark)

Lakshmanan, Venkatachalam; Marinelli, Mattia; Hu, Junjie

2017-01-01

This paper studies the flexibility available with thermostatically controlled loads (TCLs) to provide power system services by demand response (DR) activation. Although the DR activation on TCLs can provide power system ancillary services, it is important to know how long such services can...... be provided for when different levels of power reduction are imposed. The flexibility change with different levels of power reduction is tested experimentally with domestic fridges used by real customers with unknown user interaction. The investigation quantifies the flexibility of household fridges...... and the impact of DR activation in terms of deviation in the average temperature. The maximum possible power reduction with the cluster of refrigerators is 67% and the available flexibility with the cluster of refrigerators is 10%. The resulting deviation in the average temperature is 14%....

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.

The effect of real-time pricing on load shifting in a highly renewable power system dominated by generation from the renewable sources of wind and photovoltaics

Science.gov (United States)

Kies, Alexander; Brown, Tom; Schlachtberger, David; Schramm, Stefan

2017-04-01

The supply-demand imbalance is a major concern in the presence of large shares of highly variable renewable generation from sources like wind and photovoltaics (PV) in power systems. Other than the measures on the generation side, such as flexible backup generation or energy storage, sector coupling or demand side management are the most likely option to counter imbalances, therefore to ease the integration of renewable generation. Demand side management usually refers to load shifting, which comprises the reaction of electricity consumers to price fluctuations. In this work, we derive a novel methodology to model the interplay of load shifting and provided incentives via real-time pricing in highly renewable power systems. We use weather data to simulate generation from the renewable sources of wind and photovoltaics, as well as historical load data, split into different consumption categories, such as, heating, cooling, domestic, etc., to model a simplified power system. Together with renewable power forecast data, a simple market model and approaches to incorporate sector coupling [1] and load shifting [2,3], we model the interplay of incentives and load shifting for different scenarios (e.g., in dependency of the risk-aversion of consumers or the forecast horizon) and demonstrate the practical benefits of load shifting. First, we introduce the novel methodology and compare it with existing approaches. Secondly, we show results of numerical simulations on the effects of load shifting: It supports the integration of PV power by providing a storage, which characteristics can be described as "daily" and provides a significant amount of balancing potential. Lastly, we propose an experimental setup to obtain empirical data on end-consumer load-shifting behaviour in response to price incentives. References [1] Brown, T., Schlachtberger, D., Kies. A., Greiner, M., Sector coupling in a highly renewable European energy system, Proc. of the 15th International Workshop on

Hybrid systems to address seasonal mismatches between electricity production and demand in nuclear renewable electrical grids

International Nuclear Information System (INIS)

Forsberg, Charles

2013-01-01

A strategy to enable zero-carbon variable electricity production with full utilization of renewable and nuclear energy sources has been developed. Wind and solar systems send electricity to the grid. Nuclear plants operate at full capacity with variable steam to turbines to match electricity demand with production (renewables and nuclear). Excess steam at times of low electricity prices and electricity demand go to hybrid fuel production and storage systems. The characteristic of these hybrid technologies is that the economic penalties for variable nuclear steam inputs are small. Three hybrid systems were identified that could be deployed at the required scale. The first option is the gigawatt-year hourly-to-seasonal heat storage system where excess steam from the nuclear plant is used to heat rock a kilometer underground to create an artificial geothermal heat source. The heat source produces electricity on demand using geothermal technology. The second option uses steam from the nuclear plant and electricity from the grid with high-temperature electrolysis (HTR) cells to produce hydrogen and oxygen. Hydrogen is primarily for industrial applications; however, the HTE can be operated in reverse using hydrogen for peak electricity production. The third option uses variable steam and electricity for shale oil production. -- Highlights: •A system is proposed to meet variable hourly to seasonal electricity demand. •Variable solar and wind electricity sent to the grid. •Base-load nuclear plants send variable steam for electricity and hybrid systems. •Hybrid energy systems can economically absorb gigawatts of variable steam. •Hybrid systems include geothermal heat storage, hydrogen, and shale-oil production

Price responsive load programs: U.S. experience in creating markets for peak demand reductions

International Nuclear Information System (INIS)

Goldberg, Miriam L.; Michelman, Thomas; Rosenberg, Mitchell

2003-01-01

Demand response programs use a variety of pricing mechanisms to induce end-use customers to reduce demand at specified periods. U.S. distribution utilities, regional market operators, and their regulators have implemented demand response programs with the objectives of improving electric system reliability, avoiding price spikes, and relieving local transmission congestion. This paper reviews the design and performance of market-linked demand response programs operated in 2001 and 2002, focusing on the relationship between program design and customer participation and the development of accurate and feasible methods to measure demand response at the facility level

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

Demand oriented biogas production to cover peak load; Bedarfsorientierte Biogasproduktion zur Erzeugung von Spitzenlaststrom. Weiterentwicklung der Biogastechnologie von Grundlast- zur Regelenergieerzeugung

Energy Technology Data Exchange (ETDEWEB)

Wallmann, Rainer; Ganagin, Waldemar; Loewe, Kirsten; Loewen, Achim [HAWK - Hochschule fuer angewandte Wissenschaft und Kunst, Fachhochschule Hildesheim, Holzminden, Goettingen (Germany)

2010-08-15

In contrast to solar and wind energy, biogas production is independent from environmental influences. The better part of biogas plants provide almost constant power and, thus, cover base load. However, it is possible to match biogas production with changing demand in different ways. Besides installing sufficiently dimensioned storages, a flexible generation of gas is possible by adjusting the digestion processes and installing appropriate control technologies. This enables flexible biogas production oriented towards customer demand. Peak load energy can be produced and marketed even without the advantage of reimbursement guaranteed by the renewable energy law. The Department of Sustainable Energy and Environmental Technology NEUTec at the University of Applied Science and Arts HAWK in Goettingen has carried out a research project to prove this concept of flexible biogas production. Operating a two-stage digestion plant, the capability to cover peak load was investigated by digesting energyrich liquid substrate in fixed bed reactors that represented the methanogenesis stage. These reactors showed extreme stability and flexibility. The promising results let expect a great potential of fixed bed reactors for on-demand biogas production from liquid substrates. In addition, with up to 80 % very high methane contents could be achieved in the produced gas. (orig.)

Solving unit commitment and economic load dispatch problems ...

African Journals Online (AJOL)

Economic Load Dispatch (ELD) and Unit Commitment (UC) are very important applications to predict the optimized cost of load in a power system. UC determines working states for existing generating units under some operational constraints and then optimizing the operation cost for all running units w.r.t. load demand ...

Effects of Demand Response on Retail and Wholesale Power Markets

Energy Technology Data Exchange (ETDEWEB)

Chassin, David P.; Kalsi, Karanjit

2012-07-26

Demand response has grown to be a part of the repertoire of resources used by utilities to manage the balance between generation and load. In recent years, advances in communications and control technology have enabled utilities to consider continuously controlling demand response to meet generation, rather than the other way around. This paper discusses the economic applications of a general method for load resource analysis that parallels the approach used to analyze generation resources and uses the method to examine the results of the US Department of Energy’s Olympic Peninsula Demonstration Testbed. A market-based closed-loop system of controllable assets is discussed with necessary and sufficient conditions on system controllability, observability and stability derived.

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.

Sensitivity analysis of energy demands on performance of CCHP system

International Nuclear Information System (INIS)

Li, C.Z.; Shi, Y.M.; Huang, X.H.

2008-01-01

Sensitivity analysis of energy demands is carried out in this paper to study their influence on performance of CCHP system. Energy demand is a very important and complex factor in the optimization model of CCHP system. Average, uncertainty and historical peaks are adopted to describe energy demands. The mix-integer nonlinear programming model (MINLP) which can reflect the three aspects of energy demands is established. Numerical studies are carried out based on energy demands of a hotel and a hospital. The influence of average, uncertainty and peaks of energy demands on optimal facility scheme and economic advantages of CCHP system are investigated. The optimization results show that the optimal GT's capacity and economy of CCHP system mainly lie on the average energy demands. Sum of capacities of GB and HE is equal to historical heating demand peaks, and sum of capacities of AR and ER are equal to historical cooling demand peaks. Maximum of PG is sensitive with historical peaks of energy demands and not influenced by uncertainty of energy demands, while the corresponding influence on DH is adverse

Demand for food products in Finland: A demand system approach

Directory of Open Access Journals (Sweden)

Ilkka P. Laurila

1994-07-01

Full Text Available The study was concerned with the estimation of food-demand parameters in a system context. The patterns of food consumption in Finland were presented over the period 1950-1991, and a complete demand system of food expenditures was estimated. Price and expenditure elasticities of demand were derived, and the results were used to obtain projections on future consumption. While the real expenditure on food has increased, the budget share of food has decreased. In the early 19505, combined Food-at-Home and Food-away-from-Home corresponded to about 40% of consumers’ total expenditure. In 1991 the share was 28%. There was a shift to meals eaten outside the home. While the budget share of Food-away-from-Home increased from 3% to 7% over the observation period, Food-at-Home fell from 37% to 21%, and Food-at-Home excluding Alcoholic Drinks fell from 34% to 16%. Within Food-at-Home, the budget shares of the broad aggregate groups, Animalia (food from animal sources, Beverages, and Vegetablia (food from vegetable sources, remained about the same over the four decades, while structural change took place within the aggregates. Within Animalia, consumption shifted from Dairy Products (other than Fresh Milk to Meat and Fish. Within Beverages, consumption shifted from Fresh Milk and Hot Drinks to Alcoholic Drinks and Soft Drinks. Within Vegetablia, consumption shifted from Flour to Fruits, while the shares of Bread and Cake and Vegetables remained about the same. As the complete demand system, the Almost Ideal Demand System (AIDS was employed. The conventional AIDS was extended by developing a dynamic generalisation of the model and allowing for systematic shifts in structural relationships over time. A four-stage budgeting system was specified, consisting of seven sub-systems (groups, and covering 18 food categories. Tests on parameter restrictions and misspecification tests were used to choose the most preferred model specification for each group. Generally

Dynamic inventory rationing strategies for inventory systems with two demand classes, Poisson demand and backordering

NARCIS (Netherlands)

Teunter, Ruud H.; Haneveld, Willem K. Klein

2008-01-01

We study inventory systems with two demand classes (critical and non-critical), Poisson demand and backordering. We analyze dynamic rationing strategies where the number of items reserved for critical demand depends on the remaining time until the next order arrives. Different from results in the

Optimum residential load management strategy for real time pricing (RTP) demand response programs

International Nuclear Information System (INIS)

Lujano-Rojas, Juan M.; Monteiro, Cláudio; Dufo-López, Rodolfo; Bernal-Agustín, José L.

2012-01-01

This paper presents an optimal load management strategy for residential consumers that utilizes the communication infrastructure of the future smart grid. The strategy considers predictions of electricity prices, energy demand, renewable power production, and power-purchase of energy of the consumer in determining the optimal relationship between hourly electricity prices and the use of different household appliances and electric vehicles in a typical smart house. The proposed strategy is illustrated using two study cases corresponding to a house located in Zaragoza (Spain) for a typical day in summer. Results show that the proposed model allows users to control their diary energy consumption and adapt their electricity bills to their actual economical situation. - Highlights: ► This work shows an optimal load management strategy for residential consumers. ► It has been considered the communication infrastructure of the future smart grid. ► A study case shows the optimal utilization of some appliances and electric vehicles. ► Results showed that the proposed model allows users to reduce their electricity bill.

Performance improvement of a battery/PV/fuel cell/grid hybrid energy system considering load uncertainty modeling using IGDT

International Nuclear Information System (INIS)

Nojavan, Sayyad; Majidi, Majid; Zare, Kazem

2017-01-01

Highlights: • Optimum performance of PV/battery/fuel cell/grid hybrid system under load uncertainty. • Employing information gap decision theory (IGDT) to model the load uncertainty. • Robustness and opportunity functions of IGDT are modeled for risk-averse and risk-taker. • Robust strategy of hybrid system's operation obtained from robustness function. • Opportunistic strategy of hybrid system's operation obtained from opportunity function. - Abstract: Nowadays with the speed that electrical loads are growing, system operators are challenged to manage the sources they use to supply loads which means that that besides upstream grid as the main sources of electric power, they can utilize renewable and non-renewable energy sources to meet the energy demand. In the proposed paper, a photovoltaic (PV)/fuel cell/battery hybrid system along with upstream grid has been utilized to supply two different types of loads: electrical load and thermal load. Operators should have to consider load uncertainty to manage the strategies they employ to supply load. In other words, operators have to evaluate how load variation would affect their energy procurement strategies. Therefore, information gap decision theory (IGDT) technique has been proposed to model the uncertainty of electrical load. Utilizing IGDT approach, robustness and opportunity functions are achieved which can be used by system operator to take the appropriate strategy. The uncertainty modeling of load enables operator to make appropriate decisions to optimize the system’s operation against possible changes in load. A case study has been simulated to validate the effects of proposed technique.

Load Management in District Heating Operation

OpenAIRE

Li, Hongwei; Wang, Stephen Jia

2015-01-01

Smooth operation of district heating system will avoid installation of expensive peak heat boilers, improve plant partial load performance, increase the system redundancy for further network expansion and improve its resilience to ensuresecurity of supply during severe heating seasons. The peak heating load can be reduced through building demand side management. The building thermal mass can be used to shift the heating supply under the circumstance withoutjeopardizing the consumer thermal co...

Pneumatic load compensating or controlling system

Science.gov (United States)

Rogers, J. R. (Inventor)

1975-01-01

A pneumatic load compensating or controlling system for restraining a load with a predetermined force or applying a predetermined force to the load is described; it includes a source of pressurized air, a one-way pneumatic actuator operatively connected to a load, and a fluid conduit fluidically connecting the actuator with the source of pressurized air. The actuator is of the piston and cylinder type, and the end of the fluid conduit is connected to the upper or lower portion of the cylinder whereby the actuator alternatively and selectively restrains the load with a predetermined force or apply a predetermined force to the load. Pressure regulators are included within the system for variably selectively adjusting the pressurized fluid to predetermined values as desired or required; a pressure amplifier is included within the system for multiplying the pressurized values so as to achieve greater load forces. An accumulator is incorporated within the system as a failsafe operating mechanism, and visual and aural alarm devices, operatively associated with pressure detecting apparatus, readily indicate the proper or improper functioning of the system.

Emerging technologies for demand side management. Demand side management jitsugen no tame no saishin gijutsu

Energy Technology Data Exchange (ETDEWEB)

Suzuki, H; Iyoda, I [Mitsubishi Electric Corp., Tokyo (Japan)

1993-11-05

This paper explains the latest situation in hardware technologies to realize the demand side management, divided into the following technologies: communications technology, measurement technology, client information system technology, load controlling technology, home automation technology, and energy storing and saving technologies. Speaking of the communications technology, information exchange between the supply side and the demand side is important in the demand side management, whereas a technology intended of automatic power distribution and automatic meter-reading is advancing in development. The technology covers transmissions using from power lines and telephone lines to optical cables and wireless communications. Power line communications using power transmission lines as communication lines are simple and economical, but weak against noise, and not suitable for long-distance communications. Wireless communications have been drawing attentions along with the development of mobile communication device technologies. These technologies will give benefits to electric power companies in the initial stage of their use, such as for load investigation and general automation in power distribution. They would shift to benefiting users in about 2010 covering from security information such as about power interruption to publicity information and educations. 8 refs., 8 figs., 1 tab.

Metabolic Demand and Internal Training Load in Technical-Tactical Training Sessions of Professional Futsal Players.

Science.gov (United States)

Wilke, Carolina F; Ramos, Guilherme P; Pacheco, Diogo A S; Santos, Weslley H M; Diniz, Mateus S L; Gonçalves, Gabriela G P; Marins, João C B; Wanner, Samuel P; Silami-Garcia, Emerson

2016-08-01

Wilke, CF, Ramos, GP, Pacheco, DAS, Santos, WHM, Diniz, MSL, Gonçalves, GGP, Marins, JCB, Wanner, SP, and Silami-Garcia, E. Metabolic demand and internal training load in technical-tactical training sessions of professional futsal players. J Strength Cond Res 30(8): 2330-2340, 2016-The aim of the study was to characterize aspects of technical-tactical training sessions of a professional futsal team. We addressed 4 specific aims: characterize the metabolic demands and intensity of these training sessions, compare the training intensity among players of different positions, compare the intensity of different futsal-specific activities (4 × 4, 6 × 4, and match simulation), and investigate the association between an objective (training impulse; TRIMP) and a subjective method (session rating of perceived exertion; sRPE) of measuring a player's internal training load. Twelve top-level futsal players performed an incremental exercise to determine their maximal oxygen consumption, maximal heart rate (HRmax), ventilatory threshold (VT), and respiratory compensation point (RCP). Each player's HR and RPE were measured and used to calculate energy expenditure, TRIMP, and sRPE during 37 training sessions over 8 weeks. The average intensity was 74 ± 4% of HRmax, which corresponded to 9.3 kcal·min. The players trained at intensities above the RCP, between the RCP and VT and below the VT for 20 ± 8%, 28 ± 6%, and 51 ± 10% of the session duration, respectively. Wingers, defenders, and pivots exercised at a similar average intensity but with different intensity distributions. No difference in intensity was found between the 3 typical activities. A strong correlation between the average daily TRIMP and sRPE was observed; however, this relationship was significant for only 4 of 12 players, indicating that sRPE is a useful tool for monitoring training loads but that it should be interpreted for each player individually rather than collectively.

Load Management in Residential Buildings Considering Techno-Economic and Environmental Aspects

Energy Technology Data Exchange (ETDEWEB)

Abaravicius, Juozas

2004-12-01

Load problems in electricity markets occur both on the supply and demand side and can have technical, economic and even political causes. Commonly, such problems have been solved by expanding production and/or distribution capacity, importing electricity or by load management. Load management is a techno-economic measure for harmonizing the relations between supply and demand sides, optimizing power generation and transmission and increasing security of supply. Interest in load management differs depending on the perspective of the actors involved: from customer, utility, or producer to state policy maker. The problem of load demand and load management in residential sector is in this thesis approached from different perspectives, i.e. technical, economic, and environmental. The study does not go deep into detailed analyses of each perspective, but rather aims to establish and analyze the links between them. This trans-disciplinary approach is the key methodological moment used in the research work performed by the research group for load management in buildings at the Lund Institute of Technology. The key objective of this study is to analyze load demand variation and load management possibilities in residential sector, particularly detached and semi-detached houses, to experimentally test and analyze the conditions and potential of direct load management from customer and utility viewpoint. Techno-economic and environmental aspects are investigated. The study was performed in collaboration with one electric utility in Southern Sweden. Ten electric-heated houses were equipped with extra meters, enabling hourly load measurements for heating, hot water and total electricity use. Household heating and hot water systems were controlled by the utility using an existing remote reading and monitoring system. The residents noticed some of the control periods, although they didn't express any larger discomfort. The experiments proved that direct load management might

Electrical Load Survey and Forecast for a Decentralized Hybrid ...

