Analysis on factors affecting household customers decision in using electricity at peak time and its correlation towards saving electricity

Science.gov (United States)

Pasasa, Linus; Marbun, Parlin; Mariza, Ita

2015-09-01

The purpose of this paper is to study and analyse the factors affecting customer decisions in using electricity at peak-load hours (between 17.00 to 22.00 WIB) and their behaviors towards electricity conservation in Indonesian household. The underlying rationale is to influence a reduction in energy consumption by stimulating energy saving behaviors, thereby reducing the impact of energy use on the environment. How is the correlation between the decisions in using electricity during peak load hours with the household customer's behavior towards saving electricity? The primary data is obtained by distributing questionnaires to customers of PT. PLN Jakarta Raya and Tangerang Distribution from Household segment. The data is analysed using the Structural Equation Model (SEM) and AMOS Software. The research is finding that all factors (Personal, Social, PLN Services, Psychological, and Cultural) are positively influence customer decision in using electricity at peak load hours. There is a correlation between the decisions in using electricity during peak load hours with the household customer's behavior towards saving electricity.

Hydrogen or Fossil Combustion Nuclear Combined Cycle Systems for Baseload and Peak Load Electricity Production. Annex X

Energy Technology Data Exchange (ETDEWEB)

NONE

2013-12-15

A combined cycle power plant is described that uses: (i) heat from a high temperature nuclear reactor to meet baseload electrical demands; and (ii) heat from the same high temperature reactor and burning natural gas, jet fuel or hydrogen to meet peak load electrical demands. For baseload electricity production, fresh air is compressed, then flows through a heat exchanger, where it is heated to between 700 and 900{sup o}C by using heat provided by a high temperature nuclear reactor via an intermediate heat transport loop, and finally exits through a high temperature gas turbine to produce electricity. The hot exhaust from the Brayton cycle gas turbine is then fed to a heat recovery steam generator that provides steam to a steam turbine for added electrical power production. To meet peak electricity demand, the air is first compressed and then heated with the heat from a high temperature reactor. Natural gas, jet fuel or hydrogen is then injected into the hot air in a combustion chamber, combusts and heats the air to 1300{sup o}C - the operating conditions for a standard natural gas fired combined cycle plant. The hot gas then flows through a gas turbine and a heat recovery steam generator before being sent to the exhaust stack. The higher temperatures increase the plant efficiency and power output. If hydrogen is used, it can be produced at night using energy from the nuclear reactor and stored until required. With hydrogen serving as the auxiliary fuel for peak power production, the electricity output to the electrical grid can vary from zero (i.e. when hydrogen is being produced) to the maximum peak power while the nuclear reactor operates at constant load. As nuclear heat raises air temperatures above the auto-ignition temperatures of the various fuels and powers the air compressor, the power output can be varied rapidly (compared with the capabilities of fossil fired turbines) to meet spinning reserve requirements and stabilize the electrical grid. This combined

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

Technical Potential for Peak Load Management Programs in New Jersey

Energy Technology Data Exchange (ETDEWEB)

Kirby, B.J.

2002-12-13

Restructuring is attempting to bring the economic efficiency of competitive markets to the electric power industry. To at least some extent it is succeeding. New generation is being built in most areas of the country reversing the decades-long trend of declining reserve margins. Competition among generators is typically robust, holding down wholesale energy prices. Generators have shown that they are very responsive to price signals in both the short and long term. But a market that is responsive only on the supply side is only half a market. Demand response (elasticity) is necessary to gain the full economic advantages that restructuring can offer. Electricity is a form of energy that is difficult to store economically in large quantities. However, loads often have some ability to (1) conveniently store thermal energy and (2) defer electricity consumption. These inherent storage and control capabilities can be exploited to help reduce peak electric system consumption. In some cases they can also be used to provide system reliability reserves. Fortunately too, technology is helping. Advances in communications and control technologies are making it possible for loads ranging from residential through commercial and industrial to respond to economic signals. When we buy bananas, we don't simply take a dozen and wait a month to find out what the price was. We always ask about the price before we decide how many bananas we want. Technology is beginning to allow at least some customers to think about their electricity consumption the same way they think about most of their other purchases. And power system operators and regulators are beginning to understand that customers need to remain in control of their own destinies. Many customers (residential through industrial) are willing to respond to price signals. Most customers are not able to commit to specific responses months or years in advance. Electricity is a fluid market commodity with a volatile value to both

Specific gas turbines for extreme peak-load

International Nuclear Information System (INIS)

Bellot, C.

1992-12-01

As with other European countries, in France peak consumption of electricity occurs during winter. Due to the increasing use of electricity for domestic heating, outside temperature greatly influences consumption (1 200 MW for a drop of 1 deg C). To meet requirements during cold spells, EDF has sought to determine which special facilities are best suited for extreme peak load conditions (i.e. offering short lifespan and minimum capital cost) and has studied the possibility of installing generation means in transformer substations (20 kV). This solution does not require extension of networks since these means are scattered near consumption areas. An experiment conducted on 3 Diesel generators of 800 kWe each at Senlis revealed some of the disadvantages of Diesel (maintenance requirements, polluting emissions and noise). EDF then examined, for this same application, the use of gas turbines, for which these drawbacks are significantly less. A study carried out under an EDF contract by the French manufacturer TURBOMECA showed that it is possible to design a small capacity gas turbine that can compete with Diesel generators, and that capital costs could be minimized by simplifying the machine, adapting its lifespan to extreme peak load needs, and taking advantage of lower cost provided by mass production. TURBOMECA defined the machine's characteristics (2 MW, 6 000 hours lifespan) and aerodynamic flow. It also estimated the cost of packaging. In terms of overall cost (including initial investment, maintenance and fuel) the gas turbine appears cheaper than Diesel generators for annual operation times of less than one hundred hours, which corresponds closely with extreme peak load use. The lower maintenance costs and the better availability counterbalance the higher capital cost (+6%) and the greater consumption (+50%). (author). 7 figs

Peak-load management, the security of supply warranty

International Nuclear Information System (INIS)

2010-01-01

Even if France owns an efficient power generation park, largely exporting and clean (90% with no CO 2 emission), it encounters some difficulties during peak-load periods. The successive peak power demand records which are recorded each year represent as many alerts about a possible collapse of the power system. In order to warrant the electricity supply, the present day regulatory framework must be changed to allow the industrial players to carry out the necessary investments

Forecasting monthly peak demand of electricity in India—A critique

International Nuclear Information System (INIS)

Rallapalli, Srinivasa Rao; Ghosh, Sajal

2012-01-01

The nature of electricity differs from that of other commodities since electricity is a non-storable good and there have been significant seasonal and diurnal variations of demand. Under such condition, precise forecasting of demand for electricity should be an integral part of the planning process as this enables the policy makers to provide directions on cost-effective investment and on scheduling the operation of the existing and new power plants so that the supply of electricity can be made adequate enough to meet the future demand and its variations. Official load forecasting in India done by Central Electricity Authority (CEA) is often criticized for being overestimated due to inferior techniques used for forecasting. This paper tries to evaluate monthly peak demand forecasting performance predicted by CEA using trend method and compare it with those predicted by Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) model. It has been found that MSARIMA model outperforms CEA forecasts both in-sample static and out-of-sample dynamic forecast horizons in all five regional grids in India. For better load management and grid discipline, this study suggests employing sophisticated techniques like MSARIMA for peak load forecasting in India. - Highlights: ► This paper evaluates monthly peak demand forecasting performance by CEA. ► Compares CEA forecasts it with those predicted by MSARIMA model. ► MSARIMA model outperforms CEA forecasts in all five regional grids in India. ► Opportunity exists to improve the performance of CEA forecasts.

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.

Contribution to performing gas solutions and the complementarity of energies to address electric peak consumptions

International Nuclear Information System (INIS)

2015-01-01

This article aims at outlining the contribution that gas-based solutions may have for the reduction of the seasonal electricity peak consumption. After having recalled the principles related to electricity peak consumption (daily peak in summer and in winter due to the use of various equipment which lasts few hours, seasonal peak in winter due to the use of electric heating which may last several weeks) and the associated evolution of electricity consumptions over the last years, this article describes the main challenges related to the electric peak consumption: how to maintain the balance in real time between production and consumption. In France, the network manager must use, beside nuclear power stations, thermal productions (gas or coal-based) which result in higher CO 2 emissions. Electricity imports from Germany also degrade the French carbon footprint. Thus, the management of daily and seasonal peaks can be based on three levers of action: to act on supply by developing capacities to face the residual peak, to act on demand by smoothing the load curve by controlling the load of electric equipment, or to act on demand by a global reduction of the thermo-sensitive consumption of electricity

Extreme daily increases in peak electricity demand: Tail-quantile estimation

International Nuclear Information System (INIS)

Sigauke, Caston; Verster, Andréhette; Chikobvu, Delson

2013-01-01

A Generalized Pareto Distribution (GPD) is used to model extreme daily increases in peak electricity demand. The model is fitted to years 2000–2011 recorded data for South Africa to make a comparative analysis with the Generalized Pareto-type (GP-type) distribution. Peak electricity demand is influenced by the tails of probability distributions as well as by means or averages. At times there is a need to depart from the average thinking and exploit information provided by the extremes (tails). Empirical results show that both the GP-type and the GPD are a good fit to the data. One of the main advantages of the GP-type is the estimation of only one parameter. Modelling of extreme daily increases in peak electricity demand helps in quantifying the amount of electricity which can be shifted from the grid to off peak periods. One of the policy implications derived from this study is the need for day-time use of electricity billing system similar to the one used in the cellular telephone/and fixed line-billing technology. This will result in the shifting of electricity demand on the grid to off peak time slots as users try to avoid high peak hour charges. - Highlights: ► Policy makers should design demand response strategies to save electricity. ► Peak electricity demand is influenced by tails of probability distributions. ► Both the GSP and the GPD are a good fit to the data. ► Accurate assessment of level and frequency of extreme load forecasts is important.

Impacts of Using Distributed Energy Resources to Reduce Peak Loads in Vermont

Energy Technology Data Exchange (ETDEWEB)

Ruth, Mark F. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lunacek, Monte S. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jones, Birk [Univ. of New Mexico, Albuquerque, NM (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-11-28

To help the United States develop a modern electricity grid that provides reliable power from multiple resources as well as resiliency under extreme conditions, the U.S. Department of Energy (DOE) is leading the Grid Modernization Initiative (GMI) to help shape the future of the nation's grid. Under the GMI, DOE funded the Vermont Regional Initiative project to provide the technical support and analysis to utilities that need to mitigate possible impacts of increasing renewable generation required by statewide goals. Advanced control of distributed energy resources (DER) can both support higher penetrations of renewable energy by balancing controllable loads to wind and photovoltaic (PV) solar generation and reduce peak demand by shedding noncritical loads. This work focuses on the latter. This document reports on an experiment that evaluated and quantified the potential benefits and impacts of reducing the peak load through demand response (DR) using centrally controllable electric water heaters (EWHs) and batteries on two Green Mountain Power (GMP) feeders. The experiment simulated various hypothetical scenarios that varied the number of controllable EWHs, the amount of distributed PV systems, and the number of distributed residential batteries. The control schemes were designed with several objectives. For the first objective, the primary simulations focused on reducing the load during the independent system operator (ISO) peak when capacity charges were the primary concern. The second objective was to mitigate DR rebound to avoid new peak loads and high ramp rates. The final objective was to minimize customers' discomfort, which is defined by the lack of hot water when it is needed. We performed the simulations using the National Renewable Energy Laboratory's (NREL's) Integrated Energy System Model (IESM) because it can simulate both electric power distribution feeder and appliance end use performance and it includes the ability to simulate

Modelling and analysis of a novel compressed air energy storage system for trigeneration based on electrical energy peak load shifting

International Nuclear Information System (INIS)

Lv, Song; He, Wei; Zhang, Aifeng; Li, Guiqiang; Luo, Bingqing; Liu, Xianghua

2017-01-01

Highlights: • A new CAES system for trigeneration based on electrical peak load shifting is proposed. • The theoretical models and the thermodynamics process are established and analyzed. • The relevant parameters influencing its performance have been discussed and optimized. • A novel energy and economic evaluation methods is proposed to evaluate the performance of the system. - Abstract: The compressed air energy storage (CAES) has made great contribution to both electricity and renewable energy. In the pursuit of reduced energy consumption and relieving power utility pressure effectively, a novel trigeneration system based on CAES for cooling, heating and electricity generation by electrical energy peak load shifting is proposed in this paper. The cooling power is generated by the direct expansion of compressed air, and the heating power is recovered in the process of compression and storage. Based on the working principle of the typical CAES, the theoretical analysis of the thermodynamic system models are established and the characteristics of the system are analyzed. A novel method used to evaluate energy and economic performance is proposed. A case study is conducted, and the economic-social and technical feasibility of the proposed system are discussed. The results show that the trigeneration system works efficiently at relatively low pressure, and the efficiency is expected to reach about 76.3% when air is compressed and released by 15 bar. The annual monetary cost saving annually is about 53.9%. Moreover, general considerations about the proposed system are also presented.

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

Peak load-impulse characterization of critical pulse loads in structural dynamics

International Nuclear Information System (INIS)

Abrahamson, G.R.; Lindberg, H.E.

1975-01-01

In presenting the characterization scheme, some general features are described first. A detailed analysis is given for the rigid-plastic system of one degree of freedom to illustrate the calculation of critical load curves in terms of peak load and impulse. This is followed by the presentation of critical load curves for uniformly loaded rigid-plastic beams and plates and for dynamic buckling of cylindrical shells under uniform lateral loads. The peak load-impulse characterization of critical pulse loads is compared with the dynamic load factor characterization, and some aspects of the history of the peak load-pulse scheme are presented. (orig./HP) [de

Impact of roof integrated PV orientation on the residential electricity peak demand

International Nuclear Information System (INIS)

Sadineni, Suresh B.; Atallah, Fady; Boehm, Robert F.

2012-01-01

Highlights: ► A study to demonstrate peak load reductions at the substation. ► A new residential energy efficient community named Villa Trieste is being developed. ► The peak demand from the homes has decreased by 38% through energy efficiency. ► Orientation of roof integrated PV has less influence on the summer peak demand. ► Increasing thermostat temperature during peak by 1 °C can significantly reduce peaks. -- Abstract: Peak electricity demand has been an issue in the Desert Southwest region of the US, due to extreme summer temperatures. To address this issue, a consortium was formed between the University of Nevada, Las Vegas, Pulte Homes, and NV Energy. An energy efficient residential community was developed by the team in Las Vegas with approximately 200 homes to study substation-level peak reduction strategies. A summer peak reduction of more than 65%, between 1:00 PM and 7:00 PM, compared to code standard housing developments is the targeted goal of the project. Approximately 50 homes are already built and some are occupied. The energy performances of the homes have been monitored and are presented in this paper. Several peak electric load reduction strategies such as energy efficiency in buildings, roof integrated photovoltaics (PV) and direct load control have been applied. Though all the homes in the developed community are installed with 1.8 kW p PV systems, the orientation of the PV system depends on the building orientation. Focus of this paper is to find the impact of PV orientation on the peak load from a building. In addition, different time-of-use (TOU) energy pricing options are offered by the local electrical utility company. Hence it is important to find an optimal pricing option for each building. A computer model has been developed for one of the homes in the new development using building energy simulation code, ENERGY-10. Calculations on the PV orientations have shown that a south and 220° (i.e. 40° west of due south

Energy conservation prospects through electric load management

Energy Technology Data Exchange (ETDEWEB)

El-Shirbeeny, E H.T.

1984-04-01

In this paper, concepts of electric load management are discussed for effective energy conservation. It is shown that the conservation program must be comprehensive to provide solutions to the problems facing the electric consumer, the electric utility and the society by reducing the rate of growth of energy consumption and power system peak demand requirements. The impact of energy management programs on electric energy conservation is examined, with emphasis on efficiency, storage, cogeneration and controls with computers.

Research of Charging(Discharging Orderly and Optimizing Load Curve for Electric Vehicles Based on Dynamic Electric Price and V2G

Directory of Open Access Journals (Sweden)

Yang Shuai

2016-01-01

Full Text Available Firstly, using the Monte Carlo method and simulation analysis, this paper builds models for the behaviour of electric vehicles, the conventional charging model and the fast charging model. Secondly, this paper studies the impact that the number of electric vehicles which get access to power grid has on the daily load curve. Then, the paper put forwards a dynamic pricing mechanism of electricity, and studies how this dynamic pricing mechanism guides the electric vehicles to charge orderly. Last but not the least, the paper presents a V2G mechanism. Under this mechanism, electric vehicles can charge orderly and take part in the peak shaving. Research finds that massive electric vehicles’ access to the power grid will increase the peak-valley difference of daily load curve. Dynamic pricing mechanism and V2G mechanism can effectively lead the electric vehicles to take part in peak-shaving, and optimize the daily load curve.

Peak load pricing lowers generation costs

International Nuclear Information System (INIS)

Lande, R.H.

1980-01-01

Before a utility implements peak load pricing for different classes of consumers, the costs and the benefits should be compared. The methodology described enables a utility to determine whether peak load pricing should be introduced for specific users. Cost-benefit analyses for domestic consumers and commercial/industrial consumers, showing break-even points are presented. (author)

Further Development of the Nordic Electricity Market - a Common Solution for Investments in Transmission, Congestion Management and Peak Load Capacity

International Nuclear Information System (INIS)

Granstroem, Per-Olof

2005-06-01

The Nordic market fits well into place as a regional market in the over all European development, and it is therefore necessary to change the perspectives from a national one to a common Nordic approach. Despite the fact that the Nordic market is seen as a success, significant further improvements for customers and society can be made through deeper Nordic integration. The ongoing work on the Nordic electricity market within the Nordic Council of Ministers is therefore very welcomed and the Nordel report 'Enhancing Efficient Functioning of the Nordic Electricity Market' constitutes a good basis material for the further development of the market. There is a need to accelerate the pace of the harmonisation process, by making a clear timetable and prioritisation for the further work. Key issues for the next step are: Harmonisation of the legal framework and hence intensified co-operation among the Nordic governments; Implementation of the five known transmission investments, including a cost-benefit analysis; A more precise definition of the TSO responsibilities and core businesses, including operational reserves a prerequisite for further work on, e.g. the peak load issue; Initiation of cost-benefit analysis concerning future transmission investments; Guaranteed cross border capacity for market players; An analysis on settlement of imbalances and how this is affecting the peak load issue

Managing peak loads in energy grids: Comparative economic analysis

International Nuclear Information System (INIS)

Zhuk, A.; Zeigarnik, Yu.; Buzoverov, E.; Sheindlin, A.

2016-01-01

One of the key issues in modern energy technology is managing the imbalance between the generated power and the load, particularly during times of peak demand. The increasing use of renewable energy sources makes this problem even more acute. Various existing technologies, including stationary battery energy storage systems (BESS), can be employed to provide additional power during peak demand times. In the future, integration of on-board batteries of the growing fleet of electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) into the grid can provide power during peak demand hours (vehicle-to-grid, or V2G technology). This work provides cost estimates of managing peak energy demands using traditional technologies, such as maneuverable power plants, conventional hydroelectric, pumped storage plants and peaker generators, as well as BESS and V2G technologies. The derived estimates provide both per kWh and kW year of energy supplied to the grid. The analysis demonstrates that the use of battery storage is economically justified for short peak demand periods of <1 h. For longer durations, the most suitable technology remains the use of maneuverable steam gas power plants, gas turbine,reciprocating gas engine peaker generators, conventional hydroelectric, pumped storage plants. - Highlights: • Cost of managing peak energy demand employing different technologies are estimated. • Traditional technologies, stationary battery storage and V2G are compared. • Battery storage is economically justified for peak demand periods of <1 h. • V2G appears to have better efficiency than stationary battery storage in low voltage power grids.

Valence of wind power, photovoltaic and peak-load power plants as a part of the entire electricity system

International Nuclear Information System (INIS)

Schüppel, A.

2014-01-01

The transition to a higher share of renewable energy sources in the electricity sector leads to a multitude of challenges for the current electricity system. Within this thesis, the development of wind power and photovoltaics generation capacities in Germany is analysed based on the evaluation of technical and economic criteria. In order to derive those criteria, different scenarios with a separated and combined increase of wind and photovoltaics capacity are simulated using the model ATLANTIS. The results are compared to a reference scenario without additional wind and PV capacities. Furthermore, the value and functionality of the energy only market based on economic methods, as well as the value of peak load power plants based on opportunity costs are determined. The results of this thesis show, that the current market system is able to gain an additional annual welfare of four to six billion Euro at the best. This result shows that the task of optimising the power plant dispatch is well fulfilled by the current market design. However, the effects, e.g. fuel costs, which may influence this margin. The value of wind power and photovoltaics within the overall electricity system can be derived from the effort which is necessary to integrate these generation technologies into the existing system, and the changes in total costs of electricity generation. Based on the evaluation of time dependencies (seasonality of energy yield from wind and PV) as well as the development of total generation costs, the conclusion can be drawn that wind power is the more suitable RES generation technology for Germany. However, when it comes to grid integration measures, PV shows better results due to a higher generation potential in Southern Germany, which leads to a higher degree of utilisation. Therefore, there is no need to transport electricity from Northern to Southern Germany as it is the case with wind power. A common expansion of wind power and photovoltaics even shows slight

Electricity Portfolio Management: Optimal Peak / Off-Peak Allocations

OpenAIRE

Huisman, Ronald; Mahieu, Ronald; Schlichter, Felix

2007-01-01

textabstractElectricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to allocate optimal positions in peak and off-peak forward contracts. It is shown that the optimal allocations are based on the difference in risk premiums per unit of day-ahead risk as a measure of relati...

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

Directory of Open Access Journals (Sweden)

Jacopo Torriti

2017-03-01

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

Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States.

Science.gov (United States)

Auffhammer, Maximilian; Baylis, Patrick; Hausman, Catherine H

2017-02-21

It has been suggested that climate change impacts on the electric sector will account for the majority of global economic damages by the end of the current century and beyond [Rose S, et al. (2014) Understanding the Social Cost of Carbon: A Technical Assessment ]. The empirical literature has shown significant increases in climate-driven impacts on overall consumption, yet has not focused on the cost implications of the increased intensity and frequency of extreme events driving peak demand, which is the highest load observed in a period. We use comprehensive, high-frequency data at the level of load balancing authorities to parameterize the relationship between average or peak electricity demand and temperature for a major economy. Using statistical models, we analyze multiyear data from 166 load balancing authorities in the United States. We couple the estimated temperature response functions for total daily consumption and daily peak load with 18 downscaled global climate models (GCMs) to simulate climate change-driven impacts on both outcomes. We show moderate and heterogeneous changes in consumption, with an average increase of 2.8% by end of century. The results of our peak load simulations, however, suggest significant increases in the intensity and frequency of peak events throughout the United States, assuming today's technology and electricity market fundamentals. As the electricity grid is built to endure maximum load, our findings have significant implications for the construction of costly peak generating capacity, suggesting additional peak capacity costs of up to 180 billion dollars by the end of the century under business-as-usual.

A robust flexible-probabilistic programming method for planning municipal energy system with considering peak-electricity price and electric vehicle

International Nuclear Information System (INIS)

Yu, L.; Li, Y.P.; Huang, G.H.; An, C.J.

2017-01-01

Highlights: • A robust flexible probabilistic programming method is developed for planning MES. • Multiple uncertainties with various violations and satisfaction levels are examined. • Solutions of considering peak electricity prices and electric vehicles are analyzed. • RFPP-MES can better improve energy system reliability and abate pollutant emission. - Abstract: Effective electric power systems (EPS) planning with considering electricity price of 24-h time is indispensable in terms of load shifting, pollutant mitigation and energy demand-supply reliability as well as reducing electricity expense of end-users. In this study, a robust flexible probabilistic programming (RFPP) method is developed for planning municipal energy system (MES) with considering peak electricity prices (PEPs) and electric vehicles (EVs), where multiple uncertainties regarded as intervals, probability distributions and flexibilities as well as their combinations can be effectively reflected. The RFPP-MES model is then applied to planning Qingdao’s MES, where electrical load of 24-h time is simulated based on Monte Carlo. Results reveal that: (a) different time intervals lead to changes of energy supply patterns, the energy supply patterns would tend to the transition from self-supporting dominated (i.e. in valley hours) to outsourcing-dominated (i.e. in peak hours); (b) 15.9% of total imported electricity expense would be reduced compared to that without considering PEPs; (c) with considering EVs, the CO_2 emissions of Qingdao’s transportation could be reduced directly and the reduction rate would be 2.5%. Results can help decision makers improve energy supply patterns, reduce energy system costs and abate pollutant emissions as well as adjust end-users’ consumptions.

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.

Puget Sound Area Electric Reliability Plan. Appendix D, Conservation, Load Management and Fuel Switching Analysis : Draft Environmental Impact Statement.

Energy Technology Data Exchange (ETDEWEB)

United States. Bonneville Power Administration.

1991-09-01

Various conservation, load management, and fuel switching programs were considered as ways to reduce or shift system peak load. These programs operate at the end-use level, such as residential water heat. Figure D-1a shows what electricity consumption for water heat looks like on normal and extreme peak days. Load management programs, such as water heat control, are designed to reduce electricity consumption at the time of system peak. On the coldest day in average winter, system load peaks near 8:00 a.m. In a winter with extremely cold weather, electricity consumption increases fr all hours, and the system peak shifts to later in the morning. System load shapes in the Puget Sound area are shown in Figure D-1b for a normal winter peak day (February 2, 1988) and extreme peak day (February 3, 1989). Peak savings from any program are calculated to be the reduction in loads on the entire system at the hour of system peak. Peak savings for all programs are measured at 8:00 a.m. on a normal peak day and 9:00 a.m. on an extreme peak day. On extremely cold day, some water heat load shifts to much later in the morning, with less load available for shedding at the time of system peak. Models of hourly end-use consumption were constructed to simulate the impact of conservation, land management, and fuel switching programs on electricity consumption. Javelin, a time-series simulating package for personal computers, was chosen for the hourly analysis. Both a base case and a program case were simulated. 15 figs., 7 tabs.

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

Science.gov (United States)

Anthony, Abigail Walker

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

Thermal Energy Storage for Building Load Management: Application to Electrically Heated Floor

Directory of Open Access Journals (Sweden)

Hélène Thieblemont

2016-07-01

Full Text Available In cold climates, electrical power demand for space conditioning becomes a critical issue for utility companies during certain periods of the day. Shifting a portion or all of it to off-peak periods can help reduce peak demand and reduce stress on the electrical grid. Sensible thermal energy storage (TES systems, and particularly electrically heated floors (EHF, can store thermal energy in buildings during the off-peak periods and release it during the peak periods while maintaining occupants’ thermal comfort. However, choosing the type of storage system and/or its configuration may be difficult. In this paper, the performance of an EHF for load management is studied. First, a methodology is developed to integrate EHF in TRNSYS program in order to investigate the impact of floor assembly on the EHF performance. Then, the thermal comfort (TC of the night-running EHF is studied. Finally, indicators are defined, allowing the comparison of different EHF. Results show that an EHF is able to shift 84% of building loads to the night while maintaining acceptable TC in cold climate. Moreover, this system is able to provide savings for the customer and supplier if there is a significant difference between off-peak and peak period electricity prices.

Analysis of the same day of the week increases in peak electricity ...

African Journals Online (AJOL)

Modelling of the same day of the week increases in peak electricity demand improves the reliability of a power network if an accurate assessment of the level and frequency of future extreme load forecasts is carried out. Key words: Gibbs sampling, generalized single pareto, generalized pareto distribution, pareto quantile ...

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.

Daily Nigerian peak load forecasting using artificial neural network ...

African Journals Online (AJOL)

A daily peak load forecasting technique that uses artificial neural network with seasonal indices is presented in this paper. A neural network of relatively smaller size than the main prediction network is used to predict the daily peak load for a period of one year over which the actual daily load data are available using one ...

System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads

Science.gov (United States)

Lu, Bin; Yang, Yi; Sharma, Santosh K; Zambare, Prachi; Madane, Mayura A

2014-12-23

A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.

GMDH-Based Semi-Supervised Feature Selection for Electricity Load Classification Forecasting

Directory of Open Access Journals (Sweden)

Lintao Yang

2018-01-01

Full Text Available With the development of smart power grids, communication network technology and sensor technology, there has been an exponential growth in complex electricity load data. Irregular electricity load fluctuations caused by the weather and holiday factors disrupt the daily operation of the power companies. To deal with these challenges, this paper investigates a day-ahead electricity peak load interval forecasting problem. It transforms the conventional continuous forecasting problem into a novel interval forecasting problem, and then further converts the interval forecasting problem into the classification forecasting problem. In addition, an indicator system influencing the electricity load is established from three dimensions, namely the load series, calendar data, and weather data. A semi-supervised feature selection algorithm is proposed to address an electricity load classification forecasting issue based on the group method of data handling (GMDH technology. The proposed algorithm consists of three main stages: (1 training the basic classifier; (2 selectively marking the most suitable samples from the unclassified label data, and adding them to an initial training set; and (3 training the classification models on the final training set and classifying the test samples. An empirical analysis of electricity load dataset from four Chinese cities is conducted. Results show that the proposed model can address the electricity load classification forecasting problem more efficiently and effectively than the FW-Semi FS (forward semi-supervised feature selection and GMDH-U (GMDH-based semi-supervised feature selection for customer classification models.

Empirical Investigations of the Opportunity Limits of Automatic Residential Electric Load Shaping: Preprint

Energy Technology Data Exchange (ETDEWEB)

Cruickshank, Robert F.; Henze, Gregor P.; Balaji, Rajagopalan; Hodge, Bri-Mathias S.; Florita, Anthony R.

2017-04-01

Residential electric load shaping is often modeled as infrequent, utility-initiated, short-duration deferral of peak demand through direct load control. In contrast, modeled herein is the potential for frequent, transactive, intraday, consumer-configurable load shaping for storage-capable thermostatically controlled electric loads (TCLs), including refrigerators, freezers, and hot water heaters. Unique to this study are 28 months of 15-minute-interval observations of usage in 101 homes in the Pacific Northwest United States that specify exact start, duration, and usage patterns of approximately 25 submetered loads per home. The magnitudes of the load shift from voluntarily-participating TCL appliances are aggregated to form hourly upper and lower load-shaping limits for the coordination of electrical generation, transmission, distribution, storage, and demand. Empirical data are statistically analyzed to define metrics that help quantify load-shaping opportunities.

Optimal Planning Method of On-load Capacity Regulating Distribution Transformers in Urban Distribution Networks after Electric Energy Replacement Considering Uncertainties

Directory of Open Access Journals (Sweden)

Yu Su

2018-06-01

Full Text Available Electric energy replacement is the umbrella term for the use of electric energy to replace oil (e.g., electric automobiles, coal (e.g., electric heating, and gas (e.g., electric cooking appliances, which increases the electrical load peak, causing greater valley/peak differences. On-load capacity regulating distribution transformers have been used to deal with loads with great valley/peak differences, so reasonably replacing conventional distribution transformers with on-load capacity regulating distribution transformers can effectively cope with load changes after electric energy replacement and reduce the no-load losses of distribution transformers. Before planning for on-load capacity regulating distribution transformers, the nodal effective load considering uncertainties within the life cycle after electric energy replacement was obtained by a Monte Carlo method. Then, according to the loss relation between on-load capacity regulating distribution transformers and conventional distribution transformers, three characteristic indexes of annual continuous apparent power curve and replacement criteria for on-load capacity regulating distribution transformers were put forward in this paper, and a set of distribution transformer replaceable points was obtained. Next, based on cost benefit analysis, a planning model of on-load capacity regulating distribution transformers which consists of investment profitability index within the life cycle, investment cost recouping index and capacity regulating cost index was put forward. The branch and bound method was used to solve the planning model within replaceable point set to obtain upgrading and reconstruction scheme of distribution transformers under a certain investment. Finally, planning analysis of on-load capacity regulating distribution transformers was carried out for electric energy replacement points in one urban distribution network under three scenes: certain load, uncertain load and nodal

Modelling Load Shifing Using Electric Vehicles in a Smart Grid Environment

Energy Technology Data Exchange (ETDEWEB)

NONE

2010-07-01

Electric vehicles (EVs) represent both a new demand for electricity and a possible storage medium that could supply power to utilities. The 'load shifting' and 'vehicle-to-grid' concepts could help cut electricity demand during peak periods and prove especially helpful in smoothing variations in power generation introduced to the grid by variable renewable resources such as wind and solar power. This paper proposes a method for simulating the potential benefits of using EVs in load shifting and 'vehicle-to-grid' applications for four different regions -- the United States, Western Europe, China and Japan -- that are expected to have large numbers of EVs by 2050.

Electricity use and load management in electricity heated one-family houses from customer and utility perspective; Effekten av effekten - Elanvaendning och laststyrning i elvaermda smaahus ur kund- och foeretagsperspektiv

Energy Technology Data Exchange (ETDEWEB)

Sernhed, Kerstin

2004-11-01

Until recently, the increase in electricity demand and peak power demand has been met by expansion of the electricity production. Today, due to the deregulation of the electricity market, the production capacity is decreasing. Therefore, there is a national interest in finding solutions to peak problems also on the demand side. In the studies described here (Study 1 and 2) ten households in electrically heated houses were examined. In 1999 the utility equipped their customers with a remote metering system (CustCom) that has an in-built load control component. In Study 1, the load pattern of ten households was examined by using energy diaries combined with frequent meter readings (every five minutes) of the load demand for heating, hot water service and domestic electricity use. Household members kept energy diaries over a four-day period in January 2004, noting time, activities and the use of household appliances that run on electricity. The analysis showed that the use of heat-producing household appliances, e.g. sauna, washing machine and dryer, appliances used for cooking, dishwasher and extra electric heaters, contribute to the household's highest peaks. Turning on the sauna and at the same time using the shower equates to a peak load of 7-9 kW. This, in addition to the use of electricity for heating and lighting along alongside electricity use for refrigerators and freezers, results in some households reaching their main fuse level (roughly 13,8 kW for a main fuse of 20 A). This means that the domestic use of electricity makes up a considerable part of the highest peak loads in a household, but the highest peaks occur together with the use of electricity for heating and hot water. In the second study, Study 2, the households participated in a load control experiment, in which the utility was able to turn on and switch off the heating and hot water systems remotely, using the CustCom system. Heating and water heaters were switched off for periods of 1

Alaska Village Electric Load Calculator

Energy Technology Data Exchange (ETDEWEB)

Devine, M.; Baring-Gould, E. I.

2004-10-01

As part of designing a village electric power system, the present and future electric loads must be defined, including both seasonal and daily usage patterns. However, in many cases, detailed electric load information is not readily available. NREL developed the Alaska Village Electric Load Calculator to help estimate the electricity requirements in a village given basic information about the types of facilities located within the community. The purpose of this report is to explain how the load calculator was developed and to provide instructions on its use so that organizations can then use this model to calculate expected electrical energy usage.

Spatial electric load forecasting

CERN Document Server

Willis, H Lee

2002-01-01

Spatial Electric Load Forecasting Consumer Demand for Power and ReliabilityCoincidence and Load BehaviorLoad Curve and End-Use ModelingWeather and Electric LoadWeather Design Criteria and Forecast NormalizationSpatial Load Growth BehaviorSpatial Forecast Accuracy and Error MeasuresTrending MethodsSimulation Method: Basic ConceptsA Detailed Look at the Simulation MethodBasics of Computerized SimulationAnalytical Building Blocks for Spatial SimulationAdvanced Elements of Computerized SimulationHybrid Trending-Simulation MethodsAdvanced

An exploratory analysis of California residential customer response to critical peak pricing of electricity

International Nuclear Information System (INIS)

Herter, Karen; McAuliffe, Patrick; Rosenfeld, Arthur

2007-01-01

This paper summarizes the results from an exploratory analysis of residential customer response to a critical peak pricing (CPP) experiment in California, in which 15 times per year participating customers received high price signals dispatched by a local electricity distribution company. The high prices were about three times the on-peak price for the otherwise applicable time-of-use rate. Using hourly load data collected during the 15-month experiment, we find statistically significant load reduction for participants both with and without automated end-use control technologies. During 5-h critical peak periods, participants without control technology used up to 13% less energy than they did during normal peak periods. Participants equipped with programmable communicating thermostats used 25% and 41% less for 5 and 2h critical events, respectively. Thus, this paper offers convincing evidence that the residential sector can provide substantial contributions to retail demand response, which is considered a potential tool for mitigating market power, stabilizing wholesale market prices, managing system reliability, and maintaining system resource adequacy. (author)

Application of SVR with chaotic GASA algorithm in cyclic electric load forecasting

International Nuclear Information System (INIS)

Zhang, Wen Yu; Hong, Wei-Chiang; Dong, Yucheng; Tsai, Gary; Sung, Jing-Tian; Fan, Guo-feng

2012-01-01

The electric load forecasting is complicated, and it sometimes reveals cyclic changes due to cyclic economic activities or climate seasonal nature, such as hourly peak in a working day, weekly peak in a business week, and monthly peak in a demand planned year. Hybridization of support vector regression (SVR) with chaotic sequence and evolutionary algorithms has successfully been applied to improve forecasting accuracy, and to effectively avoid trapping in a local optimum. However, it has not been widely explored to employ SVR-based model to deal with cyclic electric load forecasting. This paper will firstly investigate the potentiality of a novel hybrid algorithm, namely chaotic genetic algorithm-simulated annealing algorithm (CGASA), with an SVR model to improve load forecasting accurate performance. In which, the proposed CGASA employs internal randomness of chaotic iterations to overcome premature local optimum. Secondly, the seasonal mechanism will then be applied to well adjust the cyclic load tendency. Finally, a numerical example from an existed reference is employed to compare the forecasting performance of the proposed SSVRCGASA model. The forecasting results show that the SSVRCGASA model yields more accurate forecasting results than ARIMA and TF-ε-SVR-SA models. -- Highlights: ► Hybridizing the seasonal adjustment mechanism into an SVR model. ► Employing chaotic sequence to improve the premature convergence of genetic algorithm and simulated annealing algorithm. ► Successfully providing significant accurate monthly load demand forecasting.