African Journals Online (AJOL)

Electrical Load Survey and Forecast for a Decentralized Hybrid Power System at Elebu, Kwara State, Nigeria. ... Nigerian Journal of Technology ... The paper reports the results of electrical load demand and forecast for Elebu rural community ...

Software Sub-system in Loading Automatic Test System for the Measurement of Power Line Filters

Directory of Open Access Journals (Sweden)

Yu Bo

2017-01-01

Full Text Available The loading automatic test system for measurement of power line filters are in urgent demand. So the software sub-system of the whole test system was proposed. Methods: structured the test system based on the virtual instrument framework, which consisted of lower and up computer and adopted the top down approach of design to perform the system and its modules, according to the measurement principle of the test system. Results: The software sub-system including human machine interface, data analysis and process software, expert system, communication software, control software in lower computer, etc. had been designed. Furthermore, it had been integrated into the entire test system. Conclusion: This sub-system provided a fiendly software platform for the whole test system, and had many advantages such as strong functions, high performances, low prices. It not only raises the test efficiency of EMI filters, but also renders some creativities.

Load management in electrical networks. Objectives, methods, prospects

International Nuclear Information System (INIS)

Gabioud, D.

2008-01-01

This illustrated article takes up the problems related to the variation of the load in electricity networks. How to handle the peak load? Different solutions in the energy demand management are discussed. Method based on the price, method based on the reduction of the load by electric utilities. Information systems are presented which gives the consumer the needed data to participate in the local load management.

Optimal load allocation of complex ship power plants

International Nuclear Information System (INIS)

Baldi, Francesco; Ahlgren, Fredrik; Melino, Francesco; Gabrielii, Cecilia; Andersson, Karin

2016-01-01

Highlights: • The optimal operation of the prime movers of hybrid ship power plants is addressed. • Both mechanical, electric and thermal power demand are considered. • The problem is modelled as a mixed integer-nonlinear programming problem. • Up to 3% savings can be achieved with hybrid power plants. • Including the thermal power demand improves the solution by up to 4%. - Abstract: In a world with increased pressure on reducing fuel consumption and carbon dioxide emissions, the cruise industry is growing in size and impact. In this context, further effort is required for improving the energy efficiency of cruise ship energy systems. In this paper, we propose a generic method for modelling the power plant of an isolated system with mechanical, electric and thermal power demands and for the optimal load allocation of the different components that are able to fulfil the demand. The optimisation problem is presented in the form of a mixed integer linear programming (MINLP) problem, where the number of engines and/or boilers running is represented by the integer variables, while their respective load is represented by the non-integer variables. The individual components are modelled using a combination of first-principle models and polynomial regressions, thus making the system nonlinear. The proposed method is applied to the load-allocation problem of a cruise ship sailing in the Baltic Sea, and used to compare the existing power plant with a hybrid propulsion plant. The results show the benefits brought by using the proposing method, which allow estimating the performance of the hybrid system (for which the load allocation is a non-trivial problem) while also including the contribution of the heat demand. This allows showing that, based on a reference round voyage, up to 3% savings could be achieved by installing the proposed system, compared to the existing one, and that a NPV of 11 kUSD could be achieved already 5 years after the installation of the

Flexible Demand Control to Enhance the Dynamic Operation of Low Voltage Networks

DEFF Research Database (Denmark)

Diaz de Cerio Mendaza, Iker; Szczesny, Ireneusz Grzegorz; Pillai, Jayakrishnan Radhakrishna

2015-01-01

Moving towards a carbon free energy system has become an objective for many countries nowadays. Among other changes, the electrification of strategic sectors such as heating and transportation is inevitable. As a consequence, the current power system load will substantially increase...... for controlling the demand response of a low voltage grid. This is designed to; i) maximize the grid utilization, thereby reducing the need for reinforcement, ii) accommodate the maximum number of flexible loads and iii) satisfy the power and comfort requirements from each of the consumers in the network....... In this context, the nature of the expected loads (heat pumps, plug-in electric vehicles, etc.) makes the low voltage networks specially targeted. A promising solution to overcome the challenges resulting from their grid integration, is demand response. This paper introduces a hierarchical structure...

Analysis of load reduction possibilities using a hydraulic soft yaw system for a 5-MW turbine and its sensitivity to yaw-bearing friction

DEFF Research Database (Denmark)

Stubkier, S.; Pedersen, H. C.; Jonkman, J. M.

2014-01-01

With the increasing size of wind turbines and with increasing lifetime demands, new methods for load reduction in the turbines need to be examined. One method is to make the yaw system of the turbine flexible, thereby dampening the loads to the system. This paper presents a hydraulic soft yaw...... concept and investigates the effect this has on critical loads in the turbine. To analyze the system, a novel friction model is developed and implemented for the yaw system using the NREL 5-MW turbine in the aerodynamic code FAST. Based on this model, the influence of friction is investigated...

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.

ECONOMETRIC ANALYSIS OF CEREAL DEMAND IN MOROCCO USING THE ALMOST IDEAL DEMAND SYSTEM

Directory of Open Access Journals (Sweden)

Sara Essaten

2018-04-01

Full Text Available Following up the agricultural policy in Morocco and enforcing it, the new strategy Green Morocco Plan (GMP launched in 2008 also stressed on the cereals’ supply. Meantime, despite their significant nutritional role, little attention has been paid to the demand side. This paper intends to perform an econometric analysis of the demand of five main cereals - Common wheat, Durum wheat, Barley, Corn and Rice- using a linear version of the flexible Almost Ideal Demand System (LA/AIDS model. A Seemingly Unrelated Regression (SUR approach has been applied to the demand system equations with annual data covering the period from 1980 to 2015. At the overall, regular econometric restrictions (stability, structural separability, validity, etc. have been respected our results suggest that the relations of complementarity or substitution are not determining in the cereal bundle in Morocco. Also, the Moroccan consumer behavior is characterized by a strong sensibility towards common wheat price’s changes and by a difficult access for the durum wheat as it is considered as luxury good.

Influence of Shading on Cooling Energy Demand

Science.gov (United States)

Rabczak, Sławomir; Bukowska, Maria; Proszak-Miąsik, Danuta; Nowak, Krzysztof

2017-10-01

The article presents an analysis of the building cooling load taking into account the variability of the factors affecting the size of the heat gains. In order to minimize the demand for cooling, the effect of shading elements installed on the outside on the windows and its effect on size of the cooling capacity of air conditioning system for the building has been estimated. Multivariate building cooling load calculations to determine the size of the reduction in cooling demand has derived. Determination of heat gain from the sun is laborious, but gives a result which reflects the influence of the surface transparent partitions, devices used as sunscreen and its location on the building envelope in relation to the world, as well as to the internal heat gains has great attention in obtained calculation. In this study, included in the balance sheet of solar heat gains are defined in three different shading of windows. Calculating the total demand cooling is made for variants assuming 0% shading baffles transparent, 50% shading baffles transparent external shutters at an angle of 45 °, 100% shading baffles transparent hours 12 from the N and E and from 12 from the S and W of the outer slat blinds. The calculation of the average hourly cooling load was taken into account the option assuming the hypothetical possibility of default by up to 10% of the time assumed the cooling season temperatures in the rooms. To reduce the consumption of electricity energy in the cooling system of the smallest variant identified the need for the power supply for the operation of the cooling system. Also assessed the financial benefits of the temporary default of comfort.

Application of PSAT to Load Flow Analysis with STATCOM under Load Increase Scenario and Line Contingencies

Science.gov (United States)

Telang, Aparna S.; Bedekar, P. P.

2017-09-01

Load flow analysis is the initial and essential step for any power system computation. It is required for choosing better options for power system expansion to meet with ever increasing load demand. Implementation of Flexible AC Transmission System (FACTS) device like STATCOM, in the load flow, which is having fast and very flexible control, is one of the important tasks for power system researchers. This paper presents a simple and systematic approach for steady state power flow calculations with FACTS controller, static synchronous compensator (STATCOM) using command line usage of MATLAB tool-power system analysis toolbox (PSAT). The complexity of MATLAB language programming increases due to incorporation of STATCOM in an existing Newton-Raphson load flow algorithm. Thus, the main contribution of this paper is to show how command line usage of user friendly MATLAB tool, PSAT, can extensively be used for quicker and wider interpretation of the results of load flow with STATCOM. The novelty of this paper lies in the method of applying the load increase pattern, where the active and reactive loads have been changed simultaneously at all the load buses under consideration for creating stressed conditions for load flow analysis with STATCOM. The performance have been evaluated on many standard IEEE test systems and the results for standard IEEE-30 bus system, IEEE-57 bus system, and IEEE-118 bus system are presented.

Transport aircraft loading and balancing system: Using a CLIPS expert system for military aircraft load planning

Science.gov (United States)

Richardson, J.; Labbe, M.; Belala, Y.; Leduc, Vincent

1994-01-01

The requirement for improving aircraft utilization and responsiveness in airlift operations has been recognized for quite some time by the Canadian Forces. To date, the utilization of scarce airlift resources has been planned mainly through the employment of manpower-intensive manual methods in combination with the expertise of highly qualified personnel. In this paper, we address the problem of facilitating the load planning process for military aircraft cargo planes through the development of a computer-based system. We introduce TALBAS (Transport Aircraft Loading and BAlancing System), a knowledge-based system designed to assist personnel involved in preparing valid load plans for the C130 Hercules aircraft. The main features of this system which are accessible through a convivial graphical user interface, consists of the automatic generation of valid cargo arrangements given a list of items to be transported, the user-definition of load plans and the automatic validation of such load plans.

Design and Modelling of Thermostatically Controlled Loads as Frequency Controlled Reserve

DEFF Research Database (Denmark)

Xu, Zhao; Østergaard, Jacob; Togeby, Mikael

2007-01-01

Using demand as frequency controlled reserve (DFR) is beneficial to power systems in many aspects. To study the impacts of this technology on power system operation, control logics and simulation models of relevant loads should be carefully developed. Two advanced control logics for using demand...... frequency, is developed. The developed simulation model is able to represent a variety of aggregated thermostatically controlled loads, such as heaters or refrigerators. Uncertainties including customer behaviours and ambient temperature variation are also modelled. Preliminary simulation results...

Mobile Learning Application Interfaces: First Steps to a Cognitive Load Aware System

Science.gov (United States)

Deegan, Robin

2013-01-01

Mobile learning is a cognitively demanding application and more frequently the ubiquitous nature of mobile computing means that mobile devices are used in cognitively demanding environments. This paper examines the nature of this use of mobile devices from a Learning, Usability and Cognitive Load Theory perspective. It suggests scenarios where…

Intelligent demand side management of residential building energy systems

Science.gov (United States)

Sinha, Maruti N.

Advent of modern sensing technologies, data processing capabilities and rising cost of energy are driving the implementation of intelligent systems in buildings and houses which constitute 41% of total energy consumption. The primary motivation has been to provide a framework for demand-side management and to improve overall reliability. The entire formulation is to be implemented on NILM (Non-Intrusive Load Monitoring System), a smart meter. This is going to play a vital role in the future of demand side management. Utilities have started deploying smart meters throughout the world which will essentially help to establish communication between utility and consumers. This research is focused on investigation of a suitable thermal model of residential house, building up control system and developing diagnostic and energy usage forecast tool. The present work has considered measurement based approach to pursue. Identification of building thermal parameters is the very first step towards developing performance measurement and controls. The proposed identification technique is PEM (Prediction Error Method) based, discrete state-space model. The two different models have been devised. First model is focused toward energy usage forecast and diagnostics. Here one of the novel idea has been investigated which takes integral of thermal capacity to identify thermal model of house. The purpose of second identification is to build up a model for control strategy. The controller should be able to take into account the weather forecast information, deal with the operating point constraints and at the same time minimize the energy consumption. To design an optimal controller, MPC (Model Predictive Control) scheme has been implemented instead of present thermostatic/hysteretic control. This is a receding horizon approach. Capability of the proposed schemes has also been investigated.

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

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.

A mathematical programming framework for energy planning in services' sector buildings under uncertainty in load demand: The case of a hospital in Athens

International Nuclear Information System (INIS)

Mavrotas, George; Diakoulaki, Danae; Florios, Kostas; Georgiou, Paraskevas

2008-01-01

The aim of this paper is to provide an integrated modeling and optimization framework for energy planning in large consumers of the services' sector based on mathematical programming. The power demand is vaguely known and the underlying uncertainty is modeled using elements from fuzzy set theory. The defined fuzzy programming model is subsequently transformed to an equivalent multi-objective problem, where the minimization of cost and the maximization of demand satisfaction are the objective functions. The Pareto optimal solutions of this problem are obtained using a novel version of the ε-constraint method and represent the possibly optimal solutions of the original problem under uncertainty. In the present case, in order to select the most preferred Pareto optimal solution, the minimax regret criterion is properly used to indicate the preferred configuration of the system (i.e. the size of the installed units) given the load uncertainty. Furthermore, the paper proposes a model reduction technique that can be used in similar cases and further examines its effect in the final results. The above methodology is applied to the energy rehabilitation of a hospital in the Athens area. The technologies under consideration include a combined heat and power unit for providing power and heat, an absorption unit and/or a compression unit for providing cooling load. The obtained results demonstrate that, increasing the degree of demand satisfaction, the total annual cost increases almost linearly. Although data compression allows obtaining realistic results, the size of the proposed units might be slightly changed

Modelling self-optimised short term load forecasting for medium voltage loads using tunning fuzzy systems and Artificial Neural Networks

International Nuclear Information System (INIS)

Mahmoud, Thair S.; Habibi, Daryoush; Hassan, Mohammed Y.; Bass, Octavian

2015-01-01

Highlights: • A novel Short Term Medium Voltage (MV) Load Forecasting (STLF) model is presented. • A knowledge-based STLF error control mechanism is implemented. • An Artificial Neural Network (ANN)-based optimum tuning is applied on STLF. • The relationship between load profiles and operational conditions is analysed. - Abstract: This paper presents an intelligent mechanism for Short Term Load Forecasting (STLF) models, which allows self-adaptation with respect to the load operational conditions. Specifically, a knowledge-based FeedBack Tunning Fuzzy System (FBTFS) is proposed to instantaneously correlate the information about the demand profile and its operational conditions to make decisions for controlling the model’s forecasting error rate. To maintain minimum forecasting error under various operational scenarios, the FBTFS adaptation was optimised using a Multi-Layer Perceptron Artificial Neural Network (MLPANN), which was trained using Backpropagation algorithm, based on the information about the amount of error and the operational conditions at time of forecasting. For the sake of comparison and performance testing, this mechanism was added to the conventional forecasting methods, i.e. Nonlinear AutoRegressive eXogenous-Artificial Neural Network (NARXANN), Fuzzy Subtractive Clustering Method-based Adaptive Neuro Fuzzy Inference System (FSCMANFIS) and Gaussian-kernel Support Vector Machine (GSVM), and the measured forecasting error reduction average in a 12 month simulation period was 7.83%, 8.5% and 8.32% respectively. The 3.5 MW variable load profile of Edith Cowan University (ECU) in Joondalup, Australia, was used in the modelling and simulations of this model, and the data was provided by Western Power, the transmission and distribution company of the state of Western Australia.

Basic analysis on the load management in consumer section

Energy Technology Data Exchange (ETDEWEB)

Tezuka, Tetsuo; Nishikawa, Eiichi

1988-05-01

The load management of the energy (electric power, gas and oil products) in consumer section means to move demand characteristics in desirable directions. The demand characteristics are represented by the energy consumption characteristics along time and their annual sum. The load management is analyzed here from a more practical point of view. As the total thermal demand has been fixed to some extent from the aspect of a total system, the trade-off occurs among objectives of industries. For the quantitative consistency, the model analysis is effective. Changes in the consumers' attitude have been observed as indicated by the cogeneration, heat storage technology and automatic energy management by consumers. Techniques for changing the demand characteristics include the charging system, financial aids for equipment installation, favorable provisions in taxation, law revision and marketing. Stable supply and improved consumption are the future tasks. (2 figs, 6 tabs, 28 refs)

Real-Time Demand Side Management Algorithm Using Stochastic Optimization

Directory of Open Access Journals (Sweden)

Moses Amoasi Acquah

2018-05-01

Full Text Available A demand side management technique is deployed along with battery energy-storage systems (BESS to lower the electricity cost by mitigating the peak load of a building. Most of the existing methods rely on manual operation of the BESS, or even an elaborate building energy-management system resorting to a deterministic method that is susceptible to unforeseen growth in demand. In this study, we propose a real-time optimal operating strategy for BESS based on density demand forecast and stochastic optimization. This method takes into consideration uncertainties in demand when accounting for an optimal BESS schedule, making it robust compared to the deterministic case. The proposed method is verified and tested against existing algorithms. Data obtained from a real site in South Korea is used for verification and testing. The results show that the proposed method is effective, even for the cases where the forecasted demand deviates from the observed demand.

Ontario demand forecast from January 2004 to December 2013

International Nuclear Information System (INIS)

2003-01-01

This document examined the demand forecast for electricity on the Independent Market Operator (IMO)-controlled grid in Ontario for the period 2004-2013. It serves as an assessment tool to determine whether existing and proposed generation and transmission facilities in the province will be sufficient to meet future electricity needs. Changes in methodology have been made to allow for an hourly peak versus the previously reported 20-minute peak value. Actual data through to the end of October 2002 was used to re-estimate energy demand. Compared to other developed countries, the outlook for the Canadian economy is optimistic. In addition, the economic forecast is better than that which formed the basis of the last ten-year forecast. Energy demand in the median growth scenario is increasing at an annual rate of 1.1 per cent rather than 0.9 per cent for the forecasted period of 2003-2012. The combination of a higher growth rate and a higher starting point results in a 2010 forecast of 168 TWh. It is expected that peak demand will grow faster than in the previous forecast. Summer peak demand averaging an annual growth of 1.3 per cent is forecasted for the period 2003-2012, with winter peak demand averaging a growth of 0.8 per cent. Under normal weather conditions, the electricity system is expected to peak in the summer of 2005 due to the continued demand for cooling load. However, under an extreme weather scenario, the system is already summer peaking. The improved economic outlook and higher starting point resulted in a higher forecast for energy. The electricity system is expected to winter peak during the first years of the forecasted period. The heating load is not expected to experience rapid growth in the next few years. 15 tabs., 14 figs

Criteria for demand response systems

NARCIS (Netherlands)

Lampropoulos, I.; Kling, W.L.; Bosch, van den P.P.J.; Ribeiro, P.F.; Berg, van den J.

2013-01-01

The topic of demand side management is currently becoming more important than ever, in parallel with the further deregulation of the electricity sector, and the increasing integration of renewable energy sources. A historical review of automation integration in power system control assists in

Smart Demand for Improving Short-term Voltage Control on Distribution Networks

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; P. Da Silva, Luiz C.; Xu, Zhao

2009-01-01

customer integration to aid power system performance is almost inevitable. This study introduces a new type of smart demand side technology, denoted demand as voltage controlled reserve (DVR), to improve short-term voltage control, where customers are expected to play a more dynamic role to improve voltage...... control. The technology can be provided by thermostatically controlled loads as well as other types of load. This technology is proven to be effective in case of distribution systems with a large composition of induction motors, where the voltage presents a slow recovery characteristic due to deceleration...... of the motors during faults. This study presents detailed models, discussion and simulation tests to demonstrate the technical viability and effectiveness of the DVR technology for short-term voltage control....

Modeling and simulation of the power demand and supply of a hydrothermal power generating system

International Nuclear Information System (INIS)

Pronini, R.A.

1996-01-01

Security of supply of electric energy is measured by the capacity to cover the energy demand and power of a supply grid. This coverage is important because the winter peak load period in Switzerland will become problematical in the near future. The objective of this research project is to analyze the ability of a power generating system to satisfy the power requirements of the corresponding supply network. The behaviour of the energy system in critical cases (loss of the largest generator, lack of available power from an external supplier or reduced capacity for energy storage) is tested for the present situation and for the rise in the annual load. The simulation of the load of the supply network is carried out by using a model developed for this project. This model is based on the analysis of half-hourly changes of load and on the statistical maximum values. The power generating system consists of nuclear generating units, hydro units with large reservoirs, run of the river installations and imported energy. Standby units such as gas turbines, spot market and coal-fired power stations are also available. Stochastic and deterministic energy and power models have been developed for the various power stations of the hydrothermal power system. In the case of nuclear power stations, a model has been developed on the basis of the output level, production losses and time and length of outages. The possible feeder streams of the run of the river installations and of the hydro units with a large reservoir are simulated using stochastic methods based on the historical values of the last 35 years. The commitment of the hydro units depends on the peak load requirements. The load and capacity over a period of several days and weeks have been simulated with stochastic models based on the Monte Carlo method and constantly (by half hour intervals) compared. In this manner each month can be simulated. (author) figs., tabs., 46 refs

Exploring Demand Charge Savings from Commercial Solar

Energy Technology Data Exchange (ETDEWEB)

Darghouth, Naim [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Barbose, Galen [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mills, Andrew [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wiser, Ryan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gagnon, Pieter [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bird, Lori [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2017-07-31

Commercial retail electricity rates commonly include a demand charge component, based on some measure of the customer’s peak demand. Customer-sited solar PV can potentially reduce demand charges, but the magnitude of these savings can be difficult to predict, given variations in demand charge designs, customer loads, and PV generation profiles. Moreover, depending on the circumstances, demand charges from solar may or may not align well with associated utility cost savings. Lawrence Berkeley National Laboratory (Berkeley Lab) and the National Renewable Energy Laboratory (NREL) are collaborating in a series of studies to understand how solar PV can reduce demand charge levels for a variety of customer types and demand charges designs. Previous work focused on residential customs with solar. This study, instead, focuses on commercial customers and seeks to understand the extent and conditions under which rooftop can solar reduce commercial demand charges. To answer these questions, we simulate demand charge savings for a broad range of commercial customer types, demand charge designs, locations, and PV system characteristics. This particular analysis does not include storage, but a subsequent analysis in this series will evaluate demand charge savings for commercial customers with solar and storage.

Recent research in electric power pricing and load management

International Nuclear Information System (INIS)

Tabors, R.D.

1990-01-01

Reliable electricity is a necessity for industrial and economic development. In the developing nations, power systems are growing rapidly. Typically, demand for electricity grows faster than either total energy demand or gross domestic product. Load management systems and innovative tariff structures offer to utilities potentially significant operating and capital cost savings through increased efficiency. Benefits must be weighed against the costs of implementation, communication, control and monitoring. When comparing developed and developing country utilities one may conclude that the developing countries may have far more to gain from direct load management and innovative tariff systems. They may be able to introduce variable (cost dependent/time dependent) reliability as opposed to the constant reliability expected in the USA and Western Europe; and many utilities may be able to design more flexible (and less costly) utility systems around a combination of load management and pricing structures, that encourage a higher level of interaction between customer and utility than is the case in the more developed utilities. (author). 84 refs

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

Urban fuel demand in Ethiopia: an almost‐ideal demand system ...

African Journals Online (AJOL)

This paper investigates the opportunities for reducing the pressure of urban centers on rural forest areas, using a dataset of 350 urban households in Tigrai in northern Ethiopia. We applied an almost‐ideal demand system to fuels. The results suggest that reducing the pressure of urban centers on local forests cannot be ...

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, .......g. building energy simulations. •The demand level of houses with different number of occupants is well captured....

Modeling workforce demand in North Dakota: a System Dynamics approach

OpenAIRE

Muminova, Adiba

2015-01-01

This study investigates the dynamics behind the workforce demand and attempts to predict the potential effects of future changes in oil prices on workforce demand in North Dakota. The study attempts to join System Dynamics and Input-Output models in order to overcome shortcomings in both of the approaches and gain a more complete understanding of the issue of workforce demand. A system dynamics simulation of workforce demand within different economic sector...

Reducing Demand Charges and Onsite Generation Variability Using Behind-the-Meter Energy Storage

Energy Technology Data Exchange (ETDEWEB)

Bhattarai, Bishnu P.; Myers, Kurt S.; Bush, Jason W.

2017-04-01

Electric utilities in the United States are increasingly employing demand charges and/or real-time pricing. This directive is bringing potential opportunities in deploying behindthe-meter energy storage (BMES) systems for various grid functionalities. This study quantifies techno-economic benefits of BMES in reducing demand charge and smoothing load/generation intermittencies, and determines how those benefits vary with onsite distributed photovoltaic. We proposed a two-stage control algorithm, whereby the first stage proactively determines costoptimal BMES configuration for reducing peak-demands and demand charges, and the second stage adaptively compensates intermittent generations and short load spikes that may otherwise increase the demand charges. The performance of the proposed algorithm is evaluated through a 24 hours time sweep simulation performed using data from smart microgrid testbed at Idaho National Laboratory (INL). The simulation results demonstrated that this research provides a simple but effective solution for peak shaving, demand charge reductions, and smoothing onsite PV variability.

An energy credit based incentive mechanism for the direct load control of residential HVAC systems incorporation in day-ahead planning

NARCIS (Netherlands)

Erdinc, O.; Tascikaraoglu, A.; Paterakis, N.G.; Catalao, J.P.S.

2017-01-01

The increasing operational complexity of power systems considering the higher renewable energy penetration and changing load characteristics, together with the recent developments in the ICT field have led to more research and implementation efforts related to the activation of the demand side. In

Direct Load Control by AC Frequency Modulation

DEFF Research Database (Denmark)

Douglass, Philip James; You, Shi

2012-01-01

Fine-grained under frequency load shedding called “demand as a frequency controlled reserve“ (DFCR) has been shown to be a promising method of providingfrequency regulation service from distributed loads [1]. Micro-grids with a large portion of intermittent renewable generation will benefit greatly...... from this technology because their low inertia. The paper proposes a operating procedure for utilizing DFCR loads for energy balancing, expanding DFCR’s well known role as a power balancing resource. The system operator can use DFCR for energy balancing by adjusting the frequency controller...... of generators to schedule off-nominal system frequency values. The feasibility of the proposed system is evaluated on an existing small island power system....

Optimal electricity dispatch on isolated mini-grids using a demand response strategy for thermal storage backup with genetic algorithms

International Nuclear Information System (INIS)

Neves, Diana; Silva, Carlos A.

2015-01-01

The present study uses the DHW (domestic hot water) electric backup from solar thermal systems to optimize the total electricity dispatch of an isolated mini-grid. The proposed approach estimates the hourly DHW load, and proposes and simulates different DR (demand response) strategies, from the supply side, to minimize the dispatch costs of an energy system. The case study consists on optimizing the electricity load, in a representative day with low solar radiation, in Corvo Island, Azores. The DHW backup is induced by three different demand patterns. The study compares different DR strategies: backup at demand (no strategy), pre-scheduled backup using two different imposed schedules, a strategy based on linear programming, and finally two strategies using genetic algorithms, with different formulations for DHW backup – one that assigns number of systems and another that assigns energy demand. It is concluded that pre-determined DR strategies may increase the generation costs, but DR strategies based on optimization algorithms are able to decrease generation costs. In particular, linear programming is the strategy that presents the lowest increase on dispatch costs, but the strategy based on genetic algorithms is the one that best minimizes both daily operation costs and total energy demand, of the system. - Highlights: • Integrated hourly model of DHW electric impact and electricity dispatch of isolated grid. • Proposal and comparison of different DR (demand response) strategies for DHW backup. • LP strategy presents 12% increase on total electric load, plus 5% on dispatch costs. • GA strategy presents 7% increase on total electric load, plus 8% on dispatch costs

A complex bid model and strategy for dispatchable loads in real-time market-based demand response

NARCIS (Netherlands)

Babar, M.; Nguyen, P.H.; Cuk, V.; Kamphuis, I.G.; Kling, W.L.

2014-01-01

The power system is moving into the new era of Smart Grid with the help of advance ICT and other developed technologies. These advancements made the demand response as an integral part of power and energy systems. Nowadays, the concept of Energy bidding is emerging in the Market-based Demand

Demand for electrical energy

International Nuclear Information System (INIS)

Bergougnoux, J.; Fouquet, D.

1983-01-01

The different utilizations of electric energy are reviewed in the residential and tertiary sectors, in the industry. The competitive position of electricity in regard to other fuels has been strengthned by the sudden rise in the price of oil in 1973-1974 and 1979-1980. The evolution of electricity prices depended on the steps taken to adjust the electricity generation system. The substitution of electricity applications for hydro-carbons is an essential point of energy policy. The adjustment at all times, at least cost and most reliability, of the supply of electricity to the demand for it is a major problem in the design and operation of electric systems. National demand for power at a given moment is extremely diversified. Electricity consumption presents daily and seasonal variations, and variations according to the different sectors. Forecasting power requirements is for any decision on operation or investment relating to an electrical system. Load management is desirable (prices according to the customers, optional tariffs for ''peak-day withdrawal''). To conclude, prospects for increased electricity consumption are discussed [fr

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Science.gov (United States)

Mohamed, Ahmed

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available

Provision of Supplementary Load Frequency Control via Aggregation of Air Conditioning Loads

Directory of Open Access Journals (Sweden)

Lei Zhou

2015-12-01

Full Text Available The integration of large-scale renewable energy poses great challenges for the operation of power system because of its increased frequency fluctuations. More load frequency control (LFC resources are demanded in order to maintain a stable system with more renewable energy injected. Unlike the costly LFC resources on generation side, the thermostatically controlled loads (TCLs on the demand side become an attractive solution on account of its substantial quantities and heat-storage capacity. It generally contains air conditioners (ACs, water heaters and fridges. In this paper, the supplementary LFC is extracted by the modeling and controlling of aggregated ACs. We first present a control framework integrating the supplementary LFC with the traditional LFC. Then, a change-time-priority-list method is proposed to control power output taking into account customers’ satisfaction. Simulations on a single-area power system with wind power integration demonstrate the effectiveness of the proposed method. The impact of ambient temperature changes and customer preferences on room temperature is also involved in the discussion. Results show that the supplementary LFC provided by ACs could closely track the LFC signals and effectively reduce the frequency deviation.

Load-bearing masonry system adoption and performance: A case study of construction company in a developing country

Science.gov (United States)

Ramli, Nor Azlinda; Abdullah, Che Sobry; Nawi, Mohd Nasrun Mohd; Bahaudin, Ahmad Yusni

2016-08-01

This study addresses the factors that influence the adoption of load-bearing masonry (LBM) system. A case study of the load-bearing masonry (LBM) system adoption is conducted through an interview to explore the situation of the technology adoption in a construction company. The finding indicates the factors influence the adoption of LBM system for the construction company are: organizational resources, usefulness, less maintenance, reduce construction time and cost. From the findings, these factors consistent with previous literature. Furthermore, the performance of the company was measured by looking into the financial and non-financial aspects. The LBM system brings good performance as it increased the profits of the company, a good quality of product and attracts more demand from customers. Thus, these factors should be considered for the other companies that are interested in implementing the LBM system in their projects.

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.

Impact of Demand Side Management in Active Distribution Networks

DEFF Research Database (Denmark)

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

2017-01-01

Demand Side Management (DSM) is an efficient flexible program which helps distribution network operators to meet the future critical peak demand. It is executed in cases of not only technical issues like voltage sag or swell, transformer burdening, cable congestions, but also to increase the degree...... of visibility in the electricity markets. The aim of this paper is to find the optimal flexible demands that can be shifted to another time in order to operate the active distribution system within secure operating limits. A simple mechanism is proposed for finding the flexibility of the loads where electric...

Solar energy storage in German households: profitability, load changes and flexibility

International Nuclear Information System (INIS)

Kaschub, Thomas; Jochem, Patrick; Fichtner, Wolf

2016-01-01

The developments of battery storage technology together with photovoltaic (PV) roof-top systems might lead to far-reaching changes in the electricity demand structures and flexibility of households. The implications are supposed to affect the generation mix of utilities, distribution grid utilization, and electricity price. Using a techno-economic optimization model of a household system, we endogenously dimension PV system and stationary battery storage (SBS). The results of the reference scenario show positive net present values (NPV) for PV systems of approx. 500–1,800 EUR/kW_p and NPV for SBS of approx. 150–500 EUR/kWh. Main influences are the demand of the households, self-consumption rates, investment costs, and electricity prices. We integrate electric vehicles (EV) with different charging strategies and find increasing NPV of the PV system and self-consumption of approx. 70%. With further declining system prices for solar energy storage and increasing electricity prices, PV systems and SBS can be profitable in Germany from 2018 on even without a guaranteed feed-in tariff or subsidies. Grid utilization substantially changes by households with EV and PV-SBS. We discuss effects of different incentives and electricity tariff options (e. g. load limits or additional demand charges). Concluding, solar energy storage systems will bring substantial changes to electricity sales. - Highlights: • Domestic photovoltaics (PV) and storage systems are techno-economically analyzed. • PV & storage are profitable in the medium term due to high self-consumption rates. • Controlled electric vehicle charging improves load flexibility and self-generation. • External procurement of electricity drastically changes and decreases to 48–58%. • Dynamic tariffs e. g. with load limits or demand charges incentivize load shifting.

Probabilistic Constrained Load Flow Considering Integration of Wind Power Generation and Electric Vehicles

DEFF Research Database (Denmark)

Vlachogiannis, Ioannis (John)

2009-01-01

A new formulation and solution of probabilistic constrained load flow (PCLF) problem suitable for modern power systems with wind power generation and electric vehicles (EV) demand or supply is represented. The developed stochastic model of EV demand/supply and the wind power generation model...... are incorporated into load flow studies. In the resulted PCLF formulation, discrete and continuous control parameters are engaged. Therefore, a hybrid learning automata system (HLAS) is developed to find the optimal offline control settings over a whole planning period of power system. The process of HLAS...

Structural response of cargo containment systems in LNG carriers under ice loads

International Nuclear Information System (INIS)

Wang, B.; Yu, H.; Basu, R.; Lee, H.; Kwon, J.C.; Jeon, B.Y.; Kim, J.H.; Daley, C.; Kendrick, A.

2008-01-01

Gas exploration has been extended into the Arctic region such as in the Russian Arctic area, because of the increasing demand for energy resources. As a result, shipping in ice-covered seas is also increasing. Many technical issues are involved in ensuring the safety of liquefied natural gas (LNG) ships during the transportation. This paper discussed an investigation of ship-ice interaction scenarios for possible operation routes in Arctic areas. Six scenarios were selected to study the structural response of cargo containment systems (CCS) in both membrane and spherical types of LNG ships. For selected ship-ice interaction scenarios, ice loads and loading areas in the hull structure were determined based on the energy theory. The configurations of LNG carriers were discussed and illustrated. The paper also outlined the assessment criteria and structure analysis procedures. It was concluded that the strength of the CCS of membrane-type LNG carrier and the strength of the skirt structure of spherical-type LNG carrier were strong enough under the design ice loads. 13 refs., 9 tabs., 18 figs

Critical kick-back mitigation through improved design of demand response

DEFF Research Database (Denmark)

Han, Xue; You, Shi; Bindner, Henrik W.

2016-01-01

The energy sector is adopting a lot of intermittent renewable energy sources nowadays. In order to successfully integrate these renewable sources, demand side resources (DSR), in a demand response (DR) setup, are able to provide power system services by exploiting their flexibility in power...... of load kick-back, not only the potential value of DR is limited significant but also power system operation can be jeopardized even more. In addition to explaining the severity of kick-back effect through illustrative examples, this paper proposes several methods to mitigate the critical kick-back effect...

A study on the optimal hydraulic loading rate and plant ratios in recirculation aquaponic system.

Science.gov (United States)

Endut, Azizah; Jusoh, A; Ali, N; Wan Nik, W B; Hassan, A

2010-03-01

The growths of the African catfish (Clarias gariepinus) and water spinach (Ipomoea aquatica) were evaluated in recirculation aquaponic system (RAS). Fish production performance, plant growth and nutrient removal were measured and their dependence on hydraulic loading rate (HLR) was assessed. Fish production did not differ significantly between hydraulic loading rates. In contrast to the fish production, the water spinach yield was significantly higher in the lower hydraulic loading rate. Fish production, plant growth and percentage nutrient removal were highest at hydraulic loading rate of 1.28 m/day. The ratio of fish to plant production has been calculated to balance nutrient generation from fish with nutrient removal by plants and the optimum ratio was 15-42 gram of fish feed/m(2) of plant growing area. Each unit in RAS was evaluated in terms of oxygen demand. Using specified feeding regime, mass balance equations were applied to quantify the waste discharges from rearing tanks and treatment units. The waste discharged was found to be strongly dependent on hydraulic loading rate. 2009 Elsevier Ltd. All rights reserved.

Advances in electric power and energy systems load and price forecasting

CERN Document Server

2017-01-01

A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally. Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial ar nas. Short-run forecasting of electricity prices has become nece...

The optimization model for multi-type customers assisting wind power consumptive considering uncertainty and demand response based on robust stochastic theory

International Nuclear Information System (INIS)

Tan, Zhongfu; Ju, Liwei; Reed, Brent; Rao, Rao; Peng, Daoxin; Li, Huanhuan; Pan, Ge

2015-01-01

Highlights: • Our research focuses on demand response behaviors of multi-type customers. • A wind power simulation method is proposed based on the Brownian motion theory. • Demand response revenue functions are proposed for multi-type customers. • A robust stochastic optimization model is proposed for wind power consumptive. • Models are built to measure the impacts of demand response on wind power consumptive. - Abstract: In order to relieve the influence of wind power uncertainty on power system operation, demand response and robust stochastic theory are introduced to build a stochastic scheduling optimization model. Firstly, this paper presents a simulation method for wind power considering external environment based on Brownian motion theory. Secondly, price-based demand response and incentive-based demand response are introduced to build demand response model. Thirdly, the paper constructs the demand response revenue functions for electric vehicle customers, business customers, industry customers and residential customers. Furthermore, robust stochastic optimization theory is introduced to build a wind power consumption stochastic optimization model. Finally, simulation analysis is taken in the IEEE 36 nodes 10 units system connected with 650 MW wind farms. The results show the robust stochastic optimization theory is better to overcome wind power uncertainty. Demand response can improve system wind power consumption capability. Besides, price-based demand response could transform customers’ load demand distribution, but its load curtailment capacity is not as obvious as incentive-based demand response. Since price-based demand response cannot transfer customer’s load demand as the same as incentive-based demand response, the comprehensive optimization effect will reach best when incentive-based demand response and price-based demand response are both introduced.