A comparison of four methods to evaluate the effect of a utility residential air-conditioner load control program on peak electricity use

Energy Technology Data Exchange (ETDEWEB)

Newsham, Guy R., E-mail: guy.newsham@nrc-cnrc.gc.ca [National Research Council Canada-Institute for Research in Construction, Building M24, 1200 Montreal Road, Ottawa, Ontario, K1A 0R6 (Canada); Birt, Benjamin J. [National Research Council Canada-Institute for Research in Construction, Building M24, 1200 Montreal Road, Ottawa, Ontario, K1A 0R6 (Canada); Rowlands, Ian H. [University of Waterloo, Ontario (Canada)

2011-10-15

We analyzed the peak load reductions due to a residential direct load control program for air-conditioners in southern Ontario in 2008. In this program, participant thermostats were increased by 2 deg. C for four hours on five event days. We used hourly, whole-house data for 195 participant households and 268 non-participant households, and four different methods of analysis ranging from simple spreadsheet-based comparisons of average loads on event days, to complex time-series regression. Average peak load reductions were 0.2-0.9 kWh/h per household, or 10-35%. However, there were large differences between event days and across event hours, and in results for the same event day/hour, with different analysis methods. There was also a wide range of load reductions between individual households, and only a minority of households contributed to any given event. Policy makers should be aware of how the choice of an analysis method may affect decisions regarding which demand-side management programs to support, and how they might be incentivized. We recommend greater use of time-series methods, although it might take time to become comfortable with their complexity. Further investigation of what type of households contribute most to aggregate load reductions would also help policy makers better target programs. - Highlights: > We analyzed peak load reductions due to residential a/c load control. > We used four methods, ranging from simple comparisons to time-series regression. > Average peak load reductions were 0.2-0.9 kW per household, varying by method. > We recommend a move towards time-series regression for future studies. > A minority of participant households contributed to a given load control event.

Electric utility load management: rational use of energy program pilot study

Energy Technology Data Exchange (ETDEWEB)

1977-08-01

In recognition of the role that load management can play in ensuring that the growing demand for electricity is met in a cost- and energy-efficient manner, in mid-1974, the NATO Committee on the Challenges of Modern Society sponsored all three meetings to provide a forum for representatives of U.S. and European utilities to exchange views and experiences on the various aspects of load management. It was the consensus of representatives at the meetings that three overall approaches offer significant opportunities for achieving improved load management: development of marginal-cost rate structures; power pooling and energy storage by utilities; and efforts by consumers. Industrial consumers can assist electric utilities in their efforts to level system loads through three important methods: interruptible power and deferred load control; peak self-generation; and shifts in operating schedules. Residential/commercial consumers also have an important role to play by managing both their electric heating load (through the interruption of direct-resistance heating and the storage of heat) and their air conditioning load. In response to the interest expressed by the participants in the CCMS conferences, the U.S. and several European governments, national electric utility industry organizations, state public utility commissions, and many individual utilities have undertaken R and D projects to investigate and test various aspects of these three approaches to load management. This report describes the projects that were presented by the utility representatives.

The load shift potential of plug-in electric vehicles with different amounts of charging infrastructure

Science.gov (United States)

Gnann, Till; Klingler, Anna-Lena; Kühnbach, Matthias

2018-06-01

Plug-in electric vehicles are the currently favoured option to decarbonize the passenger car sector. However, a decarbonisation is only possible with electricity from renewable energies and plug-in electric vehicles might cause peak loads if they started to charge at the same time. Both these issues could be solved with coordinated load shifting (demand response). Previous studies analyzed this research question by focusing on private vehicles with domestic and work charging infrastructure. This study additionally includes the important early adopter group of commercial fleet vehicles and reflects the impact of domestic, commercial, work and public charging. For this purpose, two models are combined. In a comparison of three scenarios, we find that charging of commercial vehicles does not inflict evening load peaks in the same magnitude as purely domestic charging of private cars does. Also for private cars, charging at work occurs during the day and may reduce the necessity of load shifting while public charging plays a less important role in total charging demand as well as load shifting potential. Nonetheless, demand response reduces the system load by about 2.2 GW or 2.8% when domestic and work charging are considered compared to a scenario with only domestic charging.

Households' hourly electricity consumption and peak demand in Denmark

DEFF Research Database (Denmark)

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

2017-01-01

consumption, we analyse the contribution of appliances and new services, such as individual heat pumps and electric vehicles, to peak consumption and the need for demand response incentives to reduce the peak.Initially, the paper presents a new model that represents the hourly electricity consumption profile...... of households in Denmark. The model considers hourly consumption profiles for different household appliances and their contribution to annual household electricity consumption. When applying the model to an official scenario for annual electricity consumption, assuming non-flexible consumption due...... to a considerable introduction of electric vehicles and individual heat pumps, household consumption is expected to increase considerably, especially peak hour consumption is expected to increase.Next the paper presents results from a new experiment where household customers are given economic and/or environmental...

System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

Science.gov (United States)

Lu, Bin; Harley, Ronald G.; Du, Liang; Yang, Yi; Sharma, Santosh K.; Zambare, Prachi; Madane, Mayura A.

2014-06-17

A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.

Optimisation of load control

International Nuclear Information System (INIS)

Koponen, P.

1998-01-01

Electricity cannot be stored in large quantities. That is why the electricity supply and consumption are always almost equal in large power supply systems. If this balance were disturbed beyond stability, the system or a part of it would collapse until a new stable equilibrium is reached. The balance between supply and consumption is mainly maintained by controlling the power production, but also the electricity consumption or, in other words, the load is controlled. Controlling the load of the power supply system is important, if easily controllable power production capacity is limited. Temporary shortage of capacity causes high peaks in the energy price in the electricity market. Load control either reduces the electricity consumption during peak consumption and peak price or moves electricity consumption to some other time. The project Optimisation of Load Control is a part of the EDISON research program for distribution automation. The following areas were studied: Optimization of space heating and ventilation, when electricity price is time variable, load control model in power purchase optimization, optimization of direct load control sequences, interaction between load control optimization and power purchase optimization, literature on load control, optimization methods and field tests and response models of direct load control and the effects of the electricity market deregulation on load control. An overview of the main results is given in this chapter

Optimisation of load control

Energy Technology Data Exchange (ETDEWEB)

Koponen, P [VTT Energy, Espoo (Finland)

1998-08-01

Electricity cannot be stored in large quantities. That is why the electricity supply and consumption are always almost equal in large power supply systems. If this balance were disturbed beyond stability, the system or a part of it would collapse until a new stable equilibrium is reached. The balance between supply and consumption is mainly maintained by controlling the power production, but also the electricity consumption or, in other words, the load is controlled. Controlling the load of the power supply system is important, if easily controllable power production capacity is limited. Temporary shortage of capacity causes high peaks in the energy price in the electricity market. Load control either reduces the electricity consumption during peak consumption and peak price or moves electricity consumption to some other time. The project Optimisation of Load Control is a part of the EDISON research program for distribution automation. The following areas were studied: Optimization of space heating and ventilation, when electricity price is time variable, load control model in power purchase optimization, optimization of direct load control sequences, interaction between load control optimization and power purchase optimization, literature on load control, optimization methods and field tests and response models of direct load control and the effects of the electricity market deregulation on load control. An overview of the main results is given in this chapter

Reducing Electricity Demand Peaks by Scheduling Home Appliances Usage

DEFF Research Database (Denmark)

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

2011-01-01

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

Modeling electric load and water consumption impacts from an integrated thermal energy and rainwater storage system for residential buildings in Texas

International Nuclear Information System (INIS)

Upshaw, Charles R.; Rhodes, Joshua D.; Webber, Michael E.

2017-01-01

Highlights: • Hydronic integrated rainwater thermal storage (ITHERST) system concept presented. • ITHERST system modeled to assess peak electric load shifting and water savings. • Case study shows 75% peak load reduction and 9% increase in energy consumption. • Potable rainwater collection could provide ∼50–90% of water used for case study. - Abstract: The United States’ built environment is a significant direct and indirect consumer of energy and water. In Texas, and other parts of the Southern and Western US, air conditioning loads, particularly from residential buildings, contribute significantly to the peak electricity load on the grid, straining transmission. In parallel, water resources in these regions are strained by growing populations and shrinking supplies. One potential method to address both of these issues is to develop integrated thermal energy and auxiliary water (e.g. rainwater, greywater, etc.) storage and management systems that reduce peak load and freshwater consumption. This analysis focuses on a proposed integrated thermal energy and rainwater storage (ITHERST) system that is incorporated into a residential air-source chiller/heat pump with hydronic distribution. This paper describes a step-wise hourly thermodynamic model of the thermal storage system to assess on-peak performance, and a daily volume-balance model of auxiliary water collection and consumption to assess water savings potential. While the model is generalized, this analysis uses a case study of a single family home in Austin, Texas to illustrate its capabilities. The results indicate this ITHERST system could reduce on-peak air conditioning electric power demand by over 75%, with increased overall electric energy consumption of approximately 7–9%, when optimally sized. Additionally, the modeled rainwater collection reduced municipal water consumption by approximately 53–89%, depending on the system size.

Electric vehicles as flexible loads – A simulation approach using empirical mobility data

International Nuclear Information System (INIS)

Metz, Michael; Doetsch, Christian

2012-01-01

Due to the rapid increase of wind and photovoltaic generation, flexible storage applications become more important. Electric vehicles are supposed as one option to fill the gap between a fixed energy demand and a stochastic feed in from fluctuating energy sources. But the charging loads will also affect the grid load, since the transport sector contributes considerably to the total energy consumption today. This study examines the conflicting relationship between user mobility and grid support and introduces an approach to simulate large vehicle fleets on the basis of individual driving profiles. 9744 driving profiles from the German mobility panel were used within this examination. 958 were classified as potential early adopters for electric vehicles. Those vehicles could provide grid support in 81% of the time, when charging spots are available at home and at work. We simulated the charging loads under the restrictions of the individual mobility for the scenario 2030. Uncoordinated charging will increase the load fluctuations, whereas coordinated charging loads allow load shifting without limiting the mobility. The additional electricity demand is moderate over the next two decades. -- Highlights: ► We processed and analyzed 9744 driving profiles from a German mobility study. ► We simulated 3 concepts for a charging control, resulting in different load profiles. ► Additional energy demand of electric vehicles is moderate over the next two decades. ► Uncoordinated charging will increase the total peak load, coordinated charging can balance fluctuations.

Residential implementation of critical-peak pricing of electricity

International Nuclear Information System (INIS)

Herter, Karen

2007-01-01

This paper investigates how critical-peak pricing (CPP) affects households with different usage and income levels, with the goal of informing policy makers who are considering the implementation of CPP tariffs in the residential sector. Using a subset of data from the California Statewide Pricing Pilot of 2003-04, average load change during summer events, annual percent bill change, and post-experiment satisfaction ratings are calculated across six customer segments, categorized by historical usage and income levels. Findings show that high-use customers respond significantly more in kW reduction than do low-use customers, while low-use customers save significantly more in percentage reduction of annual electricity bills than do high-use customers-results that challenge the strategy of targeting only high-use customers for CPP tariffs. Across income levels, average load and bill changes were statistically indistinguishable, as were satisfaction rates-results that are compatible with a strategy of full-scale implementation of CPP rates in the residential sector. Finally, the high-use customers earning less than $50,000 annually were the most likely of the groups to see bill increases-about 5% saw bill increases of 10% or more-suggesting that any residential CPP implementation might consider targeting this customer group for increased energy efficiency efforts

Investigation of load leveling in Hokuriku Electric Power Co., Inc.; Hokuriku denryoku no fuka heijunka eno torikumi

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-08-01

Hokuriku Electric Power Co., Inc. aims at an around 2% improvement of the load factor up to 2005, by which the quick and proper service and the proposal of load leveling menu are planned. This paper describes an outline of the investigation of load leveling. Various programs have been proposed so that the customers can further shift the load by their consideration. Proposed systems include the time-of-day electricity rate system, the load regulation contract system for industries, the seasonal time-of-day rate system, the electric power system for snowmelt in which the load is dumped at the peak, and the secondary electric power system for snowmelt. Accompanying with the revision of electric utility law, the enlargement of its available time, the price reduction, and the discount rate system for the ice regenerative air conditioners have been provided. For the business activities, a demonstration model house was exhibited to indicate a proper house with local characteristics in Hokuriku district. Furthermore, the spreading activities of regenerative systems and the consulting activities have been positively promoted. 4 figs., 1 tab.

Reducing electricity demand peaks by scheduling home appliances usage

Energy Technology Data Exchange (ETDEWEB)

Rossello-Busquet, A.; Kardaras, G.; Baek Iversen, V.; Soler, J.; Dittmann, L.

2011-05-15

Nowadays there is a tendency to consume electricity during the same period of the day leading to demand peaks. Regular energy consumption habits lead to demand peaks at specific temporal intervals, because users consume power at the same time. In order to avoid demand peaks, users' appliances should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions. On the contrary, the low priority devices have to pause their operation, when the algorithm dictates it, and resume it in the future. This can become beneficial for both energy companies and users. The electricity suppliers companies will be capable of regulating power generation during demand peaks periods. Moreover, users can be granted lower electricity bill rates for accepting delaying the operation of some of their appliances. In order to analyze this scenario, teletraffic engineering theory, which is used in evaluating the performance of telecommunication networks, is used. A reversible fair scheduling (RFS) algorithm, which was originally developed for telecommunication networks, is applied. The purpose is to analyze how a power consumption limit and priorities for home appliances will affect the demand peak and the users' everyday life. Verification of the effectiveness of the RFS algorithm is done by means of simulation and by using real data for power consumption and operation hours. The defined maximum power limit of 750 and 1000 Watt was not exceeded during

Sound-Intensity Feedback During Running Reduces Loading Rates and Impact Peak.

Science.gov (United States)

Tate, Jeremiah J; Milner, Clare E

2017-08-01

Study Design Controlled laboratory study, within-session design. Background Gait retraining has been proposed as an effective intervention to reduce impact loading in runners at risk of stress fractures. Interventions that can be easily implemented in the clinic are needed. Objective To assess the immediate effects of sound-intensity feedback related to impact during running on vertical impact peak, peak vertical instantaneous loading rate, and vertical average loading rate. Methods Fourteen healthy, college-aged runners who ran at least 9.7 km/wk participated (4 male, 10 female; mean ± SD age, 23.7 ± 2.0 years; height, 1.67 ± 0.08 m; mass, 60.9 ± 8.7 kg). A decibel meter provided real-time sound-intensity feedback of treadmill running via an iPad application. Participants were asked to reduce the sound intensity of running while receiving continuous feedback for 15 minutes, while running at their self-selected preferred speed. Baseline and follow-up ground reaction force data were collected during overground running at participants' self-selected preferred running speed. Results Dependent t tests indicated a statistically significant reduction in vertical impact peak (1.56 BW to 1.13 BW, P≤.001), vertical instantaneous loading rate (95.48 BW/s to 62.79 BW/s, P = .001), and vertical average loading rate (69.09 BW/s to 43.91 BW/s, P≤.001) after gait retraining, compared to baseline. Conclusion The results of the current study support the use of sound-intensity feedback during treadmill running to immediately reduce loading rate and impact force. The transfer of within-session reductions in impact peak and loading rates to overground running was demonstrated. Decreases in loading were of comparable magnitude to those observed in other gait retraining methods. J Orthop Sports Phys Ther 2017;47(8):565-569. Epub 6 Jul 2017. doi:10.2519/jospt.2017.7275.

Mean and peak wind load reduction on heliostats

Energy Technology Data Exchange (ETDEWEB)

Peterka, J.A.; Tan, L.; Bienkiewcz, B.; Cermak, J.E.

1987-09-01

This report presents the results of wind-tunnel tests supported through the Solar Energy Research Institute (SERI) by the Office of Solar Thermal Technology of the US Department of Energy as part of the SERI research effort on innovative concentrators. As gravity loads on drive mechanisms are reduced through stretched-membrane technology, the wind-load contribution of the required drive capacity increases in percentage. Reduction of wind loads can provide economy in support structure and heliostat drive. Wind-tunnel tests have been directed at finding methods to reduce wind loads on heliostats. The tests investigated both mean and peak forces, and moments. A significant increase in ability to predict heliostat wind loads and their reduction within a heliostat field was achieved. In addition, a preliminary review of wind loads on parabolic dish collectors was conducted, resulting in a recommended research program for these type collectors. 42 refs., 38 figs., 1 tab.

Space station electrical power distribution analysis using a load flow approach

Science.gov (United States)

Emanuel, Ervin M.

1987-01-01

The space station's electrical power system will evolve and grow in a manner much similar to the present terrestrial electrical power system utilities. The initial baseline reference configuration will contain more than 50 nodes or busses, inverters, transformers, overcurrent protection devices, distribution lines, solar arrays, and/or solar dynamic power generating sources. The system is designed to manage and distribute 75 KW of power single phase or three phase at 20 KHz, and grow to a level of 300 KW steady state, and must be capable of operating at a peak of 450 KW for 5 to 10 min. In order to plan far into the future and keep pace with load growth, a load flow power system analysis approach must be developed and utilized. This method is a well known energy assessment and management tool that is widely used throughout the Electrical Power Utility Industry. The results of a comprehensive evaluation and assessment of an Electrical Distribution System Analysis Program (EDSA) is discussed. Its potential use as an analysis and design tool for the 20 KHz space station electrical power system is addressed.

Building Automation and Control Systems and Electrical Distribution Grids: A Study on the Effects of Loads Control Logics on Power Losses and Peaks

Directory of Open Access Journals (Sweden)

Salvatore Favuzza

2018-03-01

Full Text Available Growing home comfort is causing increasing energy consumption in residential buildings and a consequent stress in urban medium and low voltage distribution networks. Therefore, distribution system operators are obliged to manage problems related to the reliability of the electricity system and, above all, they must consider investments for enhancing the electrical infrastructure. The purpose of this paper is to assess how the reduction of building electricity consumption and the modification of the building load profile, due to load automation, combined with suitable load control programs, can improve network reliability and distribution efficiency. This paper proposes an extensive study on this issue, considering various operating scenarios with four load control programs with different purposes, the presence/absence of local generation connected to the buildings and different external thermal conditions. The study also highlights how different climatic conditions can influence the effects of the load control logics.

Daily Peak Load Forecasting of Next Day using Weather Distribution and Comparison Value of Each Nearby Date Data

Science.gov (United States)

Ito, Shigenobu; Yukita, Kazuto; Goto, Yasuyuki; Ichiyanagi, Katsuhiro; Nakano, Hiroyuki

By the development of industry, in recent years; dependence to electric energy is growing year by year. Therefore, reliable electric power supply is in need. However, to stock a huge amount of electric energy is very difficult. Also, there is a necessity to keep balance between the demand and supply, which changes hour after hour. Consequently, to supply the high quality and highly dependable electric power supply, economically, and with high efficiency, there is a need to forecast the movement of the electric power demand carefully in advance. And using that forecast as the source, supply and demand management plan should be made. Thus load forecasting is said to be an important job among demand investment of electric power companies. So far, forecasting method using Fuzzy logic, Neural Net Work, Regression model has been suggested for the development of forecasting accuracy. Those forecasting accuracy is in a high level. But to invest electric power in higher accuracy more economically, a new forecasting method with higher accuracy is needed. In this paper, to develop the forecasting accuracy of the former methods, the daily peak load forecasting method using the weather distribution of highest and lowest temperatures, and comparison value of each nearby date data is suggested.

Load leveling efforts of The Hokkaido Electric Power Co. Inc.; Hokkaido Denryoku no fuka heijunka eno torikumi ni tsuite

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-04-01

The Hokkaido Electric Power Co., Inc., aiming to enhance power generation efficiency through power load levelling, strives to expand and substantiate its electricity billing menu and to popularize and encourage the use of levelling-oriented apparatuses and systems most of which are designed for utilizing midnight power. The billing menu has in it a snow-melting power which is cut off for load levelling during the peak demand time zone. For domestic use, a time zone-specified lighting system named Dream Eight is created, which is one of the billing systems dependent upon time zone. Introduced therein for industrial use is a demand/supply adjustment contract system. Furthermore, in compliance with the amended Electricity Business Law that came into force in 1995, efforts are under way for revising the period wherein power is to be supplied for melting snow, expanding the scope of application of the power supply system dependent upon time zone, and newly introducing a heat accumulation assisted peak adjustment contract system and an operation adjustment contract system. As for business efforts in relation to load levelling, the company proposes household electrical systems centering about 200V high-efficiency apparatuses, electric water warmer contributing to the enhancement of year-round load levelling, popularization and reinforcement of electric snow melting systems, and power utilizing technologies capable of meeting local demands raised for example by agriculture and fishery.

Government procurement of peak capacity in the New Zealand electricity market

International Nuclear Information System (INIS)

Poletti, Steve

2009-01-01

This paper analyzes the impact of government procurement of reserve electricity generation capacity on the long-run equilibrium in the electricity market. The approach here is to model the electricity market in a context where the supply companies have market power. The model is then used to analyze the impact of government direct supply of peak capacity on the market. We find that the firms build less peak-generation capacity when the government procures peak generating capacity. The long-run equilibrium with N firms and government capacity of K G results in an increase of total peak generation capacity of K G /(N+1) compared to the long-run equilibrium with no government capacity. Supply disruptions of baseline capacity during the peak time period are also considered. It is found that peak prices do not go up any further with (anticipated) supply disruptions. Instead the entire cost of the extra peakers is borne by customers on traditional meters and off-peak customers who face real-time pricing. (author)

Puget Sound area electric reliability plan

Energy Technology Data Exchange (ETDEWEB)

1991-09-01

Various conservation, load management, and fuel switching programs were considered as ways to reduce or shift system peak load. These programs operate at the end-use level, such as residential water heat. Figure D-1a shows what electricity consumption for water heat looks like on normal and extreme peak days. Load management programs, such as water heat control, are designed to reduce electricity consumption at the time of system peak. On the coldest day in average winter, system load peaks near 8:00 a.m. In a winter with extremely cold weather, electricity consumption increases fr all hours, and the system peak shifts to later in the morning. System load shapes in the Puget Sound area are shown in Figure D-1b for a normal winter peak day (February 2, 1988) and extreme peak day (February 3, 1989). Peak savings from any program are calculated to be the reduction in loads on the entire system at the hour of system peak. Peak savings for all programs are measured at 8:00 a.m. on a normal peak day and 9:00 a.m. on an extreme peak day. On extremely cold day, some water heat load shifts to much later in the morning, with less load available for shedding at the time of system peak. Models of hourly end-use consumption were constructed to simulate the impact of conservation, land management, and fuel switching programs on electricity consumption. Javelin, a time-series simulating package for personal computers, was chosen for the hourly analysis. Both a base case and a program case were simulated. 15 figs., 7 tabs.

A methodology for Electric Power Load Forecasting

Directory of Open Access Journals (Sweden)

Eisa Almeshaiei

2011-06-01

Full Text Available Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. Therefore, this paper presents a pragmatic methodology that can be used as a guide to construct Electric Power Load Forecasting models. This methodology is mainly based on decomposition and segmentation of the load time series. Several statistical analyses are involved to study the load features and forecasting precision such as moving average and probability plots of load noise. Real daily load data from Kuwaiti electric network are used as a case study. Some results are reported to guide forecasting future needs of this network.

Gas inventory charges and peak-load reliability

International Nuclear Information System (INIS)

Lyon, T.P.; Hackett, S.C.

1990-01-01

The natural gas industry has historically been organized through a vertical sequence of long-term contracts, the first between wellhead producer and pipeline, and the second between pipeline and local distribution company (LDC). These long-term contracts contained provisions, variously called take-or-pay (TOP) clauses or minimum bills, that required buyers to pay for a minimum level of supply in all later time periods, regardless of the buyers' actual demand requirements. As a result, the pipeline's purchase obligation was typically offset by the distributor's purchase obligation, so that the pipeline essentially passed the minimum purchase requirement directly from producer to distributor. The authors focus on the role GICs (Gas Inventory Charges) can play in the provision of peak-load reliability, and the effects of GICs and their treatment by regulators on pipeline system design. In particular, they compare the various options available to local distribution companies (LDCs) for providing peak-load reliability, emphasizing the alternative downstream storage. They find that the ratemaking decisions of state regulators may distort LDC choices between different gas supply options, inducing what may be an inefficient demand for new storage facilities. GICs, when competitively prices, offer state regulators a means of circumventing these distortions

Future energy loads for a large-scale adoption of electric vehicles in the city of Los Angeles: Impacts on greenhouse gas (GHG) emissions

International Nuclear Information System (INIS)

Kim, Jae D.; Rahimi, Mansour

2014-01-01

Using plug-in electric vehicles (PEVs) has become an important component of greenhouse gas (GHG) emissions reduction strategy in the transportation sector. Assessing the net effect of PEVs on GHG emissions, however, is dependent on factors such as type and scale of electricity generation sources, adoption rate, and charging behavior. This study creates a comprehensive model that estimates the energy load and GHG emissions impacts for the years 2020 and 2030 for the city of Los Angeles. For 2020, model simulations show that the PEV charging loads will be modest with negligible effects on the overall system load profile. Contrary to previous study results, the average marginal carbon intensity is higher if PEV charging occurs during off-peak hours. These results suggest that current economic incentives to encourage off-peak charging result in greater GHG emissions. Model simulations for 2030 show that PEV charging loads increase significantly resulting in potential generation shortages. There are also significant grid operation challenges as the region's energy grid is required to ramp up and down rapidly to meet PEV loads. For 2030, the average marginal carbon intensity for off-peak charging becomes lower than peak charging mainly due to the removal of coal from the power generation portfolio. - Highlights: • Future energy load from PEV charging in the city of Los Angeles is modeled. • Changes in the marginal carbon intensity of the region's electric grid are modeled. • In the short run, offpeak charging results in higher marginal carbon intensity. • There is a mismatch between emissions and economic incentives for charging

Security of supply, energy spillage control and peaking options within a 100% renewable electricity system for New Zealand

International Nuclear Information System (INIS)

Mason, I.G.; Page, S.C.; Williamson, A.G.

2013-01-01

In this paper, issues of security of supply, energy spillage control, and peaking options, within a fully renewable electricity system, are addressed. We show that a generation mix comprising 49% hydro, 23% wind, 13% geothermal, 14% pumped hydro energy storage peaking plant, and 1% biomass-fuelled generation on an installed capacity basis, was capable of ensuring security of supply over an historic 6-year period, which included the driest hydrological year on record in New Zealand since 1931. Hydro spillage was minimised, or eliminated, by curtailing a proportion of geothermal generation. Wind spillage was substantially reduced by utilising surplus generation for peaking purposes, resulting in up to 99.8% utilisation of wind energy. Peaking requirements were satisfied using 1550 MW of pumped hydro energy storage generation, with a capacity factor of 0.76% and an upper reservoir storage equivalent to 8% of existing hydro storage capacity. It is proposed that alternative peaking options, including biomass-fuelled gas turbines and demand-side measures, should be considered. As a transitional policy, the use of fossil-gas–fuelled gas turbines for peaking would result in a 99.8% renewable system on an energy basis. Further research into whether a market-based system is capable of delivering such a renewable electricity system is suggested. - Highlights: • A 100% renewable electricity system was modelled over a 6-year period. • Security of supply was demonstrated, including for the driest year since 1931. • Stored energy spillage was controlled by using flexible base-load generation. • Wind energy utilisation of 99.8% was obtained. • Transitional use of fossil gas for peaking resulted in a 99.8% renewable system

Load shift potential of electric vehicles in Europe

Science.gov (United States)

Babrowski, Sonja; Heinrichs, Heidi; Jochem, Patrick; Fichtner, Wolf

2014-06-01

Many governments highly encourage electric mobility today, aiming at a high market penetration. This development would bring forth an impact on the energy system, which strongly depends on the driving and charging behavior of the users. While an uncontrolled immediate charging might strain the local grid and/or higher peak loads, there are benefits to be gained by a controlled charging. We examine six European mobility studies in order to display the effects of controlled and uncontrolled unidirectional charging. Taking into account country-specific driving patterns, we generate for each country a charging load curve corresponding to uncontrolled charging and consider the corresponding parking time at charging facilities in order to identify load shift potentials. The main results are that besides the charging power of the vehicles, the possibility to charge at the work place has a significant influence on the uncontrolled charging curve. Neither national nor regional differences are as significant. When charging is only possible at home, the vehicle availability at charging facilities during the day for all countries is at least 24%. With the additional possibility to charge at work, at least 45% are constantly available. Accordingly, we identified a big potential for load shifting through controlled charging.

Intelligent electrical outlet for collective load control

Science.gov (United States)

Lentine, Anthony L.; Ford, Justin R.; Spires, Shannon V.; Goldsmith, Steven Y.

2015-10-27

Various technologies described herein pertain to an electrical outlet that autonomously manages loads in a microgrid. The electrical outlet can provide autonomous load control in response to variations in electrical power generation supply in the microgrid. The electrical outlet includes a receptacle, a sensor operably coupled to the receptacle, and an actuator configured to selectively actuate the receptacle. The sensor measures electrical parameters at the receptacle. Further, a processor autonomously controls the actuator based at least in part on the electrical parameters measured at the receptacle, electrical parameters from one or more disparate electrical outlets in the microgrid, and a supply of generated electric power in the microgrid at a given time.

Impact of Electric Vehicle Charging Station Load on Distribution Network

Directory of Open Access Journals (Sweden)

Sanchari Deb

2018-01-01

Full Text Available Recent concerns about environmental pollution and escalating energy consumption accompanied by the advancements in battery technology have initiated the electrification of the transportation sector. With the universal resurgence of Electric Vehicles (EVs the adverse impact of the EV charging loads on the operating parameters of the power system has been noticed. The detrimental impact of EV charging station loads on the electricity distribution network cannot be neglected. The high charging loads of the fast charging stations results in increased peak load demand, reduced reserve margins, voltage instability, and reliability problems. Further, the penalty paid by the utility for the degrading performance of the power system cannot be neglected. This work aims to investigate the impact of the EV charging station loads on the voltage stability, power losses, reliability indices, as well as economic losses of the distribution network. The entire analysis is performed on the IEEE 33 bus test system representing a standard radial distribution network for six different cases of EV charging station placement. It is observed that the system can withstand placement of fast charging stations at the strong buses up to a certain level, but the placement of fast charging stations at the weak buses of the system hampers the smooth operation of the power system. Further, a strategy for the placement of the EV charging stations on the distribution network is proposed based on a novel Voltage stability, Reliability, and Power loss (VRP index. The results obtained indicate the efficacy of the VRP index.

Load profiles analysis for electricity market

Directory of Open Access Journals (Sweden)

Radu Porumb

2014-04-01

Full Text Available In the wake of electric power system transition towards smart grids, and the adoption of the electric market schemes, electric utilities are facing the need of a better load profiles understanding for their customers. In this work, some key objectives were addresses, such as definition of the mathematical model for calculating the hourly energy specific, identification of the three target groups for users who have developed consumer profiles, definition of the two types of significant load and assessment of the impact of using consumer profiles on users.

Daily Air Temperature and Electricity Load in Spain.

Science.gov (United States)

Valor, Enric; Meneu, Vicente; Caselles, Vicente

2001-08-01

Weather has a significant impact on different sectors of the economy. One of the most sensitive is the electricity market, because power demand is linked to several weather variables, mainly the air temperature. This work analyzes the relationship between electricity load and daily air temperature in Spain, using a population-weighted temperature index. The electricity demand shows a significant trend due to socioeconomic factors, in addition to daily and monthly seasonal effects that have been taken into account to isolate the weather influence on electricity load. The results indicate that the relationship is nonlinear, showing a `comfort interval' of ±3°C around 18°C and two saturation points beyond which the electricity load no longer increases. The analysis has also revealed that the sensitivity of electricity load to daily air temperature has increased along time, in a higher degree for summer than for winter, although the sensitivity in the cold season is always more significant than in the warm season. Two different temperature-derived variables that allow a better characterization of the observed relationship have been used: the heating and cooling degree-days. The regression of electricity data on them defines the heating and cooling demand functions, which show correlation coefficients of 0.79 and 0.87, and predicts electricity load with standard errors of estimate of ±4% and ±2%, respectively. The maximum elasticity of electricity demand is observed at 7 cooling degree-days and 9 heating degree-days, and the saturation points are reached at 11 cooling degree-days and 13 heating degree-days, respectively. These results are helpful in modeling electricity load behavior for predictive purposes.

Load Forecasting in Electric Utility Integrated Resource Planning

Energy Technology Data Exchange (ETDEWEB)

Carvallo, Juan Pablo [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Larsen, Peter H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sanstad, Alan H [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goldman, Charles A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2017-07-19

Integrated resource planning (IRP) is a process used by many vertically-integrated U.S. electric utilities to determine least-cost/risk supply and demand-side resources that meet government policy objectives and future obligations to customers and, in many cases, shareholders. Forecasts of energy and peak demand are a critical component of the IRP process. There have been few, if any, quantitative studies of IRP long-run (planning horizons of two decades) load forecast performance and its relationship to resource planning and actual procurement decisions. In this paper, we evaluate load forecasting methods, assumptions, and outcomes for 12 Western U.S. utilities by examining and comparing plans filed in the early 2000s against recent plans, up to year 2014. We find a convergence in the methods and data sources used. We also find that forecasts in more recent IRPs generally took account of new information, but that there continued to be a systematic over-estimation of load growth rates during the period studied. We compare planned and procured resource expansion against customer load and year-to-year load growth rates, but do not find a direct relationship. Load sensitivities performed in resource plans do not appear to be related to later procurement strategies even in the presence of large forecast errors. These findings suggest that resource procurement decisions may be driven by other factors than customer load growth. Our results have important implications for the integrated resource planning process, namely that load forecast accuracy may not be as important for resource procurement as is generally believed, that load forecast sensitivities could be used to improve the procurement process, and that management of load uncertainty should be prioritized over more complex forecasting techniques.

Remote control and load management of electric power distribution networks; Fjaerroevervakning och belastningsstyrning av eldistributionsnaet

Energy Technology Data Exchange (ETDEWEB)

Jonsson, Mats; Larsson, Mikael

1993-02-01

Remote control and load management increase the electricity distributors possibilities to even out the consumption of electricity for optimal usage of electricity subscription and supply system. Controlling can be done either through technology or through encouragement of off-peak consumption. There are a number of similar systems for controlling consumption, where the manufacturers have chosen different ways to solve the main problem, namely the communication. We have concentrated in examining systems which communicate through the supply system, different types of telephone connections and wireless communication links. In the future demands for better electricity consumption control will be put forward. This will bring along a greater need at distribution level for continuous monitoring of purchased and used electricity flow. The distributors will also need better possibilities to directly affect power consumption. Those manufacturers who do not use load management today should acquire experience through provincial installations in suitable areas with equipment ready for tomorrows needs and requirements. Today there are some different systems on the market that offer flexibility and ready-to-use possibilities. (3 refs., 17 figs.)

Experimenting with Electrical Load Sensing on a Backhoe Loader

DEFF Research Database (Denmark)

Andersen, Torben Ole; Hansen, Michael Rygaard; Pedersen, Henrik Clemmensen

2005-01-01

Where traditional load sensing is made using hydro-mechanical regulators and load pressure is fed back hydraulically, electrical load sensing employs the usage of electronic sensors and electrically actuated components. This brings forth new possibilities, but also imposes problems concerning...... dynamic performance and stability. In this paper the possibilities for implementing electrical load sensing (ELS) on a backhoe loader is investigated. Major components in the system are modelled and verified, and a linear model of the pump is presented, which is used for designing the pump controller....... By comparing results from linear analyses performed on both the conventional hydraulic load sensing system (HLS) and the modified electrical load sensing system, it is concluded that system performance closely matching the conventional system is obtainable....

Market Designs : A Survey and Analysis of Methods to Ensure Peak Capacity

OpenAIRE

Gullberg, Erik

2008-01-01

The production and consumption of electricity must be in balance in order to maintain the frequency in an electrical grid. During peak loads this may be troublesome to achieve due to lack of adequate production capabilities. Competitive electricity markets with price caps have a problem - insufficient revenues for peak production units which lead to mothballing or decommissioning of power plants. Inadequate production capability is solved through design of the electricity markets which render...

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

NARCIS (Netherlands)

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

2015-01-01

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

Commodity hydrogen from off-peak electricity

Energy Technology Data Exchange (ETDEWEB)

Darrow, K.; Biederman, N.; Konopka, A.

1977-01-01

This paper considers the use of off-peak electrical power as an energy source for the electrolytic production of hydrogen. The present industrial uses for hydrogen are examined to determine if hydrogen produced in this fashion would be competitive with the industry's onsite production or existing hydrogen prices. The paper presents a technical and economic feasibility analysis of the various components required and of the operation of the system as a whole including production, transmission, storage, and markets.

Assessment of end-use electricity consumption and peak demand by Townsville's housing stock

International Nuclear Information System (INIS)

Ren, Zhengen; Paevere, Phillip; Grozev, George; Egan, Stephen; Anticev, Julia

2013-01-01

We have developed a comprehensive model to estimate annual end-use electricity consumption and peak demand of housing stock, considering occupants' use of air conditioning systems and major appliances. The model was applied to analyse private dwellings in Townsville, Australia's largest tropical city. For the financial year (FY) 2010–11 the predicted results agreed with the actual electricity consumption with an error less than 10% for cooling thermostat settings at the standard setting temperature of 26.5 °C and at 1.0 °C higher than the standard setting. The greatest difference in monthly electricity consumption in the summer season between the model and the actual data decreased from 21% to 2% when the thermostat setting was changed from 26.5 °C to 27.5 °C. Our findings also showed that installation of solar panels in Townville houses could reduce electricity demand from the grid and would have a minor impact on the yearly peak demand. A key new feature of the model is that it can be used to predict probability distribution of energy demand considering (a) that appliances may be used randomly and (b) the way people use thermostats. The peak demand for the FY estimated from the probability distribution tracked the actual peak demand at 97% confidence level. - Highlights: • We developed a model to estimate housing stock energy consumption and peak demand. • Appliances used randomly and thermostat settings for space cooling were considered. • On-site installation of solar panels was also considered. • Its' results agree well with the actual electricity consumption and peak demand. • It shows the model could provide the probability distribution of electricity demand

Online forecasting of electrical load for distributed management of plug-in electric vehicles

OpenAIRE

Basu , Kaustav; Ovalle , Andres; Guo , Baoling; Hably , Ahmad; Bacha , Seddik; Hajar , Khaled

2016-01-01

International audience; The paper aims at making online forecast of electrical load at the MV-LV transformer level. Optimal management of the Plug-in Electric Vehicles (PEV) charging requires the forecast of the electrical load for future hours. The forecasting module needs to be online (i.e update and make forecast for the future hours, every hour). The inputs to the predictor are historical electrical and weather data. Various data driven machine learning algorithms are compared to derive t...

Predicting the Response of Electricity Load to Climate Change

Energy Technology Data Exchange (ETDEWEB)

Sullivan, Patrick [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Colman, Jesse [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Kalendra, Eric [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2015-07-28

Our purpose is to develop a methodology to quantify the impact of climate change on electric loads in the United States. We perform simple linear regression, assisted by geospatial smoothing, on paired temperature and load time-series to estimate the heating- and coolinginduced sensitivity to temperature across 300 transmission zones and 16 seasonal and diurnal time periods. The estimated load sensitivities can be coupled with climate scenarios to quantify the potential impact of climate change on load, with a primary application being long-term electricity scenarios. The method allows regional and seasonal differences in climate and load response to be reflected in the electricity scenarios. While the immediate product of this analysis was designed to mesh with the spatial and temporal resolution of a specific electricity model to enable climate change scenarios and analysis with that model, we also propose that the process could be applied for other models and purposes.

Electricity load modelling using computational intelligence

NARCIS (Netherlands)

Ter Borg, R.W.

2005-01-01

As a consequence of the liberalisation of the electricity markets in Europe, market players have to continuously adapt their future supply to match their customers' demands. This poses the challenge of obtaining a predictive model that accurately describes electricity loads, current in this thesis.

Electric peak power forecasting by year 2025

International Nuclear Information System (INIS)

Alsayegh, O.A.; Al-Matar, O.A.; Fairouz, F.A.; Al-Mulla Ali, A.

2005-01-01

Peak power demand in Kuwait up to the year 2025 was predicted using an artificial neural network (ANN) model. The aim of the study was to investigate the effect of air conditioning (A/C) units on long-term power demand. Five socio-economic factors were selected as inputs for the simulation: (1) gross national product, (2) population, (3) number of buildings, (4) imports of A/C units, and (5) index of industrial production. The study used socio-economic data from 1978 to 2000. Historical data of the first 10 years of the studied time period were used to train the ANN. The electrical network was then simulated to forecast peak power for the following 11 years. The calculated error was then used for years in which power consumption data were not available. The study demonstrated that average peak power rates increased by 4100 MW every 5 years. Various scenarios related to changes in population, the number of buildings, and the quantity of A/C units were then modelled to estimate long-term peak power demand. Results of the study demonstrated that population had the strongest impact on future power demand, while the number of buildings had the smallest impact. It was concluded that peak power growth can be controlled through the use of different immigration policies, increased A/C efficiency, and the use of vertical housing. 7 refs., 2 tabs., 6 figs

Electric peak power forecasting by year 2025

Energy Technology Data Exchange (ETDEWEB)

Alsayegh, O.A.; Al-Matar, O.A.; Fairouz, F.A.; Al-Mulla Ali, A. [Kuwait Inst. for Scientific Research, Kuwait City (Kuwait). Div. of Environment and Urban Development

2005-07-01

Peak power demand in Kuwait up to the year 2025 was predicted using an artificial neural network (ANN) model. The aim of the study was to investigate the effect of air conditioning (A/C) units on long-term power demand. Five socio-economic factors were selected as inputs for the simulation: (1) gross national product, (2) population, (3) number of buildings, (4) imports of A/C units, and (5) index of industrial production. The study used socio-economic data from 1978 to 2000. Historical data of the first 10 years of the studied time period were used to train the ANN. The electrical network was then simulated to forecast peak power for the following 11 years. The calculated error was then used for years in which power consumption data were not available. The study demonstrated that average peak power rates increased by 4100 MW every 5 years. Various scenarios related to changes in population, the number of buildings, and the quantity of A/C units were then modelled to estimate long-term peak power demand. Results of the study demonstrated that population had the strongest impact on future power demand, while the number of buildings had the smallest impact. It was concluded that peak power growth can be controlled through the use of different immigration policies, increased A/C efficiency, and the use of vertical housing. 7 refs., 2 tabs., 6 figs.

A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China

International Nuclear Information System (INIS)

Yu, L.; Li, Y.P.; Huang, G.H.

2016-01-01

In this study, a FSSOM (fuzzy-stochastic simulation-optimization model) is developed for planning EPS (electric power systems) with considering peak demand under uncertainty. FSSOM integrates techniques of SVR (support vector regression), Monte Carlo simulation, and FICMP (fractile interval chance-constrained mixed-integer programming). In FSSOM, uncertainties expressed as fuzzy boundary intervals and random variables can be effectively tackled. In addition, SVR coupled Monte Carlo technique is used for predicting the peak-electricity demand. The FSSOM is applied to planning EPS for the City of Qingdao, China. Solutions of electricity generation pattern to satisfy the city's peak demand under different probability levels and p-necessity levels have been generated. Results reveal that the city's electricity supply from renewable energies would be low (only occupying 8.3% of the total electricity generation). Compared with the energy model without considering peak demand, the FSSOM can better guarantee the city's power supply and thus reduce the system failure risk. The findings can help decision makers not only adjust the existing electricity generation/supply pattern but also coordinate the conflict interaction among system cost, energy supply security, pollutant mitigation, as well as constraint-violation risk. - Highlights: • FSSOM (Fuzzy-stochastic simulation-optimization model) is developed for planning EPS. • It can address uncertainties as fuzzy-boundary intervals and random variables. • FSSOM can satisfy peak-electricity demand and optimize power allocation. • Solutions under different probability levels and p-necessity levels are analyzed. • Results create tradeoff among system cost and peak-electricity demand violation risk.

Particle creation by peak electric field

Energy Technology Data Exchange (ETDEWEB)

Adorno, T.C. [Tomsk State University, Department of Physics, Tomsk (Russian Federation); Gavrilov, S.P. [Tomsk State University, Department of Physics, Tomsk (Russian Federation); Herzen State Pedagogical University of Russia, Department of General and Experimental Physics, St. Petersburg (Russian Federation); Gitman, D.M. [Tomsk State University, Department of Physics, Tomsk (Russian Federation); P. N. Lebedev Physical Institute, Moscow (Russian Federation); University of Sao Paulo, Institute of Physics, CP 66318, Sao Paulo, SP (Brazil)

2016-08-15

The particle creation by the so-called peak electric field is considered. The latter field is a combination of two exponential parts, one exponentially increasing and another exponentially decreasing. We find exact solutions of the Dirac equation with the field under consideration with appropriate asymptotic conditions and calculate all the characteristics of particle creation effect, in particular, differential mean numbers of created particle, total number of created particles, and the probability for a vacuum to remain a vacuum. Characteristic asymptotic regimes are discussed in detail and a comparison with the pure asymptotically decaying field is considered. (orig.)

Evaluation of the Effects of Nationwide Conservation Voltage Reduction on Peak-Load Shaving Using SOMAS Data

Directory of Open Access Journals (Sweden)

Soon-Ryul Nam

2013-12-01

Full Text Available In this paper we propose a new method to evaluate the effects of nationwide conservation voltage reduction (CVR on peak-load shaving, using substation operating results management system (SOMAS data. Its evaluation is based on a national CVR factor, which is defined as the weighted average of CVR factors associated with all transformer banks and weighting coefficients are determined by the reconstructed loads corresponding to each transformer bank. To make use of the data resulting from nationwide CVR without installing additional measuring devices, we adopt a linearized static-load model with a linearizing parameter. SOMAS data are used to evaluate the effects of nationwide CVR on peak-load shaving in the Korean power system. Evaluation results show that the national CVR factor of the Korean power system has small values in the summer season and large values in the winter season. This means that the effect of nationwide CVR on peak-load shaving in the Korean power system presents stronger benefits during winter months.

Peak shifting and cross-class subsidization: The impacts of solar PV on changes in electricity costs

International Nuclear Information System (INIS)

Johnson, Erik; Beppler, Ross; Blackburn, Chris; Staver, Benjamin; Brown, Marilyn; Matisoff, Daniel

2017-01-01

The expansion of distributed solar necessitates additional research into the impacts on both utilities and their customers. In this paper we use New Jersey solar data, PJM market data, and demand profiles from a PJM utility to investigate rate and bill impacts of large-scale solar penetration. In addition to the subsidization of solar adopters by non-participants, we highlight the channels through which cross-subsidization of rate classes can arise in practice. The results of our study indicate that the fear of a utility “death spiral” may be exaggerated. Significant solar can be incorporated with only a 2% increase in non-participant bills. At high levels of penetration, distributed solar has the potential to alter the system peak hour which affects the allocation of costs across rate-classes. As the peak hour shifts to the evening when solar production diminishes, residential customers face higher distribution costs. Policy makers and utilities need to be aware of these challenges in designing the next generation of rates that are better aligned with cost causality. - Highlights: • We develop a model of electricity costs with large amounts of solar adoption. • Solar adoption leads to cost redistribution across customer classes. • Costs are redistributed partially because peak utility load shifts later in the day. • Residential distributed solar generation affects electricity bills the most. • We confirm the subsidy of participants by non-participants in net metering programs.

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 ...

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.

New consumer load prototype for electricity theft monitoring

International Nuclear Information System (INIS)

Abdullateef, A I; Salami, M J E; Musse, M A; Onasanya, M A; Alebiosu, M I

2013-01-01

Illegal connection which is direct connection to the distribution feeder and tampering of energy meter has been identified as a major process through which nefarious consumers steal electricity on low voltage distribution system. This has contributed enormously to the revenue losses incurred by the power and energy providers. A Consumer Load Prototype (CLP) is constructed and proposed in this study in order to understand the best possible pattern through which the stealing process is effected in real life power consumption. The construction of consumer load prototype will facilitate real time simulation and data collection for the monitoring and detection of electricity theft on low voltage distribution system. The prototype involves electrical design and construction of consumer loads with application of various standard regulations from Institution of Engineering and Technology (IET), formerly known as Institution of Electrical Engineers (IEE). LABVIEW platform was used for data acquisition and the data shows a good representation of the connected loads. The prototype will assist researchers and power utilities, currently facing challenges in getting real time data for the study and monitoring of electricity theft. The simulation of electricity theft in real time is one of the contributions of this prototype. Similarly, the power and energy community including students will appreciate the practical approach which the prototype provides for real time information rather than software simulation which has hitherto been used in the study of electricity theft

New consumer load prototype for electricity theft monitoring

Science.gov (United States)

Abdullateef, A. I.; Salami, M. J. E.; Musse, M. A.; Onasanya, M. A.; Alebiosu, M. I.

2013-12-01

Illegal connection which is direct connection to the distribution feeder and tampering of energy meter has been identified as a major process through which nefarious consumers steal electricity on low voltage distribution system. This has contributed enormously to the revenue losses incurred by the power and energy providers. A Consumer Load Prototype (CLP) is constructed and proposed in this study in order to understand the best possible pattern through which the stealing process is effected in real life power consumption. The construction of consumer load prototype will facilitate real time simulation and data collection for the monitoring and detection of electricity theft on low voltage distribution system. The prototype involves electrical design and construction of consumer loads with application of various standard regulations from Institution of Engineering and Technology (IET), formerly known as Institution of Electrical Engineers (IEE). LABVIEW platform was used for data acquisition and the data shows a good representation of the connected loads. The prototype will assist researchers and power utilities, currently facing challenges in getting real time data for the study and monitoring of electricity theft. The simulation of electricity theft in real time is one of the contributions of this prototype. Similarly, the power and energy community including students will appreciate the practical approach which the prototype provides for real time information rather than software simulation which has hitherto been used in the study of electricity theft.

A RTS-based method for direct and consistent calculating intermittent peak cooling loads

International Nuclear Information System (INIS)

Chen Tingyao; Cui, Mingxian

2010-01-01

The RTS method currently recommended by ASHRAE Handbook is based on continuous operation. However, most of air-conditioning systems, if not all, in commercial buildings, are intermittently operated in practice. The application of the current RTS method to intermittent air-conditioning in nonresidential buildings could result in largely underestimated design cooling loads, and inconsistently sized air-conditioning systems. Improperly sized systems could seriously deteriorate the performance of system operation and management. Therefore, a new method based on both the current RTS method and the principles of heat transfer has been developed. The first part of the new method is the same as the current RTS method in principle, but its calculation procedure is simplified by the derived equations in a close form. The technical data available in the current RTS method can be utilized to compute zone responses to a change in space air temperature so that no efforts are needed for regenerating new technical data. Both the overall RTS coefficients and the hourly cooling loads computed in the first part are used to estimate the additional peak cooling load due to a change from continuous operation to intermittent operation. It only needs one more step after the current RTS method to determine the intermittent peak cooling load. The new RTS-based method has been validated by EnergyPlus simulations. The root mean square deviation (RMSD) between the relative additional peak cooling loads (RAPCLs) computed by the two methods is 1.8%. The deviation of the RAPCL varies from -3.0% to 5.0%, and the mean deviation is 1.35%.

The effectiveness of plug-in hybrid electric vehicles and renewable power in support of holistic environmental goals: Part 2 - Design and operation implications for load-balancing resources on the electric grid

Science.gov (United States)

Tarroja, Brian; Eichman, Joshua D.; Zhang, Li; Brown, Tim M.; Samuelsen, Scott

2015-03-01

A study has been performed that analyzes the effectiveness of utilizing plug-in vehicles to meet holistic environmental goals across the combined electricity and transportation sectors. In this study, plug-in hybrid electric vehicle (PHEV) penetration levels are varied from 0 to 60% and base renewable penetration levels are varied from 10 to 63%. The first part focused on the effect of installing plug-in hybrid electric vehicles on the environmental performance of the combined electricity and transportation sectors. The second part addresses impacts on the design and operation of load-balancing resources on the electric grid associated with fleet capacity factor, peaking and load-following generator capacity, efficiency, ramp rates, start-up events and the levelized cost of electricity. PHEVs using smart charging are found to counteract many of the disruptive impacts of intermittent renewable power on balancing generators for a wide range of renewable penetration levels, only becoming limited at high renewable penetration levels due to lack of flexibility and finite load size. This study highlights synergy between sustainability measures in the electric and transportation sectors and the importance of communicative dispatch of these vehicles.

Climate control loads prediction of electric vehicles

International Nuclear Information System (INIS)

Zhang, Ziqi; Li, Wanyong; Zhang, Chengquan; Chen, Jiangping

2017-01-01

Highlights: • A model of vehicle climate control loads is proposed based on experiments. • Main climate control loads of the modeled vehicle are quantitatively analyzed. • Range reductions of the modeled vehicle under different conditions are simulated. - Abstract: A new model of electric vehicle climate control loads is provided in this paper. The mathematical formulations of the major climate control loads are developed, and the coefficients of the formulations are experimentally determined. Then, the detailed climate control loads are analyzed, and the New European Driving Cycle (NEDC) range reductions due to these loads are calculated under different conditions. It is found that in an electric vehicle, the total climate control loads vary with the vehicle speed, HVAC mode and blower level. The ventilation load is the largest climate control load, followed by the solar radiation load. These two add up to more than 80% of total climate control load in summer. The ventilation load accounts for 70.7–83.9% of total heating load under the winter condition. The climate control loads will cause a 17.2–37.1% reduction of NEDC range in summer, and a 17.1–54.1% reduction in winter, compared to the AC off condition. The heat pump system has an advantage in range extension. A heat pump system with an average heating COP of 1.7 will extend the range by 7.6–21.1% based on the simulation conditions.

Impact Study on Power Factor of Electrical Load in Power Distribution System

International Nuclear Information System (INIS)

Syirrazie Che Soh; Harzawardi Hasim; Ahmad Asraf, A.S.

2014-01-01

Low Power Factor of electrical loads cause high current is drawn from power supply. The impact of this circumstance is influenced by impedance of electrical load. Therefore, the key consideration of this study is how impedance of electrical loads influence power factor of electrical loads, and then power distribution as the whole. This study is important to evaluate the right action to mitigate low power factor effectively for electrical energy efficiency purpose. (author)

Management strategies for surplus electricity loads using electrolytic hydrogen

International Nuclear Information System (INIS)

Gutierrez-Martin, F.; Garcia-De Maria, J.M.; Bairi, A.; Laraqi, N.

2009-01-01

Management of electricity-hydrogen binomials is greatly enhanced by the knowledge of power variations, together with an optimized performance of the electrolyzers. Strategies include the regulation of current densities to minimize hydrogen costs, which depend of the energy prices, the power of installations and utilization factors. The objective is to convert the energy in distinct periods of electricity demand, taking into account the size and efficiency of the equipments; this approach indicates the possibility to reduce costs below a reference price, either by using small facilities which consume high proportions of surplus energy or larger plants for shorter off-peak periods. Thus, we study the viability of large scale production of hydrogen via electrolysis, within the context of excess electricity loads in France (estimated at 22 TWh in 2007): that gives a daily hydrogen potential of 1314 ton, from a total installed power of 5800 MW and average utilization ratios of 42.8%; the production cost approaches 1$/kg H2 , and CO 2 reduction potential amounts 6720 kton/year (if all the produced hydrogen is used to feed 3 million of new fuel-cell vehicles). This analysis serves to demonstrate the great potentials for converting the surplus energy into hydrogen carriers and for managing the power subsystem in thoroughly electrified societies. (author)

Ranking Method for Peak-Load Shifting Considering Different Types of Data

DEFF Research Database (Denmark)

Wang, Peng; Wen, Fushuan; Pinson, Pierre

2016-01-01

, an evaluation system for the purpose of peak-load shifting is established from three aspects: economic, social, and environmental impacts. Then a mixed-data dominance method is employed in this work to determine the comprehensive closeness degree of each user under each index, and an optimal comprehensive...

Sizing community energy storage systems to reduce transformer overloading with emphasis on plug-in electric vehicle loads

Science.gov (United States)

Trowler, Derik Wesley

The research objective of this study was to develop a sizing method for community energy storage systems with emphasis on preventing distribution transformer overloading due to plug-in electric vehicle charging. The method as developed showed the formulation of a diversified load profile based upon residential load data for several customers on the American Electric Power system. Once a load profile was obtained, plug-in electric vehicle charging scenarios which were based upon expected adoption and charging trends were superimposed on the load profile to show situations where transformers (in particular 25 kVA, 50 kVA, and 100 kVA) would be overloaded during peak hours. Once the total load profiles were derived, the energy and power requirements of community energy storage systems were calculated for a number of scenarios with different combinations of numbers of homes and plug-in electric vehicles. The results were recorded and illustrated into charts so that one could determine the minimum size per application. Other topics that were covered in this thesis were the state of the art and future trends in plug-in electric vehicle and battery chemistry adoption and development. The goal of the literature review was to confirm the already suspected notion that Li-ion batteries are best suited and soon to be most cost-effective solution for applications requiring small, efficient, reliable, and light-weight battery systems such as plug-in electric vehicles and community energy storage systems. This thesis also includes a chapter showing system modeling in MATLAB/SimulinkRTM. All in all, this thesis covers a wide variety of considerations involved in the designing and deploying of community energy storage systems intended to mitigate the effects of distribution transformer overloading.

Peak load shifting control using different cold thermal energy storage facilities in commercial buildings: A review

International Nuclear Information System (INIS)

Sun, Yongjun; Wang, Shengwei; Xiao, Fu; Gao, Diance

2013-01-01

Highlights: • Little study reviews the load shifting control using different facilities. • This study reviews load shifting control using building thermal mass. • This study reviews load shifting control using thermal energy storage systems. • This study reviews load shifting control using phase change material. • Efforts for developing more applicable load shifting control are addressed. - Abstract: For decades, load shifting control, one of most effective peak demand management methods, has attracted increasing attentions from both researchers and engineers. Different load shifting control strategies have been developed when diverse cold thermal energy storage facilities are used in commercial buildings. The facilities include building thermal mass (BTM), thermal energy storage system (TES) and phase change material (PCM). Little study has systematically reviewed these load shifting control strategies and therefore this study presents a comprehensive review of peak load shifting control strategies using these thermal energy storage facilities in commercial buildings. The research and applications of the load shifting control strategies are presented and discussed. The further efforts needed for developing more applicable load shifting control strategies using the facilities are also addressed

Optimum Insulation Thickness for Walls and Roofs for Reducing Peak Cooling Loads in Residential Buildings in Lahore

Directory of Open Access Journals (Sweden)

SIBGHA SIDDIQUE SIDDIQUE

2016-10-01

Full Text Available Thermal insulation is the most effective energy saving measure for cooling in buildings. Therefore, the main subject of many engineering investigations is the selection and determination of the optimum insulation thickness. In the present study, the optimum insulation thickness on external walls and roofs is determined based on the peak cooling loads for an existing residential building in Lahore, Pakistan. Autodesk® Revit 2013 is used for the analysis of the building and determination of the peak cooling loads. The analysis shows that the optimum insulation thickness to reduce peak cooling loads up to 40.1% is 1 inch for external walls and roof respectively.

Optimum Insulation Thickness for Walls and Roofs for Reducing Peak Cooling Loads in Residential Buildings in Lahore

International Nuclear Information System (INIS)

Siddique, S.; Arif, S.; Khan, A.; Alam, A.T.

2016-01-01

Thermal insulation is the most effective energy saving measure for cooling in buildings. Therefore, the main subject of many engineering investigations is the selection and determination of the optimum insulation thickness. In the present study, the optimum insulation thickness on external walls and roofs is determined based on the peak cooling loads for an existing residential building in Lahore, Pakistan. Autodesk at the rate Revit 2013 is used for the analysis of the building and determination of the peak cooling loads. The analysis shows that the optimum insulation thickness to reduce peak cooling loads up to 40.1 percent is 1 inch for external walls and roof respectively. (author)

Optimal Residential Load Scheduling Under Utility and Rooftop Photovoltaic Units

Directory of Open Access Journals (Sweden)

Ghulam Hafeez

2018-03-01

Full Text Available With the rapid advancement in technology, electrical energy consumption is increasing rapidly. Especially, in the residential sector, more than 80% of electrical energy is being consumed because of consumer negligence. This brings the challenging task of maintaining the balance between the demand and supply of electric power. In this paper, we focus on the problem of load balancing via load scheduling under utility and rooftop photovoltaic (PV units to reduce electricity cost and peak to average ratio (PAR in demand-side management. For this purpose, we adopted genetic algorithm (GA, binary particle swarm optimization (BPSO, wind-driven optimization (WDO, and our proposed genetic WDO (GWDO algorithm, which is a hybrid of GA and WDO, to schedule the household load. For energy cost estimation, combined real-time pricing (RTP and inclined block rate (IBR were used. The proposed algorithm shifts load from peak consumption hours to off-peak hours based on combined pricing scheme and generation from rooftop PV units. Simulation results validate our proposed GWDO algorithm in terms of electricity cost and PAR reduction while considering all three scenarios which we have considered in this work: (1 load scheduling without renewable energy sources (RESs and energy storage system (ESS, (2 load scheduling with RESs, and (3 load scheduling with RESs and ESS. Furthermore, our proposed scheme reduced electricity cost and PAR by 22.5% and 29.1% in scenario 1, 47.7% and 30% in scenario 2, and 49.2% and 35.4% in scenario 3, respectively, as compared to unscheduled electricity consumption.

Research, Development and Demonstration of Peak Load Reduction on Distribution Feeders Using Distributed Energy Resources for the City of Fort Collins

Energy Technology Data Exchange (ETDEWEB)

Sumner, Dennis [City of Fort Collins Utilities, CO (United States); Vosburg, Tom [City of Fort Collins Utilities, CO (United States); Brunner, Steve [Brendle Group, Fort Collins, CO (United States); Gates, Judy [Woodward, Inc., Fort Collins, CO (United States); Howard, Nathan [Spirae, Inc., Fort Collins, CO (United States); Merton, Andrew [Spirae, Inc., Fort Collins, CO (United States); Wright, Don [Spirae, Inc., Fort Collins, CO (United States); Birlingmair, Doug [Spirae, Inc., Fort Collins, CO (United States)

2015-10-01

This project titled “Research, Development and Demonstration of Peak Load Reduction on Distribution Feeders Using Distributed Energy Resources for the City of Fort Collins” evolved in response to the Department of Energy’s (DOE) Funding Opportunity Announcement (FOA) Number DE-PS26-07NT43119. Also referred to as the Fort Collins Renewable and Distributed System Integration (RDSI) Project, the effort was undertaken by a diverse group of local government, higher education and business organizations; and was driven by three overarching goals: I. Fulfill the requirements of the DOE FOA’s Area of Interest 2: Renewable and Distributed System Integration; most notably, to demonstrate the ability to reduce electric system distribution feeder peak load by 15% or more through the coordinated use of Distributed Energy Resources (DER). II. Advance the expertise, technologies and infrastructure necessary to support the long term vision of the Fort Collins Zero Energy District (FortZED) and move towards creating a zero energy district in the Fort Collins “Old Town” area. III. Further the goals of the City of Fort Collins Energy Policy, including the development of a Smart Grid-enabled distribution system in Fort Collins, expanded use of renewable energy, increased energy conservation, and peak load reduction. Through the collaborative efforts of the partner organizations, the Fort Collins RDSI project was successful in achieving all three of these goals. This report is organized into two distinct sections corresponding to the two phases of the project: • Part 1: Feeder Peak Load Reduction and the FortZED Initiative. • Part 2: Forming and Operating Utility Microgrids and Managing Load and Production Variability The original project scope addressed the Part 1 feeder peak load reduction. That work took place from 2009 through 2011 and was largely complete when the project scope was amended to include a demonstration of microgrid operations. While leveraging the

Efforts of load leveling in Tohoku Electric Power Co. Inc.; Tohoku denryoku no fuka heijunka eno torikumi ni tsuite

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-05-01

This paper describes efforts of load leveling in Tohoku Electric Power Co., Inc. from the viewpoint of the rate system and business development. For the approach from the rate system, various rate menus for the peak shift have been arranged for domestic and large industry customers. To create the midnight demand, spread and expansion of electric hot water service are promoted. Consequently, the contract of midnight power has reached 914,000 kW at the end of 1995, which was 774,000 kW in 1985. To spread the ice regenerative air conditioning systems, the grant of incentive to the manufacturers and special discount of electricity rate have been conducted. These systems have been introduced in the eight places of Tohoku Electric Power`s business. The spread incident system has been created to introduce the automatic vending machines for beverages with the power peak cut function. Unused energy, such as exhaust heat from the non-treated sewage water and substations has been utilized as a heat supply project for city redevelopment. Multi-functional heat pump with regenerative function has been developed. This system aims at the peak shift by combining multi-functional heat pump and electric hot water service. 2 figs., 2 tabs.

Hybrid ellipsoidal fuzzy systems in forecasting regional electricity loads

Energy Technology Data Exchange (ETDEWEB)

Pai, Ping-Feng [Department of Information Management, National Chi Nan University, 1 University Road, Puli, Nantou 545, Taiwan (China)

2006-09-15

Because of the privatization of electricity in many countries, load forecasting has become one of the most crucial issues in the planning and operations of electric utilities. In addition, accurate regional load forecasting can provide the transmission and distribution operators with more information. The hybrid ellipsoidal fuzzy system was originally designed to solve control and pattern recognition problems. The main objective of this investigation is to develop a hybrid ellipsoidal fuzzy system for time series forecasting (HEFST) and apply the proposed model to forecast regional electricity loads in Taiwan. Additionally, a scaled conjugate gradient learning method is employed in the supervised learning phase of the HEFST model. Subsequently, numerical data taken from the existing literature is used to demonstrate the forecasting performance of the HEFST model. Simulation results reveal that the proposed model has better forecasting performance than the artificial neural network model and the regression model. Thus, the HEFST model is a valid and promising alternative for forecasting regional electricity loads. (author)

Performance of fuzzy approach in Malaysia short-term electricity load forecasting

Science.gov (United States)

Mansor, Rosnalini; Zulkifli, Malina; Yusof, Muhammad Mat; Ismail, Mohd Isfahani; Ismail, Suzilah; Yin, Yip Chee

2014-12-01

Many activities such as economic, education and manafucturing would paralyse with limited supply of electricity but surplus contribute to high operating cost. Therefore electricity load forecasting is important in order to avoid shortage or excess. Previous finding showed festive celebration has effect on short-term electricity load forecasting. Being a multi culture country Malaysia has many major festive celebrations such as Eidul Fitri, Chinese New Year and Deepavali but they are moving holidays due to non-fixed dates on the Gregorian calendar. This study emphasis on the performance of fuzzy approach in forecasting electricity load when considering the presence of moving holidays. Autoregressive Distributed Lag model was estimated using simulated data by including model simplification concept (manual or automatic), day types (weekdays or weekend), public holidays and lags of electricity load. The result indicated that day types, public holidays and several lags of electricity load were significant in the model. Overall, model simplification improves fuzzy performance due to less variables and rules.

Kinetic energy storage of off-peak electricity

International Nuclear Information System (INIS)

Simpson, L.A.; Oldaker, I.E.; Stermscheg, J.

1975-09-01

The concept of using large flywheels to store off-peak electricity has been considered. The development of high strength composite materials has made possible improvements in the energy storage capacity of such devices. The problems involved in designing large flywheels and their economic advantages over alternative means of energy storage are discussed. The economic arguments are based on the present or near future capabilities and costs of structural composite materials. The flywheel costs turn out to be considerably higher than for many alternative schemes including advanced batteries, gas turbine generators and pumped storage schemes. (author)

Optimal Charge control of Electric Vehicles in Electricity Markets

DEFF Research Database (Denmark)

Lan, Tian; Hu, Junjie; Wu, Guang

2011-01-01

Environment constraints, petroleum scarcity, high price on fuel resources and recent advancements in battery technology have led to emergence of Electric Vehicles (EVs). As increasing numbers of EVs enter the electricity market, these extra loads may cause peak load and need to be properly...... controlled. In this paper, an algorithm is presented for every individual vehicles to minimize the charging cost while satisfying the vehicle owner’s requirements. The algorithm is based on a given future electricity prices and uses dynamic programming. Optimization aims to find the economically optimal...... solution for each vehicle....

Electric reaction arising in bone subjected to mechanical loadings

Science.gov (United States)

Murasawa, Go; Cho, Hideo; Ogawa, Kazuma

2006-03-01

The aim of present study is the investigation of the electric reaction arising in bone subjected to mechanical loadings. Firstly, specimen was fabricated from femur of cow, and ultrasonic propagation in bone was measured by ultrasonic technique. Secondary, 4-point bending test was conducted up to fracture, and electric reaction arising in bone was measured during loading. Thirdly, cyclic 4-point bending test was conducted to investigate the effect of applied displacement speed on electric reaction.

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

A Bi-Level Optimization Approach to Charging Load Regulation of Electric Vehicle Fast Charging Stations Based on a Battery Energy Storage System

Directory of Open Access Journals (Sweden)

Yan Bao

2018-01-01

Full Text Available Fast charging stations enable the high-powered rapid recharging of electric vehicles. However, these stations also face challenges due to power fluctuations, high peak loads, and low load factors, affecting the reliable and economic operation of charging stations and distribution networks. This paper introduces a battery energy storage system (BESS for charging load control, which is a more user-friendly approach and is more robust to perturbations. With the goals of peak-shaving, total electricity cost reduction, and minimization of variation in the state-of-charge (SOC range, a BESS-based bi-level optimization strategy for the charging load regulation of fast charging stations is proposed in this paper. At the first level, a day-ahead optimization strategy generates the optimal planned load curve and the deviation band to be used as a reference for ensuring multiple control objectives through linear programming, and even for avoiding control failure caused by insufficient BESS energy. Based on this day-ahead optimal plan, at a second level, real-time rolling optimization converts the control process to a multistage decision-making problem. The predictive control-based real-time rolling optimization strategy in the proposed model was used to achieve the above control objectives and maintain battery life. Finally, through a horizontal comparison of two control approaches in each case study, and a longitudinal comparison of the control robustness against different degrees of load disturbances in three cases, the results indicated that the proposed control strategy was able to significantly improve the charging load characteristics, even with large disturbances. Meanwhile, the proposed approach ensures the least amount of variation in the range of battery SOC and reduces the total electricity cost, which will be of a considerable benefit to station operators.

North-south polarization of European electricity consumption under future warming.

Science.gov (United States)

Wenz, Leonie; Levermann, Anders; Auffhammer, Maximilian

2017-09-19

There is growing empirical evidence that anthropogenic climate change will substantially affect the electric sector. Impacts will stem both from the supply side-through the mitigation of greenhouse gases-and from the demand side-through adaptive responses to a changing environment. Here we provide evidence of a polarization of both peak load and overall electricity consumption under future warming for the world's third-largest electricity market-the 35 countries of Europe. We statistically estimate country-level dose-response functions between daily peak/total electricity load and ambient temperature for the period 2006-2012. After removing the impact of nontemperature confounders and normalizing the residual load data for each country, we estimate a common dose-response function, which we use to compute national electricity loads for temperatures that lie outside each country's currently observed temperature range. To this end, we impose end-of-century climate on today's European economies following three different greenhouse-gas concentration trajectories, ranging from ambitious climate-change mitigation-in line with the Paris agreement-to unabated climate change. We find significant increases in average daily peak load and overall electricity consumption in southern and western Europe (∼3 to ∼7% for Portugal and Spain) and significant decreases in northern Europe (∼-6 to ∼-2% for Sweden and Norway). While the projected effect on European total consumption is nearly zero, the significant polarization and seasonal shifts in peak demand and consumption have important ramifications for the location of costly peak-generating capacity, transmission infrastructure, and the design of energy-efficiency policy and storage capacity.

Exploring the impact of network tariffs on household electricity expenditures using load profiles and socio-economic characteristics

Science.gov (United States)

Azarova, Valeriya; Engel, Dominik; Ferner, Cornelia; Kollmann, Andrea; Reichl, Johannes

2018-04-01

Growing self-generation and storage are expected to cause significant changes in residential electricity utilization patterns. Commonly applied volumetric network tariffs may induce imbalance between different groups of households and their respective contribution to recovering the operating costs of the grid. Understanding consumer behaviour and appliance usage together with socio-economic factors can help regulatory authorities to adapt network tariffs to new circumstances in a fair way. Here, we assess the effects of 11 network tariff scenarios on household budgets using real load profiles from 765 households. Thus we explore the possibly disruptive impact of applying peak-load-based tariffs on the budgets of households when they have been mainly charged for consumed volumes before. Our analysis estimates the change in household network expenditure for different combinations of energy, peak and fixed charges, and can help to design tariffs that recover the costs needed for the sustainable operation of the grid.

Resident Load Influence Analysis Method for Price Based on Non-intrusive Load Monitoring and Decomposition Data

Science.gov (United States)

Jiang, Wenqian; Zeng, Bo; Yang, Zhou; Li, Gang

2018-01-01

In the non-invasive load monitoring mode, the load decomposition can reflect the running state of each load, which will help the user reduce unnecessary energy costs. With the demand side management measures of time of using price, a resident load influence analysis method for time of using price (TOU) based on non-intrusive load monitoring data are proposed in the paper. Relying on the current signal of the resident load classification, the user equipment type, and different time series of self-elasticity and cross-elasticity of the situation could be obtained. Through the actual household load data test with the impact of TOU, part of the equipment will be transferred to the working hours, and users in the peak price of electricity has been reduced, and in the electricity at the time of the increase Electrical equipment, with a certain regularity.