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

Science.gov (United States)

Prakash, S.; Sinha, S. K.

2015-09-01

In this research work, two areas hydro-thermal power system connected through tie-lines is considered. The perturbation of frequencies at the areas and resulting tie line power flows arise due to unpredictable load variations that cause mismatch between the generated and demanded powers. Due to rising and falling power demand, the real and reactive power balance is harmed; hence frequency and voltage get deviated from nominal value. This necessitates designing of an accurate and fast controller to maintain the system parameters at nominal value. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. The intelligent controllers like fuzzy logic, artificial neural network (ANN) and hybrid fuzzy neural network approaches are used for automatic generation control for the two area interconnected power systems. Area 1 consists of thermal reheat power plant whereas area 2 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent (ANFIS, ANN and fuzzy) control and conventional PI and PID control approaches. To enhance the performance of controller sliding surface i.e. variable structure control is included. The model of interconnected power system has been developed with all five types of said controllers and simulated using MATLAB/SIMULINK package. The performance of the intelligent controllers has been compared with the conventional PI and PID controllers for the interconnected power system. A comparison of ANFIS, ANN, Fuzzy and PI, PID based approaches shows the superiority of proposed ANFIS over ANN, fuzzy and PI, PID. Thus the hybrid fuzzy neural network controller has better dynamic response i.e., quick in operation, reduced error magnitude and minimized frequency transients.

A Smart Grid Framework for Optimally Integrating Supply-Side, Demand-Side and Transmission Line Management Systems

Directory of Open Access Journals (Sweden)

Chukwuka Monyei

2018-04-01

Full Text Available A coordinated centralized energy management system (ConCEMS is presented in this paper that seeks to integrate for optimal grid operation—the supply side energy management system (SSEMS, home energy management system (HEMS and transmission line management system (TLMS. ConCEMS in ensuring the optimal operation of an IEEE 30-bus electricity network harmonizes the individual objective function of SSEMS, HEMS and TLMS to evolve an optimal dispatch of participating demand response (DR loads that does not violate transmission line ampacity limits (TLMS constraint while minimizing consumer cost (HEMS constraint and supply side operations cost (SSEMS constraint. An externally constrained genetic algorithm (ExC-GA that is influenced by feedback from TLMS is also presented that intelligently varies the dispatch time of participating DR loads to meet the individual objective functions. Hypothetical day ahead dynamic pricing schemes (Price1, Price2 and Price3 have also been adopted alongside an existing time of use (Price0 pricing scheme for comparison and discussion while a dynamic thermal line rating (DTLR algorithm has also been incorporated to dynamically compute power limits based on real time associated data.

Demand response in Germany: Technical potential, benefits and regulatory challenges

OpenAIRE

Stede, Jan

2016-01-01

An increased flexibility of the electricity demand side through demand response (DR) is an opportunity to support the integration of renewable energies. By optimising the use of the generation, transmission and distribution infrastructure, DR reduces the need for costly investments and contributes to system security. There is a significant technical DR potential for load reduction from industrial production processes in Germany, as well as from cross-cutting technologies in industry and the t...

Integrated tuning of PID-derivative load frequency controller for two ...

African Journals Online (AJOL)

DR OKE

1*Department of Electrical Engineering, National Institute of Technology Hamirpur, INDIA ... The adequate operation of interconnected power system requires the matching of total generation with total load demand and .... system reliability.

Short-term load forecasting of power system

Science.gov (United States)

Xu, Xiaobin

2017-05-01

In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

Load Management in District Heating Operation

DEFF Research Database (Denmark)

Li, Hongwei; Wang, Stephen Jia

2015-01-01

Smooth operation of district heating system will avoid installation of expensive peak heat boilers, improve plant partial load performance, increase the system redundancy for further network expansion and improve its resilience to ensure security of supply during severe heating seasons. The peak...... heating load can be reduced through building demand side management. The building thermal mass can be used to shift the heating supply under the circumstance without jeopardizing the consumer thermal comfort. In this paper, the multi-agent framework is applied to a simplified building dynamic model...

Load Frequency Control of Two-Area Network using Renewable Energy Resources and Battery Energy Storage System

Directory of Open Access Journals (Sweden)

Norhafiz Bin SALIM

2017-06-01

Full Text Available In an interconnected system, the frequency and tie-line power interchange are very susceptible with the diversification of power load demand. Literally, in a multi-area power system, the load frequency control (LFC is substantially aimed to minimise the deviations of these parameters relatively. Knowingly, the power production from renewable energy resources could offer promising solutions despite their intermittency (i.e. photovoltaic/wind generation, hence in this context, a battery energy storage system (BESS is proposed to delineate dynamic response along with grid—connection. This study has proposed LFC with BESS control method to suppress frequency deviations for a power system and being compared with photovoltaic (PV approach. The effectiveness was verified using newly developed AGC30 model of Japanese Power System and was modelled using MATLAB Simulink. Furthermore, an analysis of the tie-line power oscillations also are carried out and comparison analysis demonstrates further the reliability of the proposed model and control methods.

Option value of electricity demand response

Energy Technology Data Exchange (ETDEWEB)

Sezgen, Osman; Goldman, C.A. [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley CA 94720 (United States); Krishnarao, P. [Citigroup Energy Inc., 1301 Fannin St, Houston, TX 77002 (United States)

2007-02-15

As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand-response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand-response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution-specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets. (author)

Option value of electricity demand response

International Nuclear Information System (INIS)

Sezgen, Osman; Goldman, C.A.; Krishnarao, P.

2007-01-01

As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand-response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand-response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution-specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets. (author)

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

Control strategies and cycling demands for Li-ion storage batteries in residential micro-cogeneration systems

International Nuclear Information System (INIS)

Darcovich, K.; Kenney, B.; MacNeil, D.D.; Armstrong, M.M.

2015-01-01

Highlights: • Canadian home energy system modeled with PV, ICE CHP, battery and power grid. • Battery function is modeled on fundamental electrochemical principles. • Techno-economics of control strategies assessed. • Impact of control strategies battery cycles is developed for wear analysis. • Non-monotonic nature of battery cycles with transient renewables is discussed. - Abstract: Energy storage units have become important components in residential micro-cogeneration (MCG) systems. As MCG systems are often connected to single residences or buildings in a wide variety of settings, they are frequently unique and highly customized. Lithium-ion batteries have recently gained some profile as energy storage units of choice, because of their good capacity, high efficiency, robustness and ability to meet the demands of typical residential electrical loads. In the present work, modeled scenarios are explored which examine the performance of a MCG system with an internal combustion engine, photovoltaic input and a Li-ion storage battery. An electricity demand profile from new data collected in Ottawa, Canada is used to provide a full year energy use context for the analyses. The demands placed on the battery are examined to assess the suitability of the battery size and performance, as well as control related functionalities which reveal significantly varying battery use, and led to a quantitative expression for equivalent cycles. The energy use simulations are derived from electrochemical fundamentals adapted for a larger battery pack. Simulation output provides the basis for techno-economic commentary on how to assess large-scale Li-ion batteries for effective electrical storage purposes in MCG systems, and the impact of the nature of the control strategy on the battery service life

Impact of Battery Energy Storage System Operation Strategy on Power System: An Urban Railway Load Case under a Time-of-Use Tariff

Directory of Open Access Journals (Sweden)

Hyeongig Kim

2017-01-01

Full Text Available Customer-owned battery energy storage systems (BESS have been used to reduce electricity costs of energy storage owners (ESOs under a time-of-use (TOU tariff in Korea. However, the current TOU tariff can unintentionally induce customer’s electricity usage to have a negative impact on power systems. This paper verifies the impact of different BESS operation strategies on power systems under a TOU tariff by analyzing the TOU tariff structure and the customer’s load pattern. First, several BESS operation strategies of ESO are proposed to reduce the electricity cost. In addition, a degradation cost calculation method for lithium ion batteries is considered for the ESO to determine the optimal BESS operation strategy that maximizes both electricity cost and annual investment cost. The optimal BESS operation strategy that maximizes ESO’s net benefit is illustrated by simulation using an urban railway load data from Namgwangju Station, Korea. The results show that BESS connected to urban railway loads can negative impact power system operation. This is due to the high BESS degradation costs and lack of incentive of differential rates in TOU tariff that can effectively induce proper demand response.

Analysis of load monitoring system in hydraulic mobile cranes

Science.gov (United States)

Kalairassan, G.; Boopathi, M.; Mohan, Rijo Mathew

2017-11-01

Load moment limiters or safe load control systems or are very important in crane safety. The system detects the moment of lifting load and compares this actual moment with the rated moment. The system uses multiple sensors such as boom angle sensor, boom length sensor for telescopic booms, pressure transducers for measuring the load, anti-two block switch and roller switches. The system works both on rubber and on outriggers. The sensors measure the boom extension, boom angle and load to give as inputs to the central processing, which calculate the safe working load range for that particular configuration of the crane and compare it with the predetermined safe load. If the load exceeds the safe load, actions will be taken which will reduce the load moment, which is boom telescopic retraction and boom lifting. Anti-two block switch is used to prevent the two blocking condition. The system is calibrated and load tested for at most precision.

Analysis of Mesh Distribution Systems Considering Load Models and Load Growth Impact with Loops on System Performance

Science.gov (United States)

Kumar Sharma, A.; Murty, V. V. S. N.

2014-12-01

The distribution system is the final link between bulk power system and consumer end. A distinctive load flow solution method is used for analysis of the load flow of radial and weakly meshed network based on Kirchhoff's Current Law (KCL) and KVL. This method has excellent convergence characteristics for both radial as well as weakly meshed structure and is based on bus injection to branch current and branch-current to bus-voltage matrix. The main contribution of the paper is: (i) an analysis has been carried out for a weekly mesh network considering number of loops addition and its impact on the losses, kW and kVAr requirements from a system, and voltage profile, (ii) different load models, realistic ZIP load model and load growth impact on losses, voltage profile, kVA and kVAr requirements, (iii) impact of addition of loops on losses, voltage profile, kVA and kVAr requirements from substation, and (iv) comparison of system performance with radial distribution system. Voltage stability is a major concern in planning and operation of power systems. This paper also includes identifying the closeness critical bus which is the most sensitive to the voltage collapse in radial distribution networks. Node having minimum value of voltage stability index is the most sensitive node. Voltage stability index values are computed for meshed network with number of loops added in the system. The results have been obtained for IEEE 33 and 69 bus test system. The results have also been obtained for radial distribution system for comparison.

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

Solar Heating And Cooling Of Buildings (SHACOB): Requirements definition and impact analysis-2. Volume 3: Customer load management systems

Science.gov (United States)

Cretcher, C. K.; Rountredd, R. C.

1980-11-01

Customer Load Management Systems, using off-peak storage and control at the residences, are analyzed to determine their potential for capacity and energy savings by the electric utility. Areas broadly representative of utilities in the regions around Washington, DC and Albuquerque, NM were of interest. Near optimum tank volumes were determined for both service areas, and charging duration/off-time were identified as having the greatest influence on tank performance. The impacts on utility operations and corresponding utility/customer economics were determined in terms of delta demands used to estimate the utilities' generating capacity differences between the conventional load management, (CLM) direct solar with load management (DSLM), and electric resistive systems. Energy differences are also determined. These capacity and energy deltas are translated into changes in utility costs due to penetration of the CLM or DSLM systems into electric resistive markets in the snapshot years of 1990 and 2000.

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.

Demand side management. Benefits and challenges

International Nuclear Information System (INIS)

Strbac, Goran

2008-01-01

In this paper, the major benefits and challenges of electricity demand side management (DSM) are discussed in the context of the UK electricity system. The relatively low utilisation of generation and networks (of about 50%) means that there is significant scope for DSM to contribute to increasing the efficiency of the system investment. The importance of the diversity of electricity load is discussed and the negative effects of DSM on load diversity illustrated. Ageing assets, the growth in renewable and other low-carbon generation technologies and advances in information and communication technologies are identified as major additional drivers that could lead to wider applications of DSM in the medium term. Potential benefits of DSM are discussed in the context of generation and of transmission and distribution networks. The provision of back-up capacity by generation may not be efficient as it will be needed relatively infrequently, and DSM may be better placed to support security. We also present an analysis of the value of DSM in balancing generation and demand in a future UK electricity system with significant variable renewable generation. We give a number of reasons for the relatively slow uptake of DSM, particularly in the residential, commercial and small business sectors. They include a lack of metering, information and communication infrastructure, lack of understanding of the benefits of DSM, problems with the competitiveness of DSM when compared with traditional approaches, an increase in the complexity of system operation and inappropriate market incentives. (author)

Effect of physical property of supporting media and variable hydraulic loading on hydraulic characteristics of advanced onsite wastewater treatment system.

Science.gov (United States)

Sharma, Meena Kumari; Kazmi, Absar Ahmad

2015-01-01

A laboratory-scale study was carried out to investigate the effects of physical properties of the supporting media and variable hydraulic shock loads on the hydraulic characteristics of an advanced onsite wastewater treatment system. The system consisted of two upflow anaerobic reactors (a septic tank and an anaerobic filter) accommodated within a single unit. The study was divided into three phases on the basis of three different supporting media (Aqwise carriers, corrugated ring and baked clay) used in the anaerobic filter. Hydraulic loadings were based on peak flow factor (PFF), varying from one to six, to simulate the actual conditions during onsite wastewater treatment. Hydraulic characteristics of the system were identified on the basis of residence time distribution analyses. The system showed a very good hydraulic efficiency, between 0.86 and 0.93, with the media of highest porosity at the hydraulic loading of PFF≤4. At the higher hydraulic loading of PFF 6 also, an appreciable hydraulic efficiency of 0.74 was observed. The system also showed good chemical oxygen demand and total suspended solids removal efficiency of 80.5% and 82.3%, respectively at the higher hydraulic loading of PFF 6. Plug-flow dispersion model was found to be the most appropriate one to describe the mixing pattern of the system, with different supporting media at variable loading, during the tracer study.

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.

Evaluating impact of market changes on increasing cell-load variation in dynamic cellular manufacturing systems using a hybrid Tabu search and simulated annealing algorithms

Directory of Open Access Journals (Sweden)

Aidin Delgoshaei

2016-06-01

Full Text Available In this paper, a new method is proposed for scheduling dynamic cellular manufacturing systems (D-CMS in the presence of uncertain product demands. The aim of this method is to control the process of trading off between in-house manufacturing and outsourcing while product demands are uncertain and can be varied from period to period. To solve the proposed problem, a hybrid Tabu Search and Simulated Annealing are developed to overcome hardness of the proposed model and then results are compared with a Branch and Bound and Simulated Annealing algorithms. A Taguchi method (L_27 orthogonal optimization is used to estimate parameters of the proposed method in order to solve experiments derived from literature. An in-depth analysis is conducted on the results in consideration of various factors. For evaluating the system imbalance in dynamic market demands, a new measuring index is developed. Our findings indicate that the uncertain condition of market demands affects the routing of product parts and may induce machine-load variations that yield to cell-load diversity. The results showed that the proposed hybrid method can provide solutions with better quality.

Coordinated Scheme of Under-Frequency Load Shedding with Intelligent Appliances in a Cyber Physical Power System

Directory of Open Access Journals (Sweden)

Qi Wang

2016-08-01

Full Text Available The construction of a cyber physical system in a power grid provides more potential control strategies for the power grid. With the rapid employment of intelligent terminal equipment (e.g., smart meters and intelligent appliances in the environment of a smart grid, abundant dynamic response information could be introduced to support a secure and stable power system. Combining demand response technology with the traditional under-frequency load shedding (UFLS scheme, a new UFLS strategy-determining method involving intelligent appliances is put forward to achieve the coordinated control of quick response resources and the traditional control resources. Based on this method, intelligent appliances can be used to meet the regulatory requirements of system operation in advance and prevent significant frequency drop, thereby improving the flexibility and stability of the system. Time-domain simulation verifies the effectiveness of the scheme, which is able to mitigate frequency drop and reduce the amount of load shedding.

Optimalisatie Draagsysteem (Optimization of the Load Carriage System)

National Research Council Canada - National Science Library

Koerhuis, C. L; Rensink, P; Schijndel, J. van

2008-01-01

Besides positive effects of an earlier developed load carriage system in which the load was carried predominantly on the hips, mobility was increased and protection and load carriage was integrated into one system (ILCS...

Demand-side management and demand response in the Ontario energy sectors

International Nuclear Information System (INIS)

2003-01-01

In June 2003, the Ontario Energy Board was asked by the Minister of Energy to identify and review options for the delivery of demand-side management (DSM) and demand response (DR) activities within the electricity sector, by consulting with stakeholders. The role of local distribution company (distributor) in such activities was also to be determined. The objective was to balance implementation costs with the benefits to consumers and the entire system. The preliminary research and ideas were presented in this discussion paper. Definitions of both DSM and DR were provided, followed by an overview of economic theory and competitive markets. The framework for discussion was presented, along with a list of issues and other considerations. A spectrum of potential approaches to a DSM and DR framework was included and jurisdictional examples provided. A brief overview of the concept of load aggregation was presented and the next steps for consultations were outlined. 30 refs., 7 tabs

Short term load forecasting of anomalous load using hybrid soft computing methods

Science.gov (United States)

Rasyid, S. A.; Abdullah, A. G.; Mulyadi, Y.

2016-04-01

Load forecast accuracy will have an impact on the generation cost is more economical. The use of electrical energy by consumers on holiday, show the tendency of the load patterns are not identical, it is different from the pattern of the load on a normal day. It is then defined as a anomalous load. In this paper, the method of hybrid ANN-Particle Swarm proposed to improve the accuracy of anomalous load forecasting that often occur on holidays. The proposed methodology has been used to forecast the half-hourly electricity demand for power systems in the Indonesia National Electricity Market in West Java region. Experiments were conducted by testing various of learning rate and learning data input. Performance of this methodology will be validated with real data from the national of electricity company. The result of observations show that the proposed formula is very effective to short-term load forecasting in the case of anomalous load. Hybrid ANN-Swarm Particle relatively simple and easy as a analysis tool by engineers.

Load Management of Data Centers as Regulation Capacity in Denmark

DEFF Research Database (Denmark)

Clausen, Anders; Ghatikar, Girish; Jørgensen, Bo Nørregaard

2014-01-01

are of special interest as they account for 500 GWh of consumption in Denmark or nearly 2% of the total electricity consumption. This paper performs an analysis on load management capabilities of data centers in Denmark based on the experiences in the U.S. We characterize the load management capabilities...... for transmission system operators and distribution system operators and balance errors in forecasts made by balance responsible parties. By enabling the demand-side to adapt consumption to match power generation, we can address this in a cost-effective and environmental sound way. In this context, data centers...... of the data centers based on their types, technology, and their application as grid management resources. Further, we identify demand-side entry barriers towards market participation. Our findings suggest that groups of data centers can offer dynamic load flexibility as virtual power plants, and thereby...