Peak Load Regulation and Cost Optimization for Microgrids by Installing a Heat Storage Tank and a Portable Energy System

Directory of Open Access Journals (Sweden)

Hong Zhang

2018-04-01

Full Text Available With the rapid growth of electricity demands, many traditional distributed networks cannot cover their peak demands, especially in the evening. Additionally, with the interconnection of distributed electrical and thermal grids, system operational flexibility and energy efficiency can be affected as well. Therefore, by adding a portable energy system and a heat storage tank to the traditional distributed system, this paper proposes a newly defined distributed network to deal with the aforementioned problems. Simulation results show that by adding a portable energy system, fossil fuel energy consumption and daily operation cost can be reduced by 8% and 28.29%, respectively. Moreover, system peak load regulating capacity can be significantly improved. However, by introducing the portable energy system to the grid, system uncertainty can be increased to some extent. Therefore, chance constrained programming is proposed to control the system while considering system uncertainty. By applying Particle Swarm Optimization—Monte Carlo to solve the chance constrained programming, results show that power system economy and uncertainty can be compromised by selecting appropriate confidence levels α and β. It is also reported that by installing an extra heat storage tank, combined heat and power energy efficiency can be significantly improved and the installation capacity of the battery can be reduced.

Short-Term Load Forecast in Electric Energy System in Bulgaria

Directory of Open Access Journals (Sweden)

Irina Asenova

2010-01-01

Full Text Available As the accuracy of the electricity load forecast is crucial in providing better cost effective risk management plans, this paper proposes a Short Term Electricity Load Forecast (STLF model with high forecasting accuracy. Two kind of neural networks, Multilayer Perceptron network model and Radial Basis Function network model, are presented and compared using the mean absolute percentage error. The data used in the models are electricity load historical data. Even though the very good performance of the used model for the load data, weather parameters, especially the temperature, take important part for the energy predicting which is taken into account in this paper. A comparative evaluation between a traditional statistical method and artificial neural networks is presented.

Dielectric properties of PLZT-x/65/35 (2≤x≤13 under mechanical stress, electric field and temperature loading

Directory of Open Access Journals (Sweden)

K. Pytel

2013-01-01

Full Text Available We investigated the effect of uniaxial pressure (0÷1000 bars applied parallely to the ac electric field on dielectric properties of PLZT-x/65/35 (2≤x≤13 ceramics. There was revealed a significant effect of the external stress on these properties. The application of uniaxial pressure leads to the change of the peak intensity of the electric permittivity (ϵ, of the frequency dispersion as well as of the dielectric hysteresis. The peak intensity ϵ becomes diffused/sharpened and shifts to a higher/lower temperatures with increasing the pressure. It was concluded that the application of uniaxial pressure induces similar effects as increasing the Ti ion concentration in PZT system. We interpreted our results based on the domain switching processes under the action of combined electromechanical loading.

An electricity price model with consideration to load and gas price effects.

Science.gov (United States)

Huang, Min-xiang; Tao, Xiao-hu; Han, Zhen-xiang

2003-01-01

Some characteristics of the electricity load and prices are studied, and the relationship between electricity prices and gas (fuel) prices is analyzed in this paper. Because electricity prices are strongly dependent on load and gas prices, the authors constructed a model for electricity prices based on the effects of these two factors; and used the Geometric Mean Reversion Brownian Motion (GMRBM) model to describe the electricity load process, and a Geometric Brownian Motion(GBM) model to describe the gas prices; deduced the price stochastic process model based on the above load model and gas price model. This paper also presents methods for parameters estimation, and proposes some methods to solve the model.

Towards Efficient Energy Management of Smart Buildings Exploiting Heuristic Optimization with Real Time and Critical Peak Pricing Schemes

Directory of Open Access Journals (Sweden)

Sheraz Aslam

2017-12-01

Full Text Available The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM. Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the electricity cost and Peak to Average Ratio (PAR with minimum user waiting time. There are many studies on Home Energy Management (HEM for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction at the same time as user waiting time was minimum for residential consumers with multiple homes. Hence, in this work, we propose an efficient HEM scheme using the well-known meta-heuristic Genetic Algorithm (GA, the recently developed Cuckoo Search Optimization Algorithm (CSOA and the Crow Search Algorithm (CSA, which can be used for electricity cost and peak load alleviation with minimum user waiting time. The integration of a smart Electricity Storage System (ESS is also taken into account for more efficient operation of the Home Energy Management System (HEMS. Furthermore, we took the real-time electricity consumption pattern for every residence, i.e., every home has its own living pattern. The proposed scheme is implemented in a smart building; comprised of thirty smart homes (apartments, Real-Time Pricing (RTP and Critical Peak Pricing (CPP signals are examined in terms of electricity cost estimation for both a single smart home and a smart building. In addition, feasible regions are presented for single and multiple smart homes, which show the relationship among the electricity cost, electricity consumption and user waiting time. Experimental results demonstrate the effectiveness of our proposed scheme for single and multiple smart

Short-Term Load Forecasting Based on the Analysis of User Electricity Behavior

Directory of Open Access Journals (Sweden)

Yuancheng Li

2016-11-01

Full Text Available The smart meter is an important part of the smart grid, and in order to take full advantage of smart meter data, this paper mines the electricity behaviors of smart meter users to improve the accuracy of load forecasting. First, the typical day loads of users are calculated separately according to different date types (ordinary workdays, day before holidays, holidays. Second, the similarity between user electricity behaviors is mined and the user electricity loads are clustered to classify the users with similar behaviors into the same cluster. Finally, the load forecasting model based on the Online Sequential Extreme Learning Machine (OS-ELM is applied to different clusters to conduct load forecasting and the load forecast is summed to obtain the system load. In order to prove the validity of the proposed method, we performed simulation experiments on the MATLAB platform using smart meter data from the Ireland electric power cooperation. The experimental results show that the proposed method is able to mine the user electricity behaviors deeply, improve the accuracy of load forecasting by the reasonable clustering of users, and reveal the relationship between forecasting accuracy and cluster numbers.

A hybrid dielectric and iris loaded periodic accelerating structure

International Nuclear Information System (INIS)

Zou, P.; Xiao, L.; Sun, X.; Gai, W.

2001-01-01

One disadvantage of conventional iris-loaded accelerating structures is the high ratio of the peak surface electric field to the peak axial electric field useful for accelerating a beam. Typically this ratio E s /E a ≥ 2. The high surface electric field relative to the accelerating gradient may prove to be a limitation for realizing technologies for very high gradient accelerators. In this paper, we present a scheme that uses a hybrid dielectric and iris loaded periodic structure to reduce E s /E a to near unity, while the shunt impedance per unit length r and the quality factor Q compare favorably with conventional metallic structures. The analysis based on MAFIA simulations of such structures shows that we can lower the peak surface electric field close to the accelerating gradient while maintaining high acceleration efficiency as measured by r/Q. Numerical examples of X-band hybrid accelerating structures are given

North–south polarization of European electricity consumption under future warming

Science.gov (United States)

Wenz, Leonie; Levermann, Anders; Auffhammer, Maximilian

2017-01-01

There is growing empirical evidence that anthropogenic climate change will substantially affect the electric sector. Impacts will stem both from the supply side—through the mitigation of greenhouse gases—and from the demand side—through adaptive responses to a changing environment. Here we provide evidence of a polarization of both peak load and overall electricity consumption under future warming for the world’s third-largest electricity market—the 35 countries of Europe. We statistically estimate country-level dose–response functions between daily peak/total electricity load and ambient temperature for the period 2006–2012. After removing the impact of nontemperature confounders and normalizing the residual load data for each country, we estimate a common dose–response function, which we use to compute national electricity loads for temperatures that lie outside each country’s currently observed temperature range. To this end, we impose end-of-century climate on today’s European economies following three different greenhouse-gas concentration trajectories, ranging from ambitious climate-change mitigation—in line with the Paris agreement—to unabated climate change. We find significant increases in average daily peak load and overall electricity consumption in southern and western Europe (∼3 to ∼7% for Portugal and Spain) and significant decreases in northern Europe (∼−6 to ∼−2% for Sweden and Norway). While the projected effect on European total consumption is nearly zero, the significant polarization and seasonal shifts in peak demand and consumption have important ramifications for the location of costly peak-generating capacity, transmission infrastructure, and the design of energy-efficiency policy and storage capacity. PMID:28847939

Short term and medium term power distribution load forecasting by neural networks

International Nuclear Information System (INIS)

Yalcinoz, T.; Eminoglu, U.

2005-01-01

Load forecasting is an important subject for power distribution systems and has been studied from different points of view. In general, load forecasts should be performed over a broad spectrum of time intervals, which could be classified into short term, medium term and long term forecasts. Several research groups have proposed various techniques for either short term load forecasting or medium term load forecasting or long term load forecasting. This paper presents a neural network (NN) model for short term peak load forecasting, short term total load forecasting and medium term monthly load forecasting in power distribution systems. The NN is used to learn the relationships among past, current and future temperatures and loads. The neural network was trained to recognize the peak load of the day, total load of the day and monthly electricity consumption. The suitability of the proposed approach is illustrated through an application to real load shapes from the Turkish Electricity Distribution Corporation (TEDAS) in Nigde. The data represents the daily and monthly electricity consumption in Nigde, Turkey

Electric vehicle utilization for ancillary grid services

Science.gov (United States)

Aziz, Muhammad

2018-02-01

Electric vehicle has been developed through several decades as transportation mean, without paying sufficient attention of its utilization for other purposes. Recently, the utilization of electric vehicle to support the grid electricity has been proposed and studied intensively. This utilization covers several possible services including electricity storage, spinning reserve, frequency and voltage regulation, and emergency energy supply. This study focuses on theoretical and experimental analysis of utilization of electric vehicles and their used batteries to support a small-scale energy management system. Charging rate of electric vehicle under different ambient temperature (seasonal condition) is initially analyzed to measure the correlation of charging rate, charging time, and state-of-charge. It is confirmed that charging under warmer condition (such as in summer or warmer region) shows higher charging rate than one in colder condition, therefore, shorter charging time can be achieved. In addition, in the demonstration test, each five electric vehicles and used batteries from the same electric vehicles are employed and controlled to support the electricity of the office building. The performance of the system is evaluated throughout a year to measure the load leveling effect during peak-load time. The results show that the targeted peak-load can be shaved well under certain calculated peak-shaving threshold. The finding confirms that the utilization of electric vehicle for supporting the electricity of grid or certain energy management system is feasible and deployable in the future.

Important variables in explaining real-time peak price in the independent power market of Ontario

International Nuclear Information System (INIS)

Rueda, I.E.A.; Marathe, A.

2005-01-01

This paper uses support vector machines (SVM) based learning algorithm to select important variables that help explain the real-time peak electricity price in the Ontario market. The Ontario market was opened to competition only in May 2002. Due to the limited number of observations available, finding a set of variables that can explain the independent power market of Ontario (IMO) real-time peak price is a significant challenge for the traders and analysts. The kernel regressions of the explanatory variables on the IMO real-time average peak price show that non-linear dependencies exist between the explanatory variables and the IMO price. This non-linear relationship combined with the low variable-observation ratio rule out conventional statistical analysis. Hence, we use an alternative machine learning technique to find the important explanatory variables for the IMO real-time average peak price. SVM sensitivity analysis based results find that the IMO's predispatch average peak price, the actual import peak volume, the peak load of the Ontario market and the net available supply after accounting for load (energy excess) are some of the most important variables in explaining the real-time average peak price in the Ontario electricity market. (author)

Provision of Flexible Load Control by Multi-Flywheel-Energy-Storage System in Electrical Vehicle Charging Stations

DEFF Research Database (Denmark)

Sun, Bo; Dragicevic, Tomislav; Andrade, Fabio

2015-01-01

in order to support basic electrical operation. This paper proposes a local implementation of a hysteresis-based aggregation algorithm for coordinated control of multiple stations that can provide functions such as peak shaving, spinning reserves, frequency control, regulation and load following. Local......Electrical vehicle (EV) chargers are going to occupy a considerable portion of total energy consumption in the future smart grid. Fast charging stations (FCS), as the most demanding representatives of charging infrastructure, will be requested to provide some ancillary services to the power system...... stability. Finally, corresponding hardware in the loop results based on dSPACE1006 platform have been reported in order to verify the validity of proposed approach....

Superconducting magnetic energy storage for electric utility load leveling: A study of cost vs. stored energy

International Nuclear Information System (INIS)

Luongo, C.A.; Loyd, R.J.

1987-01-01

Superconducting Magnetic Energy Storage (SMES) is a promising technology for electric utility load leveling. This paper presents the results of a study to establish the capital cost of SMES as a function of stored energy. Energy-related coil cost and total installed plant cost are given for construction in nominal soil and in competent rock. Economic comparisons are made between SMES and other storage technologies and peaking gas turbines. SMES is projected to be competitive at stored energies as low as 1000 MWh

Process for improving the load factor of an electricity generating power station

International Nuclear Information System (INIS)

Rostaing, Michel.

1974-01-01

A description is given of a process for improving the load factor of an electricity generating power station feeding a supply network in which all or part of the power not required by the network during off-peak hours is used for producing hydrogen which is then stored. The stored hydrogen is then burned and the heat generated is employed for superheating the steam generated by the nuclear reactor of the power plant. This combustion is carried out permanently. The hydrogen is produced by water electrolysis. The oxygen also produced in this manner is used as a comburent in the combustion of the hydrogen. The reactor is of the pressurized water type [fr

Regulating electricity demand peaks for home appliances using reversible fair scheduling

DEFF Research Database (Denmark)

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

2010-01-01

This paper describes a novel methodology for regulating electricity demand peaks for home appliances. To achieve this objective, we will make use of the reversible fair scheduling algorithm originally developed for telecommunication networks. The main concept behind this approach is the aggregati...

Analysis of the location for peak heating in CHP based combined district heating systems

International Nuclear Information System (INIS)

Wang, Haichao; Lahdelma, Risto; Wang, Xin; Jiao, Wenling; Zhu, Chuanzhi; Zou, Pinghua

2015-01-01

Combined heat and power (CHP) is the main technology for providing the base load of district heating in China. However, CHP is not efficient for providing the peak load; instead, a peak boiler with high efficiency could be used to compensate the peak load. This paper studies how the location of the peak boiler can affect the energy efficiency and economic performance of such CHP based combined district heating system. Firstly, the connection mode and the control strategy for different peak heating locations are analyzed. Then the effect of the peak boiler's location on the initial investment of the network and the cost for distributing heat is studied. The objective is to place the peak boiler in a location where the overall costs are the smallest. Following this rule, the results indicate that the peak boiler should be located at the CHP plant if that allows using cheaper ‘self-use electricity’ in CHP for distributing the heat. However, if the market electricity price is used everywhere, or if energy efficiency is more emphasized, the location of the peak boiler should be closer to the users with dense heat loads. - Highlights: • Location for peak heating in the CHP based combined DH system is studied. • Regulation or control strategies for combined DH are summarized. • The heat load duration curve for combined DH is demonstrated. • Network design for combined DH with peak boiler outside of the CHP is analyzed

Factor Analysis of the Aggregated Electric Vehicle Load Based on Data Mining

Directory of Open Access Journals (Sweden)

Yao Wang

2012-06-01

Full Text Available Electric vehicles (EVs and the related infrastructure are being developed rapidly. In order to evaluate the impact of factors on the aggregated EV load and to coordinate charging, a model is established to capture the relationship between the charging load and important factors based on data mining. The factors can be categorized as internal and external. The internal factors include the EV battery size, charging rate at different places, penetration of the charging infrastructure, and charging habits. The external factor is the time-of-use pricing (TOU policy. As a massive input data is necessary for data mining, an algorithm is implemented to generate a massive sample as input data which considers real-world travel patterns based on a historical travel dataset. With the input data, linear regression was used to build a linear model whose inputs were the internal factors. The impact of the internal factors on the EV load can be quantified by analyzing the sign, value, and temporal distribution of the model coefficients. The results showed that when no TOU policy is implemented, the rate of charging at home and range anxiety exerts the greatest influence on EV load. For the external factor, a support vector regression technique was used to build a relationship between the TOU policy and EV load. Then, an optimization model based on the relationship was proposed to devise a TOU policy that levels the load. The results suggest that implementing a TOU policy reduces the difference between the peak and valley loads remarkably.

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

ENERGY EFFICIENCY DETERMINATION OF LOADING-BACK SYSTEM OF ELECTRIC TRACTION MACHINES

Directory of Open Access Journals (Sweden)

A. M. Afanasov

2014-03-01

Full Text Available Purpose.Acceptance post-repair testsof electric traction machinesare conducted onloading-backstandsthat reducethe overall power costsfor the tests.Currentlya numberof possiblecircuit designs of loading-backsystems of electric machines are known, but there is nomethod of determiningtheir energy efficiency. This in turn makes difficult the choiceof rationaloptions. The purpose of the article is the development of the corresponding methodo-logy to make easier this process. Methodology. Expressions for determining theenergy efficiency ofa stand for testingof electric traction machineswere obtained using the generalizedscheme analysisof energy transformationsin the loading-backsystems of universal structure. Findings.Thetechnique wasoffered and the analytical expressions for determining the energy efficiency of loading-backsystemsof electric traction machines wereobtained. Energy efficiency coefficientofloading-backsystemisproposed to consider as the ratio of the total actionenergy of the mechanical and electromotive forces, providing anchors rotation and flowof currents in electric machines, which are being tested,to the total energy, consumed during the test from the external network. Originality. The concept was introduced and the analytical determination method of the energy efficiency of loading-backsystem in electric traction machines was offered. It differs by efficiency availability of power sources and converters, as well as energy efficiency factors of indirect methods of loss compensation. Practical value. The proposed technique of energy efficiency estimation of a loading-backsystemcan be used in solving the problem of rational options choice of schematics stands decisions for electric traction machines acceptance tests of main line and industrial transport.

MODELS OF ELECTRICAL POWER MANAGEMENT IN APPLICATION OF ENERGY CONSERVATION BASED ON THE ENVIRONMENT.

OpenAIRE

Janter; Herman Mawengkang; Usman Ba afai; Nasruddin M. N.

2018-01-01

Utilization of conventional electrical energy as the fulfillment of living necessities for lighting and electrical equipment is increasing, which can cause problems in the provision of electrical energy. Energy management is needed to solve the problem of energy utilization, especially the problem of energy demand during peak load. The greatest energy consumption during peak loads is for building lighting at night, including street lighting. The use of electrical energy for the national publi...

Assessing and Reducing Miscellaneous Electric Loads (MELs) in Lodging

Energy Technology Data Exchange (ETDEWEB)

Rauch, Emily M.

2011-09-01

Miscellaneous electric loads (MELs) are the loads outside of a building's core functions of heating, ventilating, air conditioning, lighting, and water heating. This report reviews methods to reduce MELs in lodging.

Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data

International Nuclear Information System (INIS)

Raesaenen, Teemu; Voukantsis, Dimitrios; Niska, Harri; Karatzas, Kostas; Kolehmainen, Mikko

2010-01-01

The recent technological developments monitoring the electricity use of small customers provides with a whole new view to develop electricity distribution systems, customer-specific services and to increase energy efficiency. The analysis of customer load profile and load estimation is an important and popular area of electricity distribution technology and management. In this paper, we present an efficient methodology, based on self-organizing maps (SOM) and clustering methods (K-means and hierarchical clustering), capable of handling large amounts of time-series data in the context of electricity load management research. The proposed methodology was applied on a dataset consisting of hourly measured electricity use data, for 3989 small customers located in Northern-Savo, Finland. Information for the hourly electricity use, for a large numbers of small customers, has been made available only recently. Therefore, this paper presents the first results of making use of these data. The individual customers were classified into user groups based on their electricity use profile. On this basis, new, data-based load curves were calculated for each of these user groups. The new user groups as well as the new-estimated load curves were compared with the existing ones, which were calculated by the electricity company, on the basis of a customer classification scheme and their annual demand for electricity. The index of agreement statistics were used to quantify the agreement between the estimated and observed electricity use. The results indicate that there is a clear improvement when using data-based estimations, while the new-estimated load curves can be utilized directly by existing electricity power systems for more accurate load estimates.

Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data

Energy Technology Data Exchange (ETDEWEB)

Raesaenen, Teemu; Niska, Harri; Kolehmainen, Mikko [Department of Environmental Sciences, University of Eastern Finland P.O. Box 1627, FIN-70211 Kuopio (Finland); Voukantsis, Dimitrios; Karatzas, Kostas [Department of Mechanical Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki (Greece)

2010-11-15

The recent technological developments monitoring the electricity use of small customers provides with a whole new view to develop electricity distribution systems, customer-specific services and to increase energy efficiency. The analysis of customer load profile and load estimation is an important and popular area of electricity distribution technology and management. In this paper, we present an efficient methodology, based on self-organizing maps (SOM) and clustering methods (K-means and hierarchical clustering), capable of handling large amounts of time-series data in the context of electricity load management research. The proposed methodology was applied on a dataset consisting of hourly measured electricity use data, for 3989 small customers located in Northern-Savo, Finland. Information for the hourly electricity use, for a large numbers of small customers, has been made available only recently. Therefore, this paper presents the first results of making use of these data. The individual customers were classified into user groups based on their electricity use profile. On this basis, new, data-based load curves were calculated for each of these user groups. The new user groups as well as the new-estimated load curves were compared with the existing ones, which were calculated by the electricity company, on the basis of a customer classification scheme and their annual demand for electricity. The index of agreement statistics were used to quantify the agreement between the estimated and observed electricity use. The results indicate that there is a clear improvement when using data-based estimations, while the new-estimated load curves can be utilized directly by existing electricity power systems for more accurate load estimates. (author)

Energy use, cost and CO2 emissions of electric cars

International Nuclear Information System (INIS)

van Vliet, Oscar; Brouwer, Anne Sjoerd; Kuramochi, Takeshi; van den Broek, Machteld; Faaij, Andre

2011-01-01

We examine efficiency, costs and greenhouse gas emissions of current and future electric cars (EV), including the impact from charging EV on electricity demand and infrastructure for generation and distribution. Uncoordinated charging would increase national peak load by 7% at 30% penetration rate of EV and household peak load by 54%, which may exceed the capacity of existing electricity distribution infrastructure. At 30% penetration of EV, off-peak charging would result in a 20% higher, more stable base load and no additional peak load at the national level and up to 7% higher peak load at the household level. Therefore, if off-peak charging is successfully introduced, electric driving need not require additional generation capacity, even in case of 100% switch to electric vehicles. GHG emissions from electric driving depend most on the fuel type (coal or natural gas) used in the generation of electricity for charging, and range between 0 g km -1 (using renewables) and 155 g km -1 (using electricity from an old coal-based plant). Based on the generation capacity projected for the Netherlands in 2015, electricity for EV charging would largely be generated using natural gas, emitting 35-77 g CO 2 eq km -1 . We find that total cost of ownership (TCO) of current EV are uncompetitive with regular cars and series hybrid cars by more than 800 EUR year -1 . TCO of future wheel motor PHEV may become competitive when batteries cost 400 EUR kWh -1 , even without tax incentives, as long as one battery pack can last for the lifespan of the vehicle. However, TCO of future battery powered cars is at least 25% higher than of series hybrid or regular cars. This cost gap remains unless cost of batteries drops to 150 EUR kWh -1 in the future. Variations in driving cost from charging patterns have negligible influence on TCO. GHG abatement costs using plug-in hybrid cars are currently 400-1400 EUR tonne -1 CO 2eq and may come down to -100 to 300 EUR tonne -1 . Abatement cost using

Hybridizing DEMD and Quantum PSO with SVR in Electric Load Forecasting

Directory of Open Access Journals (Sweden)

Li-Ling Peng

2016-03-01

Full Text Available Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR, this paper presents an SVR model hybridized with the differential empirical mode decomposition (DEMD method and quantum particle swarm optimization algorithm (QPSO for electric load forecasting. The DEMD method is employed to decompose the electric load to several detail parts associated with high frequencies (intrinsic mode function—IMF and an approximate part associated with low frequencies. Hybridized with quantum theory to enhance particle searching performance, the so-called QPSO is used to optimize the parameters of SVR. The electric load data of the New South Wales (Sydney, Australia market and the New York Independent System Operator (NYISO, New York, USA are used for comparing the forecasting performances of different forecasting models. The results illustrate the validity of the idea that the proposed model can simultaneously provide forecasting with good accuracy and interpretability.

End-User Tools Towards AN Efficient Electricity Consumption: the Dynamic Smart Grid

Science.gov (United States)

Kamel, Fouad; Kist, Alexander A.

2010-06-01

Growing uncontrolled electrical demands have caused increased supply requirements. This causes volatile electrical markets and has detrimental unsustainable environmental impacts. The market is presently characterized by regular daily peak demand conditions associated with high electricity prices. A demand-side response system can limit peak demands to an acceptable level. The proposed scheme is based on energy demand and price information which is available online. An online server is used to communicate the information of electricity suppliers to users, who are able to use the information to manage and control their own demand. A configurable, intelligent switching system is used to control local loads during peak events and mange the loads at other times as necessary. The aim is to shift end user loads towards periods where energy demand and therefore also prices are at the lowest. As a result, this will flatten the load profile and avoiding load peeks which are costly for suppliers. The scheme is an endeavour towards achieving a dynamic smart grid demand-side-response environment using information-based communication and computer-controlled switching. Diffusing the scheme shall lead to improved electrical supply services and controlled energy consumption and prices.

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

Will we be heating with green electricity tomorrow? The large potential of load-variable private customer tariffs; Heizen wir kuenftig mit Oekostrom? Das grosse Potenzial lastvariabler Privatkundentarife

Energy Technology Data Exchange (ETDEWEB)

Zierdt, Tobias; Lang, Dirk [RWE Effizienz GmbH, Dortmund (Germany)

2012-09-15

Momentous changes loom ahead for Germany's energy supply system as a result of the energy turnaround. One central question is how load peaks from renewable energy plants can be conveniently accommodated on the demand side. Two research projects are currently being carried out to examine the acceptance of time-variable and load-variable tariffs for private households. First results show that using green electricity for heat generation is significantly more attractive for both customers and energy suppliers than using it to cover day-to-day electricity demand at a later time.

Coupling mechanism of electric vehicle and grid under the background of smart grid

Science.gov (United States)

Dong, Mingyu; Li, Dezhi; Chen, Rongjun; Shu, Han; He, Yongxiu

2018-02-01

With the development of smart distribution technology in the future, electric vehicle users can not only charge reasonably based on peak-valley price, they can also discharge electricity into the power grid to realize their economic benefit when it’s necessary and thus promote peak load shifting. According to the characteristic that future electric vehicles can discharge, this paper studies the interaction effect between electric vehicles and the grid based on TOU (time of use) Price Strategy. In this paper, four scenarios are used to compare the change of grid load after implementing TOU Price Strategy. The results show that the wide access of electric vehicles can effectively reduce peak and valley difference.

Methods for Analyzing Electric Load Shape and its Variability

Energy Technology Data Exchange (ETDEWEB)

Price, Philip

2010-05-12

Current methods of summarizing and analyzing electric load shape are discussed briefly and compared. Simple rules of thumb for graphical display of load shapes are suggested. We propose a set of parameters that quantitatively describe the load shape in many buildings. Using the example of a linear regression model to predict load shape from time and temperature, we show how quantities such as the load?s sensitivity to outdoor temperature, and the effectiveness of demand response (DR), can be quantified. Examples are presented using real building data.

Variable electricity and steam from salt, helium and sodium cooled base-load reactors with gas turbines and heat storage - 15115

International Nuclear Information System (INIS)

Forsberg, C.; McDaniel, P.; Zohuri, B.

2015-01-01

Advances in utility natural-gas-fired air-Brayton combed cycle technology is creating the option of coupling salt-, helium-, and sodium-cooled nuclear reactors to Nuclear air-Brayton Combined Cycle (NACC) power systems. NACC may enable a zero-carbon electricity grid and improve nuclear power economics by enabling variable electricity output with base-load nuclear reactor operations. Variable electricity output enables selling more electricity at times of high prices that increases plant revenue. Peak power is achieved using stored heat or auxiliary fuel (natural gas, bio-fuels, hydrogen). A typical NACC cycle includes air compression, heating compressed air using nuclear heat and a heat exchanger, sending air through a turbine to produce electricity, reheating compressed air, sending air through a second turbine, and exhausting to a heat recovery steam generator (HRSG). In the HRSG, warm air produces steam that is used to produce added electricity. For peak power production, auxiliary heat (natural gas, stored heat) is added before the air enters the second turbine to raise air temperatures and power output. Like all combined cycle plants, water cooling requirements are dramatically reduced relative to other power cycles because much of the heat rejection is in the form of hot air. (authors)

Possible standards for relieving the load of operational thermal power plants to the minimum of the power system's electric loads

Energy Technology Data Exchange (ETDEWEB)

Gitman, M.I.; Smirnov, I.A.

1988-03-01

Describes how operational measures involving feeding the steam extraction load into existing off-peak hot-water boilers produce a reduction in electric power at night and on public holidays by an average of 35% without the need for reconstruction, special equipment or changing the heat circuit. This method enables coal-fired central heating systems to be relieved by 20-30% and gaz-mazout systems (the majority) by 50-70%. To compensate for the loss of manoeuverability in central heating units on holidays in the colder period of the year, it may be necessary to stop supplementary power units (KEhS units) several times a year. 5 refs.

Design of digital load torque observer in hybrid electric vehicle

Science.gov (United States)

Sun, Yukun; Zhang, Haoming; Wang, Yinghai

2008-12-01

In hybrid electric vehicle, engine begain to work only when motor was in high speed in order to decrease tail gas emission. However, permanent magnet motor was sensitive to its load, adding engine to the system always made its speed drop sharply, which caused engine to work in low efficiency again and produced much more environment pollution. Dynamic load torque model of permanent magnet synchronous motor is established on the basic of motor mechanical equation and permanent magnet synchronous motor vector control theory, Full- digital load torque observer and compensation control system is made based on TMS320F2407A. Experiment results prove load torque observer and compensation control system can detect and compensate torque disturbing effectively, which can solve load torque disturbing and decrease gas pollution of hybrid electric vehicle.

multilevel buck converter for automotive electrical load

African Journals Online (AJOL)

user

The electrical low voltage load requirement in the passenger vehicle is ... oxides emissions, and 82% of carbon monoxides (CO). [4]. ... government placed an order restricting the movement ... transient and steady-state characteristics of the.

A peaking-regulation-balance-based method for wind & PV power integrated accommodation

Science.gov (United States)

Zhang, Jinfang; Li, Nan; Liu, Jun

2018-02-01

Rapid development of China’s new energy in current and future should be focused on cooperation of wind and PV power. Based on the analysis of system peaking balance, combined with the statistical features of wind and PV power output characteristics, a method of comprehensive integrated accommodation analysis of wind and PV power is put forward. By the electric power balance during night peaking load period in typical day, wind power installed capacity is determined firstly; then PV power installed capacity could be figured out by midday peak load hours, which effectively solves the problem of uncertainty when traditional method hard determines the combination of the wind and solar power simultaneously. The simulation results have validated the effectiveness of the proposed method.

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.

Distributed energy storage systems on the basis of electric-vehicle fleets

Science.gov (United States)

Zhuk, A. Z.; Buzoverov, E. A.; Sheindlin, A. E.

2015-01-01

Several power technologies directed to solving the problem of covering nonuniform loads in power systems are developed at the Joint Institute of High Temperatures, Russian Academy of Sciences (JIHT RAS). One direction of investigations is the use of storage batteries of electric vehicles to compensate load peaks in the power system (V2G—vehicle-to-grid technology). The efficiency of energy storage systems based on electric vehicles with traditional energy-saving technologies is compared in the article by means of performing computations. The comparison is performed by the minimum-cost criterion for the peak energy supply to the system. Computations show that the distributed storage systems based on fleets of electric cars are efficient economically with their usage regime to 1 h/day. In contrast to traditional methods, the prime cost of regulation of the loads in the power system based on V2G technology is independent of the duration of the load compensation period (the duration of the consumption peak).

Regression models for predicting peak and continuous three-dimensional spinal loads during symmetric and asymmetric lifting tasks.

Science.gov (United States)

Fathallah, F A; Marras, W S; Parnianpour, M

1999-09-01

Most biomechanical assessments of spinal loading during industrial work have focused on estimating peak spinal compressive forces under static and sagittally symmetric conditions. The main objective of this study was to explore the potential of feasibly predicting three-dimensional (3D) spinal loading in industry from various combinations of trunk kinematics, kinetics, and subject-load characteristics. The study used spinal loading, predicted by a validated electromyography-assisted model, from 11 male participants who performed a series of symmetric and asymmetric lifts. Three classes of models were developed: (a) models using workplace, subject, and trunk motion parameters as independent variables (kinematic models); (b) models using workplace, subject, and measured moments variables (kinetic models); and (c) models incorporating workplace, subject, trunk motion, and measured moments variables (combined models). The results showed that peak 3D spinal loading during symmetric and asymmetric lifting were predicted equally well using all three types of regression models. Continuous 3D loading was predicted best using the combined models. When the use of such models is infeasible, the kinematic models can provide adequate predictions. Finally, lateral shear forces (peak and continuous) were consistently underestimated using all three types of models. The study demonstrated the feasibility of predicting 3D loads on the spine under specific symmetric and asymmetric lifting tasks without the need for collecting EMG information. However, further validation and development of the models should be conducted to assess and extend their applicability to lifting conditions other than those presented in this study. Actual or potential applications of this research include exposure assessment in epidemiological studies, ergonomic intervention, and laboratory task assessment.

Load management through agent based coordination of flexible electricity consumers

DEFF Research Database (Denmark)

Clausen, Anders; Demazeau, Yves; Jørgensen, Bo Nørregaard

2015-01-01

Demand Response (DR) offers a cost-effective and carbonfriendly way of performing load balancing. DR describes a change in the electricity consumption of flexible consumers in response to the supply situation. In DR, flexible consumers may perform their own load balancing through load management...

A novel graphene nanoribbon FET with an extra peak electric field (EFP-GNRFET) for enhancing the electrical performances

Energy Technology Data Exchange (ETDEWEB)

Akbari Eshkalak, Maedeh [Young Researchers and Elite Club, Lahijan Branch, Islamic Azad University, Lahijan (Iran, Islamic Republic of); Anvarifard, Mohammad K., E-mail: m.anvarifard@guilan.ac.ir [Department of Engineering Sciences, Faculty of Technology and Engineering, East of Guilan, University of Guilan, Rudsar-Vajargah (Iran, Islamic Republic of)

2017-04-25

This work has provided an efficient technique to improve the electrical performance for the Graphene Nanoribbon Field Effect Transistors (GNRFETs) successfully. The physical gate length is divided into two gates named as the original gate and the other one as the virtual gate. We have applied a voltage source between these gates to control the channel of the GNRFETs. This technique has created an extra peak electric field in the middle of the channel resulting in the redistribution of surface potential profile. The proposed structure named as EFP-GNRFET has been compared with a simple GNRFET and has shown many improvements in terms of the critical parameters such as short channel effects, leakage current, subthreshold swing, ON-state to OFF-state current ratio, transconductance, output conductance and voltage gain. The structures under the study in this paper benefits from the Non-Equilibrium Green Function (NEGF) approach for solving Schrödinger equation coupled with the two-dimensional (2D) Poisson equation in a self-consistent manner. - Highlights: • Proposal of a novel graphene nanoribbon FET. • Creation of an extra peak in electric field. • Modification of the channel potential with the help of virtual gate. • Considerable improvement on electrical performances.

Financial incentive approaches for reducing peak electricity demand, experience from pilot trials with a UK energy provider

International Nuclear Information System (INIS)

Bradley, Peter; Coke, Alexia; Leach, Matthew

2016-01-01

Whilst tariff-based approaches to load-shifting are common in the residential sector, incentive-based approaches are rare. This is so, even though providing customers incentives to shape their power consumption patterns has substantial potential. This paper presents findings from an exploratory UK pilot study that trials financial payments and detailed energy feedback to incentivise load-shifting of residential electricity consumption. An intervention study was implemented measuring actual energy use by individual households as well as conducting surveys and interviews. From the trials it was found that the approaches resulted in reductions in peak time energy use. Evidence from the study found that the incentives-based approaches were able to overcome some of the barriers to response experienced in Time-of-Use studies, though less good on others. Interestingly, the height of the barriers varied by the electricity-using practice and the incentivising approach applied. The height of the barriers also varied by participant. The study concludes by identifying that broad participation in demand response is likely to require a suite of incentivising approaches that appeal to different people, a key policy finding of interest to international agencies, government, public and private sector entities. - Highlights: • Novel study of financial incentive approaches for shifting residential energy. • First academic paper comprehensively identifying barriers to time of use tariffs. • First study reporting barriers to financial incentive approaches for demand response. • Incentive study design can be applied by government and energy companies.

High Electricity Demand in the Northeast U.S.: PJM Reliability Network and Peaking Unit Impacts on Air Quality.