Load shedding and emergency load sequencing system at Sizewell B power station

International Nuclear Information System (INIS)

Bowcock, S.; Miller, D.

1992-01-01

Sizewell B Nuclear Power Station has a main electrical system that connects together the main turbo-generators, generating at 23.5kV, the 400kV grid and the auxiliary equipment required to operate the station. A separate essential electrical system fed from the main electrical system, supplies all the auxiliaries required to shut-down the nuclear reactor and maintain it in a safe shut-down condition. For safety reasons four similar independent essential electrical systems are provided, each headed by a 3.3kV switchboard and a stand-by 8MW diesel generator. Feeds from the 3.3kV switchboards in turn supply the essential 3.3kV drives and transformer fed 415V essential switchboards. The function of the Load Shedding and Emergency Load Sequencing (LSELS) System is to monitor the condition of the 3.3kV incoming supply from the main electrical system to each essential 3.3kV switchboard and initiate its replacement, with the supply from the associated diesel generator, if it is outside set parameters. In order to achieve this transfer the essential electrical system load must be reduced to a level which the diesel can accommodate as a standing load and then allow the sequenced reconnection of required loads so as not to overload the diesel. The LSELS equipment is categorised as Safety Category 1E and has a significant importance to the safe operation of the power station. Therefore the design of the system must be highly reliable and the purpose of this paper is to detail the design approach used to ensure that a high system reliability is achieved. (Author)

Modular load flow for restructured power systems

CERN Document Server

Hariharan, M V; Gupta, Pragati P

2016-01-01

In the subject of power systems, authors felt that a re-look is necessary at some conventional methods of analysis. In this book, the authors have subjected the time-honoured load flow to a close scrutiny. Authors have discovered and discussed a new load flow procedure – Modular Load Flow. Modular Load Flow explores use of power – a scalar – as source for electrical circuits which are conventionally analysed by means of phasors – the ac voltages or currents. The method embeds Kirchhoff’s circuit laws as topological property into its scalar equations and results in a unique wonderland where phase angles do not exist! Generators are shown to have their own worlds which can be superimposed to obtain the state of the composite power system. The treatment is useful in restructured power systems where stakeholders and the system operators may desire to know individual generator contributions in line flows and line losses for commercial reasons. Solution in Modular Load Flow consists of explicit expression...

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

1-GWh diurnal load-leveling superconducting magnetic energy storage system reference design

International Nuclear Information System (INIS)

Hassenzahl, W.V.; Rogers, J.D.

1979-01-01

A point reference design has been completed for a 1-GWh Superconducting Magnetic Energy Storage system. The system is for electric utility dirunal load leveling; however, such a device will function to meet much faster power demands including dynamic stabilization. The study has explored several concepts of design not previously considered in the same detail as treated here. Because the study is for a point design, optimization in all respects is not complete. The study examines aspects of the coil design; superconductor supported off of the dewar shell; the dewar shell, its configuration and stresses; the underground excavation and related construction for holding the superconducting coil and its dewar; the helium refrigeration system; the electrical converter system; the vacuum system; the guard coil; and the costs. The report is a condensation of the more comprehensive study which is in the process of being printed

Response to severe changes of load on the reactor system of nuclear ship Mutsu

International Nuclear Information System (INIS)

Ishida, Toshihisa; Kusunoki, Tsuyoshi; Ochiai, Masa-aki; Tanaka, Yoshimi; Yao, Toshiaki; Inoue, Kimio.

1993-01-01

The response of the nuclear power system of N.S. Mutsu to severe changes of load have been studied from records taken during the power-raising tests performed on the ship in 1990. The records examined were those involving the most severe load changes foreseen for marine reactors: (a) sharp load increase with total steam flow raised from 25 to 70 % rated full flow in 13s, (b) crash astern maneuver with the position of propulsion turbine command handle changed-taking several seconds-from cruising ahead to STOP, and after about 50s, further changed-taking 30s-to bring the astern propulsion turbine to full speed-to consume approximately 60 % rated total steam flow and (c) turbine trip with the ahead turbine intentionally tripped when operating at roughly 100 % rated total steam flow. The foregoing records from load changes-of severity beyond what is foreseen for land-based reactors-proved that the Mutsu reactor is capable of responding smoothly and securely to such severe load changes. These load changes occasioned relatively large mismatches between reactor power supply and steam flow demand, but with notable freedom from any conspicuous overshooting or hunting of the reactor power. This performance can be attributed to (a) correct functioning of the automatic power control system, (b) effective contribution of the self-regulating reactor control property deriving from the large negative feedback between moderator temperature and reactivity, and (c) the ample inventories of coolant in the primary and secondary loops. The responses to load change are discussed covering those relevant to (a) reactor power, (b) primary loop pressure, and (c) steam generator pressure, with particular reference to the differences seen in response to mild and to severe load changes. (author)

Electricity demand profile with high penetration of heat pumps in Nordic area

DEFF Research Database (Denmark)

Liu, Zhaoxi; Wu, Qiuwei; Nielsen, Arne Hejde

2013-01-01

This paper presents the heat pump (HP) demand profile with high HP penetration in the Nordic area in order to achieve the carbon neutrality power system. The calculation method in the European Standard EN14825 was used to estimate the HP electricity demand profile. The study results show...... there will be high power demand from HPs and the selection of supplemental heating for heat pumps has a big impact on the peak electrical power load of heating. The study in this paper gives an estimate of the scale of the electricity demand with high penetration of heat pumps in the Nordic area....

Modulation strategies of integrated HVAC systems used in residential buildings for demand-side management at different scales

OpenAIRE

Georges, Emeline

2017-01-01

The integration of renewable energy sources in the electricity production mix has an important impact on the management of the electricity grid, due to their intermittency. In particular, to ensure grid balancing, there is a rising need for flexibility, both on the supply and demand sides. A possible solution to help achieve grid balancing is the smart modulation of the electrical load in a "demand following supply" scheme through demand-side management. In this context, the objective of...

Multi-Temporal Decomposed Wind and Load Power Models for Electric Energy Systems

Science.gov (United States)

Abdel-Karim, Noha

This thesis is motivated by the recognition that sources of uncertainties in electric power systems are multifold and may have potentially far-reaching effects. In the past, only system load forecast was considered to be the main challenge. More recently, however, the uncertain price of electricity and hard-to-predict power produced by renewable resources, such as wind and solar, are making the operating and planning environment much more challenging. The near-real-time power imbalances are compensated by means of frequency regulation and generally require fast-responding costly resources. Because of this, a more accurate forecast and look-ahead scheduling would result in a reduced need for expensive power balancing. Similarly, long-term planning and seasonal maintenance need to take into account long-term demand forecast as well as how the short-term generation scheduling is done. The better the demand forecast, the more efficient planning will be as well. Moreover, computer algorithms for scheduling and planning are essential in helping the system operators decide what to schedule and planners what to build. This is needed given the overall complexity created by different abilities to adjust the power output of generation technologies, demand uncertainties and by the network delivery constraints. Given the growing presence of major uncertainties, it is likely that the main control applications will use more probabilistic approaches. Today's predominantly deterministic methods will be replaced by methods which account for key uncertainties as decisions are made. It is well-understood that although demand and wind power cannot be predicted at very high accuracy, taking into consideration predictions and scheduling in a look-ahead way over several time horizons generally results in more efficient and reliable utilization, than when decisions are made assuming deterministic, often worst-case scenarios. This change is in approach is going to ultimately require new

FY 1999 report on the results of the experimental verification on the establishment of a centralized load control system. Study of an advanced centralized load control system, etc.; 1999 nendo fuka shuchu seigyo system kakuritsu jissho shikehn kodo fuka shuchu seigyo system nado no kenkyu. Fuka shuchu seigyo system kakuritsu jissho shiken

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-03-01

The paper described the FY 1999 results of the experimental verification on a centralized load control system for the residential electric power demand. The air conditioning control is effective for load leveling, and for it, it is important to infiltrate the consciousness of energy saving into people. Users are not very interested in the information on power rates, would rather tend to seek comfortableness, and are less conscious of energy saving on days of unusual summer heat. Further, the power control in peal time zone was made by indicating users the actual state of power use by a combination of the two-way communication and the automatic meter reading system. However, at present, it cannot be denied that the power rate is higher even in indirect load control equipment with necessary/minimum conditions than the existing power source. It is a must to reduce the cost. The liberalization of electric power is progressing fast, and incentives for DSM are decreasing, but each of advanced countries is getting sensitive to the obedience to COP3. In addition to DSM such as the rebate program and financing program by the existing surcharge system, they are making efforts for development/promotion of new energy by creating the green electric power market. The load control technology is expected which does not disturb comfortableness and amenity of users. (NEDO)

Feasibility of solid oxide fuel cell dynamic hydrogen coproduction to meet building demand

Science.gov (United States)

Shaffer, Brendan; Brouwer, Jacob

2014-02-01

A dynamic internal reforming-solid oxide fuel cell system model is developed and used to simulate the coproduction of electricity and hydrogen while meeting the measured dynamic load of a typical southern California commercial building. The simulated direct internal reforming-solid oxide fuel cell (DIR-SOFC) system is controlled to become an electrical load following device that well follows the measured building load data (3-s resolution). The feasibility of the DIR-SOFC system to meet the dynamic building demand while co-producing hydrogen is demonstrated. The resulting thermal responses of the system to the electrical load dynamics as well as those dynamics associated with the filling of a hydrogen collection tank are investigated. The DIR-SOFC system model also allows for resolution of the fuel cell species and temperature distributions during these dynamics since thermal gradients are a concern for DIR-SOFC.

The Demand for Divisia Money in the United States: A Dynamic Flexible Demand System.

OpenAIRE

Serletis, Apostolos

1991-01-01

This paper applies the Anderson and Blundell (1982) approach to the analysis of the demand for money and attempts to establish the nature of the relationship between Divisia money, defined from narrow to broad, and the "nested like assets" at different levels of aggregation. This is achieved by conducting the analysis within a microtheoretical framework--utilizing the demand system approach--and by estimating a sequence of nested dynamic specifications and performing tests of the nested struc...

Demand as frequency controlled reserve

Energy Technology Data Exchange (ETDEWEB)

Xu, Z.; Togeby, M.; OEstergaard, J.

2008-09-15

Using demand as frequency controlled reserve (DFR) is an emerging technology which allow demand to participate actively in maintaining the system operation without reducing the energy service delivered to the customer and without need of user interaction. The basic premise is that traditional frequency controlled reserves from power plants and interconnections with neighbouring systems can be costly, slow and not fulfil the need for future power grids with a high share of wind power and fewer central power plants, and an intention to perform flexible operation such as is landing. Electricity demands, on the other hand, have advantages as frequency reserve including fast activation speed, smooth linear activation, low expected costs, and well-dispersed in the distribution grid. The main challenge of DFR is new methods for monitoring the available capacity. This project has investigated the technology of using electricity demands for providing frequency reserve to power systems. Within the project the potential and economy of DFR compatible loads in Denmark has been investigated, control logic has been designed, power system impact has been investigated, potential business models has been evaluated and an implementation strategy has been suggested. The tasks and goals of the project have been successfully accomplished based on which the conclusion and future recommendation are made. This project has developed the DFR technology that enables electricity demands to autonomously disconnect or reconnect to the grid in response to system frequency variations. The developed DFR technology is proved to be a promising technology from several perspectives. Technically, using DFR is feasible to provide reserves and enhance power system frequency control, while fulfilling technical requirements such as linear activation (or reconnection) according to frequency (or time). Environmentally, the DFR technology is pollution free in contrast to traditional reserves from generation

Structural load inventory database for the Kansas City Plant

International Nuclear Information System (INIS)

Hashimoto, P.S.; Johnson, M.W.; Nakaki, D.K.; Wilson, J.J.; Lynch, D.T.; Drury, M.A.

1993-01-01

A structural load inventory database (LID) has been developed to support configuration management at the DOE Kansas City Plant (KCP). The objective of the LID is to record loads supported by the plant structures and to provide rapid assessments of the impact of future facility modifications on structural adequacy. Development of the LID was initiated for the KCP's Main Manufacturing Building. Field walkdowns were performed to determine all significant loads supported by the structure, including the weight of piping, service equipment, etc. These loads were compiled in the LID. Structural analyses for natural phenomena hazards were performed in accordance with UCRL-15910. Software to calculate demands on the structural members due to gravity loads, total demands including both gravity and seismic loads, and structural member demand-to-capacity ratios were also developed and integrated into the LID. Operation of the LID is menu-driven. The LID user has options to review and print existing loads and corresponding demand-to-capacity ratios, and to update the supported loads and demand-to-capacity ratios for any future facility modifications

A design of cascade control system and adaptive load compensator for battery/ultracapacitor hybrid energy storage-based direct current microgrid

International Nuclear Information System (INIS)

Pavković, Danijel; Lobrović, Mihael; Hrgetić, Mario; Komljenović, Ante

2016-01-01

Highlights: • Battery/ultracapacitor storage is considered for a direct-current microgrid. • Microgrid voltage cascade control system with load compensator is designed. • Current references are allocated so that ultracapacitor takes on transient loads. • Adaptive Kalman filter-based estimator is used for indirect load compensation. • Control strategy has been verified on a downscaled hardware-in-the-loop setup. - Abstract: A control system design based on an actively-controlled battery/ultracapacitor hybrid energy storage system suitable for direct current microgrid energy management purposes is presented in this paper. The proposed cascade control system arrangement is based on the superimposed proportional–integral voltage controller designed according to Damping Optimum criterion and a zero-pole canceling feed-forward load compensator aimed at voltage excursion suppression under variable load conditions. The superimposed controller commands the inner battery and ultracapacitor current control loops through a dynamic current reference distribution scheme, wherein the ultracapacitor takes on the highly-dynamic (transient) current demands, and the battery covers for steady-state loads. In order to avoid deep discharges of the ultracapacitor module, it is equipped with an auxiliary state-of-charge controller. Finally, for those applications where load is not measured, an adaptive Kalman filter-based load compensator is proposed and tested. The presented control strategy has been implemented on the low-cost industrial controller unit, and its effectiveness has been verified by means of simulations and experiments for the cases of abrupt load changes and quasi-stochastic load profiles using a downscaled battery/ultracapacitor hardware-in-the-loop experimental setup.

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

US EPA's photovoltaic demand-side management project. Report for September 1992-July 1993

International Nuclear Information System (INIS)

Kern, E.C.; Spiegel, R.J.

1993-01-01

The paper discusses an investigation of how photovoltaics (PV) may be used as both a pollution-mitigating energy replacement for fossil fuels and a demand-side management (DSM) option to reduce peak electrical demands of commercial and residential buildings. Eleven electric utilities are partners in this first nationwide demonstration of PV DSM. The approach is to install and monitor standardized PV systems in diverse geographic areas with varying solar energy resource and electric power demand, production, and cost conditions. The systems are being monitored for a year to record direct and diffuse irradiance, ambient air temperature, PV power generation, and building loads. Utilities are providing the electric system operations data needed to determine the pollution mitigation and peak demand reduction that can result from the PV electrical power generation

Hydraulic Soft Yaw System Load Reduction and Prototype Results

DEFF Research Database (Denmark)

Stubkier, Søren; Pedersen, Henrik C.; Markussen, Kristian

2013-01-01

Introducing a hydraulic soft yaw concept for wind turbines leads to significant load reductions in the wind turbine structure. The soft yaw system operates as a shock absorption system on a car, hence absorbing the loading from turbulent wind conditions instead of leading them into the stiff wind...... turbine structure. Results presented shows fatigue reductions of up to 40% and ultimate load reduction of up to 19%. The ultimate load reduction increases even more when the over load protection system in the hydraulic soft yaw system is introduced and results show how the exact extreme load cut off...... operates. Further it is analyzed how the soft yaw system influence the power production of the turbine. It is shown that the influence is minimal, but at larger yaw errors the effect is possitive. Due to the implemeted functions in the hydraulic soft yaw system such as even load distribution on the pinions...

Modeling of Generic Slung Load System

DEFF Research Database (Denmark)

Bisgaard, Morten; Bendtsen, Jan Dimon; la Cour-Harbo, Anders

2009-01-01

This paper presents the result of the modelling and verification of a generic slung load system using a small-scale helicopter. The model is intended for use in simulation, pilot training, estimation, and control. The model is derived using a redundant coordinate formulation based on Gauss...... slackening and tightening as well as aerodynamic coupling between the helicopter and the load. Furthermore, it is shown how the model can be easily used for multi-lift systems either with multiple helicopters or multiple loads. A numerical stabilisation algorithm is introduced and finally the use...... of the model is illustrated through simulations and flight verifications.  ...

Delivering Training for Highly Demanding Information Systems

Science.gov (United States)

Norton, Andrew Lawrence; Coulson-Thomas, Yvette May; Coulson-Thomas, Colin Joseph; Ashurst, Colin

2012-01-01

Purpose: There is a lack of research covering the training requirements of organisations implementing highly demanding information systems (HDISs). The aim of this paper is to help in the understanding of appropriate training requirements for such systems. Design/methodology/approach: This research investigates the training delivery within a…

Large Scale Demand Response of Thermostatic Loads

DEFF Research Database (Denmark)

Totu, Luminita Cristiana

This study is concerned with large populations of residential thermostatic loads (e.g. refrigerators, air conditioning or heat pumps). The purpose is to gain control over the aggregate power consumption in order to provide balancing services for the electrical grid. Without affecting the temperat......This study is concerned with large populations of residential thermostatic loads (e.g. refrigerators, air conditioning or heat pumps). The purpose is to gain control over the aggregate power consumption in order to provide balancing services for the electrical grid. Without affecting....... The control architecture is defined by parsimonious communication requirements that also have a high level data privacy, and it furthermore guarantees a robust and secure local operation. Mathematical models are put forward, and the effectiveness is shown by numerical simulations. A case study of 10000...

Open Architecture Data System for NASA Langley Combined Loads Test System

Science.gov (United States)

Lightfoot, Michael C.; Ambur, Damodar R.

1998-01-01

The Combined Loads Test System (COLTS) is a new structures test complex that is being developed at NASA Langley Research Center (LaRC) to test large curved panels and cylindrical shell structures. These structural components are representative of aircraft fuselage sections of subsonic and supersonic transport aircraft and cryogenic tank structures of reusable launch vehicles. Test structures are subjected to combined loading conditions that simulate realistic flight load conditions. The facility consists of two pressure-box test machines and one combined loads test machine. Each test machine possesses a unique set of requirements or research data acquisition and real-time data display. Given the complex nature of the mechanical and thermal loads to be applied to the various research test articles, each data system has been designed with connectivity attributes that support both data acquisition and data management functions. This paper addresses the research driven data acquisition requirements for each test machine and demonstrates how an open architecture data system design not only meets those needs but provides robust data sharing between data systems including the various control systems which apply spectra of mechanical and thermal loading profiles.