Science.gov (United States)

Farkas, Caroline M; Moeller, Michael D; Felder, Frank A; Henderson, Barron H; Carlton, Annmarie G

2016-08-02

On high electricity demand days, when air quality is often poor, regional transmission organizations (RTOs), such as PJM Interconnection, ensure reliability of the grid by employing peak-use electric generating units (EGUs). These "peaking units" are exempt from some federal and state air quality rules. We identify RTO assignment and peaking unit classification for EGUs in the Eastern U.S. and estimate air quality for four emission scenarios with the Community Multiscale Air Quality (CMAQ) model during the July 2006 heat wave. Further, we population-weight ambient values as a surrogate for potential population exposure. Emissions from electricity reliability networks negatively impact air quality in their own region and in neighboring geographic areas. Monitored and controlled PJM peaking units are generally located in economically depressed areas and can contribute up to 87% of hourly maximum PM2.5 mass locally. Potential population exposure to peaking unit PM2.5 mass is highest in the model domain's most populated cities. Average daily temperature and national gross domestic product steer peaking unit heat input. Air quality planning that capitalizes on a priori knowledge of local electricity demand and economics may provide a more holistic approach to protect human health within the context of growing energy needs in a changing world.

Modeling spot markets for electricity and pricing electricity derivatives

Science.gov (United States)

Ning, Yumei

Spot prices for electricity have been very volatile with dramatic price spikes occurring in restructured market. The task of forecasting electricity prices and managing price risk presents a new challenge for market players. The objectives of this dissertation are: (1) to develop a stochastic model of price behavior and predict price spikes; (2) to examine the effect of weather forecasts on forecasted prices; (3) to price electricity options and value generation capacity. The volatile behavior of prices can be represented by a stochastic regime-switching model. In the model, the means of the high-price and low-price regimes and the probabilities of switching from one regime to the other are specified as functions of daily peak load. The probability of switching to the high-price regime is positively related to load, but is still not high enough at the highest loads to predict price spikes accurately. An application of this model shows how the structure of the Pennsylvania-New Jersey-Maryland market changed when market-based offers were allowed, resulting in higher price spikes. An ARIMA model including temperature, seasonal, and weekly effects is estimated to forecast daily peak load. Forecasts of load under different assumptions about weather patterns are used to predict changes of price behavior given the regime-switching model of prices. Results show that the range of temperature forecasts from a normal summer to an extremely warm summer cause relatively small increases in temperature (+1.5%) and load (+3.0%). In contrast, the increases in prices are large (+20%). The conclusion is that the seasonal outlook forecasts provided by NOAA are potentially valuable for predicting prices in electricity markets. The traditional option models, based on Geometric Brownian Motion are not appropriate for electricity prices. An option model using the regime-switching framework is developed to value a European call option. The model includes volatility risk and allows changes

Power system operation risk analysis considering charging load self-management of plug-in hybrid electric vehicles

International Nuclear Information System (INIS)

Liu, Zhe; Wang, Dan; Jia, Hongjie; Djilali, Ned

2014-01-01

Highlights: • The interactive mechanism between system and PHEVs is presented. • The charging load self-management without sacrificing user requirements is proposed. • The charging load self-management is coupled to system operation risk analysis. • The charging load self-management can reduce the extra risk brought by PHEVs. • The charging load self-management can shift charging power to the time with low risk. - Abstract: Many jurisdictions around the world are supporting the adoption of electric vehicles through incentives and the deployment of a charging infrastructure to reduce greenhouse gas emissions. Plug-in hybrid electric vehicles (PHEVs), with offer mature technology and stable performance, are expected to gain an increasingly larger share of the consumer market. The aggregated effect on power grid due to large-scale penetration of PHEVs needs to be analyzed. Nighttime-charging which typically characterizes PHEVs is helpful in filling the nocturnal load valley, but random charging of large PHEV fleets at night may result in new load peaks and valleys. Active response strategy is a potentially effective solution to mitigate the additional risks brought by the integration of PHEVs. This paper proposes a power system operation risk analysis framework in which charging load self-management is used to control system operation risk. We describe an interactive mechanism between the system and PHEVs in conjunction with a smart charging model is to simulate the time series power consumption of PHEVs. The charging load is managed with adjusting the state transition boundaries and without violating the users’ desired charging constraints. The load curtailment caused by voltage or power flow violation after outages is determined by controlling charging power. At the same time, the system risk is maintained under an acceptable level through charging load self-management. The proposed method is implemented using the Roy Billinton Test System (RBTS) and

Decree nr 2014-764 of the 3 July 2014 related to electricity load managements

International Nuclear Information System (INIS)

Valls, Manuel; Royal, Segolene; Montebourg, Arnaud

2014-01-01

This decree issued by the Ministry of ecology, sustainable development and energy aims at defining the methodology used to establish rules of valorisation of electricity load managements. It concerns energy suppliers and load management operators. A first chapter defines what electricity load management is and who a load management operator is. The next chapter addresses the methodology, the definition of the electricity load management volume, data used for the certification of load management volumes. The third chapter describes how to calculate the premium awarded to load management operators. The last chapters indicate how the ministries define the premium amount, and some aspects related to the communication of data to load management operators

A veracity preserving model for synthesizing scalable electricity load profiles

OpenAIRE

Huang, Yunyou; Zhan, Jianfeng; Luo, Chunjie; Wang, Lei; Wang, Nana; Zheng, Daoyi; Fan, Fanda; Ren, Rui

2018-01-01

Electricity users are the major players of the electric systems, and electricity consumption is growing at an extraordinary rate. The research on electricity consumption behaviors is becoming increasingly important to design and deployment of the electric systems. Unfortunately, electricity load profiles are difficult to acquire. Data synthesis is one of the best approaches to solving the lack of data, and the key is the model that preserves the real electricity consumption behaviors. In this...

Time-varying value of electric energy efficiency

Energy Technology Data Exchange (ETDEWEB)

Mims, Natalie A.; Eckman, Tom; Goldman, Charles

2017-06-30

Electric energy efficiency resources save energy and may reduce peak demand. Historically, quantification of energy efficiency benefits has largely focused on the economic value of energy savings during the first year and lifetime of the installed measures. Due in part to the lack of publicly available research on end-use load shapes (i.e., the hourly or seasonal timing of electricity savings) and energy savings shapes, consideration of the impact of energy efficiency on peak demand reduction (i.e., capacity savings) has been more limited. End-use load research and the hourly valuation of efficiency savings are used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity and demand response planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service. This study reviews existing literature on the time-varying value of energy efficiency savings, provides examples in four geographically diverse locations of how consideration of the time-varying value of efficiency savings impacts the calculation of power system benefits, and identifies future research needs to enhance the consideration of the time-varying value of energy efficiency in cost-effectiveness screening analysis. Findings from this study include: -The time-varying value of individual energy efficiency measures varies across the locations studied because of the physical and operational characteristics of the individual utility system (e.g., summer or winter peaking, load factor, reserve margin) as well as the time periods during which savings from measures occur. -Across the four locations studied, some of the largest capacity benefits from energy efficiency are derived from the deferral of transmission and distribution system infrastructure upgrades. However, the deferred cost of such upgrades also exhibited the greatest range

Battery Peak Power Shaving Strategy to Prolong Battery Life for Electric Buses

NARCIS (Netherlands)

Pham, T.H.; Rosea, B.; Wilkins, S.

2016-01-01

This paper presents a battery peak power shaving strategy for battery electric buses. The developed strategy restricts the battery charge/discharge power when the propulsion power demand is high to avoid high deterioration of the battery capacity during operation. Without reducing the propulsion

Exergy and Exergoeconomic Model of a Ground-Based CAES Plant for Peak-Load Energy Production

Directory of Open Access Journals (Sweden)

Giampaolo Manfrida

2013-02-01

Full Text Available Compressed Air Energy Storage is recognized as a promising technology for applying energy storage to grids which are more and more challenged by the increasing contribution of renewable such as solar or wind energy. The paper proposes a medium-size ground-based CAES system, based on pressurized vessels and on a multiple-stage arrangement of compression and expansion machinery; the system includes recovery of heat from the intercoolers, and its storage as sensible heat in two separate (hot/cold water reservoirs, and regenerative reheat of the expansions. The CAES plant parameters were adapted to the requirements of existing equipment (compressors, expanders and heat exchangers. A complete exergy analysis of the plant was performed. Most component cost data were procured from the market, asking specific quotations to the industrial providers. It is thus possible to calculate the final cost of the electricity unit (kWh produced under peak-load mode, and to identify the relative contribution between the two relevant groups of capital and component inefficiencies costs.

A Universal Educational and Research Stand to Simulate Electrical Drive Loading

Directory of Open Access Journals (Sweden)

V. S. Grishin

2016-01-01

Full Text Available Universal educational and research stand was developed for analyzing an electrical drive’s behavior with different load disturbance effects. Major components of the stand are two electrical drives with rigidly coupled shafts. As a result, first electrical drive (loader has a capability to imitate effects of different loading types to another one (trial drive.Control software for the stand is developed. It allows us to combine a variety of loading types and change parameters of current loading such as joint moment, damping, additional inertia, and external torque. Also there is a capability to imitate effects of elasticity and backlash of mechanical transmissions. The paper considers the main challenge of creating the given system, i.e. discretization with a variable step. Some methods to decrease its negative effects on system stability are suggested.The given system allows to change loading parameters more rapidly and in a wider range as compared to a system with real mechanical outfit.These stands are currently used for laboratory classes within the course “Electrical robotic drives” at SM7 department in Bauman Moscow State Technical University. Also the system of interdepended stands for semi-realistic simulation of manipulation systems is under development.

77 FR 70484 - Preoperational Testing of Onsite Electric Power Systems To Verify Proper Load Group Assignments...

Science.gov (United States)

2012-11-26

...-1294, ``Preoperational Testing of On-Site Electric Power Systems to Verify Proper Load Group... entitled ``Preoperational Testing of On- Site Electric Power Systems to Verify Proper Load Group... Electric Power Systems to Verify Proper Load Group Assignments, Electrical Separation, and Redundancy...

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

Science.gov (United States)

Berardino, Jonathan

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

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

OpenAIRE

Jinchao Li; Lin Chen; Yuwei Xiang; Jinying Li; Dong Peng

2018-01-01

Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have pos...

Simultaneous day-ahead forecasting of electricity price and load in smart grids

International Nuclear Information System (INIS)

Shayeghi, H.; Ghasemi, A.; Moradzadeh, M.; Nooshyar, M.

2015-01-01

Highlights: • This paper presents a novel MIMO-based support vector machine for forecasting. • Considered uncertainties for better simulation for filtering in input data. • Used LSSVM technique for learning. • Proposed a new modification for standard artificial bee colony algorithm to optimize LSSVM engine. - Abstract: In smart grids, customers are promoted to change their energy consumption patterns by electricity prices. In fact, in this environment, the electricity price and load consumption are highly corrected such that the market participants will have complex model in their decisions to maximize their profit. Although the available forecasting mythologies perform well in electricity market by way of little or no load and price interdependencies, but cannot capture load and price dynamics if they exist. To overcome this shortage, a Multi-Input Multi-Output (MIMO) model is presented which can consider the correlation between electricity price and load. The proposed model consists of three components known as a Wavelet Packet Transform (WPT) to make valuable subsets, Generalized Mutual Information (GMI) to select best input candidate and Least Squares Support Vector Machine (LSSVM) based on MIMO model, called LSSVM-MIMO, to make simultaneous load and price forecasts. Moreover, the LSSVM-MIMO parameters are optimized by a novel Quasi-Oppositional Artificial Bee Colony (QOABC) algorithm. Some forecasting indices based on error factor are considered to evaluate the forecasting accuracy. Simulations carried out on New York Independent System Operator, New South Wales (NSW) and PJM electricity markets data, and showing that the proposed hybrid algorithm has good potential for simultaneous forecasting of electricity price and load

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.

A New Two-Stage Approach to Short Term Electrical Load Forecasting

Directory of Open Access Journals (Sweden)

Dragan Tasić

2013-04-01

Full Text Available In the deregulated energy market, the accuracy of load forecasting has a significant effect on the planning and operational decision making of utility companies. Electric load is a random non-stationary process influenced by a number of factors which make it difficult to model. To achieve better forecasting accuracy, a wide variety of models have been proposed. These models are based on different mathematical methods and offer different features. This paper presents a new two-stage approach for short-term electrical load forecasting based on least-squares support vector machines. With the aim of improving forecasting accuracy, one more feature was added to the model feature set, the next day average load demand. As this feature is unknown for one day ahead, in the first stage, forecasting of the next day average load demand is done and then used in the model in the second stage for next day hourly load forecasting. The effectiveness of the presented model is shown on the real data of the ISO New England electricity market. The obtained results confirm the validity advantage of the proposed approach.

Analysis of thermal characteristics of electrical wiring for load groups in cattle barns.

Science.gov (United States)

Kim, Doo Hyun; Yoo, Sang-Ok; Kim, Sung Chul; Hwang, Dong Kyu

2015-01-01

The purpose of the current study is to analyze the thermal characteristics of electrical wirings depending on the number of operating load by connecting four types of electrical wirings that are selected by surveying the conditions for the electric fans, automatic waterers and halogen warm lamps that were installed in cattle barns in different years. The conditions of 64 cattle barns were surveyed and an experimental test was conducted at a cattle barn. The condition-survey covered inappropriate design, construction and misuse of electrical facility, including electrical wiring mostly used, and the mode of load current was evaluated. The survey showed that the mode of load current increased as the installation year of the fans, waterers and halogen lamps became older. Accordingly, the cattle barn manager needed to increase the capacity of the circuit breaker, which promoted the degradation of insulation of the electrical wires' sheath and increased possibility for electrical fires in the long-run. The test showed that the saturation temperature of the wire insulated sheath increased depending on the installation year of the load groups, in case of VCTFK and VFF electric wires, therefore, requiring their careful usage in the cattle barns.

Automatic determination of pressurized water reactor core loading patterns that maximize beginning-of-cycle reactivity within power-peaking and burnup constraints

International Nuclear Information System (INIS)

Hobson, G.H.; Turinsky, P.J.

1986-01-01

Computational capability has been developed to automatically determine a good estimate of the core loading pattern, which minimizes fuel cycle costs for a pressurized water reactor (PWR). Equating fuel cycle cost minimization with core reactivity maximization, the objective is to determine the loading pattern that maximizes core reactivity while satisfying power peaking, discharge burnup, and other constraints. The method utilizes a two-dimensional, coarse-mesh, finite difference scheme to evaluate core reactivity and fluxes for an initial reference loading pattern. First-order perturbation theory is applied to determine the effects of assembly shuffling on reactivity, power distribution, end-of-cycle burnup. Monte Carlo integer programming is then used to determine a near-optimal loading pattern within a range of loading patterns near the reference pattern. The process then repeats with the new loading pattern as the reference loading pattern and terminates when no better loading pattern can be determined. The process was applied with both reactivity maximization and radial power-peaking minimization as objectives. Results on a typical large PWR indicate that the cost of obtaining an 8% improvement in radial power-peaking margin is ≅2% in fuel cycle costs, for the reload core loaded without burnable poisons that was studied

Study on Impact of Electric Vehicles Charging Models on Power Load

Science.gov (United States)

Cheng, Chen; Hui-mei, Yuan

2017-05-01

With the rapid increase in the number of electric vehicles, which will lead the power load on grid increased and have an adversely affect. This paper gives a detailed analysis of the following factors, such as scale of the electric cars, charging mode, initial charging time, initial state of charge, charging power and other factors. Monte Carlo simulation method is used to compare the two charging modes, which are conventional charging and fast charging, and MATLAB is used to model and simulate the electric vehicle charging load. The results show that compared with the conventional charging mode, fast charging mode can meet the requirements of fast charging, but also bring great load to the distribution network which will affect the reliability of power grid.

Analysis of the need for intermediate and peaking technologies in the year 2000

Energy Technology Data Exchange (ETDEWEB)

Barrager, S.M.; Campbell, G.L.

1980-04-01

This analysis was conducted to assess the impact of load management on the future need for intermediate- and peak-generating technologies (IPTs) such as combustion turbines, pumped storage, and cycling coal plants. There will be a reduced need for IPTs if load-management activities such as time-of-use pricing, together with customer-owned energy-storage devices, hot-water-heater controls, and interruptible service, can economically remove most of the variation from electric-power demands. Therefore, the analysis assesses the need for IPTs in an uncertain future, which will probably include load management and time-differentiated electricity prices. Section 2 provides a condensed description of the models used in the analysis. (Details and data sets are contained in the appendixes.) Results of sensitivities on growth rates, model parameters, and appliance saturations are discussed in Section 3, which also contains the analysis of the potential impacts of customer energy storage, appliance control, and time-of-use pricing. The future need for intermediate and peaking technologies is analyzed in Section 4.

Temperature and seasonality influences on Spanish electricity load

International Nuclear Information System (INIS)

Pardo, Angel; Meneu, Vicente; Valor, Enric

2002-01-01

Deregulation of the Spanish electricity market in 1998 and the possible listing of electricity or weather derivative contracts have encouraged the study of the relationship between electricity demand and weather in Spain. In this paper, a transfer function intervention model is developed for forecasting daily electricity load from cooling and heating degree-days. The influence of weather and seasonality is proved, and is significant even when the autoregressive effects and the dynamic specification of the temperature are taken into account. The estimated general model shows a high predictive power. The results and information presented in this paper could be of interest for current users and potential traders in the deregulated Spanish electricity market

Temperature and seasonality influences on Spanish electricity load

Energy Technology Data Exchange (ETDEWEB)

Pardo, Angel; Meneu, Vicente [Departamento de Economia Financiera y Matematica, Facultad de Economia, Avda. de los Naranjos s/n., Edificio Departamental Oriental, Universidad de Valencia, 46022 Valencia (Spain); Valor, Enric [Departamento de Termodinamica, Universidad de Valencia, 46100 Burjassot, Valencia (Spain)

2002-01-01

Deregulation of the Spanish electricity market in 1998 and the possible listing of electricity or weather derivative contracts have encouraged the study of the relationship between electricity demand and weather in Spain. In this paper, a transfer function intervention model is developed for forecasting daily electricity load from cooling and heating degree-days. The influence of weather and seasonality is proved, and is significant even when the autoregressive effects and the dynamic specification of the temperature are taken into account. The estimated general model shows a high predictive power. The results and information presented in this paper could be of interest for current users and potential traders in the deregulated Spanish electricity market.

Establishment of windows-based load management system for electricity cost savings in competitive electricity markets

International Nuclear Information System (INIS)

Chung, K.H.; Kim, B.H.; Hur, D.

2007-01-01

For electricity markets to function in a truly competitive and efficient manner, it is not enough to focus solely on improving the efficiencies of power supply. To recognize price-responsive load as a reliability resource, the customer must be provided with price signals and an instrument to respond to these signals, preferably automatically. This paper attempts to develop the Windows-based load management system in competitive electricity markets, allowing the user to monitor the current energy consumption or billing information, to analyze the historical data, and to implement the consumption strategy for cost savings with nine possible scenarios adopted. Finally, this modeling framework will serve as a template containing the basic concepts that any load management system should address. (author)

The Effect of Lifting Speed on Cumulative and Peak Biomechanical Loading for Symmetric Lifting Tasks

Directory of Open Access Journals (Sweden)

Kasey O. Greenland

2013-06-01

Conclusion: Based on peak values, BCF is highest for fast speeds, but the BCF cumulative loading is highest for slow speeds, with the largest difference between fast and slow lifts. This may imply that a slow lifting speed is at least as hazardous as a fast lifting speed. It is important to consider the duration of lift when determining risks for back and shoulder injuries due to lifting and that peak values alone are likely not sufficient.

Generation Mix Study Focusing on Nuclear Power by Practical Peak Forecast

International Nuclear Information System (INIS)

Shin, Jung Ho; Roh, Myung Sub

2013-01-01

The excessive underestimation can lead to a range of problem; expansion of LNG plant requiring short construction period, the following increase of electricity price, low reserve margin and inefficient configuration of power source. With regard to nuclear power, the share of the stable and economic base load plant, nuclear power, can reduce under the optimum level. Amongst varied factors which contribute to the underestimate, immoderate target for demand side management (DSM) including double deduction of the constraint amount by DSM from peak demand forecast is one of the causes. The hypothesis in this study is that the better optimum generation mix including the adequate share of nuclear power can be obtained under the condition of the peak demand forecast without deduction of DSM target because this forecast is closer to the actual peak demand. In this study, the hypothesis is verified with comparison between peak demand forecast before (or after) DSM target application and the actual peak demand in the 3 rd through 5 th BPE from 2006 to 2010. Furthermore, this research compares and analyzes several generation mix in 2027 focusing on the nuclear power by a few conditions using the WASP-IV program on the basis of the 6 th BPE in 2013. According to the comparative analysis on the peak demand forecast and actual peak demand from 2006 to 2010, the peak demand forecasts without the deduction of the DSM target is closer to the actual peak demand than the peak demand forecasts considering the DSM target in the 3 th , 4 th , 5 th entirely. In addition, the generation mix until 2027 is examined by the WASP-IV. As a result of the program run, when considering the peak demand forecast without DSM reflection, since the base load plants including nuclear power take up adequate proportion, stable and economic supply of electricity can be achieved. On the contrary, in case of planning based on the peak demand forecast with DSM reflected and then compensating the shortage by

Reducing electricity consumption peaks with parametrised dynamic pricing strategies given maximal unit prices

NARCIS (Netherlands)

N.F. Höning (Nicolas); J.A. La Poutré (Han); F. Lopes; Z. Vale; J. Sousa; H. Coelho

2013-01-01

htmlabstractDemand response is a crucial mechanism for flattening of peak loads. For its implementation, we not only require consumers who react to price changes, but also intelligent strategies to select prices. We propose a parametrised meta-strategy for dynamic pricing and identify suitable

Using adaptive network based fuzzy inference system to forecast regional electricity loads

International Nuclear Information System (INIS)

Ying, L.-C.; Pan, M.-C.

2008-01-01

Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads

Using adaptive network based fuzzy inference system to forecast regional electricity loads

Energy Technology Data Exchange (ETDEWEB)

Ying, Li-Chih [Department of Marketing Management, Central Taiwan University of Science and Technology, 11, Pu-tzu Lane, Peitun, Taichung City 406 (China); Pan, Mei-Chiu [Graduate Institute of Management Sciences, Nanhua University, 32, Chung Keng Li, Dalin, Chiayi 622 (China)

2008-02-15

Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads. (author)

Short-Term City Electric Load Forecasting with Considering Temperature Effects: An Improved ARIMAX Model

Directory of Open Access Journals (Sweden)

Herui Cui

2015-01-01

Full Text Available Short-term electric load is significantly affected by weather, especially the temperature effects in summer. External factors can result in mutation structures in load data. Under the influence of the external temperature factors, city electric load cannot be easily forecasted as usual. This research analyzes the relationship between electricity load and daily temperature in city. An improved ARIMAX model is proposed in this paper to deal with the mutation data structures. It is found that information amount of the improved ARIMAX model is smaller than that of the classic method and its relative error is less than AR, ARMA and Sigmoid-Function ANN models. The forecasting results are more accurately fitted. This improved model is highly valuable when dealing with mutation data structure in the field of load forecasting. And it is also an effective technique in forecasting electric load with temperature effects.

Machine learning based switching model for electricity load forecasting

Energy Technology Data Exchange (ETDEWEB)

Fan, Shu; Lee, Wei-Jen [Energy Systems Research Center, The University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States); Chen, Luonan [Department of Electronics, Information and Communication Engineering, Osaka Sangyo University, 3-1-1 Nakagaito, Daito, Osaka 574-0013 (Japan)

2008-06-15

In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma. (author)

Machine learning based switching model for electricity load forecasting

Energy Technology Data Exchange (ETDEWEB)

Fan Shu [Energy Systems Research Center, University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States); Chen Luonan [Department of Electronics, Information and Communication Engineering, Osaka Sangyo University, 3-1-1 Nakagaito, Daito, Osaka 574-0013 (Japan); Lee, Weijen [Energy Systems Research Center, University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States)], E-mail: wlee@uta.edu

2008-06-15

In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma.

Machine learning based switching model for electricity load forecasting

International Nuclear Information System (INIS)

Fan Shu; Chen Luonan; Lee, Weijen

2008-01-01

In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma

Energy efficiency indicators for high electric-load buildings

Energy Technology Data Exchange (ETDEWEB)

Aebischer, Bernard; Balmer, Markus A.; Kinney, Satkartar; Le Strat, Pascale; Shibata, Yoshiaki; Varone, Frederic

2003-06-01

Energy per unit of floor area is not an adequate indicator for energy efficiency in high electric-load buildings. For two activities, restaurants and computer centres, alternative indicators for energy efficiency are discussed.

Towards Cost and Comfort Based Hybrid Optimization for Residential Load Scheduling in a Smart Grid

Directory of Open Access Journals (Sweden)

Nadeem Javaid

2017-10-01

Full Text Available In a smart grid, several optimization techniques have been developed to schedule load in the residential area. Most of these techniques aim at minimizing the energy consumption cost and the comfort of electricity consumer. Conversely, maintaining a balance between two conflicting objectives: energy consumption cost and user comfort is still a challenging task. Therefore, in this paper, we aim to minimize the electricity cost and user discomfort while taking into account the peak energy consumption. In this regard, we implement and analyse the performance of a traditional dynamic programming (DP technique and two heuristic optimization techniques: genetic algorithm (GA and binary particle swarm optimization (BPSO for residential load management. Based on these techniques, we propose a hybrid scheme named GAPSO for residential load scheduling, so as to optimize the desired objective function. In order to alleviate the complexity of the problem, the multi dimensional knapsack is used to ensure that the load of electricity consumer will not escalate during peak hours. The proposed model is evaluated based on two pricing schemes: day-ahead and critical peak pricing for single and multiple days. Furthermore, feasible regions are calculated and analysed to develop a relationship between power consumption, electricity cost, and user discomfort. The simulation results are compared with GA, BPSO and DP, and validate that the proposed hybrid scheme reflects substantial savings in electricity bills with minimum user discomfort. Moreover, results also show a phenomenal reduction in peak power consumption.

A novel method for decomposing electricity feeder load into elementary profiles from customer information

International Nuclear Information System (INIS)

Gerossier, Alexis; Barbier, Thibaut; Girard, Robin

2017-01-01

Highlights: •Use of aggregated electricity load profiles and customer description at feeder level. •Statistical recovery of elementary load profiles with customer categorization. •Generation of load demand profiles for unknown feeders and new local areas. •Relevancy of the different categorizations. -- Abstract: To plan a distribution grid involves making a long-term forecast of sub-hourly demand, which requires modeling the demand and its dynamics with aggregated measurement data. Distribution system operators (DSOs) have been recording electricity sub-hourly demand delivered by their medium-voltage feeders (around 1000—10,000 customers) for several years. Demand profiles differ widely among the various considered feeders. This is partly due to the varying mix of customer categories from one feeder to another. To overcome this issue, elementary demand profiles are often associated with customer categories and then combined according to a mix description. This paper presents a novel method to estimate elementary profiles that only requires several feeder demand curves and a description of customers. The method relies on a statistical blind source model and a new estimation procedure based on the augmented Lagrangian method. The use of feeders to estimate elementary profiles means that measurements are fully representative and continuously updated. We illustrate the proposed method through a case study comprising around 1000 feeder demand curves operated by the main French DSO Enedis. We propose an application o that uses the obtained profiles to evaluate the contribution of any set of new customers to a feeder peak load. We show that profiles enable a simulation of new unmeasured areas with errors of around 20%. We also show how our method can be used to evaluate the relevancy of different customer categorizations.

Wind integration in self-regulating electric load distributions

Energy Technology Data Exchange (ETDEWEB)

Parkinson, Simon; Wang, Dan; Crawford, Curran; Djilali, Ned [University of Victoria, Department of Mechanical Engineering, Institute for Integrated Energy Systems, STN CSC, Victoria, BC (Canada)

2012-12-15

The purpose of this paper is to introduce and assess an alternative method of mitigating short-term wind energy production variability through the control of electric loads. In particular, co-located populations of electric vehicles and heat pumps are targeted to provide regulation-based ancillary services, as the inherent operational flexibility and autonomous device-level control strategy associated with these load-types provide an ideal platform to mitigate enhanced variability within the power system. An optimal control strategy capable of simultaneously balancing these grid-side objectives with those typically expected on the demand-side is introduced. End-use digital communication hardware is used to track and control population dynamics through the development of online aggregate load models equivalent to conventional dispatchable generation. The viability of the proposed 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 online regulation reserve capacity in systems considering a high penetration of wind energy, thereby allowing conventional generation to operate more efficiently. (orig.)

Analyzing and Forecasting Electrical Load Consumption in Healthcare Buildings

Directory of Open Access Journals (Sweden)

Rodolfo Gordillo-Orquera

2018-02-01

Full Text Available Healthcare buildings exhibit a different electrical load predictability depending on their size and nature. Large hospitals behave similarly to small cities, whereas primary care centers are expected to have different consumption dynamics. In this work, we jointly analyze the electrical load predictability of a large hospital and that of its associated primary care center. An unsupervised load forecasting scheme using combined classic methods of principal component analysis (PCA and autoregressive (AR modeling, as well as a supervised scheme using orthonormal partial least squares (OPLS, are proposed. Both methods reduce the dimensionality of the data to create an efficient and low-complexity data representation and eliminate noise subspaces. Because the former method tended to underestimate the load and the latter tended to overestimate it in the large hospital, we also propose a convex combination of both to further reduce the forecasting error. The analysis of data from 7 years in the hospital and 3 years in the primary care center shows that the proposed low-complexity dynamic models are flexible enough to predict both types of consumption at practical accuracy levels.

Grips for testing of electrical characteristics of a specimen under a mechanical load

Science.gov (United States)

Briggs, Timothy; Loyola, Bryan

2018-04-24

Various technologies to facilitate coupled electrical and mechanical measurement of conductive materials are disclosed herein. A gripping device simultaneously holds a specimen in place and causes contact to be made between the specimen and a plurality of electrodes connected to an electrical measuring device. An electrical characteristic of the specimen is then measured while a mechanical load is applied to the specimen, and a relationship between the mechanical load and changes in the electrical characteristic can be identified.

Mixed price and load forecasting of electricity markets by a new iterative prediction method

International Nuclear Information System (INIS)

Amjady, Nima; Daraeepour, Ali

2009-01-01

Load and price forecasting are the two key issues for the participants of current electricity markets. However, load and price of electricity markets have complex characteristics such as nonlinearity, non-stationarity and multiple seasonality, to name a few (usually, more volatility is seen in the behavior of electricity price signal). For these reasons, much research has been devoted to load and price forecast, especially in the recent years. However, previous research works in the area separately predict load and price signals. In this paper, a mixed model for load and price forecasting is presented, which can consider interactions of these two forecast processes. The mixed model is based on an iterative neural network based prediction technique. It is shown that the proposed model can present lower forecast errors for both load and price compared with the previous separate frameworks. Another advantage of the mixed model is that all required forecast features (from load or price) are predicted within the model without assuming known values for these features. So, the proposed model can better be adapted to real conditions of an electricity market. The forecast accuracy of the proposed mixed method is evaluated by means of real data from the New York and Spanish electricity markets. The method is also compared with some of the most recent load and price forecast techniques. (author)

Electricity portfolio management : optimal peak/off-peak allocations

NARCIS (Netherlands)

Huisman, R.; Mahieu, R.J.; Schlichter, F.

2009-01-01

Electricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to optimally

Electricity Portfolio Management: Optimal Peak / Off-Peak Allocations

NARCIS (Netherlands)

R. Huisman (Ronald); R.J. Mahieu (Ronald); F. Schlichter (Felix)

2007-01-01

textabstractElectricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to

Managing time-substitutable electricity usage using dynamic controls

Science.gov (United States)

Ghosh, Soumyadip; Hosking, Jonathan R.; Natarajan, Ramesh; Subramaniam, Shivaram; Zhang, Xiaoxuan

2017-02-21

A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

Managing time-substitutable electricity usage using dynamic controls

Science.gov (United States)

Ghosh, Soumyadip; Hosking, Jonathan R.; Natarajan, Ramesh; Subramaniam, Shivaram; Zhang, Xiaoxuan

2017-02-07

A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

The dispatch and load duration curve of the interconnected electrical system, in the hypothetical context of the 450ppm scenario of the Iea

International Nuclear Information System (INIS)

Villanueva M, C.

2017-09-01

The concept of the annual load duration curve of the national interconnected system is presented, which by means of a quadrature procedure becomes a 3-block diagram: one for the base load that occurs at 8,760 hours of the year; another for intermediate load, above the minimum that occurs in a variable number of hours of the year, and another for the peak demand that only happens a few hours of the year. The data of the table of capacity and generation of electric power in 2014, according to Annex A of the Mexico Energy Outlook document of the International Energy Agency (Iea), are converted into a block diagram adjusted to the annual curve of load duration of that year. The procedure is repeated with the capacity and electric power generation data projected by the Iea at 2030 and 2040, according to the 450ppm scenario, which is considered necessary to stabilize the concentration of CO 2 in the atmosphere at 450 parts per million and ensure that the increase in the global temperature of the planet does not exceed 2 degrees Celsius, compared to pre-industrial levels. Then, the same capacity and generation data projected by the Iea by 2040 are tabulated by technology type, grouped now within the base, intermediate and peak blocks of the annual load duration curve for that year, and ordered from according to its plant factor, indicative of its availability to be dispatched. The above, in order to estimate the aggregate result of the annual dispatch that could be made by CENACE, if the projections of electric power generation to the year 2040 foreseen in the ambitious 450ppm scenario were given. Finally, an exercise is carried out to estimate, at 2015 prices, the unit costs of technologies generation in the year 2040, expressed in US D (2015)/ MWh and broken down into fixed and variable reference costs. (Author)

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.

Hood River Conservation Project load analysis

Energy Technology Data Exchange (ETDEWEB)

Stovall, T.K.

1987-11-01

As a part of the Hood River Conservation Project (HRCP), 314 homes were monitored to measure electrical energy use. The total electrical load, space heating load, water heating load (in about 200 homes), wood-stove heat output (in about 100 homes), and indoor temperature were monitored. Data were collected for one full year before and one full year after these homes were retrofit with conservation measures. Local weather information was also collected on a 15-min basis. This data base was used to evaluate the load savings attributable to HRCP. Two methods of weather normalization were used and showed close agreement. The weather-normalized diversified residential load savings on the Pacific Power and Light system and Hood River area peak days were >0.5 kW/household. The average spring, summer, and fall savings were much smaller, <0.1 kW/household. The load factor for the diversified residential load decreased following the conservation retrofit actions. 11 refs., 40 figs., 13 tabs.

Bulk Electric Load Cost Calculation Methods: Iraqi Network Comparative Study

Directory of Open Access Journals (Sweden)

Qais M. Alias

2016-09-01

Full Text Available It is vital in any industry to regain the spent capitals plus running costs and a margin of profits for the industry to flourish. The electricity industry is an everyday life touching industry which follows the same finance-economic strategy. Cost allocation is a major issue in all sectors of the electric industry, viz, generation, transmission and distribution. Generation and distribution service costing’s well documented in the literature, while the transmission share is still of need for research. In this work, the cost of supplying a bulk electric load connected to the EHV system is calculated. A sample basic lump-average method is used to provide a rough costing guide. Also, two transmission pricing methods are employed, namely, the postage-stamp and the load-flow based MW-distance methods to calculate transmission share in the total cost of each individual bulk load. The three costing methods results are then analyzed and compared for the 400kV Iraqi power grid considered for a case study.

Loading technique for dynamic response studies of geological materials

International Nuclear Information System (INIS)

Butler, R.I.; Forrestal, M.J.

1979-04-01

A loading technique to study the dynamic response of tuff was explored. Loading is provided by electrically exploding etched copper mesh patterns with current from a capacitor discharge. Pressure pulses with peak pressures up to 1.25 kbar and 0.10 to 0.20 ms durations were measured with a pressure bar. The upper value of peak pressure was limited by the strength of the experimental apparatus, and higher pressure generation is possible with a redesign of test hardware. 6 figures, 2 tables

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

Dynamic intelligent cleaning model of dirty electric load data

International Nuclear Information System (INIS)

Zhang Xiaoxing; Sun Caixin

2008-01-01

There are a number of dirty data in the load database derived from the supervisory control and data acquisition (SCADA) system. Thus, the data must be carefully and reasonably adjusted before it is used for electric load forecasting or power system analysis. This paper proposes a dynamic and intelligent data cleaning model based on data mining theory. Firstly, on the basis of fuzzy soft clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means soft clustering. Then, the proposed dynamic algorithm can automatically find the new clustering center (the characteristic curve of the data) with the updated sample data; At last, it is composed with radial basis function neural network (RBFNN), and then, an intelligent adjusting model is proposed to identify the dirty data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results of electrical load data analysis in Chongqing

Peak power reduction and energy efficiency improvement with the superconducting flywheel energy storage in electric railway system

Energy Technology Data Exchange (ETDEWEB)

Lee, Hansang, E-mail: hslee80@kiu.ac.kr [School of Railway and Electrical Engineering, Kyungil University, Hayang-eup, Gyeongsan-si, Gyeongsangbuk-do 712-701 (Korea, Republic of); Jung, Seungmin [School of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-712 (Korea, Republic of); Cho, Yoonsung [Department of Electric and Energy Engineering, Catholic University of Daegu, Hayang-eup, Gyeongsan-si, Gyeongsangbuk-do 712-702 (Korea, Republic of); Yoon, Donghee [Department of New and Renewable Energy, Kyungil University, Hayang-eup, Gyeongsangbuk-do 712-701 (Korea, Republic of); Jang, Gilsoo, E-mail: gjang@korea.ac.kr [School of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-712 (Korea, Republic of)

2013-11-15

Highlights: •It is important to develop power and energy management system to save operating cost. •An 100 kWh of SFES is effective to decrease peak power and energy consumption. •Operation cost saving can be achieved using superconducting flywheel energy storage. -- Abstract: This paper proposes an application of the 100 kWh superconducting flywheel energy storage systems to reduce the peak power of the electric railway system. The electric railway systems have high-power characteristics and large amount of regenerative energy during vehicles’ braking. The high-power characteristic makes operating cost high as the system should guarantee the secure capacity of electrical equipment and the low utilization rate of regenerative energy limits the significant energy efficiency improvement. In this paper, it had been proved that the peak power reduction and energy efficiency improvement can be achieved by using 100 kWh superconducting flywheel energy storage systems with the optimally controlled charging or discharging operations. Also, economic benefits had been assessed.