Environmental Aspects of Load Management

International Nuclear Information System (INIS)

Abaravicius, Juozas

2004-02-01

This study approaches load management from an environmental perspective. It identifies and discusses the possible environmental benefits of load management and evaluates their significance, primary focusing on CO 2 emissions reduction. The analysis is carried out on two levels: national - the Swedish electricity market, and local - one electric utility in southern Sweden. Our results show the importance of considering the influence of site-specific or level-specific conditions on the environmental effects of load management. On the national level, load management measures can hardly provide significant environmental benefits, due to the high hydropower production in Sweden, which is the demand following production source. Emission reductions will rather be the result of energy efficiency measures, which will cut the load demand as well as the energy demand. However, when it comes to a local (utility) level, where load management is considered as an alternative to an installation of peak diesel power plant, the benefits are clear. It is demonstrated that significant CO 2 emissions savings can be achieved due to avoided peak diesel power production

Renewable generation versus demand-side management. A comparison for the Spanish market

International Nuclear Information System (INIS)

Roldán Fernández, Juan Manuel; Burgos Payán, Manuel; Riquelme Santos, Jesús Manuel; Trigo García, Ángel Luis

2016-01-01

Conventionally the required instantaneous balance generation-load is achieved by adjusting production to fit variable consumer demand. Nowadays, a significant and increasing segment of generation is renewable. But renewable production cannot be scheduled on request since its generation is dependent on nature (wind, sun, …). In this context, demand-side management (DSM) would help since it would be advisable for part of the flexibility to be provided by the demand. The integration of renewable production and demand-side management (DSM), are compared in this work for Spain throughout 2008–2014. First a qualitative model, based on the linearization of the wholesale market, is employed to explore some hypotheses. A set of scenarios are then examined to quantify the main effects on the market. The results show that DSM exhibits the best performance in terms of economic efficiency and environmental sustainability, as well as for the reduction of load peaks and losses in the system, what suggests the convenience of promoting plans for the replacement of equipment with other more efficient as well as the implementation of real-time tariffs. - Highlights: •The impact of the integration of renewable production versus DSM has been compared. •Merit-order effect related to energy efficiency and to load-shifting is identified. •Large industries achieve energy efficiency with less CAPEX than renewable generation. •Load-shifting cycle yields a reduction of the traded energy and the economic volume.

Approaches for developing a sizing method for stand-alone PV systems with variable demand

Energy Technology Data Exchange (ETDEWEB)

Posadillo, R. [Grupo de Investigacion en Energias y Recursos Renovables, Dpto. de Fisica Aplicada, E.P.S., Universidad de Cordoba, Avda. Menendez Pidal s/n, 14004 Cordoba (Spain); Lopez Luque, R. [Grupo de Investigacion de Fisica para las Energias y Recursos Renovables, Dpto. de Fisica Aplicada. Edificio C2 Campus de Rabanales, 14071 Cordoba (Spain)

2008-05-15

Accurate sizing is one of the most important aspects to take into consideration when designing a stand-alone photovoltaic system (SAPV). Various methods, which differ in terms of their simplicity or reliability, have been developed for this purpose. Analytical methods, which seek functional relationships between variables of interest to the sizing problem, are one of these approaches. A series of rational considerations are presented in this paper with the aim of shedding light upon the basic principles and results of various sizing methods proposed by different authors. These considerations set the basis for a new analytical method that has been designed for systems with variable monthly energy demands. Following previous approaches, the method proposed is based on the concept of loss of load probability (LLP) - a parameter that is used to characterize system design. The method includes information on the standard deviation of loss of load probability ({sigma}{sub LLP}) and on two new parameters: annual number of system failures (f) and standard deviation of annual number of failures ({sigma}{sub f}). The method proves useful for sizing a PV system in a reliable manner and serves to explain the discrepancies found in the research on systems with LLP<10{sup -2}. We demonstrate that reliability depends not only on the sizing variables and on the distribution function of solar radiation, but on the minimum value as well, which in a given location and with a monthly average clearness index, achieves total solar radiation on the receiver surface. (author)

Energy Refurbishment of an Office Building with Hybrid Photovoltaic System and Demand-Side Management

Directory of Open Access Journals (Sweden)

Giovani Almeida Dávi

2017-08-01

Full Text Available On-site photovoltaic (PV and battery systems intend to improve buildings energy performance, however battery costs and monetary incentives are a major drawback for the introduction of these technologies into the electricity grids. This paper proposes an energy refurbishment of an office building based on multi-objective simulations. An innovative demand-side management approach is analyzed through the PV and battery control with the purpose of reducing grid power peaks and grid imported energy, as well as improving the project economy. Optimization results of load matching and grid interaction parameters, complemented with an economic analysis, are investigated in different scenarios. By means of battery use, the equivalent use of the grid connection is reduced by 12%, enhancing the grid interaction potential, and 10% of load matching rates can be increased. Project improvements indicate the grid connection capacity can be reduced by 13% and significant savings of up to 48% are achieved on yearly bills. The economy demonstrates the grid parity is only achieved for battery costs below 100 €/kWh and the payback period is large: 28 years. In the case with only PV system, the grid parity achieves better outcomes and the payback time is reduced by a half, making this a more attractive option.

Implementing peak load reduction algorithms for household electrical appliances

International Nuclear Information System (INIS)

Dlamini, Ndumiso G.; Cromieres, Fabien

2012-01-01

Considering household appliance automation for reduction of household peak power demand, this study explored aspects of the interaction between household automation technology and human behaviour. Given a programmable household appliance switching system, and user-reported appliance use times, we simulated the load reduction effectiveness of three types of algorithms, which were applied at both the single household level and across all 30 households. All three algorithms effected significant load reductions, while the least-to-highest potential user inconvenience ranking was: coordinating the timing of frequent intermittent loads (algorithm 2); moving period-of-day time-flexible loads to off-peak times (algorithm 1); and applying short-term time delays to avoid high peaks (algorithm 3) (least accommodating). Peak reduction was facilitated by load interruptibility, time of use flexibility and the willingness of users to forgo impulsive appliance use. We conclude that a general factor determining the ability to shift the load due to a particular appliance is the time-buffering between the service delivered and the power demand of an appliance. Time-buffering can be ‘technologically inherent’, due to human habits, or realised by managing user expectations. There are implications for the design of appliances and home automation systems. - Highlights: ► We explored the interaction between appliance automation and human behaviour. ► There is potential for considerable load shifting of household appliances. ► Load shifting for load reduction is eased with increased time buffering. ► Design, human habits and user expectations all influence time buffering. ► Certain automation and appliance design features can facilitate load shifting.

Transactive Control of Commercial Buildings for Demand Response

Energy Technology Data Exchange (ETDEWEB)

Hao, He; Corbin, Charles D.; Kalsi, Karanjit; Pratt, Robert G.

2017-01-01

Transactive control is a type of distributed control strategy that uses market mechanism to engage self-interested responsive loads to achieve power balance in the electrical power grid. In this paper, we propose a transactive control approach of commercial building Heating, Ventilation, and Air- Conditioning (HVAC) systems for demand response. We first describe the system models, and identify their model parameters using data collected from Systems Engineering Building (SEB) located on our Pacific Northwest National Laboratory (PNNL) campus. We next present a transactive control market structure for commercial building HVAC system, and describe its agent bidding and market clearing strategies. Several case studies are performed in a simulation environment using Building Control Virtual Test Bed (BCVTB) and calibrated SEB EnergyPlus model. We show that the proposed transactive control approach is very effective at peak clipping, load shifting, and strategic conservation for commercial building HVAC systems.

The Potential of Combined Heat and Power Generation, Wind Power Generation and Load Management Techniques for Cost Reduction in Small Electricity Supply Systems.

Science.gov (United States)

Bass, Jeremy Hugh

Available from UMI in association with The British Library. Requires signed TDF. An evaluation is made of the potential fuel and financial savings possible when a small, autonomous diesel system sized to meet the demands of an individual, domestic consumer is adapted to include: (1) combined heat and power (CHP) generation, (2) wind turbine generation, (3) direct load control. The potential of these three areas is investigated by means of time-step simulation modelling on a microcomputer. Models are used to evaluate performance and a Net Present Value analysis used to assess costs. A cost/benefit analysis then enables those areas, or combination of areas, that facilitate and greatest savings to be identified. The modelling work is supported by experience gained from the following: (1) field study of the Lundy Island wind/diesel system, (2) laboratory testing of a small diesel generator set, (3) study of a diesel based CHP unit, (4) study of a diesel based direct load control system, (5) statistical analysis of data obtained from the long-term monitoring of a large number of individual household's electricity consumption. Rather than consider the consumer's electrical demand in isolation, a more flexible approach is adopted, with consumer demand being regarded as the sum of primarily two components: a small, electricity demand for essential services and a large, reschedulable demand for heating/cooling. The results of the study indicate that: (1) operating a diesel set in a CHP mode is the best strategy for both financial and fuel savings. A simple retrofit enables overall conversion efficiencies to be increased from 25% to 60%, or greater, at little cost. (2) wind turbine generation in association with direct load control is a most effective combination. (3) a combination of both the above areas enables greatest overall financial savings, in favourable winds resulting in unit energy costs around 20% of those of diesel only operation.

Estimating the Impacts of Direct Load Control Programs Using GridPIQ, a Web-Based Screening Tool

Energy Technology Data Exchange (ETDEWEB)

Pal, Seemita; Thayer, Brandon L.; Barrett, Emily L.; Studarus, Karen E.

2017-11-13

In direct load control (DLC) programs, utilities can curtail the demand of participating loads to contractually agreed-upon levels during periods of critical peak load, thereby reducing stress on the system, generation cost, and required transmission and generation capacity. Participating customers receive financial incentives. The impacts of implementing DLC programs extend well beyond peak shaving. There may be a shift of load proportional to the interrupted load to the times before or after a DLC event, and different load shifts have different consequences. Tools that can quantify the impacts of such programs on load curves, peak demand, emissions, and fossil fuel costs are currently lacking. The Grid Project Impact Quantification (GridPIQ) screening tool includes a Direct Load Control module, which takes into account project-specific inputs as well as the larger system context in order to quantify the impacts of a given DLC program. This allows users (utilities, researchers, etc.) to test and compare different program specifications and their impacts.

Decentralized Voltage Control Coordination of On-Load Tap Changer Transformers, Distributed Generation Units and Flexible Loads

DEFF Research Database (Denmark)

Romani Dalmau, Aina; Martinez Perez, David; Diaz de Cerio Mendaza, Iker

2015-01-01

The increase of distributed generation is expected to generate instabilities, such as power imbalances or voltage deviations in the power system. At the distribution level, maintaining the bus voltages within the stipulated limits is one of the major challenges for the distribution system operator....... Under low penetration levels, several voltage regulation elements have been efficiently employed up to now. However, under large distributed generation levels, the traditional techniques have to be coordinated with new upcoming solutions, such us demand response. In this paper a simple and decentralized...... of the on-load tap changer and the reactive power from dispersed generation while maximizing the capacity usage of the Power-to-Gas load....

Coordinated control of smart microgrid during and after islanding operation to prevent under frequency load shedding using energy storage system

International Nuclear Information System (INIS)

Koohi-Kamali, Sam; Rahim, Nasrudin Abd

2016-01-01

Highlights: • A new power management system is proposed. • The novel idea of using energy storage systems to prevent under frequency load shedding is presented. • A method to estimate rate of change of frequency in islanding mode and to dispatch battery plant is introduced. • Two effective outer control loops are proposed for governor to synchronize the microgrid with main grid. • Solar photovoltaic and battery plants bring the voltage regulation ancillary service for microgrid. - Abstract: This work presents a smart microgrid consisting of diesel, photovoltaic (PV), and battery storage plants. One of the key features of smart grid is to provide a redundant high quality power for the consumers. In islanded microgrid, the under frequency and/or voltage collapse, caused by power deficiency, can lead to power outage. The current practice is to shed the load demand until the frequency and voltage are restored. However, the redundancy in supplying power has no meaning as long as the loads are shed. The main objective of this paper is to propose a power management system (PMS) that protects the microgrid against the load shedding. PMS is able to control the microgrid in both centralized and decentralized fashions. To prevent under frequency load shedding (UFLS), this work proposes using battery energy storage system (BESS) to compensate for the power mismatch in the islanded microgrid. A method is presented to estimate the rate of change of frequency and to calculate the power deficiency. The approximated value is exploited as the set-point to dispatch BESS. PV and battery plants are supposed to share the reactive power demand proportionally and thus regulate the voltage at the load bus. This work also suggests two outer control loops, namely, frequency restoration loop (FRL) and difference angle compensator (DAC). These loops ensure microgrid smooth transition from islanded mode to grid-connected mode. The microgrid is configured to investigate the effective

AN INVESTIGATION TO RESOLVE THE INTERACTION BETWEEN FUEL CELL, POWER CONDITIONING SYSTEM AND APPLICATION LOADS

Energy Technology Data Exchange (ETDEWEB)

Sudip K. Mazumder; Chuck McKintyre; Dan Herbison; Doug Nelson; Comas Haynes; Michael von Spakovsky; Joseph Hartvigsen; S. Elangovan

2003-11-03

Solid-Oxide Fuel Cell (SOFC) stacks respond quickly to changes in load and exhibit high part- and full-load efficiencies due to its rapid electrochemistry. However, this is not true for the thermal, mechanical, and chemical balance-of-plant subsystem (BOPS), where load-following time constants are, typically, several orders of magnitude higher. This dichotomy diminishes the reliability and performance of the electrode with increasing demand of load. Because these unwanted phenomena are not well understood, the manufacturers of SOFC use conservative schemes (such as, delayed load-following to compensate for slow BOPS response or expensive inductor filtering) to control stack responses to load variations. This limits the applicability of SOFC systems for load-varying stationary and transportation applications from a cost standpoint. Thus, a need exists for the synthesis of component- and system-level models of SOFC power-conditioning systems and the development of methodologies for investigating the system-interaction issues (which reduce the lifetime and efficiency of a SOFC) and optimizing the responses of each subsystem, leading to optimal designs of power-conditioning electronics and optimal control strategies, which mitigate the electrical-feedback effects. Equally important are ''multiresolution'' finite-element modeling and simulation studies, which can predict the impact of changes in system-level variables (e.g., current ripple and load-transients) on the local current densities, voltages, and temperature (these parameters are very difficult or cumbersome, if not impossible to obtain) within a SOFC cell. Towards that end, for phase I of this project, sponsored by the U.S. DOE (NETL), we investigate the interactions among fuel cell, power-conditioning system, and application loads and their effects on SOFC reliability (durability) and performance. A number of methodologies have been used in Phase I to develop the steady-state and transient

Measuring and controlling unfairness in decentralized planning of energy demand

NARCIS (Netherlands)

Pournaras, E.; Vasirani, M.; Kooij, R.E.; Aberer, K.

2014-01-01

Demand-side energy management improves robustness and efficiency in Smart Grids. Load-adjustment and load-shifting are performed to match demand to available supply. These operations come at a discomfort cost for consumers as their lifestyle is influenced when they adjust or shift in time their

Roadway network productivity assessment : system-wide analysis under variant travel demand

Science.gov (United States)

2008-11-01

The analysis documented in this report examines the hypothesis that the system-wide productivity of a metropolitan freeway system in peak periods is higher in moderate travel demand conditions than in excessive travel demand conditions. The approach ...

Assessing the financial impacts of distributed energy on load serving entities

International Nuclear Information System (INIS)

Wang, Zeyu; Negash, Ahlmahz; Kirschen, Daniel

2015-01-01

This article analyzes the financial impact of distributed energy resources (DERs) owned and operated by commercial customers on the load serving entities (LSEs). DERs reduce the customers' electricity bills and hence the revenues collected by their LSE. However, changes in customer demand profiles can potentially reduce the aggregated system demand profile, and therefore, reduce the LSE's costs in wholesale markets. Analysis of these financial impacts indicates that the LSE's lost revenue ultimately outweighs its reduced expenses. This is largely due to a significant reduction in revenue from demand charges. Dispatchable DERs, including energy storages and demand response, result in more financial losses for LSEs than photovoltaics. The financial losses LSEs face indicate that redesigning commercial customer tariffs is necessary in order for LSEs to accommodate customer owned DERs properly. Several suggestions on modifying commercial tariffs are presented. - Highlights: • We analyze the financial impacts on load serving entities of DERs owned by commercial customers. • Under the selected commercial tariff, load serving entities suffer economic losses. • Energy storages and demand response results in more financial losses for LSE than photovoltaics. • We provide some suggestions for tariff modifications.

Energy efficiency and demand respond programs play vital roles in short- and long-term system reliability

Energy Technology Data Exchange (ETDEWEB)

Mitola, J. P.

2003-12-01

The effects of deregulation of the electric power industry on the reliability of the power grid in the United States are examined. Three major factors -- customer load, utility infrastructure, and demand response -- together are suggested as being most important; the ability of the industry to maintain the equilibrium among these three factors will determine the success or failure of deregulation. Each of these factors are examined in turn, followed by recommendations encouraging demand response or energy efficiency innovations, particularly new demand response technologies that are reliable, measurable, competitive to end-users, and fully dispatchable to utilities.

The relationship among customer demand, competitive strategy and manufacturing system functional objectives

Directory of Open Access Journals (Sweden)

Wei Xu

2013-09-01

Full Text Available Purpose: To ascertain the relationship between the operation system function goal decision making and customer demand and competition strategy, can better discover and integrate all available resources (including important capital resources to achieve business opportunities, the establishment of sustainable competitive ability. Because, to achieve business development lead policymakers take great uncertainty, which led to the investment behavior required for the operational activities of resources also bear the enormous risks. Design/methodology/approach: Through principal component analysis on the data collected by questionnaires, the manuscript obtains dominant factors for customer demand, competitive strategy and manufacturing system functional objectives respectively. By these factors, it tests its three hypotheses with the data from northeast of China and draws some conclusions. Findings: The results show that customer demand have a significant positive effect on competitive strategy; competitive strategy have positive influence on manufacturing system functional objectives; customer demand affect the functional objectives, by competitive strategy. Research limitations/implications: In this research, competitive strategy and manufacturing system functional objectives are influenced by customer demand. The conclusion of the research can provide theoretical guidance for Chinese enterprises which carry out manufacturing system functional objectives. Originality/value: In this research, a new measure questionnaire of competition strategy, customer satisfaction and operating system function goal was used, analyzed the influence factors of time, quality, cost, efficiency, service and environment, on the operation of the system. The study shows that the effect of competition strategy and customer demand has a direct impact on the operating system functions, customer demand through competitive strategy of indirect effects operating system functions.

Willingness to pay and price elasticities of demand for energy-efficient appliances: Combining the hedonic approach and demand systems

Energy Technology Data Exchange (ETDEWEB)

Galarraga, Ibon, E-mail: ibon.galarraga@bc3research.org; Gonzalez-Eguino, Mikel, E-mail: mikel.gonzalez@bc3research.org; Markandya, Anil, E-mail: anil.markandya@bc3research.org

2011-12-15

This article proposes a combined approach for estimating willingness to pay for the attributes represented by energy efficiency labels and providing reliable price elasticities of demand (own and cross) for close substitutes (e.g. those with low energy efficiency and those with higher energy efficiency). This is done by using the results of the hedonic approach together with the Quantity Based Demand System (QBDS) model. The elasticity results obtained with the latter are then compared with those simulated using the Linear Almost Ideal Demand System (LA/AIDS). The methodology is applied to the dishwasher market in Spain: it is found that 15.6% of the final price is actually paid for the energy efficiency attribute. This accounts for about Euro 80 of the average market price. The elasticity results confirm that energy efficient appliances are more price elastic than regular ones. - Highlights: > The article shows a combined approach for estimating willingness to pay for energy efficiency labels and price elasticities. > The results of the hedonic approach is used together with the Quantity Based Demand System (QBDS) model. > The elasticity results are compared with those simulated using the Linear Almost Ideal Demand System (LA/AIDS). > The methodology is applied to the dishwasher market in Spain.

SPEAR 2 RF SYSTEM LOADS

International Nuclear Information System (INIS)

2002-01-01

The design and performance of higher order mode (HOM) dampers for the SPEAR 2 RF system is presented. The SPEAR beam had experienced occasional periods of instability due to transverse oscillations which were driven by HOMs in the RF cavities. A substantial fraction of this RF energy was coupled out of the cavity into the waveguide connecting the cavity to the klystron. This waveguide was modified by adding a stub of smaller cross section, terminated by a ferrite tile load, to the system. Design considerations of the load, and its effect on HOMs and beam stability will be discussed

Load As A Reliability Resource in the Restructured Electricity Market

Energy Technology Data Exchange (ETDEWEB)

Kueck, J.D.

2002-06-10

Recent electricity price spikes are painful reminders of the value that meaningful demand-side responses could bring to the restructuring US electricity system. Review of the aggregate offers made by suppliers confirms that even a modest increase in demand elasticity could dramatically reduce these extremes in price volatility. There is a strong need for dramatically increased customer participation in these markets to enhance system reliability and reduce price volatility. Indeed, allowing customers to manage their loads in response to system conditions might be thought of as the ultimate reliability resource. Most would agree that meaningful demand-side responses to price are the hallmark of a well-functioning competitive market [1]. Yet, in today's markets for electricity, little or no such response is evident. The reason is simple: customers currently do not experience directly the time-varying costs of their consumption decisions. Consequently, they have no incentive to modify these decisions in ways that might enhance system reliability or improve the efficiency of the markets in which electricity is traded. Increased customer participation is a necessary step in the evolution toward more efficient markets for electricity and ancillary services. This scoping report provides a three-part assessment of the current status of efforts to enhance the ability of customer's load to participate in competitive markets with a specific focus on the role of customer loads in enhancing electricity system reliability. First, this report considers the definitions of electricity-reliability-enhancing ancillary services (Section 2) and a preliminary assessment of the ability of customer's loads to provide these services. Second, is a review a variety of programs in which load has been called on as a system reliability resource (Section 3). These experiences, drawn from both past and current utility and ISO programs, focus on programs triggered by system

Flexible Demand Management under Time-Varying Prices

Science.gov (United States)

Liang, Yong

In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic

1993 Pacific Northwest Loads and Resources Study.

Energy Technology Data Exchange (ETDEWEB)

United States. Bonneville Power Administration.

1993-12-01

The Loads and Resources Study is presented in three documents: (1) this summary of Federal system and Pacific Northwest region loads and resources; (2) a technical appendix detailing forecasted Pacific Northwest economic trends and loads, and (3) a technical appendix detailing the loads and resources for each major Pacific Northwest generating utility. In this loads and resources study, resource availability is compared with a range of forecasted electricity consumption. The forecasted future electricity demands -- firm loads -- are subtracted from the projected capability of existing and {open_quotes}contracted for{close_quotes} resources to determine whether Bonneville Power Administration (BPA) and the region will be surplus or deficit. If resources are greater than loads in any particular year or month, there is a surplus of energy and/or capacity, which BPA can sell to increase revenues. Conversely, if firm loads exceed available resources, there is a deficit of energy and/or capacity, and additional conservation, contract purchases, or generating resources will be needed to meet load growth. The Pacific Northwest Loads and Resources Study analyzes the Pacific Northwest`s projected loads and available generating resources in two parts: (1) the loads and resources of the Federal system, for which BPA is the marketing agency; and (2) the larger Pacific Northwest regional power system, which includes loads and resource in addition to the Federal system. The loads and resources analysis in this study simulates the operation of the power system under the Pacific Northwest Coordination Agreement (PNCA) produced by the Pacific Northwest Coordinating Group. This study presents the Federal system and regional analyses for five load forecasts: high, medium-high, medium, medium-low, and low. This analysis projects the yearly average energy consumption and resource availability for Operating Years (OY) 1994--95 through 2003--04.

Strategies for Demand Response in Commercial Buildings

Energy Technology Data Exchange (ETDEWEB)

Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

2006-06-20

This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demand response strategies discussed herein are based on the results of three years of automated demand response field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demand response events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demand response measures are transient; they are employed to produce a temporary reduction in demand. Demand response strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demand response in commercial buildings. The goal of demand response strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demand response strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

Structural load inventory database for the Kansas City federal complex

International Nuclear Information System (INIS)

Hashimoto, P.S.; Johnson, M.W.; Nakaki, D.K.; Lynch, D.T.; Drury, M.A.

1995-01-01

A structural load inventory database (LID) has been developed to support configuration management at the DOE Kansas City Plant (KCP). The objective of the LID is to record loads supported by the plant structures and to provide rapid assessments of the impact of future facility modifications on structural adequacy. Development of the LID was initiated for the KCP's Main Manufacturing Building. Field walkdowns were performed to determine all significant loads supported by the structure, including the weight of piping, service equipment, etc. These loads were compiled in the LID. Structural analyses for natural phenomena hazards were performed in accordance with UCRL-15910. Software to calculate demands on the structural members due to gravity loads, total demands including both gravity and seismic loads, and structural member demand-to-capacity ratios were also developed and integrated into the LID. Operation of the LID is menu-driven. The LID user has options to review and print existing loads and corresponding demand-to-capacity ratios, and to update the supported loads and demand-to-capacity ratios for any future facility modifications

Demand response power system optimization in presence of renewable energy sources

Directory of Open Access Journals (Sweden)

Dumbrava Virgil

2017-07-01

Full Text Available This paper optimizes the price-based demand response of a large customer in a power system with stochastic production and classical fuel-supplied power plants. The implemented method of optimization, under uncertainty, is helpful to model both the utility functions for the consumers and their technical limitations. The consumers exposed to price-based demand can reduce their cost for electricity procurement by modifying their behavior, possibly shifting their consumption during the day to periods with low electricity prices. The demand is considered elastic to electricity price if the consumer is willing and capable to buy various amounts of energy at different price levels, the demand function being represented as purchasing bidding blocks. The demand response is seen also by the scientific literature as a possible source of the needed flexibility of modern power systems, while the flexibility of conventional generation technologies is restricted by technical constraints, such as ramp rates. This paper shows how wind power generation affects short term operation of the electricity system. Fluctuations in the amount of wind power fed into the grid require, without storage capacities, compensating changes in the output of flexible generators or in the consumers’ behavior. In the presented case study, we show the minimization of the overall costs in presence of stochastic wind power production. For highlighting the variability degree of production from renewable sources, four scenarios of production were formulated, with different probabilities of occurrence. The contribution brought by the paper is represented by the optimization model for demand-response of a large customer in a power system with fossil fueled generators and intermittent renewable energy sources. The consumer can reduce the power system costs by modifying his demand. The demand function is represented as purchasing bidding blocks for the possible price forecasted realizations

Integrating Autonomous Load Controllers in Power Systems

DEFF Research Database (Denmark)

Douglass, Philip James

, but they are characterized by variable generation that is only partly predictable. Managing loads is already used in limited circumstances to improve security and efficiency of the power system. In power systems with a large penetration of variable generation, load management has large role to play in adapting consumption......Electric energy systems stand on the brink of radical change as the urgent need to reduce greenhouse gas emissions pushes more efficient utilization of energy resources and the adoption of renewable energy sources. New renewable sources such as wind and solar have a large potential......-sensitive load controller has been designed, implemented, and tested in real-life settings. Its performance demonstrated a large potential resource, in some cases greater than the average power consumption. The accuracy of load models was validated by comparison with field data. A voltage-sensitive controller...

Alkaline electrolyzer and V2G system DIgSILENT models for demand response analysis in future distribution networks

DEFF Research Database (Denmark)

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

2013-01-01

Grid instabilities originated by unsteady generation, characteristic consequence of some renewable energy resources such as wind and solar power, claims for new power balance solutions in largely penetrated systems. Denmark's solid investment in these energy sources has awaked a need of rethinking...... about the future control and operation of the power system. A widespread idea to face these challenges is to have a flexible demand easily adjustable to the system variations. Electrothermal loads, electric vehicles and hydrogen generation are among the most mentioned technologies capable to respond......, under certain strategies, to these variations. This paper presents two DIgSILENT PowerFactory models: an alkaline electrolyzer and a vehicle to the grid system. The models were performed using DIgSILENT Simulation Language, aiming to be used for long-term distribution systems simulations. Two voltage...

Automatic demand response referred to electricity spot price. Demo description

International Nuclear Information System (INIS)

Grande, Ove S.; Livik, Klaus; Hals, Arne

2006-05-01

This report presents background, technical solution and results from a test project (Demo I) developed in the DRR Norway) project. Software and technology from two different vendors, APAS and Powel ASA, are used to demonstrate a scheme for Automatic Demand Response (ADR) referred to spot price level and a system for documentation of demand response and cost savings. Periods with shortage of energy supply and hardly any investments in new production capacity have turned focus towards the need for increased price elasticity on the demand side in the Nordic power market. The new technology for Automatic Meter Reading (AMR) and Remote Load Control (RLC) provides an opportunity to improve the direct market participation from the demand side by introducing automatic schemes that reduce the need for customer attention to hourly market prices. The low prioritized appliances, and not the total load, are in this report defined as the Demand Response Objects, based on the assumption that there is a limit for what the customers are willing to pay for different uses of electricity. Only disconnection of residential water heaters is included in the demo, due to practical limitations. The test was performed for a group of single family houses over a period of 2 months. All the houses were equipped with a radio controlled 'Ebox' unit attached to the water heater socket. The settlement and invoicing were based on hourly metered values (kWh/h), which means that the customer benefit is equivalent to the accumulated changes in the electricity cost per hour. The actual load reduction is documented by comparison between the real meter values for the period and a reference curve. The curves show significant response to the activated control in the morning hours. In the afternoon it is more difficult to register the response, probably due to 'disturbing' activities like cooking etc. Demo I shows that load reduction referred to spot price level can be done in a smooth way. The experiences

A Cyber Physical Model Based on a Hybrid System for Flexible Load Control in an Active Distribution Network

Directory of Open Access Journals (Sweden)

Yun Wang

2017-02-01

Full Text Available To strengthen the integration of the primary and secondary systems, a concept of Cyber Physical Systems (CPS is introduced to construct a CPS in Power Systems (Power CPS. The most basic work of the Power CPS is to build an integration model which combines both a continuous process and a discrete process. The advanced form of smart grid, the Active Distribution Network (ADN is a typical example of Power CPS. After designing the Power CPS model architecture and its application in ADN, a Hybrid System based model and control method of Power CPS is proposed in this paper. As an application example, ADN flexible load is modeled and controlled with ADN feeder power control by a control strategy which includes the normal condition and the underpowered condition. In this model and strategy, some factors like load power consumption and load functional demand are considered and optimized. In order to make up some of the deficiencies of centralized control, a distributed control method is presented to reduce model complexity and improve calculation speed. The effectiveness of all the models and methods are demonstrated in the case study.

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

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...... 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...... to coordinate the electricity demands of industrial loads, in compliance with external Demand Response events....

Dynamic loads on the primary system

International Nuclear Information System (INIS)

Rohde, J.

1980-01-01

As a result of pipe breaks f.ex. in the primary system of a PWR-plant dynamic forces act on the components of the system as well as on their support-structures and internals. The design basis must guarantee that LOCA or system-transient generated loads cannot produce deformations or fractures that endanger the coolability of the reactor, the emergency feedwater supply to the core-region and a safe shut-down of the reactor. In this lecture the first part of a LOCA will be discussed, where the highest dynamic loads on the primary system are expected. In this connection comments are given on the main assumptions and boundary conditions, the related regulations and guide-lines, as well as the possible consequences of an accident. Next, a review is presented of the analytical methods being used for the determination of thermohydraulic generated loads. The stress-calculations on the basis of these load-functions are discussed in the following lectures. The application of the analytical methods, i.e. the different computer codes, and the verification on the basis of the experimental results are described together with a discussion of the theoretical results. In addition a survey will be given of the research work done in connection with the problems of the dynamic loads under accident conditions. Finally, the problems of the fluid-structure interaction will be explained and comments made on computer code development now under way regarding this problem. A short film will be presented to provide a better understanding of fast transient phenomena. (orig./RW)

Flexible operation of a system of SPSs for load following

Energy Technology Data Exchange (ETDEWEB)

Collins, P Q; Tomkins, R

1984-04-01

Major conclusions of previous studies on the SPS (solar power satellite) project - the proposal to collect solar energy in orbit and to transmit it to earth as a coherent microwave beam for reconversion to electricity - are that the system appears likely to be technically feasible, but that it will be economically feasible only if major reductions are made in the cost of certain subsystems, most notably in the fields of photovoltaic cells and in space transportation and operations. The former field is currently experiencing rapid advances, along with the rest of the semiconductor industry, while the achievement of the necessary cost targets in the latter field will depend on the development of a family of fully reusable space transportation vehicles as a successor to the present U.S. space shuttle. In order to assess the system's full economic potential it is also necessary to examine the most profitable means of operation. Most studies to date have assumed that, because of the SPS's high capital cost and the corresponding need to maximise its usage, each satellite would be used to transmit base load power more or less continuously to a single rectenna. However, this assumption overlooks the fact that the value of electric power is not constant but varies during the day and over the year. It therefore narrows the scope for SPS operation, and ignores a major part of the system's potential value. It also sets the most demanding cost targets for the SPS, since it would be in competition with other base-load plant with the lowest operating costs.

Demand side management program evaluation based on industrial and commercial field data

International Nuclear Information System (INIS)

Eissa, M.M.

2011-01-01

Demand Response is increasingly viewed as an important tool for use by the electric utility industry in meeting the growing demand for electricity. There are two basic categories of demand response options: time varying retail tariffs and incentive Demand Response Programs. is applying the time varying retail tariffs program, which is not suitable according to the studied load curves captured from the industrial and commercial sectors. Different statistical studies on daily load curves for consumers connected to 22 kV lines are classified. The load curve criteria used for classification is based on peak ratio and night ratio. The data considered here is a set of 120 annual load curves corresponding to the electric power consumption (the western area in the King Saudi Arabia (KSA)) of many clients in winter and some months in the summer (peak period). The study is based on real data from several Saudi customer sectors in many geographical areas with larger commercial and industrial customers. The study proved that the suitable Demand Response for the ESC is the incentive program. - Highlights: → Study helps in selecting the proper demand side program. → A credit will be given for the customers during summer months. → Reduction in the electric bill. → Monthly bill credit is decreased based on customers' peak load reduction. → Guide for applying the proper demand side program suitable for the utility and customers.

Using Microsensor Technology to Quantify Match Demands in Collegiate Women's Volleyball.

Science.gov (United States)

Vlantes, Travis G; Readdy, Tucker

2017-12-01

Vlantes, TG and Readdy, T. Using microsensor technology to quantify match demands in collegiate women's volleyball. J Strength Cond Res 31(12): 3266-3278, 2017-The purpose of this study was to quantify internal and external load demands of women's NCAA Division I collegiate volleyball competitions using microsensor technology and session rating of perceived exertion (S-RPE). Eleven collegiate volleyball players wore microsensor technology (Optimeye S5; Catapult Sports, Chicago, IL, USA) during 15 matches played throughout the 2016 season. Parameters examined include player load (PL), high impact PL, percentage of HI PL, explosive efforts (EEs), and jumps. Session rating of perceived exertion was collected 20 minutes postmatch using a modified Borg scale. The relationship between internal and external load was explored, comparing S-RPE data with the microsensor metrics (PL, HI PL, % HI PL, EEs, and jumps). The setter had the greatest mean PL and highest number of jumps of all positions in a 5-1 system, playing all 6 rotations. Playing 4 sets yielded a mean PL increase of 25.1% over 3 sets, whereas playing 5 sets showed a 31.0% increase in PL. A multivariate analysis of variance revealed significant differences (p < 0.01) across all position groups when examining % HI PL and jumps. Cohen's d analysis revealed large (≥0.8) effect sizes for these differences. Defensive specialists recorded the greatest mean S-RPE values over all 15 matches (886 ± 384.6). Establishing positional load demands allows coaches, trainers, and strength and conditioning professionals to implement training programs for position-specific demands, creating consistent peak performance, and reducing injury risk.

Commercial equipment loads: End-Use Load and Consumer Assessment Program (ELCAP)

Energy Technology Data Exchange (ETDEWEB)

Pratt, R.G.; Williamson, M.A.; Richman, E.E.; Miller, N.E.

1990-07-01

The Office of Energy Resources of the Bonneville Power Administration is generally responsible for the agency's power and conservation resource planning. As associated responsibility which supports a variety of office functions is the analysis of historical trends in and determinants of energy consumption. The Office of Energy Resources' End-Use Research Section operates a comprehensive data collection program to provide pertinent information to support demand-side planning, load forecasting, and demand-side program development and delivery. Part of this on-going program is known as the End-Use Load and Consumer Assessment Program (ELCAP), an effort designed to collect electricity usage data through direct monitoring of end-use loads in buildings. This program is conducted for Bonneville by the Pacific Northwest Laboratory. This report provides detailed information on electricity consumption of miscellaneous equipment from the commercial portion of ELCAP. Miscellaneous equipment includes all commercial end-uses except heating, ventilating, air conditioning, and central lighting systems. Some examples of end-uses covered in this report are office equipment, computers, task lighting, refrigeration, and food preparation. Electricity consumption estimates, in kilowatt-hours per square food per year, are provided for each end-use by building type. The following types of buildings are covered: office, retail, restaurant, grocery, warehouse, school, university, and hotel/motel. 6 refs., 35 figs., 12 tabs.

A combined loading system integrated with portable winch and polyethylene chutes for loading of timber products

Directory of Open Access Journals (Sweden)

H. Hulusi Acar

2016-01-01

Full Text Available Truck loading operation is an important task during timber production operations in forestry. In Turkey, approximately 50 million timbers/logs are being produced per year, and then they are loaded into the logging trucks. The timber/logs are transported over the forest roads with an average of one million roundtrips. However, the traditional loading methods using manpower are mostly performed while some part is done by using loading machines which can be very costly and risky. This study aims developing a combined loading system in which heavy logs are loaded into logging trucks by pulling them by a log-line powered by a portable crane within the chute system. The slope of the log-line from ground to logging truck varied between 1% and 25%. Within the each work cycle of loading operation, only one log was loaded by pulling with portable crane. The average loading time was found as 161.8 seconds per cycle, in which 67% of the time was spent on pulling the log into the logging truck. The results indicated that the average pulling speed with crane power was 840.4 m/hr and productivity was calculated as 4.94 m3/hr. The result on system speed and productivity indicated close relations with results from previous studies. The hydraulic grapple loader or cranes are widely used and common loading machines, but they cannot be efficiently used in forestry operations, especially ones having a low timber productivity rate or having low economic value timber. In these conditions, loading methods that are cost efficient and do not require higher production rate should be employed. Therefore, a combined loading system introduced in this study can be a feasible solution for loading operations in those cases. Furthermore, it is believed that this loading system integrated with a portable crane can be cost efficient and time saving solution, as well as ergonomic and safe method in the field.