Peak power reduction and energy efficiency improvement with the superconducting flywheel energy storage in electric railway system

International Nuclear Information System (INIS)

Lee, Hansang; Jung, Seungmin; Cho, Yoonsung; Yoon, Donghee; Jang, Gilsoo

2013-01-01

Highlights: •It is important to develop power and energy management system to save operating cost. •An 100 kWh of SFES is effective to decrease peak power and energy consumption. •Operation cost saving can be achieved using superconducting flywheel energy storage. -- Abstract: This paper proposes an application of the 100 kWh superconducting flywheel energy storage systems to reduce the peak power of the electric railway system. The electric railway systems have high-power characteristics and large amount of regenerative energy during vehicles’ braking. The high-power characteristic makes operating cost high as the system should guarantee the secure capacity of electrical equipment and the low utilization rate of regenerative energy limits the significant energy efficiency improvement. In this paper, it had been proved that the peak power reduction and energy efficiency improvement can be achieved by using 100 kWh superconducting flywheel energy storage systems with the optimally controlled charging or discharging operations. Also, economic benefits had been assessed

Electrical properties of conducting loads produced from polyaniline deposited in natural fibers and nanoclays

International Nuclear Information System (INIS)

Kosenhoski, Dirlaine; Saade, Wesley; Pinto, Camila P.; Becker, Daniela; Dalmolin, Carla; Pachekoski, Wagner M.

2015-01-01

Conducting polymers are known for their excellent magnetic and electrical properties, but they still are an expensive and limited choice to their use as a conducting load for composite materials. An alternative to optimize the electrical conductivity of polymeric composites is the deposition of a conducting polymer on materials already used as loads, as the deposition on natural fibers or the encapsulation of polymeric chains in the voids of host structures. In this work, bananastem fiber and montmorillonite nanoclay (MMT) were used as host structures for polyaniline synthesis in order to produce conducting loads. Samples were characterized by FT-IR and X-Rays Diffraction in order to confirm the formation of polyanilina / bananastem fibers or polyanilina / nanoclays loads. Influence on the electrical properties of the composites were evaluated by Electrochemical Impedance Spectroscopy (EIS), showing the maintenance of the electric conductivity of polyaniline and its potential use as a load for the formation of conducting composites. (author)

Generation Mix Study Focusing on Nuclear Power by Practical Peak Forecast

Energy Technology Data Exchange (ETDEWEB)

Shin, Jung Ho; Roh, Myung Sub [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2013-10-15

The excessive underestimation can lead to a range of problem; expansion of LNG plant requiring short construction period, the following increase of electricity price, low reserve margin and inefficient configuration of power source. With regard to nuclear power, the share of the stable and economic base load plant, nuclear power, can reduce under the optimum level. Amongst varied factors which contribute to the underestimate, immoderate target for demand side management (DSM) including double deduction of the constraint amount by DSM from peak demand forecast is one of the causes. The hypothesis in this study is that the better optimum generation mix including the adequate share of nuclear power can be obtained under the condition of the peak demand forecast without deduction of DSM target because this forecast is closer to the actual peak demand. In this study, the hypothesis is verified with comparison between peak demand forecast before (or after) DSM target application and the actual peak demand in the 3{sup rd} through 5{sup th} BPE from 2006 to 2010. Furthermore, this research compares and analyzes several generation mix in 2027 focusing on the nuclear power by a few conditions using the WASP-IV program on the basis of the 6{sup th} BPE in 2013. According to the comparative analysis on the peak demand forecast and actual peak demand from 2006 to 2010, the peak demand forecasts without the deduction of the DSM target is closer to the actual peak demand than the peak demand forecasts considering the DSM target in the 3{sup th}, 4{sup th}, 5{sup th} entirely. In addition, the generation mix until 2027 is examined by the WASP-IV. As a result of the program run, when considering the peak demand forecast without DSM reflection, since the base load plants including nuclear power take up adequate proportion, stable and economic supply of electricity can be achieved. On the contrary, in case of planning based on the peak demand forecast with DSM reflected and then

Minimization of Load Variance in Power Grids—Investigation on Optimal Vehicle-to-Grid Scheduling

DEFF Research Database (Denmark)

Tan, Kang Miao; Ramachandaramurthy, Vigna K.; Yong, Jia Ying

2017-01-01

-to-grid optimization algorithm is implemented and tested in MATLAB software (R2013a, MathWorks, Natick, MA, USA). The performance of the optimization algorithm depends heavily on the setting of the target load, power grid load and capability of the grid-connected electric vehicles. Hence, the performance...... of the proposed algorithm under various target load and electric vehicles’ state of charge selections were analysed. The effectiveness of the vehicle-to-grid scheduling to implement the appropriate peak load shaving and load levelling services for the grid load variance minimization is verified under various...

Peak power reduction and energy efficiency improvement with the superconducting flywheel energy storage in electric railway system

Science.gov (United States)

Lee, Hansang; Jung, Seungmin; Cho, Yoonsung; Yoon, Donghee; Jang, Gilsoo

2013-11-01

This paper proposes an application of the 100 kWh superconducting flywheel energy storage systems to reduce the peak power of the electric railway system. The electric railway systems have high-power characteristics and large amount of regenerative energy during vehicles’ braking. The high-power characteristic makes operating cost high as the system should guarantee the secure capacity of electrical equipment and the low utilization rate of regenerative energy limits the significant energy efficiency improvement. In this paper, it had been proved that the peak power reduction and energy efficiency improvement can be achieved by using 100 kWh superconducting flywheel energy storage systems with the optimally controlled charging or discharging operations. Also, economic benefits had been assessed.

Using of residential load curves obtained for determination of the load diversity, and loading of distribution transformers; Utilizacao de curvas de carga de consumidores industriais medidas para determinacao de diversidade de carga, e carregamento de transformadores de distribuicao

Energy Technology Data Exchange (ETDEWEB)

Ferrari, Eduardo Luiz; Jardini, Jose Antonio

1996-07-01

This work presents some applications of the residential loads, obtained from measurements conducted by the electric power utilities in the state of Sao Paulo , Brazil. During the first application, curve of coincidence of load peaks occurrence, as function of the number of consumers simultaneously connected to a specific residential distribution transformer. This curve provides a information on the number of consumers presenting coincident load peaks coincident relative to the total numbers of consumers connected to the distribution transformer. Those curves allow to obtain the diversity curves. The second application focused the calculation of the distribution transformer life reduction.

Impacts of Electric Vehicle Loads on Power Distribution Systems

DEFF Research Database (Denmark)

Pillai, Jayakrishnan Radhakrishna; Bak-Jensen, Birgitte

2010-01-01

operation. This paper investigates the effects on the key power distribution system parameters like voltages, line drops, system losses etc. by integrating electric vehicles in the range of 0-50% of the cars with different charging capacities. The dump as well as smart charging modes of electric vehicles......Electric vehicles (EVs) are the most promising alternative to replace a significant amount of gasoline vehicles to provide cleaner, CO2 free and climate friendly transportation. On integrating more electric vehicles, the electric utilities must analyse the related impacts on the electricity system...... is applied in this analysis. A typical Danish primary power distribution system is used as a test case for the studies. From the simulation results, not more than 10% of electric vehicles could be integrated in the test system for the dump charging mode. About 40% of electric vehicle loads could...

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

A model for hedging load and price risk in the Texas electricity market

International Nuclear Information System (INIS)

Coulon, Michael; Powell, Warren B.; Sircar, Ronnie

2013-01-01

Energy companies with commitments to meet customers' daily electricity demands face the problem of hedging load and price risk. We propose a joint model for load and price dynamics, which is motivated by the goal of facilitating optimal hedging decisions, while also intuitively capturing the key features of the electricity market. Driven by three stochastic factors including the load process, our power price model allows for the calculation of closed-form pricing formulas for forwards and some options, products often used for hedging purposes. Making use of these results, we illustrate in a simple example the hedging benefit of these instruments, while also evaluating the performance of the model when fitted to the Texas electricity market. - Highlights: • We present a structural model for electricity spot prices in the ERCOT market. • Relationships between power price and factors such as load and gas price are studied. • Seasonal patterns and load-dependent spikes are shown to be well captured. • Closed-form results for prices of forwards, options and spread options are derived. • We demonstrate the effectiveness of hedging power demand with forwards and options

Analysis of the need for intermediate and peaking technologies in the year 2000. Final report

Energy Technology Data Exchange (ETDEWEB)

Barrager, S.M.; Campbell, G.L.

1980-04-01

This analysis was conducted to assess the impact of load management on the future need for intermediate- and peak-generating technologies (IPTs) such as combustion turbines, pumped storage, and cycling coal plants. There would be a reduced need for IPTs if load-management activities such as time-of-use pricing, together with customer-owned energy-storage devices, hot-water-heater controls, and interruptible service can economically remove most of the variation from electric power demands. The objective of this analysis is to assess the need for IPTs in an uncertain future, which will probably include load management and time-differentiated electricity prices. The analysis is exploratory in nature and broad in scope. It does not attempt to predict the future or to model precisely the technical characteristics or economic desirability of load management. Rather, its purpose is to provide research and development planners with some basic insights into the order of magnitude of possible hourly demand shifts on a regional basis and to determine the impact of load management on daily and seasonal variations in electricity demand.

An analytics of electricity consumption characteristics based on principal component analysis

Science.gov (United States)

Feng, Junshu

2018-02-01

Abstract . More detailed analysis of the electricity consumption characteristics can make demand side management (DSM) much more targeted. In this paper, an analytics of electricity consumption characteristics based on principal component analysis (PCA) is given, which the PCA method can be used in to extract the main typical characteristics of electricity consumers. Then, electricity consumption characteristics matrix is designed, which can make a comparison of different typical electricity consumption characteristics between different types of consumers, such as industrial consumers, commercial consumers and residents. In our case study, the electricity consumption has been mainly divided into four characteristics: extreme peak using, peak using, peak-shifting using and others. Moreover, it has been found that industrial consumers shift their peak load often, meanwhile commercial and residential consumers have more peak-time consumption. The conclusions can provide decision support of DSM for the government and power providers.

Parametric analysis of parameters for electrical-load forecasting using artificial neural networks

Science.gov (United States)

Gerber, William J.; Gonzalez, Avelino J.; Georgiopoulos, Michael

1997-04-01

Accurate total system electrical load forecasting is a necessary part of resource management for power generation companies. The better the hourly load forecast, the more closely the power generation assets of the company can be configured to minimize the cost. Automating this process is a profitable goal and neural networks should provide an excellent means of doing the automation. However, prior to developing such a system, the optimal set of input parameters must be determined. The approach of this research was to determine what those inputs should be through a parametric study of potentially good inputs. Input parameters tested were ambient temperature, total electrical load, the day of the week, humidity, dew point temperature, daylight savings time, length of daylight, season, forecast light index and forecast wind velocity. For testing, a limited number of temperatures and total electrical loads were used as a basic reference input parameter set. Most parameters showed some forecasting improvement when added individually to the basic parameter set. Significantly, major improvements were exhibited with the day of the week, dew point temperatures, additional temperatures and loads, forecast light index and forecast wind velocity.

Daily Peak Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm

Directory of Open Access Journals (Sweden)

Shuyu Dai

2018-01-01

Full Text Available Daily peak load forecasting is an important part of power load forecasting. The accuracy of its prediction has great influence on the formulation of power generation plan, power grid dispatching, power grid operation and power supply reliability of power system. Therefore, it is of great significance to construct a suitable model to realize the accurate prediction of the daily peak load. A novel daily peak load forecasting model, CEEMDAN-MGWO-SVM (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, is proposed in this paper. Firstly, the model uses the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN algorithm to decompose the daily peak load sequence into multiple sub sequences. Then, the model of modified grey wolf optimization and support vector machine (MGWO-SVM is adopted to forecast the sub sequences. Finally, the forecasting sequence is reconstructed and the forecasting result is obtained. Using CEEMDAN can realize noise reduction for non-stationary daily peak load sequence, which makes the daily peak load sequence more regular. The model adopts the grey wolf optimization algorithm improved by introducing the population dynamic evolution operator and the nonlinear convergence factor to enhance the global search ability and avoid falling into the local optimum, which can better optimize the parameters of the SVM algorithm for improving the forecasting accuracy of daily peak load. In this paper, three cases are used to test the forecasting accuracy of the CEEMDAN-MGWO-SVM model. We choose the models EEMD-MGWO-SVM (Ensemble Empirical Mode Decomposition and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, MGWO-SVM (Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, GWO-SVM (Support Vector Machine Optimized by Grey Wolf Optimization Algorithm, SVM (Support Vector

Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market

Energy Technology Data Exchange (ETDEWEB)

Mandal, Paras; Senjyu, Tomonobu [Department of Electrical and Electronics, University of the Ryukyus, 1 Senbaru, Nagakami Nishihara, Okinawa 903-0213 (Japan); Funabashi, Toshihisa [Meidensha Corporation, Tokyo 103-8515 (Japan)

2006-09-15

In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy. (author)

Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market

International Nuclear Information System (INIS)

Mandal, Paras; Senjyu, Tomonobu; Funabashi, Toshihisa

2006-01-01

In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6 h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy

Efficient Power Scheduling in Smart Homes Using Hybrid Grey Wolf Differential Evolution Optimization Technique with Real Time and Critical Peak Pricing Schemes

Directory of Open Access Journals (Sweden)

Muqaddas Naz

2018-02-01

Full Text Available With the emergence of automated environments, energy demand by consumers is increasing rapidly. More than 80% of total electricity is being consumed in the residential sector. This brings a challenging task of maintaining the balance between demand and generation of electric power. In order to meet such challenges, a traditional grid is renovated by integrating two-way communication between the consumer and generation unit. To reduce electricity cost and peak load demand, demand side management (DSM is modeled as an optimization problem, and the solution is obtained by applying meta-heuristic techniques with different pricing schemes. In this paper, an optimization technique, the hybrid gray wolf differential evolution (HGWDE, is proposed by merging enhanced differential evolution (EDE and gray wolf optimization (GWO scheme using real-time pricing (RTP and critical peak pricing (CPP. Load shifting is performed from on-peak hours to off-peak hours depending on the electricity cost defined by the utility. However, there is a trade-off between user comfort and cost. To validate the performance of the proposed algorithm, simulations have been carried out in MATLAB. Results illustrate that using RTP, the peak to average ratio (PAR is reduced to 53.02%, 29.02% and 26.55%, while the electricity bill is reduced to 12.81%, 12.012% and 12.95%, respectively, for the 15-, 30- and 60-min operational time interval (OTI. On the other hand, the PAR and electricity bill are reduced to 47.27%, 22.91%, 22% and 13.04%, 12%, 11.11% using the CPP tariff.

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.

A new approach for modeling the peak utility impacts from a proposed CUAC standard

Energy Technology Data Exchange (ETDEWEB)

LaCommare, Kristina Hamachi; Gumerman, Etan; Marnay, Chris; Chan, Peter; Coughlin, Katie

2004-08-01

This report describes a new Berkeley Lab approach for modeling the likely peak electricity load reductions from proposed energy efficiency programs in the National Energy Modeling System (NEMS). This method is presented in the context of the commercial unitary air conditioning (CUAC) energy efficiency standards. A previous report investigating the residential central air conditioning (RCAC) load shapes in NEMS revealed that the peak reduction results were lower than expected. This effect was believed to be due in part to the presence of the squelch, a program algorithm designed to ensure changes in the system load over time are consistent with the input historic trend. The squelch applies a system load-scaling factor that scales any differences between the end-use bottom-up and system loads to maintain consistency with historic trends. To obtain more accurate peak reduction estimates, a new approach for modeling the impact of peaky end uses in NEMS-BT has been developed. The new approach decrements the system load directly, reducing the impact of the squelch on the final results. This report also discusses a number of additional factors, in particular non-coincidence between end-use loads and system loads as represented within NEMS, and their impacts on the peak reductions calculated by NEMS. Using Berkeley Lab's new double-decrement approach reduces the conservation load factor (CLF) on an input load decrement from 25% down to 19% for a SEER 13 CUAC trial standard level, as seen in NEMS-BT output. About 4 GW more in peak capacity reduction results from this new approach as compared to Berkeley Lab's traditional end-use decrement approach, which relied solely on lowering end use energy consumption. The new method has been fully implemented and tested in the Annual Energy Outlook 2003 (AEO2003) version of NEMS and will routinely be applied to future versions. This capability is now available for use in future end-use efficiency or other policy analysis

Recruiting, Training, Retaining, and Promoting the Workforce of the Future at Comanche Peak Steam Electric Station

International Nuclear Information System (INIS)

Sunseri, M.

1999-01-01

TXU Electric expects to encounter a relatively high turnover in the workforce in the coming years. To prepare for this challenge and to maintain a high level of performance, a number of approaches are being implemented. These approaches involve recruiting experienced personnel, recruiting and developing local nonexperienced personnel, and developing current employees. Through these approaches, TXU Electric expects to maintain a high-quality workforce for the continued support of Comanche Peak Steam Electric Station

Coarse-grained simulation of a real-time process control network under peak load

International Nuclear Information System (INIS)

George, A.D.; Clapp, N.E. Jr.

1992-01-01

This paper presents a simulation study on the real-time process control network proposed for the new ANS reactor system at ORNL. A background discussion is provided on networks, modeling, and simulation, followed by an overview of the ANS process control network, its three peak-load models, and the results of a series of coarse-grained simulation studies carried out on these models using implementations of 802.3, 802.4, and 802.5 standard local area networks

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.

Blending of electricity pricing with time flavour - an analysis of net system benefit to an electric utility in India

International Nuclear Information System (INIS)

Bhardwaj, J.L.

1992-01-01

Demand-side Management is a powerful strategy for modifying electric energy consumption patterns for the mutual benefit of consumers, the supplier and the economy as a whole Time-of-use pricing of electricity suggest a policy where the price is time-differentiated so as to reduce contribution to the system-peak which determines the capacity and investments of a power-system. This paper describes a case-study of net system benefit to an electric utility in India by offering time-of-use tariff to high voltage (HV) industrial consumers. The study shows that there is a potential of shifting about 19% H.V. Industrial loads from peak to off-peak hours thereby benefitting both, the consumers and the utility. 1 fig., 2 tabs

Summary of Market Opportunities for Electric Vehicles and Dispatchable Load in Electrolyzers

Energy Technology Data Exchange (ETDEWEB)

Denholm, Paul [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Eichman, Joshua [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Markel, Tony [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ma, Ookie [U.S Department of Energy, Washington, DC (United States)

2015-05-19

Electric vehicles (EVs) and electrolyzers are potentially significant sources of new electric loads. Both are flexible in that the amount of electricity consumed can be varied in response to a variety of factors including the cost of electricity. Because both EVs and electrolyzers can control the timing of electricity purchases, they can minimize energy costs by timing the purchases of energy to periods of lowest costs.

Climate Control Load Reduction Strategies for Electric Drive Vehicles in Warm Weather

Energy Technology Data Exchange (ETDEWEB)

Jeffers, M. A.; Chaney, L.; Rugh, J. P.

2015-04-30

Passenger compartment climate control is one of the largest auxiliary loads on a vehicle. Like conventional vehicles, electric vehicles (EVs) require climate control to maintain occupant comfort and safety, but cabin heating and air conditioning have a negative impact on driving range for all electric vehicles. Range reduction caused by climate control and other factors is a barrier to widespread adoption of EVs. Reducing the thermal loads on the climate control system will extend driving range, thereby reducing consumer range anxiety and increasing the market penetration of EVs. Researchers at the National Renewable Energy Laboratory have investigated strategies for vehicle climate control load reduction, with special attention toward EVs. Outdoor vehicle thermal testing was conducted on two 2012 Ford Focus Electric vehicles to evaluate thermal management strategies for warm weather, including solar load reduction and cabin pre-ventilation. An advanced thermal test manikin was used to assess a zonal approach to climate control. In addition, vehicle thermal analysis was used to support testing by exploring thermal load reduction strategies, evaluating occupant thermal comfort, and calculating EV range impacts. Through stationary cooling tests and vehicle simulations, a zonal cooling configuration demonstrated range improvement of 6%-15%, depending on the drive cycle. A combined cooling configuration that incorporated thermal load reduction and zonal cooling strategies showed up to 33% improvement in EV range.

Long-term forecasting of hourly electricity load: Identification of consumption profiles and segmentation of customers

DEFF Research Database (Denmark)

Møller Andersen, Frits; Larsen, Helge V.; Boomsma, Trine Krogh

2013-01-01

, to model and forecast long-term changes in the aggregated electricity load profile, we identify profiles for different categories of customers and link these to projections of the aggregated annual consumption by categories of customers. Long-term projection of the aggregated load is important for future......Data for aggregated hourly electricity demand shows systematic variations over the day, week, and seasons, and forecasting of aggregated hourly electricity load has been the subject of many studies. With hourly metering of individual customers, data for individual consumption profiles is available....... Using this data and analysing the case of Denmark, we show that consumption profiles for categories of customers are equally systematic but very different for distinct categories, that is, distinct categories of customers contribute differently to the aggregated electricity load profile. Therefore...

Measuring competitiveness of the EPEX spot market for electricity

International Nuclear Information System (INIS)

Graf, Christoph; Wozabal, David

2013-01-01

The issue of market concentration in electricity markets and resulting possible anti-competitive behavior of producers is a much discussed topic in many countries. We investigate the day-ahead market for electricity at the EPEX, the largest central European market for electricity. To analyze whether generating companies use their market power to influence prices, we use a conjectural variations approach as well as a direct approach to construct marginal costs of electricity production. Given the available data, we cannot reject the hypothesis that there was no systematic abuse of market power by the suppliers of electricity on the EPEX day-ahead spot market for the years 2007–2010. These results are essentially robust when restricting the sample to high load hours, which are generally considered to be the most prone to market manipulation. -- Highlights: •We investigate the efficiency of the German spot market for electricity. •We employ a conjectural variations approach and a fundamental market model. •Peak load hours and base load hours are analyzed separately. •We find that the market was competitive from 2007 to 2010 for both base and peak hours. •Policies to promote market transparency in Germany can be regarded as successful

Modeling for the management of peak loads on a radiology image management network

International Nuclear Information System (INIS)

Dwyer, S.J.; Cox, G.G.; Templeton, A.W.; Cook, L.T.; Anderson, W.H.; Hensley, K.S.

1987-01-01

The design of a radiology image management network for a radiology department can now be assisted by a queueing model. The queueing model requires that the designers specify the following parameters: the number of tasks to be accomplished (acquisition of image data, transmission of data, archiving of data, displaying and manipulation of data, and generation of hard copies); the average times to complete each task; the patient scheduled arrival times; and the number/type of computer nodes interfaced to the network (acquisition nodes, interactive diagnostic display stations, archiving nodes, hard copy nodes, and gateways to hospital systems). The outcomes from the queuering model include mean throughput data rates and identified bottlenecks, and peak throughput data rates and identified bottlenecks. This exhibit presents the queueing model and illustrates its use in managing peak loads on an image management network

Electricity demand load forecasting of the Hellenic power system using an ARMA model

Energy Technology Data Exchange (ETDEWEB)

Pappas, S.Sp. [ASPETE - School of Pedagogical and Technological Education Department of Electrical Engineering Educators N. Heraklion, 141 21 Athens (Greece); Ekonomou, L.; Chatzarakis, G.E.; Skafidas, P.D. [ASPETE-School of Pedagogical and Technological Education, Department of Electrical Engineering Educators, N. Heraklion, 141 21 Athens (Greece); Karampelas, P. [Hellenic American University, IT Department, 12 Kaplanon Str., 106 80 Athens (Greece); Karamousantas, D.C. [Technological Educational Institute of Kalamata, Antikalamos, 24 100 Kalamata (Greece); Katsikas, S.K. [University of Piraeus, Department of Technology Education and Digital Systems, 150 Androutsou St., 18 532 Piraeus (Greece)

2010-03-15

Effective modeling and forecasting requires the efficient use of the information contained in the available data so that essential data properties can be extracted and projected into the future. As far as electricity demand load forecasting is concerned time series analysis has the advantage of being statistically adaptive to data characteristics compared to econometric methods which quite often are subject to errors and uncertainties in model specification and knowledge of causal variables. This paper presents a new method for electricity demand load forecasting using the multi-model partitioning theory and compares its performance with three other well established time series analysis techniques namely Corrected Akaike Information Criterion (AICC), Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The suitability of the proposed method is illustrated through an application to actual electricity demand load of the Hellenic power system, proving the reliability and the effectiveness of the method and making clear its usefulness in the studies that concern electricity consumption and electricity prices forecasts. (author)

Electric power generating plant having direct-coupled steam and compressed-air cycles

Science.gov (United States)

Drost, M.K.

1981-01-07

An electric power generating plant is provided with a Compressed Air Energy Storage (CAES) system which is directly coupled to the steam cycle of the generating plant. The CAES system is charged by the steam boiler during off peak hours, and drives a separate generator during peak load hours. The steam boiler load is thereby levelized throughout an operating day.

Electric power generating plant having direct coupled steam and compressed air cycles

Science.gov (United States)

Drost, Monte K.

1982-01-01

An electric power generating plant is provided with a Compressed Air Energy Storage (CAES) system which is directly coupled to the steam cycle of the generating plant. The CAES system is charged by the steam boiler during off peak hours, and drives a separate generator during peak load hours. The steam boiler load is thereby levelized throughout an operating day.

A fresh look at weather impact on peak electricity demand and energy use of buildings using 30-year actual weather data

International Nuclear Information System (INIS)

Hong, Tianzhen; Chang, Wen-Kuei; Lin, Hung-Wen

2013-01-01

Highlights: • Weather has a significant impact on both the peak electricity demand and energy use. • Weather impact varies with building type, building efficiency level, and location. • Simulated results using TMY3 weather data can under or over estimate those of AMY. • It is crucial to assess performance of buildings using long-term actual weather data. • Findings enable building stakeholders to make better decisions on weather impact. - Abstract: Buildings consume more than one third of the world’s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980–2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: (1) annual weather variation has a greater impact on the peak electricity demand than it does

Chaotic particle swarm optimization algorithm in a support vector regression electric load forecasting model

International Nuclear Information System (INIS)

Hong, W.-C.

2009-01-01

Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. Recently, support vector regression (SVR), with nonlinear mapping capabilities of forecasting, has been successfully employed to solve nonlinear regression and time series problems. However, it is still lack of systematic approaches to determine appropriate parameter combination for a SVR model. This investigation elucidates the feasibility of applying chaotic particle swarm optimization (CPSO) algorithm to choose the suitable parameter combination for a SVR model. The empirical results reveal that the proposed model outperforms the other two models applying other algorithms, genetic algorithm (GA) and simulated annealing algorithm (SA). Finally, it also provides the theoretical exploration of the electric load forecasting support system (ELFSS)

Research on Double Price Regulations and Peak Shaving Reserve Mechanism in Coal-Electricity Supply Chain

Directory of Open Access Journals (Sweden)

Hongjun Peng

2013-01-01

Full Text Available The game models were used to study the mechanism of coal-electricity price conflict under conditions of double price regulations of coal and electricity. Based on this, the peak shaving reserve mechanism was designed to probe into the countermeasures against the coal-electricity price conflicts. The study revealed that in the boom seasons of coal demand, the initiatives of the coal enterprises to supply thermal coal and the electricity enterprises to order thermal coal are reduced under conditions of double price regulations. However, under the circumstances of coal price marketization, in the boom seasons of coal demand the thermal coal price may go up obviously, the initiatives of the coal enterprises to supply thermal coal are increased, and meanwhile the initiatives of the power enterprises to order thermal coal are decreased dramatically. The transportation capacity constraint of coal supply leads to the evident decrease of the initiatives of coal enterprises for the thermal coal supply. The mechanism of peak shaving reserve of thermal coal may not only reduce the price of coal market but also increase the enthusiasm of the power enterprises to order more thermal coal and the initiatives of the coal enterprises to supply more thermal coal.

Increasing economic benefits by load-shifting of electrical heat pumps

OpenAIRE

Laveyne, Joannes; Zwaenepoel, Brecht; Van Eetvelde, Greet; Vandevelde, Lieven

2014-01-01

Electrical heating is still widely used in the process industry. While the use of immersion heaters for the production of hot water or steam is declining, the adoption rate of electrical heat pumps is increasing rapidly. Heat pumps show great flexibility and potential for energy savings, e.g. through low temperature waste heat recuperation. In combination with thermal storage they also allow for load shifting. Because their main power source is electricity, which up to now cannot be stored ef...

Automatic determination of pressurized water reactor core loading patterns which maximize end-of-cycle reactivity within power peaking and burnup constraints

International Nuclear Information System (INIS)

Hobson, G.H.

1985-01-01

An automated procedure for determining the optimal core loading pattern for a pressurized water reactor which maximizes end-of-cycle k/sub eff/ while satisfying constraints on power peaking and discharge burnup has been developed. The optimization algorithm combines a two energy group, two-dimensional coarse-mesh finite difference diffusion theory neutronics model to simulate core conditions, a perturbation theory approach to determine reactivity, flux, power and burnup changes as a function of assembly shuffling, and Monte Carlo integer programming to select the optimal loading pattern solution. The core examined was a typical Cycle 2 reload with no burnable poisons. Results indicate that the core loading pattern that maximizes end-of-cycle k/sub eff/ results in a 5.4% decrease in fuel cycle costs compared with the core loading pattern that minimizes the maximum relative radial power peak

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

Energy use, cost and CO2 emissions of electric cars

NARCIS (Netherlands)

van Vliet, O.; Brouwer, A.S.; Kuramochi, T.; van den Broek, M.A.; Faaij, A.P.C.

2010-01-01

We examine efficiency, costs and greenhouse gas emissions of current and future electric cars (EV), including the impact from charging EV on electricity demand and infrastructure for generation and distribution. Uncoordinated charging would increase national peak load by 7% at 30% penetration rate

Economic impact analysis of load forecasting

International Nuclear Information System (INIS)

Ranaweera, D.K.; Karady, G.G.; Farmer, R.G.

1997-01-01

Short term load forecasting is an essential function in electric power system operations and planning. Forecasts are needed for a variety of utility activities such as generation scheduling, scheduling of fuel purchases, maintenance scheduling and security analysis. Depending on power system characteristics, significant forecasting errors can lead to either excessively conservative scheduling or very marginal scheduling. Either can induce heavy economic penalties. This paper examines the economic impact of inaccurate load forecasts. Monte Carlo simulations were used to study the effect of different load forecasting accuracy. Investigations into the effect of improving the daily peak load forecasts, effect of different seasons of the year and effect of utilization factors are presented

Forecasted electric power demands for the Baltimore Gas and Electric Company. Volume 1 and Volume 2. Documentation manual

International Nuclear Information System (INIS)

Estomin, S.L.; Beach, J.E.; Goldsmith, J.V.

1991-05-01

The two-volume report presents the results of an econometric forecast of peak load and electric power demand for the Baltimore Gas and Electric Company (BG ampersand E) through the year 2009. Separate energy sales models were estimated for residential sales in Baltimore City, residential sales in the BG ampersand E service area excluding Baltimore City, commercial sales, industrial sales, streetlighting sales, and Company use plus losses. Econometric equations were also estimated for electric space heating and air conditioning saturation in Baltimore City and in the remainder of the BG ampersand E service territory. In addition to the energy sales models and the electric space conditioning saturation models, econometric models of summer and winter peak demand on the BG ampersand E system were estimated

Mutual Information-Based Inputs Selection for Electric Load Time Series Forecasting

Directory of Open Access Journals (Sweden)

Nenad Floranović

2013-02-01

Full Text Available Providing accurate load forecast to electric utility corporations is essential in order to reduce their operational costs and increase profits. Hence, training set selection is an important preprocessing step which has to be considered in practice in order to increase the accuracy of load forecasts. The usage of mutual information (MI has been recently proposed in regression tasks, mostly for feature selection and for identifying the real instances from training sets that contains noise and outliers. This paper proposes a methodology for the training set selection in a least squares support vector machines (LS-SVMs load forecasting model. A new application of the concept of MI is presented for the selection of a training set based on MI computation between initial training set instances and testing set instances. Accordingly, several LS-SVMs models have been trained, based on the proposed methodology, for hourly prediction of electric load for one day ahead. The results obtained from a real-world data set indicate that the proposed method increases the accuracy of load forecasting as well as reduces the size of the initial training set needed for model training.

Standalone Photovoltaic System Sizing using Peak Sun Hour Method and Evaluation by TRNSYS Simulation

OpenAIRE

Riza, Dimas Firmanda Al; Gilani, Syed Ihtshamul-Haq

2016-01-01

This paper presents sizing and evaluation of a standalone photovoltaic system for residential load. Peak Sun Hour method is used to determine photovoltaic panel and battery capacity, then the sizing results is tested and evaluated using hourly time-step transient simulation model by using TRNSYS 16.0. The results shows for typical Malaysian terraced house that have about 6 kWh daily electricity load, the photovoltaic system requirement consist of 1.9 kWp photovoltaic panel and 2200 Ah battery...

Estimate of China's energy carbon emissions peak and analysis on electric power carbon emissions

Directory of Open Access Journals (Sweden)

Zhi-Xuan Wang

2014-12-01

Full Text Available China's energy carbon emissions are projected to peak in 2030 with approximately 110% of its 2020 level under the following conditions: 1 China's gross primary energy consumption is 5 Gtce in 2020 and 6 Gtce in 2030; 2 coal's share of the energy consumption is 61% in 2020 and 55% in 2030; 3 non-fossil energy's share increases from 15% in 2020 to 20% in 2030; 4 through 2030, China's GDP grows at an average annual rate of 6%; 5 the annual energy consumption elasticity coefficient is 0.30 in average; and 6 the annual growth rate of energy consumption steadily reduces to within 1%. China's electricity generating capacity would be 1,990 GW, with 8,600 TW h of power generation output in 2020. Of that output 66% would be from coal, 5% from gas, and 29% from non-fossil energy. By 2030, electricity generating capacity would reach 3,170 GW with 11,900 TW h of power generation output. Of that output, 56% would be from coal, 6% from gas, and 37% from non-fossil energy. From 2020 to 2030, CO2 emissions from electric power would relatively fall by 0.2 Gt due to lower coal consumption, and relatively fall by nearly 0.3 Gt with the installation of more coal-fired cogeneration units. During 2020–2030, the portion of carbon emissions from electric power in China's energy consumption is projected to increase by 3.4 percentage points. Although the carbon emissions from electric power would keep increasing to 118% of the 2020 level in 2030, the electric power industry would continue to play a decisive role in achieving the goal of increase in non-fossil energy use. This study proposes countermeasures and recommendations to control carbon emissions peak, including energy system optimization, green-coal-fired electricity generation, and demand side management.

Demand side management in recycling and electricity retail pricing

Science.gov (United States)

Kazan, Osman

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

Application of fuzzy – Neuro to model weather parameter variability impacts on electrical load based on long-term forecasting

Directory of Open Access Journals (Sweden)

Danladi Ali

2018-03-01

Full Text Available Long-term load forecasting provides vital information about future load and it helps the power industries to make decision regarding electrical energy generation and delivery. In this work, fuzzy – neuro model is developed to forecast a year ahead load in relation to weather parameter (temperature and humidity in Mubi, Adamawa State. It is observed that: electrical load increased with increase in temperature and relative humidity does not show notable effect on electrical load. The accuracy of the prediction is obtained at 98.78% with the corresponding mean absolute percentage error (MAPE of 1.22%. This confirms that fuzzy – neuro is a good tool for load forecasting. Keywords: Electrical load, Load forecasting, Fuzzy logic, Back propagation, Neuro-fuzzy, Weather parameter

Using vehicle-to-grid technology for frequency regulation and peak-load reduction

Science.gov (United States)

White, Corey D.; Zhang, K. Max

This paper explores the potential financial return for using plug-in hybrid electric vehicles as a grid resource. While there is little financial incentive for individuals when the vehicle-to-grid (V2G) service is used exclusively for peak reduction, there is a significant potential for financial return when the V2G service is used for frequency regulation. We propose that these two uses for V2G technology are not mutually exclusive, and that there could exist a "dual-use" program that utilizes V2G for multiple uses simultaneously. In our proposition, V2G could be used for regulation on a daily basis to ensure profits, and be used for peak reduction on days with high electricity demand and poor ambient air quality in order to reap the greatest environmental benefits. The profits for the individual in this type of dual-use program are close to or even higher than the profits experienced in either of the single-use programs. More importantly, we argue that the external benefits of this type of program are much greater as well. At higher V2G participation rates, our analysis shows that the market for regulation capacity could become saturated by V2G-based regulation providers. At the same time, there is plenty of potential for widespread use of V2G technology, especially if the demand for regulation, reserves, and storage grows as more intermittent renewable resources are being incorporated into the power systems.