An economic welfare analysis of demand response in the PJM electricity market

International Nuclear Information System (INIS)

Walawalkar, Rahul; Blumsack, Seth; Apt, Jay; Fernands, Stephen

2008-01-01

We analyze the economic properties of the economic demand-response (DR) program in the PJM electricity market in the United States using DR market data. PJM's program provided subsidies to customers who reduced load in response to price signals. The program incorporated a 'trigger point', at a locational marginal price of $75/MWh, at or beyond which payments for load reduction included a subsidy payment. Particularly during peak hours, such a program saves money for the system, but the subsidies involved introduce distortions into the market. We simulate demand-side bidding into the PJM market, and compare the social welfare gains with the subsidies paid to price-responsive load using load and price data for year 2006. The largest economic effect is wealth transfers from generators to non price-responsive loads. Based on the incentive payment structure that was in effect through the end of 2007, we estimate that the social welfare gains exceed the distortions introduced by the subsidies. Lowering the trigger point increases the transfer from generators to consumers, but may result in the subsidy outweighing the social welfare gains due to load curtailment. We estimate that the socially optimal range for the incentive trigger point would be $66-77/MWh

The best-mix of power demand and supply. Energy system integration

International Nuclear Information System (INIS)

Ogimoto, Kazuhiko

2012-01-01

In September 2012 after nationwide discussions, Energy and Environmental Council decided 'Innovative Strategy for Energy and the Environment': (1) Realization of a society not dependent on nuclear power, (2) Realization of green energy revolution, (3) For ensuring stable supply of energy, (4) Bold implementation of reform of electricity power systems and (5) Steady implementation of global warming countermeasures. Energy problem should be considered as supply and demand of whole energy. However, long-term energy problem such as in 2050 should assume global limits of fossil fuel supply and carbon dioxide emission and then in order to realize sustainable demand and supply of energy, maximum deployment of renewable energy power in primary energy and most practicable electrification of final demand for energy conservation should be implemented. Best mix of power and energy demand and supply would be significant to some extent. This article outlined analysis of power demand and supply in a long term, future power technologies and demand side management, and problems of power system operation and their solution, and then described energy system integration to realize power and energy/society best mix. (T. Tanaka)

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

International Nuclear Information System (INIS)

Gyamfi, Samuel; Krumdieck, Susan

2011-01-01

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: → Multiple-factor behaviour intervention is necessarily for effective residential demand response. → Security signals can achieve result comparable to price. → The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. → New Zealand's energy policy should include innovation and development of VDR programmes and technologies.

Load Control System Reliability

Energy Technology Data Exchange (ETDEWEB)

Trudnowski, Daniel [Montana Tech of the Univ. of Montana, Butte, MT (United States)

2015-04-03

This report summarizes the results of the Load Control System Reliability project (DOE Award DE-FC26-06NT42750). The original grant was awarded to Montana Tech April 2006. Follow-on DOE awards and expansions to the project scope occurred August 2007, January 2009, April 2011, and April 2013. In addition to the DOE monies, the project also consisted of matching funds from the states of Montana and Wyoming. Project participants included Montana Tech; the University of Wyoming; Montana State University; NorthWestern Energy, Inc., and MSE. Research focused on two areas: real-time power-system load control methodologies; and, power-system measurement-based stability-assessment operation and control tools. The majority of effort was focused on area 2. Results from the research includes: development of fundamental power-system dynamic concepts, control schemes, and signal-processing algorithms; many papers (including two prize papers) in leading journals and conferences and leadership of IEEE activities; one patent; participation in major actual-system testing in the western North American power system; prototype power-system operation and control software installed and tested at three major North American control centers; and, the incubation of a new commercial-grade operation and control software tool. Work under this grant certainly supported the DOE-OE goals in the area of “Real Time Grid Reliability Management.”

A future Demand Side Management (DSM) opportunity for utility as variable renewable penetrate scale up using agriculture.

Science.gov (United States)

Ines, A.; Bhattacharjee, A.; Modi, V.; Robertson, A. W.; Lall, U.; Kocaman Ayse, S.; Chaudhary, S.; Kumar, A.; Ganapathy, A.; Kumar, A.; Mishra, V.

2015-12-01

Energy demand management, also known as demand side management (DSM), is the modification of consumer demand for energy through various methods such as smart metering, incentive based schemes, payments for turning off loads or rescheduling loads. Usually, the goal of demand side management is to encourage the consumer to use less power during periods of peak demand, or to move the time of energy use to off-peak times. Peak demand management does not necessarily decrease total energy consumption, but could be expected to reduce the need for investments in networks and/or power plants for meeting peak demands. Electricity use can vary dramatically on short and medium time frames, and the pricing system may not reflect the instantaneous cost as additional higher-cost that are brought on-line. In addition, the capacity or willingness of electricity consumers to adjust to prices by altering elasticity of demand may be low, particularly over short time frames. In the scenario of Indian grid setup, the retail customers do not follow real-time pricing and it is difficult to incentivize the utility companies for continuing the peak demand supply. A question for the future is how deeper penetration of renewable will be handled? This is a challenging problem since one has to deal with high variability, while managing loss of load probabilities. In the case of managing the peak demand using agriculture, in the future as smart metering matures with automatic turn on/off for a pump, it will become possible to provide an ensured amount of water or energy to the farmer while keeping the grid energized for 24 hours. Supply scenarios will include the possibility of much larger penetration of solar and wind into the grid. While, in absolute terms these sources are small contributors, their role will inevitably grow but DSM using agriculture could help reduce the capital cost. The other option is of advancing or delaying pump operating cycle even by several hours, will still ensure

Multi-objective dynamic economic emission dispatch of electric power generation integrated with game theory based demand response programs

International Nuclear Information System (INIS)

Nwulu, Nnamdi I.; Xia, Xiaohua

2015-01-01

Highlights: • In this work, a game theory based DR program is integrated into the DEED problem. • Objectives are to minimize fuel and emissions costs and maximize the DR benefit. • Optimal generator output, customer load and customer incentive are determined. • Developed model is tested with two different scenarios. • Model provides superior results than independent optimization of DR or DEED. - Abstract: The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demand response program into the DEED problem. The game theory based demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model

Do 'enabling technologies' affect customer performance in price-responsive load programs?

International Nuclear Information System (INIS)

Goldman, Charles A.; Kintner-Meyer, Michael; Heffner, Grayson

2002-01-01

Price-responsive load (PRL) programs vary significantly in overall design, the complexity of relationships between program administrators, load aggregators, and customers, and the availability of ''enabling technologies''. Enabling technologies include such features as web-based power system and price monitoring, control and dispatch of curtailable loads, communications and information systems links to program participants, availability of interval metering data to customers in near real time, and building/facility/end-use automation and management capabilities. Two state agencies - NYSERDA in New York and the CEC in California - have been conspicuous leaders in the demonstration of demand response (DR) programs utilizing enabling technologies. In partnership with key stakeholders in these two states (e.g., grid operator, state energy agencies, and program administrators), Lawrence Berkeley National Laboratory (LBNL) and Pacific Northwest National Laboratory (PNNL) surveyed 56 customers who worked with five contractors participating in CEC or NYSERDA-sponsored DR programs. We combined market research and actual load curtailment data when available (i.e., New York) or customer load reduction targets in order to explore the relative importance of contractor's program design features, sophistication of control strategies, and reliance on enabling technologies in predicting customer's ability to deliver load reductions in DR programs targeted to large commercial/industrial customers. We found preliminary evidence that DR enabling technology has a positive effect on load curtailment potential. Many customers indicated that web-based energy information tools were useful for facilitating demand response (e.g., assessing actual performance compared to load reduction contract commitments), that multiple notification channels facilitated timely response, and that support for and use of backup generation allowed customers to achieve significant and predictable load

Energy demand projections based on an uncertain dynamic system modeling approach

International Nuclear Information System (INIS)

Dong, S.

2000-01-01

Today, China has become the world's second largest pollution source of CO 2 . Owing to coal-based energy consumption, it is estimated that 85--90% of the SO 2 and CO 2 emission of China results from coal use. With high economic growth and increasing environmental concerns, China's energy consumption in the next few decades has become an issue of active concern. Forecasting of energy demand over long periods, however, is getting more complex and uncertain. It is believed that the economic and energy systems are chaotic and nonlinear. Traditional linear system modeling, used mostly in energy demand forecasts, therefore, is not a useful approach. In view of uncertainty and imperfect information about future economic growth and energy development, an uncertain dynamic system model, which has the ability to incorporate and absorb the nature of an uncertain system with imperfect or incomplete information, is developed. Using the model, the forecasting of energy demand in the next 25 years is provided. The model predicts that China's energy demand in 2020 will be about 2,700--3,000 Mtce, coal demand 3,500 Mt, increasing by 128% and 154%, respectively, compared with that of 1995

An Intuitive Definition of Demand Flexibility in Direct Load Control

DEFF Research Database (Denmark)

Tahersima, Fatemeh; Madsen, Per Printz; Andersen, Palle

2013-01-01

Two control approaches: direct and indirect control of demand side energy management in a smart grid are studied. Indirect control of energy demands is based on economic incentives. In this approach, consumers will shift their energy consumption with the benefit of a cut down in the electricity b...

Study of Power Fluctuation from Dispersed Generations and Loads and its Impact on a Distribution Network through a Probabilistic Approach

DEFF Research Database (Denmark)

Chen, Peiyuan; Chen, Zhe; Bak-Jensen, Birgitte

2007-01-01

In order to assess the performance of distribution system under normal operating conditions with large integration of renewable energy based dispersed generation (DG) units, probabilistic modeling of the distribution system is necessary in order to take into consideration the stochastic behavior...... of load demands and DG units such as wind generation and combined heat and power plant generation. This paper classifies probabilistic models of load demands and DG units into summer and winter period, weekday and weekend as well as in 24 hours a day. The voltage results from the probabilistic load flow...

Including dynamic CO2 intensity with demand response

International Nuclear Information System (INIS)

Stoll, Pia; Brandt, Nils; Nordström, Lars

2014-01-01

Hourly demand response tariffs with the intention of reducing or shifting loads during peak demand hours are being intensively discussed among policy-makers, researchers and executives of future electricity systems. Demand response rates have still low customer acceptance, apparently because the consumption habits requires stronger incentive to change than any proposed financial incentive. An hourly CO 2 intensity signal could give customers an extra environmental motivation to shift or reduce loads during peak hours, as it would enable co-optimisation of electricity consumption costs and carbon emissions reductions. In this study, we calculated the hourly dynamic CO 2 signal and applied the calculation to hourly electricity market data in Great Britain, Ontario and Sweden. This provided a novel understanding of the relationships between hourly electricity generation mix composition, electricity price and electricity mix CO 2 intensity. Load shifts from high-price hours resulted in carbon emission reductions for electricity generation mixes where price and CO 2 intensity were positively correlated. The reduction can be further improved if the shift is optimised using both price and CO 2 intensity. The analysis also indicated that an hourly CO 2 intensity signal can help avoid carbon emissions increases for mixes with a negative correlation between electricity price and CO 2 intensity. - Highlights: • We present a formula for calculating hybrid dynamic CO 2 intensity of electricity generation mixes. • We apply the dynamic CO 2 Intensity on hourly electricity market prices and generation units for Great Britain, Ontario and Sweden. • We calculate the spearman correlation between hourly electricity market price and dynamic CO 2 intensity for Great Britain, Ontario and Sweden. • We calculate carbon footprint of shifting 1 kWh load daily from on-peak hours to off-peak hours using the dynamic CO 2 intensity. • We conclude that using dynamic CO 2 intensity for

Research Based on AMESim of Electro-hydraulic Servo Loading System

Science.gov (United States)

Li, Jinlong; Hu, Zhiyong

2017-09-01

Electro-hydraulic servo loading system is a subject studied by many scholars in the field of simulation and control at home and abroad. The electro-hydraulic servo loading system is a loading device simulation of stress objects by aerodynamic moment and other force in the process of movement, its function is all kinds of gas in the lab condition to analyze stress under dynamic load of objects. The purpose of this paper is the design of AMESim electro-hydraulic servo system, PID control technology is used to configure the parameters of the control system, complete the loading process under different conditions, the optimal design parameters, optimization of dynamic performance of the loading system.

The Role of Demand Resources In Regional Transmission Expansion Planning and Reliable Operations

Energy Technology Data Exchange (ETDEWEB)

Kirby, Brendan J [ORNL

2006-07-01

Investigating the role of demand resources in regional transmission planning has provided mixed results. On one hand there are only a few projects where demand response has been used as an explicit alternative to transmission enhancement. On the other hand there is a fair amount of demand response in the form of energy efficiency, peak reduction, emergency load shedding, and (recently) demand providing ancillary services. All of this demand response reduces the need for transmission enhancements. Demand response capability is typically (but not always) factored into transmission planning as a reduction in the load which must be served. In that sense demand response is utilized as an alternative to transmission expansion. Much more demand response is used (involuntarily) as load shedding under extreme conditions to prevent cascading blackouts. The amount of additional transmission and generation that would be required to provide the current level of reliability if load shedding were not available is difficult to imagine and would be impractical to build. In a very real sense demand response solutions are equitably treated in every region - when proposed, demand response projects are evaluated against existing reliability and economic criteria. The regional councils, RTOs, and ISOs identify needs. Others propose transmission, generation, or responsive load based solutions. Few demand response projects get included in transmission enhancement plans because few are proposed. But this is only part of the story. Several factors are responsible for the current very low use of demand response as a transmission enhancement alternative. First, while the generation, transmission, and load business sectors each deal with essentially the same amount of electric power, generation and transmission companies are explicitly in the electric power business but electricity is not the primary business focus of most loads. This changes the institutional focus of each sector. Second

Active load management in an intelligent building using model predictive control strategy

DEFF Research Database (Denmark)

Zong, Yi; Kullmann, Daniel; Thavlov, Anders

2011-01-01

This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system (SYSLAB) with a high penetration of renewable energy and presents in detail on how to implement a thermal model predictive controller for load...... shifting in PowerFlexHouse heaters' power consumption scheme. With this demand side control study, it is expected that this method of demand response can dramatically raise energy efficiencies and improve grid reliability, when there is a high penetration of intermittent energy resources in the power...

Information system design for demand-driven supply networks

OpenAIRE

Selk, Bernhard

2004-01-01

Information system design for demand-driven supply networks : integrating CRM & SCM / B. Selk, K. Turowski, C. Winnewisser. - In: EIS : Fourth International ICSC Symposium on Engineering of Intelligent Systems, EIS 2004. [Elektronische Ressource]. - Millet, Alberta : ICSC Interdisciplinary Research Canada, 2004. - 8 S. auf CD-ROM

Coordinating plug-in electric vehicle charging with electric grid: Valley filling and target load following

Science.gov (United States)

Zhang, Li; Jabbari, Faryar; Brown, Tim; Samuelsen, Scott

2014-12-01

Plug-in electric vehicles (PEVs) shift energy consumption from petroleum to electricity for the personal transportation sector. This work proposes a decentralized charging protocol for PEVs with grid operators updating the cost signal. Each PEV calculates its own optimal charging profile only once based on the cost signal, after it is plugged in, and sends the result back to the grid operators. Grid operators only need to aggregate charging profiles and update the load and cost. The existing PEV characteristics, national household travel survey (NHTS), California Independent System Operator (CAISO) demand, and estimates for future renewable generation in California are used to simulate PEV operation, PEV charging profiles, grid demand, and grid net load (demand minus renewable). Results show the proposed protocol has good performance for overnight net load valley filling if the costs to be minimized are proportional to the net load. Annual results are shown in terms of overnight load variation and comparisons are made with grid level valley filling results. Further, a target load can be approached in the same manner by using the gap between current load and the target load as the cost. The communication effort involved is quite modest.

Automated system for load flow prediction in power substations using artificial neural networks

Directory of Open Access Journals (Sweden)

Arlys Michel Lastre Aleaga

2015-09-01

Full Text Available The load flow is of great importance in assisting the process of decision making and planning of generation, distribution and transmission of electricity. Ignorance of the values in this indicator, as well as their inappropriate prediction, difficult decision making and efficiency of the electricity service, and can cause undesirable situations such as; the on demand, overheating of the components that make up a substation, and incorrect planning processes electricity generation and distribution. Given the need for prediction of flow of electric charge of the substations in Ecuador this research proposes the concept for the development of an automated prediction system employing the use of Artificial Neural Networks.

Adaptive Control System for Autonomous Helicopter Slung Load Operations

DEFF Research Database (Denmark)

Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon

2010-01-01

system on the helicopter that measures the position of the slung load. The controller is a combined feedforward and feedback scheme for simultaneous avoidance of swing excitation and active swing damping. Simulations and laboratory flight tests show the effectiveness of the combined control system......This paper presents design and verification of an estimation and control system for a helicopter slung load system. The estimator provides position and velocity estimates of the slung load and is designed to augment existing navigation in autonomous helicopters. Sensor input is provided by a vision......, yielding significant load swing reduction compared to the baseline controller....

Optimization of 10 kW solar photovoltaic – diesel generator hybrid energy system for different load factors at Jaisalmer location of Rajasthan, India

Science.gov (United States)

Saraswat, S. K.; Rao, K. V. S.

2018-03-01

Jaisalmer town in Rajasthan, India is having annual average solar insolation of 5.80 kWh/m2/day and 270 – 300 clear sky days in a year. A 10 kW off-grid hybrid energy system (HES) consisting of solar photovoltaic panels – diesel generator – bidirectional converter and batteries with zero percentage loss of load for Jaisalmer is designed using HOMER (version 3.4.3) software. Different system load factors of 0.33, 0.50, 0.67, 0.83 and 1 corresponding to fraction of running hours per day of the system are considered. The system is analyzed for all three aspects, namely, electrical, economic and emission point of view. Least levelized cost of electricity (LCOE) of Rs. 8.43/kWh is obtained at a load factor value of 0.5. If diesel generator alone (without Solar PV) is used to fulfil the demand for a load factor of 0.5the value of LCOE is obtained Rs.19.23/kWh. Comparison of results obtained for HES and diesel generator are made for load factor of 0.5 and 1.

Balancing supply and demand resources

International Nuclear Information System (INIS)

Sinha, J.; Saleeby, R.G.

1990-01-01

This article deals with using demand-side management (DSM) resources as an effective means of balancing supply and demand as a part of least-cost planning. The authors present a more sophisticated application of the load forecast adjustment method that reduces the number of DSM programs that need to be evaluated and provides blocks large enough to eliminate resolution problems in production costing models

Performance Evaluation of a Thermal Load Reduction System in a Hyundai Sonata PHEV