Analytic model for ultrasound energy receivers and their optimal electric loads

Science.gov (United States)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-08-01

In this paper, we present an analytic model for thickness resonating plate ultrasound energy receivers, which we have derived from the piezoelectric and the wave equations and, in which we have included dielectric, viscosity and acoustic attenuation losses. Afterwards, we explore the optimal electric load predictions by the zero reflection and power maximization approaches present in the literature with different acoustic boundary conditions, and discuss their limitations. To validate our model, we compared our expressions with the KLM model solved numerically with very good agreement. Finally, we discuss the differences between the zero reflection and power maximization optimal electric loads, which start to differ as losses in the receiver increase.

Support Vector Regression Model Based on Empirical Mode Decomposition and Auto Regression for Electric Load Forecasting

Directory of Open Access Journals (Sweden)

Hong-Juan Li

2013-04-01

Full Text Available Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR, this paper presents a SVR model hybridized with the empirical mode decomposition (EMD method and auto regression (AR for electric load forecasting. The electric load data of the New South Wales (Australia market are employed for comparing the forecasting performances of different forecasting models. The results confirm the validity of the idea that the proposed model can simultaneously provide forecasting with good accuracy and interpretability.

Plug-in hybrid electric vehicles in smart grid

Science.gov (United States)

Yao, Yin

In this thesis, in order to investigate the impact of charging load from plug-in hybrid electric vehicles (PHEVs), a stochastic model is developed in Matlab. In this model, two main types of PHEVs are defined: public transportation vehicles and private vehicles. Different charging time schedule, charging speed and battery capacity are considered for each type of vehicles. The simulation results reveal that there will be two load peaks (at noon and in evening) when the penetration level of PHEVs increases continuously to 30% in 2030. Therefore, optimization tool is utilized to shift load peaks. This optimization process is based on real time pricing and wind power output data. With the help of smart grid, power allocated to each vehicle could be controlled. As a result, this optimization could fulfill the goal of shifting load peaks to valley areas where real time price is low or wind output is high.

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

Energy Technology Data Exchange (ETDEWEB)

Hong, Tianzhen; Chang, Wen-Kuei; Lin, Hung-Wen

2013-05-01

Buildings consume more than one third of the world?s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small

101 Modelling and Forecasting Periodic Electric Load for a ...

African Journals Online (AJOL)

User

2012-01-24

Jan 24, 2012 ... Electricity load consumption in Nigeria is of great concern and its government is ... This is because the energy needed for any system is based on ... is a tool for verifying the validity and reliability of a chosen model. It tells how ...

Research and Application of a Hybrid Forecasting Model Based on Data Decomposition for Electrical Load Forecasting

Directory of Open Access Journals (Sweden)

Yuqi Dong

2016-12-01

Full Text Available Accurate short-term electrical load forecasting plays a pivotal role in the national economy and people’s livelihood through providing effective future plans and ensuring a reliable supply of sustainable electricity. Although considerable work has been done to select suitable models and optimize the model parameters to forecast the short-term electrical load, few models are built based on the characteristics of time series, which will have a great impact on the forecasting accuracy. For that reason, this paper proposes a hybrid model based on data decomposition considering periodicity, trend and randomness of the original electrical load time series data. Through preprocessing and analyzing the original time series, the generalized regression neural network optimized by genetic algorithm is used to forecast the short-term electrical load. The experimental results demonstrate that the proposed hybrid model can not only achieve a good fitting ability, but it can also approximate the actual values when dealing with non-linear time series data with periodicity, trend and randomness.

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...

A new cascade NN based method to short-term load forecast in deregulated electricity market

International Nuclear Information System (INIS)

Kouhi, Sajjad; Keynia, Farshid

2013-01-01

Highlights: • We are proposed a new hybrid cascaded NN based method and WT to short-term load forecast in deregulated electricity market. • An efficient preprocessor consist of normalization and shuffling of signals is presented. • In order to select the best inputs, a two-stage feature selection is presented. • A new cascaded structure consist of three cascaded NNs is used as forecaster. - Abstract: Short-term load forecasting (STLF) is a major discussion in efficient operation of power systems. The electricity load is a nonlinear signal with time dependent behavior. The area of electricity load forecasting has still essential need for more accurate and stable load forecast algorithm. To improve the accuracy of prediction, a new hybrid forecast strategy based on cascaded neural network is proposed for STLF. This method is consists of wavelet transform, an intelligent two-stage feature selection, and cascaded neural network. The feature selection is used to remove the irrelevant and redundant inputs. The forecast engine is composed of three cascaded neural network (CNN) structure. This cascaded structure can be efficiently extract input/output mapping function of the nonlinear electricity load data. Adjustable parameters of the intelligent feature selection and CNN is fine-tuned by a kind of cross-validation technique. The proposed STLF is tested on PJM and New York electricity markets. It is concluded from the result, the proposed algorithm is a robust forecast method

Assessing and Reducing Miscellaneous Electric Loads (MELs) in Banks

Energy Technology Data Exchange (ETDEWEB)

Rauch, Emily M.

2012-09-01

Miscellaneous electric loads (MELs) are loads outside of a building's core functions of heating, ventilating, air conditioning, lighting, and water heating. MELs are a large percentage of total building energy loads. This report reviews methods for reducing MELs in Banks. Reducing MELs in a bank setting requires both local and corporate action. Corporate action centers on activities to prioritize and allocate the right resources to correct procurement and central control issues. Local action includes branch assessment or audits to identify specific loads and needs. The worksheet at the end of this guide can help with cataloging needed information and estimating savings potential. The following steps provide a guide to MEL reductions in Bank Branches. The general process has been adapted from a process developed for office buildings the National Renewable Energy Laboratory (NREL, 2011).

1992 statistical data on electricity consumption and generation in Bulgaria

International Nuclear Information System (INIS)

Georgiev, A.

1993-01-01

The report provides data on monthly power consumption based on peak-day load profiles, power balance of electric system in peak hours of absolute maximal load and analysis of usability of different kinds of power plants in the country. The total energy production for all power plants for 1992 is 35555 ml kWh - 48.6 % TPP, 32.5% NPP, 5.8% HPP, 8.5% in-house TPP, 4.6 district heating PP. 14 tabs., 5 figs. (author)

Technical Specifications, Comanche Peak Steam Electric Station, Unit 1 (Docket No. 50-445)

International Nuclear Information System (INIS)

1990-04-01

The Technical Specifications for Comanche Peak Steam Electric Station, Unit 1 were prepared by the US Nuclear Regulatory Commission. They set forth the limits, operating conditions, and other requirements applicable to a nuclear reactor facility, as set forth in Section 50.36 of Title 10 of the Code of Federal Regulations Part 50, for the protection of the health and safety of the public

Three Players Nash Equilibrium Game Concerning the Charging Time and Place of Employee Electric Vehicles

DEFF Research Database (Denmark)

Fetene, Gebeyehu Manie; Hirte, Georg; Tscharaktschiew, Stefan

the charging time and increases the share of EVs as commuting mode, it results in unintended consequences including electricity peak-load problem, an increase in electricity tariff for household use, and an increase in car use that worsens traffic congestion. For the electricity supplier, workplace charging...... and when the labor tax is high; ii) employers pay less electricity tariff than households do; iii) the employment contract duration is long; iv) recharging electric vehicles (EVs) takes longer time and the value of time is higher. Accessibility of cheaper charging facility at workplace, while saves...... increases the cost of supplying electricity by aggravating the daytime peak-load problem and by increasing the demand variation from the mean. Tax based on yearly travel distance, and restriction on free workplace charging access improves social welfare. The results from this study are relevant in (i...

An Optimal Domestic Electric Vehicle Charging Strategy for Reducing Network Transmission Loss While Taking Seasonal Factors into Consideration

Directory of Open Access Journals (Sweden)

Yuancheng Zhao

2018-01-01

Full Text Available With the rapid growth of domestic electric vehicle charging loads, the peak-valley gap and power fluctuation rate of power systems increase sharply, which can lead to the increase of network losses and energy efficiency reduction. This paper tries to regulate network loads and reduce power system transmission loss by optimizing domestic electric vehicle charging loads. In this paper, a domestic electric vehicle charging loads model is first developed by analyzing the key factors that can affect users’ charging behavior. Subsequently, the Monte Carlo method is proposed to simulate the power consumption of a cluster of domestic electric vehicles. After that, an optimal electric vehicle charging strategy based on the 0-1 integer programming is presented to regulate network daily loads. Finally, by taking the IEEE33 distributed power system as an example, this paper tries to verify the efficacy of the proposed optimal charging strategy and the necessity for considering seasonal factors when scheduling electric vehicle charging loads. Simulation results show that the proposed 0-1 integer programming method does have good performance in reducing the network peak-valley gap, voltage fluctuation rate, and transmission loss. Moreover, it has some potential to further reduce power system transmission loss when seasonal factors are considered.

Modelling the Load Curve of Aggregate Electricity Consumption Using Principal Components

OpenAIRE

Matteo Manera; Angelo Marzullo

2003-01-01

Since oil is a non-renewable resource with a high environmental impact, and its most common use is to produce combustibles for electricity, reliable methods for modelling electricity consumption can contribute to a more rational employment of this hydrocarbon fuel. In this paper we apply the Principal Components (PC) method to modelling the load curves of Italy, France and Greece on hourly data of aggregate electricity consumption. The empirical results obtained with the PC approach are compa...

Measurement errors in network load measurement: Effects on lead management and accounting. Messfehler bei der Netzlasterfassung: Einfluss auf Lastregelung und Leistungsverrechnung

Energy Technology Data Exchange (ETDEWEB)

Bunten, B. (Teilbereich Lastfuehrung, ABB Netzleittechnik GmbH, Ladenburg (Germany)); Dib, R.N. (Fachhochschule Giessen-Friedberg, Bereich Elektrische Energietechnik, Friedberg (Germany))

1994-05-16

In electric power supply systems continuous power measurement in the delivery points is necessary both for the purpose of load-management and for energy and power accounting. Electricity meters with pulse output points are commonly used for both applications today. The authors quantify the resulting errors in peak load measurement and load management as a function of the main influencing factors. (orig.)

Simulation of fatigue damage in ferroelectric polycrystals under mechanical/electrical loading

Science.gov (United States)

Kozinov, S.; Kuna, M.

2018-07-01

The reliability of smart-structures made of ferroelectric ceramics is essentially reduced by the formation of cracks under the action of external electrical and/or mechanical loading. In the current research a numerical model for low-cycle fatigue in ferroelectric mesostructures is proposed. In the finite element simulations a combination of two user element routines is utilized. The first one is used to model a micromechanical ferroelectric domain switching behavior inside the grains. The second one is used to simulate fatigue damage of grain boundaries by a cohesive zone model (EMCCZM) based on an electromechanical cyclic traction-separation law (TSL). For numerical simulations a scanning electron microscope image of the ceramic's grain structure was digitalized and meshed. The response of this mesostructure to cyclic electrical or mechanical loading is systematically analyzed. As a result of the simulations, the distribution of electric potential, field, displacement and polarization as well as mechanical stresses and deformations inside the grains are obtained. At the grain boundaries, the formation and evolution of damage are analyzed until final failure and induced degradation of electric permittivity. It is found that the proposed model correctly mimics polycrystalline behavior during poling processes and progressive damage under cyclic electromechanical loading. To the authors' knowledge, it is the first model and numerical analysis of ferroelectric polycrystals taking into account both domain reorientation and cohesive modeling of intergranular fracture. It can help to understand failure mechanisms taking place in ferroelectrics during fatigue processes.

Cut down the peak daytime demand for electricity at the residence; Jutaku ni okeru denryoku fuka heijunka

Energy Technology Data Exchange (ETDEWEB)

Ishihara, O. [Kumamoto University, Kumamoto (Japan). Faculty of Engineering

1996-09-05

For leveling of power load in small-scale buildings and houses, a test house with actual size was constructed in order to examine soil heat storage system using photovoltaic power generation system and nighttime power. A hundred of polycrystal silicone solar cells with about 5 kW and twenty of amorphous ones were fixed on the roof, to connect with commercial power source by the system interconnection having inverse power flow. For leveling of power load in the periods of heating and cooling, soil heat storage system was applied using nighttime power. Pipes for circulating cooling and heating water were embedded. Heat pump was operated only in the time zone of nighttime power, to obtain cooling and heating source for fan coil unit in the daytime. The sold power was larger than purchased power under continuous cooling condition for twelve hours in summer. Since cooling load was supplied from nighttime power with lower price, there was a large peak cut effect in the daytime. As a result of the tests using a house with actual size, the system was found to be applied practically both in summer and in winter. Effectiveness of peak cut of power load in summer was also provided. 7 refs., 10 figs., 2 tabs.

Effect of loading on peak power of the bar, body, and system during power cleans, squats, and jump squats.

Science.gov (United States)

McBride, Jeffrey M; Haines, Tracie L; Kirby, Tyler J

2011-08-01

Nine males (age 24.7 ± 2.1 years, height 175.3 ± 5.5 cm, body mass 80.8 ± 7.2 kg, power clean 1-RM 97.1 ± 6.36 kg, squat 1-RM = 138.3 ± 20.9 kg) participated in this study. On day 1, the participants performed a one-repetition maximum (1-RM) in the power clean and the squat. On days 2, 3, and 4, participants performed the power clean, squat or jump squat. Loading for the power clean ranged from 30% to 90% of the participant's power clean 1-RM and loading for the squat and jump squat ranged from 0% to 90% of the participant's squat 1-RM, all at 10% increments. Peak force, velocity, and power were calculated for the bar, body, and system (bar + body) for all power clean, squat, and jump squat trials. Results indicate that peak power for the bar, body, and system is differentially affected by load and movement pattern. When using the power clean, squat or jump squat for training, the optimal load in each exercise may vary. Throwing athletes or weightlifters may be most concerned with bar power, but jumpers or sprinters may be more concerned with body or system power. Thus, the exercise type and load vary according to the desired stimulus.

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....

Impact of PHEVs Penetration on Ontario’s Electricity Grid and Environmental Considerations

Directory of Open Access Journals (Sweden)

Lena Ahmadi

2012-11-01

Full Text Available Plug-in hybrid electric vehicles (PHEVs have a large potential to reduce greenhouse gases emissions and increase fuel economy and fuel flexibility. PHEVs are propelled by the energy from both gasoline and electric power sources. Penetration of PHEVs into the automobile market affects the electrical grid through an increase in electricity demand. This paper studies effects of the wide spread adoption of PHEVs on peak and base load demands in Ontario, Canada. Long-term forecasting models of peak and base load demands and the number of light-duty vehicles sold were developed. To create proper forecasting models, both linear regression (LR and non-linear regression (NLR techniques were employed, considering different ranges in the demographic, climate and economic variables. The results from the LR and NLR models were compared and the most accurate one was selected. Furthermore, forecasting the effects of PHEVs penetration is done through consideration of various scenarios of penetration levels, such as mild, normal and aggressive ones. Finally, the additional electricity demand on the Ontario electricity grid from charging PHEVs is incorporated for electricity production planning purposes.

Alberta electric industry annual statistics for 1998

International Nuclear Information System (INIS)

1999-06-01

Tables containing data on electric energy generation and capacity for Alberta are provided for the following aspects: capacity and generation of power plants for 1998; capacity of power plants by type, unit, and energy resource for 1998; generating units approved for construction for 1998; generating units completed in 1998; transmission additions approved for construction and completed for 1998; net annual generating capacity and generation for 1988-1998; net monthly generation by plant for 1998; net annual generation by energy resource and type for 1988-1998; net monthly generation by energy resource and type for 1998; generation capacity reserve; relative capacity and generation by type of energy resource for 1998; capacity, generation and fuel consumption of isolated plants for 1998; other industrial on-site plant capacity and generation for 1998. Also listed are: energy resource consumption and energy conversion efficiency of thermal power plants for 1998; stack emissions from thermal generating plants for 1998; non-utility electric generators, wind and hydro for 1998; and hydroelectric energy utilization and conversion efficiency for 1998. Tables contain information on electric energy generation and capacity for hydroelectric energy stored in reservoirs in 1998; details of non-coincident net peak generation and load by utility operators for the Alberta electric system for 1998; and Alberta electric system generation and load at peak load hour for 1998. Further tables cover electric energy distribution for interchange and distribution for 1998 and 1981-1998; annual energy distribution to ultimate customers for 1988-1998 and to ultimate customers for 1998; and the number of electric utility customers in 1998. Final tables cover the transmission and distribution systems with data on: circuit km of such lines for 1988-1998; total circuit km of such lines by major electric utility for 1998 and number of rural electric utility customers for 1998

Method and system employing finite state machine modeling to identify one of a plurality of different electric load types

Science.gov (United States)

Du, Liang; Yang, Yi; Harley, Ronald Gordon; Habetler, Thomas G.; He, Dawei

2016-08-09

A system is for a plurality of different electric load types. The system includes a plurality of sensors structured to sense a voltage signal and a current signal for each of the different electric loads; and a processor. The processor acquires a voltage and current waveform from the sensors for a corresponding one of the different electric load types; calculates a power or current RMS profile of the waveform; quantizes the power or current RMS profile into a set of quantized state-values; evaluates a state-duration for each of the quantized state-values; evaluates a plurality of state-types based on the power or current RMS profile and the quantized state-values; generates a state-sequence that describes a corresponding finite state machine model of a generalized load start-up or transient profile for the corresponding electric load type; and identifies the corresponding electric load type.

Engineering to Control Noise, Loading, and Optimal Operating Points

International Nuclear Information System (INIS)

Mitchell R. Swartz

2000-01-01

Successful engineering of low-energy nuclear systems requires control of noise, loading, and optimum operating point (OOP) manifolds. The latter result from the biphasic system response of low-energy nuclear reaction (LENR)/cold fusion systems, and their ash production rate, to input electrical power. Knowledge of the optimal operating point manifold can improve the reproducibility and efficacy of these systems in several ways. Improved control of noise, loading, and peak production rates is available through the study, and use, of OOP manifolds. Engineering of systems toward the OOP-manifold drive-point peak may, with inclusion of geometric factors, permit more accurate uniform determinations of the calibrated activity of these materials/systems

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.

Ultrasonic Transducer Peak-to-Peak Optical Measurement

Directory of Open Access Journals (Sweden)

Pavel Skarvada

2012-01-01

Full Text Available Possible optical setups for measurement of the peak-to-peak value of an ultrasonic transducer are described in this work. The Michelson interferometer with the calibrated nanopositioner in reference path and laser Doppler vibrometer were used for the basic measurement of vibration displacement. Langevin type of ultrasonic transducer is used for the purposes of Electro-Ultrasonic Nonlinear Spectroscopy (EUNS. Parameters of produced mechanical vibration have to been well known for EUNS. Moreover, a monitoring of mechanical vibration frequency shift with a mass load and sample-transducer coupling is important for EUNS measurement.

Role of nuclear energy in the establishment of smart electricity networks in the United States

International Nuclear Information System (INIS)

Harding, Margaret

2012-01-01

The concept that smart grids are separate from, and conflict with, traditional grids has been discussed in recent times. A key fact that has to be understood is that in the current electricity grid of the US, electricity is generated as it is demanded. With the advent of intermittent power suppliers like wind and solar, and changing load curves due to increasing electricity usage (electric cars, more electrical appliances and equipment), the traditional methods of managing the grid are being significantly stressed. There are significant losses of electricity occurring in the current US transmission and distribution system as well as inflexibility for transmission of electricity across long distance required to use intermittent sources that are generally more available in the west at major population and industrial centers in the east. Smart grid is really about improving the reliability of the overall electricity supply. This entails managing supply as well as demand, but most importantly, the transmission and distribution of electricity. Nuclear energy tends to be used as base load supply. The reasons for this are primarily economic, though technology does play a role. The economic reasons center around the fact that nuclear is a capital intensive energy source. Nuclear and solar can work together in some interesting and more optimal ways. Because solar is tied to hours of daylight and tends to peak at midday when demand is starting to rise to peak as well, nuclear and solar can work as base load and peak demand response effectively.

Local CHP Plants between the Natural Gas and Electricity Systems

DEFF Research Database (Denmark)

Bregnbæk, Lars; Schaumburg-Müller, Camilla

2005-01-01

, and they contribute significantly to the electricity production. CHP is, together with the wind power, the almost exclusive distributed generation in Denmark. This paper deals with the CHP as intermediary between the natural gas system and the electricity system. In particular, the relationship between the peak hour......Local combined heat and power (CHP) plants in Denmark constitute an important part of the national energy conversion capacity. In particular they supply a large share of the district heating networks with heat. At the same time they are important consumers as seen from the gas network system...... characteristics of the electricity and gas systems will be investigated. The point is here that the two systems will tend to have peak demand during the same hours. This is the typical situation, since load is high during the same hours of the day and of the year. Moreover, the random variations in the load...

Economically optimized electricity trade modeling. Iran-Turkey case

International Nuclear Information System (INIS)

Shakouri G, H.; Eghlimi, M.; Manzoor, D.

2009-01-01

The advantages of power trade between countries, which are attainable for various facts, are distinguished now. Daily differences in the peak-load times of neighboring countries commonly occur for differences in the longitudes of their location. Seasonal differences are also caused by differences in the latitudes leading to different climates. Consequently, different load curves help to have such a production schedule that reduces blackouts and investments for power generation by planning for a proper trade between countries in a region. This paper firstly describes the methodology and framework for the power trade and then the results of an optimal power trade model between Iran and Turkey, which shows a potential benefit for both countries by peak shaving, are presented. The results, in the worst case design, represent optimality of about 1500 MW electricity export from Iran to Turkey at the Turkish peak times, as well as 447 MW electricity import from Turkey at the Iranian peak times. In addition, results derived from running a Long-Run model show that there will be greater potential for power export from Iran to Turkey, which is a guideline of an energy conservation strategy for both countries in the future. (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....

Passive radio frequency peak power multiplier

Science.gov (United States)

Farkas, Zoltan D.; Wilson, Perry B.

1977-01-01

Peak power multiplication of a radio frequency source by simultaneous charging of two high-Q resonant microwave cavities by applying the source output through a directional coupler to the cavities and then reversing the phase of the source power to the coupler, thereby permitting the power in the cavities to simultaneously discharge through the coupler to the load in combination with power from the source to apply a peak power to the load that is a multiplication of the source peak power.

Development of electrical heating in the Czech Republic and its consequences

International Nuclear Information System (INIS)

Mravinac, L.

1996-01-01

After 1990 the necessity to improve ecological conditions in the Czech Republic increased significantly. One of the measures to achieve this aim was the governmental support of households to replace fossil fuel heating by gas or electrical heating. This support, connected with the fact that prices of the electricity for households were and still are below a cost level resulted in a substantial increase of the electricity consumption of these consumers. This increase had a very unfavorable influence on the whole electrical system. While a consumption of industrial consumers had decreased after the year 1990 (as a result of changes in the national economy) and started to increase slowly only last year, the household consumption has recorded a continuous increase (of 17 % in 1994, for example). At present the installed capacity by direct electrical heating is estimated to amount up to 2200 MW while it was practically zero in 1991. The consumption diagram has accordingly changed. The difference between the summer minimum and the winter peak load has substantially increased. With nearly the same average consumption, the peak load in 1995 was about 800 Mw higher than in 1989. In the same period, the needed regulation capacity increased too. The increase in power demand for electrical heating will probably increase in the next years and accordingly new power capacities and new peak sources will be required. (author) 3 figs., 2 tabs

Safety evaluation report related to the operation of Comanche Peak Steam Electric Station, Units 1 and 2 (Docket Nos. 50-445 and 50-446)

International Nuclear Information System (INIS)

1988-11-01

Supplement 19 to the Safety Evaluation Report related to the operation of the Comanche Peak Steam Electric Station (CPSES), Units 1 and 2 (NUREG-0797), has been prepared by the Office of Special Projects of the US Nuclear Regulatory Commission (NRC). The facility is located in Somervell County, Texas, approximately 40 miles southwest of Fort Worth, Texas. This supplement presents the staff's evaluation of the Texas Utilities Electric Company's (lead applicant's) corrective action program (CAP) related to equipment qualification. The scope and methodology for the CAP workscope, as summarized in Revision 0 to the Equipment Qualification Project Status Report and as detailed in related documents, were developed to resolve various issues raised by the Comanche Peak Response Team (CPRT) and the NRC staff to ensure that plant equipment is appropriately environmentally and/or seismically and dynamically qualified and documented in accordance with the validated plant design resulting from other CAP scopes of work for Unit 1 and areas common to Units 1 and 2. The staff concludes that the CAP workscope for equipment qualification provides a comprehensive program for resolving the concerns identified by the CPRT and the NRC staff, including issues raised in the Comanche Peak Safety Evaluation Report and its supplements, and its implementation will ensure that the environmental and/or seismic and dynamic qualification of equipment at CPSES satisfies the validated plant design and the applicable requirements of 10 CFR Part 50. As is routine staff practice, the NRC staff will verify the adequacy of implementation of the environmental and seismic and dynamic equipment qualification program at CPSES during inspections that will take place before fuel loading. 97 refs

Approach undertaken by our Company for leveling electric loads; Chubu Denryoku Kabushi Kaisha no fuka heijunka eno torikumi ni tsuite

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-07-01

Measures for leveling the electric loads relying upon two facets - tariff system and business activities - in Chubu Electric Power Co., Inc. are presented. Firstly, the existing pricing systems for midnight electric power and electric light according to the period of time for the household as well as those of seasonal and time zone electric power, modifiable contract with the time zone and so forth for large industry users, together with a similar contract for the owner of regenerating installation are outlined. In addition, a price reduction system is indicated in favor of a scheduled shutdown of large industry operations as a means of avoiding electric consumption during weekdays in summer and between 13h and 16h when large demands exist. Further, a selective contract system put in service in 1995 and the price reduction for ice regenerating air conditioning system are cited. As for business facet, 1995 is regarded as the first year of the ice regenerator for its generalization through exhibition and promotive campaign to the foods processing industry, and the application of the latent heat regenerative system to perishable foods is recommended. Moreover, installation of energy saving type automatic vending machine, so-called eco-vendor is encouraged for its merit of peak-cut and energy price lowering. Lastly, activities to extend the use of electric calorifiers and the regenerative floor heating are mentioned. 2 figs., 1 tab.

Using the internet of things to enable electrical load optimisation

CSIR Research Space (South Africa)

Butgereit, L

2012-05-01

Full Text Available about itself and also allowing the object to be controlled by some process. This paper describes a research project in balancing the electrical load in the kitchens of an IT organisation. Ten kitchen appliances were enhanced with digital intelligence...

Automated Critical Peak Pricing Field Tests: Program Descriptionand Results

Energy Technology Data Exchange (ETDEWEB)

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

2006-04-06

California utilities have been exploring the use of critical peak prices (CPP) to help reduce needle peaks in customer end-use loads. CPP is a form of price-responsive demand response (DR). Recent experience has shown that customers have limited knowledge of how to operate their facilities in order to reduce their electricity costs under CPP (Quantum 2004). While the lack of knowledge about how to develop and implement DR control strategies is a barrier to participation in DR programs like CPP, another barrier is the lack of automation of DR systems. During 2003 and 2004, the PIER Demand Response Research Center (DRRC) conducted a series of tests of fully automated electric demand response (Auto-DR) at 18 facilities. Overall, the average of the site-specific average coincident demand reductions was 8% from a variety of building types and facilities. Many electricity customers have suggested that automation will help them institutionalize their electric demand savings and improve their overall response and DR repeatability. This report focuses on and discusses the specific results of the Automated Critical Peak Pricing (Auto-CPP, a specific type of Auto-DR) tests that took place during 2005, which build on the automated demand response (Auto-DR) research conducted through PIER and the DRRC in 2003 and 2004. The long-term goal of this project is to understand the technical opportunities of automating demand response and to remove technical and market impediments to large-scale implementation of automated demand response (Auto-DR) in buildings and industry. A second goal of this research is to understand and identify best practices for DR strategies and opportunities. The specific objectives of the Automated Critical Peak Pricing test were as follows: (1) Demonstrate how an automated notification system for critical peak pricing can be used in large commercial facilities for demand response (DR). (2) Evaluate effectiveness of such a system. (3) Determine how customers

INNOVATIVE HYBRID GAS/ELECTRIC CHILLER COGENERATION

Energy Technology Data Exchange (ETDEWEB)

Todd Kollross; Mike Connolly

2004-06-30

Engine-driven chillers are quickly gaining popularity in the market place (increased from 7,000 tons in 1994 to greater than 50,000 tons in 1998) due to their high efficiency, electric peak shaving capability, and overall low operating cost. The product offers attractive economics (5 year pay back or less) in many applications, based on areas cooling requirements and electric pricing structure. When heat is recovered and utilized from the engine, the energy resource efficiency of a natural gas engine-driven chiller is higher than all competing products. As deregulation proceeds, real time pricing rate structures promise high peak demand electric rates, but low off-peak electric rates. An emerging trend with commercial building owners and managers who require air conditioning today is to reduce their operating costs by installing hybrid chiller systems that combine gas and electric units. Hybrid systems not only reduce peak electric demand charges, but also allow customers to level their energy load profiles and select the most economical energy source, gas or electricity, from hour to hour. Until recently, however, all hybrid systems incorporated one or more gas-powered chillers (engine driven and/or absorption) and one or more conventional electric units. Typically, the cooling capacity of hybrid chiller plants ranges from the hundreds to thousands of refrigeration tons, with multiple chillers affording the user a choice of cooling systems. But this flexibility is less of an option for building operators who have limited room for equipment. To address this technology gap, a hybrid chiller was developed by Alturdyne that combines a gas engine, an electric motor and a refrigeration compressor within a single package. However, this product had not been designed to realize the full features and benefits possible by combining an engine, motor/generator and compressor. The purpose of this project is to develop a new hybrid chiller that can (1) reduce end-user energy

Analysis of relationships between hourly electricity price and load in deregulated real-time power markets

International Nuclear Information System (INIS)

Lo, K.L.; Wu, Y.K.

2004-01-01

Risk management in the electric power industry involves measuring the risk for all instruments owned by a company. The value of many of these instruments depends directly on electricity prices. In theory, the wholesale price in a real-time market should reflect the short-run marginal cost. However, most markets are not perfectly competitive, therefore by understanding the degree of correlation between price and physical drivers, electric traders and consumers can manage their risk more effectively and efficiently. Market data from two power-pool architectures, both pre-2003 ISO-NE and Australia's NEM, have been studied. The dynamic character of electricity price is mean-reverting, and consists of intra-day and weekly variations, seasonal fluctuations, and instant jumps. Parts of them are affected by load demands. Hourly signals on both price and load are divided into deterministic and random components with a discrete Fourier transform algorithm. Next, the real-time price-load relationship for periodic and random signals is examined. In addition, time-varying volatility models are constructed on random price and random load with the GARCH model, and the correlation between them analysed. Volatility plays a critical role on evaluating option pricing and risk management. (author)

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.

Electrical load modeling

Energy Technology Data Exchange (ETDEWEB)

Valgas, Helio Moreira; Pinto, Roberto del Giudice R.; Franca, Carlos [Companhia Energetica de Minas Gerais (CEMIG), Belo Horizonte, MG (Brazil); Lambert-Torres, Germano; Silva, Alexandre P. Alves da; Pires, Robson Celso; Costa, Junior, Roberto Affonso [Escola Federal de Engenharia de Itajuba, MG (Brazil)

1994-12-31

Accurate dynamic load models allow more precise calculations of power system controls and stability limits, which are critical mainly in the operation planning of power systems. This paper describes the development of a computer program (software) for static and dynamic load model studies using the measurement approach for the CEMIG system. Two dynamic load model structures are developed and tested. A procedure for applying a set of measured data from an on-line transient recording system to develop load models is described. (author) 6 refs., 17 figs.

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

Energy Technology Data Exchange (ETDEWEB)

Wang, Bin; Huang, Rui; Wang, Yubo; Nazaripouya, Hamidreza; Qiu, Charlie; Chu, Chi-Cheng; Gadh, Rajit

2016-05-02

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimization module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.

Minimization of Load Variance in Power Grids—Investigation on Optimal Vehicle-to-Grid Scheduling

Directory of Open Access Journals (Sweden)

Kang Miao Tan

2017-11-01

Full Text Available The introduction of electric vehicles into the transportation sector helps reduce global warming and carbon emissions. The interaction between electric vehicles and the power grid has spurred the emergence of a smart grid technology, denoted as vehicle-to grid-technology. Vehicle-to-grid technology manages the energy exchange between a large fleet of electric vehicles and the power grid to accomplish shared advantages for the vehicle owners and the power utility. This paper presents an optimal scheduling of vehicle-to-grid using the genetic algorithm to minimize the power grid load variance. This is achieved by allowing electric vehicles charging (grid-to-vehicle whenever the actual power grid loading is lower than the target loading, while conducting electric vehicle discharging (vehicle-to-grid whenever the actual power grid loading is higher than the target loading. The vehicle-to-grid optimization algorithm is implemented and tested in MATLAB software (R2013a, MathWorks, Natick, MA, USA. The performance of the optimization algorithm depends heavily on the setting of the target load, power grid load and capability of the grid-connected electric vehicles. Hence, the performance of the proposed algorithm under various target load and electric vehicles’ state of charge selections were analysed. The effectiveness of the vehicle-to-grid scheduling to implement the appropriate peak load shaving and load levelling services for the grid load variance minimization is verified under various simulation investigations. This research proposal also recommends an appropriate setting for the power utility in terms of the selection of the target load based on the electric vehicle historical data.

Peak Operation of Cascaded Hydropower Plants Serving Multiple Provinces

Directory of Open Access Journals (Sweden)

Jianjian Shen

2015-10-01

Full Text Available The bulk hydropower transmission via trans-provincial and trans-regional power networks in China provides great operational flexibility to dispatch power resources between multiple power grids. This is very beneficial to alleviate the tremendous peak load pressure of most provincial power grids. This study places the focus on peak operations of cascaded hydropower plants serving multiple provinces under a regional connected AC/DC network. The objective is to respond to peak loads of multiple provincial power grids simultaneously. A two-stage search method is developed for this problem. In the first stage, a load reconstruction strategy is proposed to combine multiple load curves of power grids into a total load curve. The purpose is to deal with different load features in load magnitudes, peaks and valleys. A mutative-scale optimization method is then used to determine the generation schedules of hydropower plants. In the second stage, an exterior point search method is established to allocate the generation among multiple receiving power grids. This method produces an initial solution using the load shedding algorithm, and further improves it by iteratively coordinating the generation among different power grids. The proposed method was implemented to the operations of cascaded hydropower plants on Xin-Fu River and another on Hongshui River. The optimization results in two cases satisfied the peak demands of receiving provincial power grids. Moreover, the maximum load difference between peak and valley decreased 12.67% and 11.32% in Shanghai Power Grid (SHPG and Zhejiang Power Grid (ZJPG, exceeding by 4.85% and 6.72% those of the current operational method, respectively. The advantage of the proposed method in alleviating peak-shaving pressure is demonstrated.

Effect of Enhanced Air Temperature (extreme heat, and Load of Non-Linear Against the Use of Electric Power

Directory of Open Access Journals (Sweden)

I Ketut Wijaya

2015-12-01

Full Text Available Usage Electric power is very easy to do, because the infrastructure for connecting  already available and widely sold. Consumption electric power is not accompanied by the ability to recognize electric power. The average increase of electricity power in Bali in extreme weather reaches 10% in years 2014, so that Bali suffered power shortages and PLN as the manager of electric power to perform scheduling on of electric power usage. Scheduling is done because many people use electric power as the load  of fan and Air Conditioner exceeding the previous time. Load of fan, air conditioning, and computers including non-linear loads which can add heat on the conductor of electricity. Non-linear load and hot weather can lead to heat on conductor so  insulation damaged  and cause electrical short circuit. Data of electric power obtained through questionnaires, surveys, measurement and retrieve data from various parties. Fires that occurred in 2014, namely 109 events, 44 is  event caused by an electric short circuit (approximately 40%. Decrease power factors can cause losses of electricity and hot. Heat can cause and adds heat on the  conductor electric. The analysis showed  understanding electric power of the average  is 27,700 with value between 20 to 40. So an understanding of the electrical power away from the understand so that many errors because of the act own. Installation tool ELCB very necessary but very necessary provide counseling   of electricity to the community.

Dynamics and stabilization of peak current-mode controlled buck converter with constant current load

International Nuclear Information System (INIS)

Leng Min-Rui; Zhou Guo-Hua; Zhang Kai-Tun; Li Zhen-Hua

2015-01-01

The discrete iterative map model of peak current-mode controlled buck converter with constant current load (CCL), containing the output voltage feedback and ramp compensation, is established in this paper. Based on this model the complex dynamics of this converter is investigated by analyzing bifurcation diagrams and the Lyapunov exponent spectrum. The effects of ramp compensation and output voltage feedback on the stability of the converter are investigated. Experimental results verify the simulation and theoretical analysis. The stability boundary and chaos boundary are obtained under the theoretical conditions of period-doubling bifurcation and border collision. It is found that there are four operation regions in the peak current-mode controlled buck converter with CCL due to period-doubling bifurcation and border-collision bifurcation. Research results indicate that ramp compensation can extend the stable operation range and transfer the operating mode, and output voltage feedback can eventually eliminate the coexisting fast-slow scale instability. (paper)

Correlated wind-power production and electric load scenarios for investment decisions

International Nuclear Information System (INIS)

Baringo, L.; Conejo, A.J.

2013-01-01

Highlights: ► Investment models require an accurate representation of the involved uncertainty. ► Demand and wind power production are correlated and uncertain parameters. ► Two methodologies are provided to represent uncertainty and correlation. ► An accurate uncertainty representation is crucial to get optimal results. -- Abstract: Stochastic programming constitutes a useful tool to address investment problems. This technique represents uncertain input data using a set of scenarios, which should accurately describe the involved uncertainty. In this paper, we propose two alternative methodologies to efficiently generate electric load and wind-power production scenarios, which are used as input data for investment problems. The two proposed methodologies are based on the load- and wind-duration curves and on the K-means clustering technique, and allow representing the uncertainty of and the correlation between electric load and wind-power production. A case study pertaining to wind-power investment is used to show the interest of the proposed methodologies and to illustrate how the selection of scenarios has a significant impact on investment decisions.

Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs

Directory of Open Access Journals (Sweden)

Jaime Buitrago

2017-01-01

Full Text Available Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN with exogenous multi-variable input (NARX. The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input. Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. The New England electrical load data are used to train and validate the forecast prediction.

HTGR-GT and electrical load integrated control

International Nuclear Information System (INIS)

Chan, T.; Openshaw, F.; Pfremmer, D.

1980-05-01

A discussion of the control and operation of the HTGR-GT power plant is presented in terms of its closely coupled electrical load and core cooling functions. The system and its controls are briefly described and comparisons are made with more conventional plants. The results of analyses of selected transients are presented to illustrate the operation and control of the HTGR-GT. The events presented were specifically chosen to show the controllability of the plant and to highlight some of the unique characteristics inherent in this multiloop closed-cycle plant

Considering supply and demand of electric energy in life cycle assessments - a review of current methodologies

International Nuclear Information System (INIS)

Rehberger, M.; Hiete, M.

2015-01-01

A stable power grid requires a balance between electricity supply and demand. To compensate for changes in the demand the network operator puts on or takes off power plants from the net. Peak load plants operate only at times of high electricity demand. As levels for air pollutants emissions are typically lower for peak load plants for reasons of cost-effectiveness, one could argue that a unit of electric energy consumed during peak load has always been associated with a higher environmental impact than at other times. Furthermore, renewable energy technologies, smart approaches for improving the matching between electricity consumption and supply and new products such as electric vehicles or net zero emission buildings gain in importance. In life cycle assessment (LCA) environmental impacts associated with the production and possibly transmission of electricity are most often assessed based on temporally averaged national electricity mixes as electricity flows cannot be traced back to their origin. Neither fluctuations in the supply structure nor the composition of energy supply at a certain moment or regional differences are accounted for. A literature review of approaches for handling electricity in LCA is carried out to compare strengths and weaknesses of the approaches. A better understanding and knowledge about the source of electricity at a given time and place might be valuable information for further reducing environmental impacts, e.g. by shifting electricity consumption to times with ample supply of renewables. Integrating such information into LCA will allow a fairer assessment of a variety of new products which accept a lower energy efficiency to achieve a better integration of renewables into the grid. (authors)

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)

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 Stabilization Strategy of Random Access Loads in Electric Vehicles Wireless Charging System at Traffic Lights

Directory of Open Access Journals (Sweden)

Linlin Tan

2016-10-01

Full Text Available An opportunity wireless charging system for electric vehicles when they stop and wait at traffic lights is proposed in this paper. In order to solve the serious power fluctuation caused by random access loads, this study presents a power stabilization strategy based on counting the number of electric vehicles in a designated area, including counting method, power source voltage adjustment strategy and choice of counting points. Firstly, the circuit model of a wireless power system with multi-loads is built and the equation of each load is obtained. Secondly, after the counting method of electric vehicles is stated, the voltage adjustment strategy, based on the number of electric vehicles when the system is at a steady state, is set out. Then, the counting points are chosen according to power curves when the voltage adjustment strategy is adopted. Finally, an experimental prototype is implemented to verify the power stabilization strategy. The experimental results show that, with the application of this strategy, the charging power is stabilized with the fluctuation of no more than 5% when loads access randomly.

Three-dimensional fracture instability of a displacement-weakening planar interface under locally peaked nonuniform loading

Science.gov (United States)

Uenishi, Koji

2018-06-01

We consider stability of fracture on a three-dimensional planar interface subjected to a loading stress that is locally peaked spatially, the level of which increases quasi-statically in time. Similar to the earlier study on the two-dimensional case (Uenishi and Rice, 2003; Rice and Uenishi, 2010), as the loading stress increases, a crack, or a region of displacement discontinuity (opening gap in tension or slip for shear fracture), develops on the interface where the stress is presumed to decrease according to a displacement-weakening constitutive relation. Upon reaching the instability point at which no further quasi-static solution for the extension of the crack on the interface exists, dynamic fracture follows. For the investigation of this instability point, we employ a dimensional analysis as well as an energy approach that gives a Rayleigh-Ritz approximation for the dependence of crack size and maximum displacement discontinuity on the level and quadratic shape of the loading stress distribution. We show that, if the linear displacement-weakening law is applied and the crack may be assumed of an elliptical form, the critical crack size at instability is independent of the curvature of the loading stress distribution and it is of the same order for all two- and three-dimensional cases.

Application of chaotic ant swarm optimization in electric load forecasting

International Nuclear Information System (INIS)

Hong, W.-C.

2010-01-01

Support vector regression (SVR) had revealed strong potential in accurate electric load forecasting, particularly by employing effective evolutionary algorithms to determine suitable values of its three parameters. Based on previous research results, however, these employed evolutionary algorithms themselves have several drawbacks, such as converging prematurely, reaching slowly the global optimal solution, and trapping into a local optimum. This investigation presents an SVR-based electric load forecasting model that applied a novel algorithm, namely chaotic ant swarm optimization (CAS), to improve the forecasting performance by searching its suitable parameters combination. The proposed CAS combines with the chaotic behavior of single ant and self-organization behavior of ant colony in the foraging process to overcome premature local optimum. The empirical results indicate that the SVR model with CAS (SVRCAS) results in better forecasting performance than the other alternative methods, namely SVRCPSO (SVR with chaotic PSO), SVRCGA (SVR with chaotic GA), regression model, and ANN model.

The origin of double peak electric field distribution in heavily irradiated silicon detectors

CERN Document Server

Eremin, V; Li, Z

2002-01-01

The first observation of double peak (DP) electric field distribution in heavily neutron irradiated (>10 sup 1 sup 4 n/cm sup 2) semiconductor detectors has been published about 6 yr ago. However, this effect was not quantitatively analyzed up to now. The explanation of the DP electric field distribution presented in this paper is based on the properties of radiation induced deep levels in silicon, which act as deep traps, and on the distribution of the thermally generated free carrier concentration in the detector bulk. In the frame of this model, the earlier published considerations on the so-called 'double junction (DJ) effect' are discussed as well. The comparison of the calculated electric field profiles at different temperatures with the experimental ones allows one to determine a set of deep levels. This set of deep levels, and their charge filling status are essential to the value and the distribution of space charge in the space charge region in the range of 305-240 K, which is actual temperature ran...

Impact of energy storage in buildings on electricity demand side management

International Nuclear Information System (INIS)

Qureshi, Waqar A.; Nair, Nirmal-Kumar C.; Farid, Mohammad M.

2011-01-01

Research highlights: → Phase change material (PCM) application for space heating has been implemented and assessed for built environment. → Real-Time Pricing (RTP) is assessed as tool to implement Demand Side Management programs effectively. → Two buildings, with and without PCM, have been compared for space heating using RTP in functional electricity market. → PCM found to offer peak load shifting, energy conservation, and reduction in price of electricity. -- Abstract: This paper assesses impact of using phase change materials (PCM) in buildings to leverage its thermal energy storage capability. The emphasis is from an electricity demand side perspective with case studies that incorporates wholesale electricity market data of New Zealand. The results presented in this paper show that for space heating application significant advantages could be obtained using PCM built structures. These positive impacts include peak load shifting, energy conservation and reduction in peak demand for network line companies and potential reduction in electricity consumption and savings for residential customers. This paper uses a testing facility that consists of two identically designed and shaped offices built at Tamaki Campus location of the University of Auckland, New Zealand. The walls and ceilings of one office are finished with ordinary gypsum boards while the interior of the other office is finished with PCM impregnated gypsum boards. Controlled heating facility is provided in both the offices for maintaining temperature within the range of human comfort. This facility is equipped with advanced data acquisition equipment for data monitoring and archiving both locally within the offices and also remotely. Through actual observations and analysis this paper demonstrates two major impacts of DSM. First, the application of phase change material (PCM) in building environment enabling efficient thermal storage to achieve some reduction in the overall electrical energy

Cost-reflective electricity pricing: Consumer preferences and perceptions

International Nuclear Information System (INIS)

Hall, Nina L.; Jeanneret, Talia D.; Rai, Alan

2016-01-01

In Australia, residential electricity peak demand has risen steeply in recent decades, leading to higher prices as new infrastructure was needed to satisfy demand. One way of limiting further infrastructure-induced retail price rises is via ‘cost-reflective’ electricity network pricing that incentivises users to shift their demand to non-peak periods. Empowering consumers with knowledge of their energy usage is critical to maximise the potential benefits of cost-reflective pricing. This research consulted residential electricity consumers in three Australian states on their perceptions and acceptance of two cost-reflective pricing scenarios (Time-of-Use and Peak Capacity pricing) and associated technologies to support such pricing (smart meters, in-home displays and direct load control devices). An energy economist presented information to focus groups on the merits and limitations of each scenario, and participants’ views were captured. Almost half of the 53 participants were agreeable to Time-of-Use pricing, but did not have a clear preference for Peak Capacity pricing, where the price was based on the daily maximum demand. Participants recommended further information to both understand and justify the potential benefits, and for technologies to be introduced to enhance the pricing options. The results have implications for utilities and providers who seek to reduce peak demand. - Highlights: •Electricity price rises can be limited by ‘cost-reflective’ pricing. •We consulted residential electricity consumers on Time-of-Use and Peak Capacity pricing. •Understanding of peak electricity demand must increase to enable demand shift. •Interactive website could enable consumers to evaluate pricing options. •Smart meter adoption may increase if voluntary and includes an in-home display.

Decreasing fuel cost weight in electric utility business. ; Urged peak measures and management constitution improvement. Denki jigyo no nenryohi weight wa gensho. ; Isogareru peak taisaku to keiei taishitsu kaizen

Energy Technology Data Exchange (ETDEWEB)

1993-09-01

The electric power industry has made stable and economic power supply possible by advancing diversification in power sources and shifting the petroleum supply sources to southern countries and China. The cost constitution of the electric utility business in the fiscal year 1992 was such that the ratio of fuel cost is 15.9% against the total cost amount of 13 trillion 399.3 billion yen. As opposed, the fuel cost percent in the fiscal 1980 was 37.7%. This means that the effect of the fuel cost on the total cost has become smaller even if the fuel cost varies as a result of external factors including fluctuation in foreign exchange rates. Peaks in the power demand have been recorded in day time in high summer when air conditioning demand increases, which have been growing year after year. Expenses to maintain facilities and functions to deal with this demand increase have been increasing. The owned capital ratio in the electric power business was 15.7% in the fiscal 1992, which is by far lower than the average of whole industry of 28%. Execution of measures against the power peaks and improvement of the management constitution are the problems posed on the electric power industry. 4 figs., 1 tab.

Impacts of Commercial Building Controls on Energy Savings and Peak Load Reduction

Energy Technology Data Exchange (ETDEWEB)

Fernandez, Nicholas E.P. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Katipamula, Srinivas [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wang, Weimin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Xie, YuLong [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhao, Mingjie [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Corbin, Charles D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2017-05-30

Commercial buildings in the United States use about 18 Quadrillion British thermal units (Quads) of primary energy annually . Studies have shown that as much as 30% of building energy consumption can be avoided by using more accurate sensing, using existing controls better, and deploying advanced controls; hence, the motivation for the work described in this report. Studies also have shown that 10% to 20% of the commercial building peak load can be temporarily managed/curtailed to provide grid services. Although many studies have indicated significant potential for reducing the energy consumption in commercial buildings, very few have documented the actual savings. The studies that did so only provided savings at the whole building level, which makes it difficult to assess the savings potential of each individual measure deployed.

Electrical engineering unit for the reactive power control of the load bus at the voltage instability

Science.gov (United States)

Kotenev, A. V.; Kotenev, V. I.; Kochetkov, V. V.; Elkin, D. A.

2018-01-01

For the purpose of reactive power control error reduction and decrease of the voltage sags in the electric power system caused by the asynchronous motors started the mathematical model of the load bus was developed. The model was built up of the sub-models of the following elements: a transformer, a transmission line, a synchronous and an asynchronous loads and a capacitor bank load, and represents the automatic reactive power control system taking into account electromagnetic processes of the asynchronous motors started and reactive power changing of the electric power system elements caused by the voltage fluctuation. The active power/time and reactive power/time characteristics based on the recommended procedure of the equivalent electric circuit parameters calculation were obtained. The derived automatic reactive power control system was shown to eliminate the voltage sags in the electric power system caused by the asynchronous motors started.

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

Science.gov (United States)

Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

1996-01-01

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the

Residential response to voluntary time-of-use electricity rates

Energy Technology Data Exchange (ETDEWEB)

Mostafa Baladi, S. [Laurits R. Christensen Associates, Inc. Ames, IA 50011-1070 (United States); Herriges, Joseph A. [Iowa State University, 280D Heady Hall, Department of Economics, Iowa State University, Ames, IA 50011-1070 (United States); Sweeney, Thomas J. [MidAmerican Energy, Des Moines, Iowa (United States)

1998-09-01

The response of residential households to voluntary Time-of-Use (TOU) electricity rates is estimated using data from a recent experiment at Midwest Power Systems of Iowa. The study`s design allows us to examine both the participation decision and the customer`s load pattern changes once the TOU rate structure was in effect. Substitution elasticities between on-peak and off-peak electricity usage are estimated and compared to those obtained in earlier mandatory programs, indicating whether program volunteers are more responsive to TOU pricing than the typical household. Attitudinal questionnaires allow us to examine the role of usage perceptions in program participation

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.

Modelling of electric characteristics of 150-watt peak solar panel using Boltzmann sigmoid function under various temperature and irradiance

Science.gov (United States)

Sapteka, A. A. N. G.; Narottama, A. A. N. M.; Winarta, A.; Amerta Yasa, K.; Priambodo, P. S.; Putra, N.

2018-01-01

Solar energy utilized with solar panel is a renewable energy that needs to be studied further. The site nearest to the equator, it is not surprising, receives the highest solar energy. In this paper, a modelling of electrical characteristics of 150-Watt peak solar panels using Boltzmann sigmoid function under various temperature and irradiance is reported. Current, voltage, temperature and irradiance data in Denpasar, a city located at just south of equator, was collected. Solar power meter is used to measure irradiance level, meanwhile digital thermometer is used to measure temperature of front and back panels. Short circuit current and open circuit voltage data was also collected at different temperature and irradiance level. Statistically, the electrical characteristics of 150-Watt peak solar panel can be modelled using Boltzmann sigmoid function with good fit. Therefore, it can be concluded that Boltzmann sigmoid function might be used to determine current and voltage characteristics of 150-Watt peak solar panel under various temperature and irradiance.

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

Investigation of control system of traction electric drive with feedbacks on load

Science.gov (United States)

Kuznetsov, N. K.; Iov, I. A.; Iov, A. A.

2018-03-01

In the article, by the example of a walking excavator, the results of a study of a control system of traction electric drive with a rigid and flexible feedback on the load are mentioned. Based on the analysis of known works, the calculation scheme has been chosen; the equations of motion of the electromechanical system have been obtained, taking into account the elasticity of the rope and feedbacks on the load in the elastic element. A simulation model of this system has been developed and mathematical modeling of the transient processes to evaluate the influence of feedback on the dynamic characteristics of the mechanism and its efficiency of work was carried out. It is shown that the use of rigid and flexible feedbacks makes it possible to reduce dynamic loads in the traction mechanism and to limit the elastic oscillation of the executive mechanism in transient operating modes in comparison with the standard control system; however, there is some decrease in productivity. It has been also established that the sign-variable of the loading of the electric drive, connected with the opening of the backlashes in the gearbox due to the action of feedbacks on the load in the elastic element, under certain conditions, can lead to undesirable phenomena in the operation of the drive and a decrease in the reliability of its operation.

Short-term electric load forecasting using computational intelligence methods

OpenAIRE

Jurado, Sergio; Peralta, J.; Nebot, Àngela; Mugica, Francisco; Cortez, Paulo

2013-01-01

Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregressive Neural Networks, Evolutionary Support Vector Machines and Fuzzy Inductive Reasoning. The performance of the suggested methods is experimentally justified with several experiments carried out...

Electric vehicle charging to support renewable energy integration in a capacity constrained electricity grid

International Nuclear Information System (INIS)

Pearre, Nathaniel S.; Swan, Lukas G.

2016-01-01

Highlights: • Examination of EV charging in a wind rich area with transmission constraints. • Multiple survey instruments to determine transportation needs, when charging occurs. • Simple charging, time-of-day scheduled, and ideal smart charging investigated. • Export power peaks reduced by 2% with TOD, 10% with smart charging 10% of fleet. • Smart charging EVs enables enough added wind capacity to power the fleet. - Abstract: Digby, Nova Scotia, is a largely rural area with a wealth of renewable energy resources, principally wind and tidal. Digby’s electrical load is serviced by an aging 69 kV transmission line that often operates at the export capacity limit because of a local wind energy converter (WEC) field. This study examines the potential of smart charging of electric vehicles (EVs) to achieve two objectives: (1) add load so as to increase export capacity; (2) charge EVs using renewable energy. Multiple survey instruments were used to determine transportation energy needs and travel timing. These were used to create EV charging load timeseries based on “convenience”, “time-of-day”, and idealized “smart” charging. These charging scenarios were evaluated in combination with high resolution data of generation at the wind field, electrical flow through the transmission system, and electricity load. With a 10% adoption rate of EVs, time-of-day charging increased local renewable energy usage by 20% and enables marginal WEC upgrading. Smart charging increases charging by local renewable energy by 73%. More significantly, it adds 3 MW of load when power exports face constraints, allowing enough additional renewable electricity generation capacity to fully power those vehicles.

The consumption of electricity in Deep River

International Nuclear Information System (INIS)

Phillips, G.J.

1981-08-01

This report records the development of the use of electricity in the Town of Deep River, Ontario since its incorporation in 1958. Electricity use is expressed as peak power demand, and as energy use by various classes of customers. Relevant data on population, weather and fuel prices are included. The accelerating displacment of fuel oil by electricity as an energy source for space heating is clearly demonstrated. The study was undertaken to document the effects of a large and rapidly growing seasonal load on the operation of a small electrical utility, and to provide background information for an experimental study of hybrid oil/electric space heating

Peak electricity demand and social practice theories: Reframing the role of change agents in the energy sector

International Nuclear Information System (INIS)

Strengers, Yolande

2012-01-01

Demand managers currently draw on a limited range of psychology and economic theories in order to shift and shed peak electricity demand. These theories place individual consumers and their attitudes, behaviours and choices at the centre of the problem. This paper reframes the issue of peak electricity demand using theories of social practices, contending that the ‘problem’ is one of transforming, technologically-mediated social practices. It reflects on how this body of theory repositions and refocuses the roles and practices of professions charged with the responsibility and agency for affecting and managing energy demand. The paper identifies three areas where demand managers could refocus their attention: (i) enabling co-management relationships with consumers; (ii) working beyond their siloed roles with a broader range of human and non-human actors; and (iii) promoting new practice ‘needs’ and expectations. It concludes by critically reflecting on the limited agency attributed to ‘change agents’ such as demand managers in dominant understandings of change. Instead, the paper proposes the need to identify and establish a new group of change agents who are actively but often unwittingly involved in reconfiguring the elements of problematic peaky practices. - Highlights: ► I reframe peak electricity demand as a problem of changing social practices. ► Micro-grids, and dynamic pricing reorient household routines and enable co-management. ► Infrastructures inside and outside the home configure peaky practices. ► Demand managers are encouraged to promote and challenge consumer ‘needs’. ► I identify a new group of change agents implicated in peaky practices.

Analysis of electric vehicle impacts in New Mexico urban utility distribution infrastructure.

Energy Technology Data Exchange (ETDEWEB)

Arellano, B. [Public Utility Service Company of New Mexico, Albuquerque, NM (United States); Sena, Santiago [Univ. of New Mexico, Albuquerque, NM (United States); Lavrova, Olga [Univ. of New Mexico, Albuquerque, NM (United States); Stratton, S. [Public Utility Service Company of New Mexico, Albuquerque, NM (United States); Abdollahy, S. [Univ. of New Mexico, Albuquerque, NM (United States); Hawkins, J. [Public Utility Service Company of New Mexico, Albuquerque, NM (United States)

2013-06-16

Modeling is going to play a crucial role for utilities as Electric Vehicle (EV) ownership percentage increases. Utilities anticipate new demand peaks due to EV charging loads, particularly at high penetration levels.

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)

Leveling of battery load and extension of battery life by serial connection of electric double layer capacitors with batteries for electric vehicles. Experimental results on the small model; Denki jidoshayo denchi to denki nijuso capacitor no chokuretsu setsuzoku ni yoru denchi futan no heijunka oyobi denchijumyo no enshinka. (kogata model ni yoru jikken seika). Kogata model ni yoru jikken seika

Energy Technology Data Exchange (ETDEWEB)

Takehara, J.; Okubo, N.; Miyaoka, K. [Chugoku Electric Power Co. Inc., Hiroshima (Japan)

1996-10-25

The load leveling method of batteries for electric vehicles was studied for extension of a battery life and mileage every charging. Under large load fluctuation conditions such as deceleration and acceleration, use of electric power sources other than battery for peek load at acceleration can improve a battery life, output power capacity and mileage every charging. Combination of effective recovery of regenerative power at deceleration with its discharge at acceleration is one of the effective methods. The electric double layer capacitors are serially connected with the batteries, regenerative power is charged only into the capacitors, and both voltages of the battery and capacitor are applied to a power circuit. Battery load is reduced by load on the capacitor. Until the capacitor is re-charged by regenerative power after full discharge, power is supplied only by battery through a diode. Capacitor power is used as effectively as possible until approaching considerably low voltage. As peak load of the battery is reduced by 30%, the mileage increases by 5.7%, and the battery cycle life becomes 1.5 times longer. 7 refs., 5 figs., 3 tabs.

Mean Velocity vs. Mean Propulsive Velocity vs. Peak Velocity: Which Variable Determines Bench Press Relative Load With Higher Reliability?

Science.gov (United States)

García-Ramos, Amador; Pestaña-Melero, Francisco L; Pérez-Castilla, Alejandro; Rojas, Francisco J; Gregory Haff, G

2018-05-01

García-Ramos, A, Pestaña-Melero, FL, Pérez-Castilla, A, Rojas, FJ, and Haff, GG. Mean velocity vs. mean propulsive velocity vs. peak velocity: which variable determines bench press relative load with higher reliability? J Strength Cond Res 32(5): 1273-1279, 2018-This study aimed to compare between 3 velocity variables (mean velocity [MV], mean propulsive velocity [MPV], and peak velocity [PV]): (a) the linearity of the load-velocity relationship, (b) the accuracy of general regression equations to predict relative load (%1RM), and (c) the between-session reliability of the velocity attained at each percentage of the 1-repetition maximum (%1RM). The full load-velocity relationship of 30 men was evaluated by means of linear regression models in the concentric-only and eccentric-concentric bench press throw (BPT) variants performed with a Smith machine. The 2 sessions of each BPT variant were performed within the same week separated by 48-72 hours. The main findings were as follows: (a) the MV showed the strongest linearity of the load-velocity relationship (median r = 0.989 for concentric-only BPT and 0.993 for eccentric-concentric BPT), followed by MPV (median r = 0.983 for concentric-only BPT and 0.980 for eccentric-concentric BPT), and finally PV (median r = 0.974 for concentric-only BPT and 0.969 for eccentric-concentric BPT); (b) the accuracy of the general regression equations to predict relative load (%1RM) from movement velocity was higher for MV (SEE = 3.80-4.76%1RM) than for MPV (SEE = 4.91-5.56%1RM) and PV (SEE = 5.36-5.77%1RM); and (c) the PV showed the lowest within-subjects coefficient of variation (3.50%-3.87%), followed by MV (4.05%-4.93%), and finally MPV (5.11%-6.03%). Taken together, these results suggest that the MV could be the most appropriate variable for monitoring the relative load (%1RM) in the BPT exercise performed in a Smith machine.

Computerized optimum distribution of loads among the turbogenerators of fossil-fuel electric power plants

Energy Technology Data Exchange (ETDEWEB)

Foshko, L S; Zusmanovich, L B; Flos, S L; Pal' chik, V A; Konevskii, B I

1979-04-01

The problem of determining the optimum distribution of loads among turbogenerators in a fossil-fuel power plant is considered based on satisfying the following requirements: distribution of electrical and thermal loads to minimize the heat expended on the turbine unit; calculation based on turbogenerator characteristics that most completely describe operating conditions; no constraints on the configuration of turbogenerator performance characteristics; calculation of load distribution based on net characteristics including the internal needs of the turbogenerators; consideration of all operational limitations in turbogenerator working conditions; results should be applicable to any predetermined differential of the load change. A flowchart is given showing the organization of the Optim-76 program complex for solution of this problem. An example is given showing application of the Optim-76 program implemented by a Minsk-32 computer in the case of a heat and electric power station with three turbogenerators. The results show that a dynamic programming method has considerable advantages for this applicaton on third-generation computers.

Gait Planning Research for an Electrically Driven Large-Load-Ratio Six-Legged Robot

Directory of Open Access Journals (Sweden)

Hong-Chao Zhuang

2017-03-01

Full Text Available Gait planning is an important basis for the walking of a legged robot. To improve the walking stability of multi-legged robots and to reduce the impact force between the foot and the ground, gait planning strategies are presented for an electrically driven large-load-ratio six-legged robot. First, the configuration and walking gait of the electrically driven large-load-ratio six-legged robot are designed. The higher-stable swing sequences of legs and typical walking modes are respectively obtained. Based on the Denavit–Hartenberg (D–H method, the analyses of the forward and inverse kinematics are implemented. The mathematical models of the articulated rotation angles are respectively established. In view of the buffer device installed at the end of shin to decrease the impact force between the foot and the ground, an initial lift height of the leg is brought into gait planning when the support phase changes into the transfer phase. The mathematical models of foot trajectories are established. Finally, a prototype of the electrically driven large-load-ratio six-legged robot is developed. The experiments of the prototype are carried out regarding the aspects of the walking speed and surmounting obstacle. Then, the reasonableness of gait planning is verified based on the experimental results. The proposed strategies of gait planning lay the foundation for effectively reducing the foot–ground impact force and can provide a reference for other large-load-ratio multi-legged robots.

Superconducting magnetic energy storage for electric utilities and fusion systems

International Nuclear Information System (INIS)

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

1978-01-01

Superconducting inductors provide a compact and efficient means of storing electrical energy without an intermediate conversion process. Energy storage inductors are under development for load leveling and transmission line stabilization in electric utility systems and for driving magnetic confinement and plasma heating coils in fusion energy systems. Fluctuating electric power demands force the electric utility industry to have more installed generating capacity than the average load requires. Energy storage can increase the utilization of base-load fossil and nuclear power plants for electric utilities. The Los Alamos Scientific Laboratory and the University of Wisconsin are developing superconducting magnetic energy storage (SMES) systems, which will store and deliver electrical energy for load leveling, peak shaving, and the stabilization of electric utility networks. In the fusion area, inductive energy transfer and storage is being developed. Both 1-ms fast-discharge theta-pinch systems and 1-to-2-s slow energy transfer tokamak systems have been demonstrated. The major components and the method of operation of a SMES unit are described, and potential applications of different size SMES systems in electric power grids are presented. Results are given of a reference design for a 10-GWh unit for load leveling, of a 30-MJ coil proposed for system stabilization, and of tests with a small-scale, 100-kJ magnetic energy storage system. The results of the fusion energy storage and transfer tests are presented. The common technology base for the various storage systems is discussed

Effects of squat lift training and free weight muscle training on maximum lifting load and isolinetic peak torque of young adults without impairments.

Science.gov (United States)

Yeung, S S; Ng, G Y

2000-06-01

Manual lifting is a frequent cause of back injury, and there is no evidence as to which training mode can provide the best training effect for lifting performance and muscle force. The purpose of this study was to examine the effects of a squat lift training and a free weight muscle training program on the maximum lifting load and isokinetic peak torque in subjects without known neuromuscular or musculoskeletal impairments. Thirty-six adults (20 male, 16 female) without known neuromuscular or musculoskeletal impairments participated. The subjects' mean age was 21.25 years (SD=1.16, range=20-24). Subjects were divided into 3 groups. Subjects in group 1 (n=12) performed squat lift training. Subjects in group 2 (n=12) participated in free weight resistance training of their shoulder abductors, elbow flexors, knee extensors and trunk extensors. Subjects in group 3 (n=12) served as controls. The maximum lifting load and isokinetic peak torques of the trunk extensors, knee extensors, elbow flexors, and shoulder abductors of each subject were measured before and after the study. Training was conducted on alternate days for 4 weeks, with an initial load of 80% of each subject's maximum capacity and with the load increased by 5% weekly. All groups were comparable for all measured variables before the study. After 4 weeks, subjects in groups 1 and 2 demonstrated more improvement in maximum lifting load and isokinetic peak torque of the back extensors compared with the subjects in group 3, but the 2 training groups were not different. The findings demonstrate that both squat lift and free weight resistance training are equally effective in improving the lifting load and isokinetic back extension performance of individuals without impairments.

Power quality load management for large spacecraft electrical power systems

Science.gov (United States)

Lollar, Louis F.

1988-01-01

In December, 1986, a Center Director's Discretionary Fund (CDDF) proposal was granted to study power system control techniques in large space electrical power systems. Presented are the accomplishments in the area of power system control by power quality load management. In addition, information concerning the distortion problems in a 20 kHz ac power system is presented.

Determining the Interruptible Load with Strategic Behavior in a Competitive Electricity Market

Directory of Open Access Journals (Sweden)

Tae Hyun Yoo

2014-12-01

Full Text Available In a deregulated market, independent system operators meet power balance based on supply and demand bids to maximize social welfare. Since electricity markets are typically oligopolies, players with market power may withhold capacity to maximize profit. Such exercise of market power can lead to various problems, including increased electricity prices, and hence lower social welfare. Here we propose an approach to maximize social welfare and prevent the exercising of market power by means of interruptible loads in a competitive market environment. Our approach enables management of the market power by analyzing the benefit to the companies of capacity withdrawal and scheduling resources with interruptible loads. Our formulation shows that we can prevent power companies and demand-resource owners from exercising market powers. The oligopolistic conditions are described using the Cournot model to reflect the capacity withdrawal in electricity markets. The numerical results confirm the effectiveness of proposed method, via a comparison of perfect competition and oligopoly scenarios. Our approach provides reductions in market-clearing prices, increases in social welfare, and more equal distribution of surpluses between players.

Monitoring and Characterization of Miscellaneous Electrical Loads in a Large Retail Environment

Energy Technology Data Exchange (ETDEWEB)

Gentile-Polese, L. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Frank, S. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sheppy, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lobato, C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Rader, E. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Smith, J. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Long, N. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2014-02-01

Buildings account for 40% of primary energy consumption in the United States (residential 22%; commercial 18%). Most (70% residential and 79% commercial) is used as electricity. Thus, almost 30% of U.S. primary energy is used to provide electricity to buildings. Plug loads play an increasingly critical role in reducing energy use in new buildings (because of their increased efficiency requirements), and in existing buildings (as a significant energy savings opportunity). If all installed commercial building miscellaneous electrical loads (CMELs) were replaced with energy-efficient equipment, a potential annual energy saving of 175 TWh, or 35% of the 504 TWh annual energy use devoted to MELs, could be achieved. This energy saving is equivalent to the annual energy production of 14 average-sized nuclear power plants. To meet DOE's long-term goals of reducing commercial building energy use and carbon emissions, the energy efficiency community must better understand the components and drivers of CMEL energy use, and develop effective reduction strategies. These goals can be facilitated through improved data collection and monitoring methodologies, and evaluation of CMELs energy-saving techniques.

Regulation of unbalanced electromagnetic moment in mutual loading systems of electric machines of traction rolling stock and multiple unit of mainline and industrial transport

Directory of Open Access Journals (Sweden)

A. M. Afanasov

2014-12-01

Full Text Available Purpose. The research data are aimed to identify the regulatory principles of unbalanced electromagnetic moment of mutually loaded electric machines of traction rolling stock and multiple unit of main and industrial transport. The purpose of this study is energy efficiency increase of the testing of traction electric machines of direct and pulse current using the improvement methods of their mutual loading, including the principles of automatic regulation of mutual loading system. Methodology. The general theoretical provisions and principles of system approach to the theoretical electric engineering, the theory of electric machines and theoretical mechanics are the methodological basis of this research. The known methods of analysis of electromagnetic and electromechanical processes in electrical machines of direct and pulse current are used in the study. Methods analysis of loading modes regulation of traction electric machines was conducted using the generalized scheme of mutual loading. It is universal for all known methods to cover the losses of idling using the electric power. Findings. The general management principles of mutual loading modes of the traction electric machines of direct and pulse current by regulating their unbalanced electric magnetic moment were developed. Regulatory options of unbalanced electromagnetic moment are examined by changing the difference of the magnetic fluxes of mutually loaded electric machines, the current difference of electric machines anchors, the difference of the angular velocities of electric machines shafts. Originality. It was obtained the scientific basis development to improve the energy efficiency test methods of traction electric machines of direct and pulse current. The management principles of mutual loading modes of traction electric machines were formulated. For the first time it is introduced the concept and developed the principles of regulation of unbalanced electromagnetic moment in

Experimental Evaluation of Simple Thermal Storage Control Strategies in Low-Energy Solar Houses to Reduce Electricity Consumption during Grid On-Peak Periods

Directory of Open Access Journals (Sweden)

Kyoung-Ho Lee

2015-08-01

Full Text Available There is growing interest in zero-energy and low-energy buildings, which have a net energy consumption (on an annual basis of almost zero. Because they can generate both electricity and thermal energy through the use of solar photovoltaic (PV and solar thermal collectors, and with the help of reduced building thermal demand, low-energy buildings can not only make a significant contribution to energy conservation on an annual basis, but also reduce energy consumption and peak demand. This study focused on electricity consumption during the on-peak period in a low-energy residential solar building and considers the use of a building’s thermal mass and thermal storage to reduce electricity consumption in summer and winter by modulation of temperature setpoints for heat pump and indoor thermostats in summer and additional use of a solar heating loop in winter. Experiments were performed at a low-energy solar demonstration house that has solar collectors, hot water storage, a ground-coupled heat pump, and a thermal storage tank. It was assumed that the on-peak periods were from 2 pm to 5 pm on hot summer days and from 5 pm to 8 pm on cold winter days. To evaluate the potential for utilizing the building’s thermal storage capacity in space cooling and heating, the use of simple control strategies on three test days in summer and two test days in the early spring were compared in terms of net electricity consumption and peak demand, which also considered the electricity generation from solar PV modules on the roof of the house.

1991 Pacific Northwest loads and resources study, Pacific Northwest economic and electricity use forecast

International Nuclear Information System (INIS)

1992-01-01

This publication provides detailed documentation of the load forecast scenarios and assumptions used in preparing BPA's 1991 Pacific Northwest Loads and Resources Study (the Study). This is one of two technical appendices to the Study; the other appendix details the utility-specific loads and resources used in the Study. The load forecasts and assumption were developed jointly by Bonneville Power Administration (BPA) and Northwest Power Planning Council (Council) staff. This forecast is also used in the Council's 1991 Northwest Conservation and Electric Power Plan (1991 Plan)

An electrical betweenness approach for vulnerability assessment of power grids considering the capacity of generators and load

Science.gov (United States)

Wang, Kai; Zhang, Bu-han; Zhang, Zhe; Yin, Xiang-gen; Wang, Bo

2011-11-01

Most existing research on the vulnerability of power grids based on complex networks ignores the electrical characteristics and the capacity of generators and load. In this paper, the electrical betweenness is defined by considering the maximal demand of load and the capacity of generators in power grids. The loss of load, which reflects the ability of power grids to provide sufficient power to customers, is introduced to measure the vulnerability together with the size of the largest cluster. The simulation results of the IEEE-118 bus system and the Central China Power Grid show that the cumulative distributions of node electrical betweenness follow a power-law and that the nodes with high electrical betweenness play critical roles in both topological structure and power transmission of power grids. The results prove that the model proposed in this paper is effective for analyzing the vulnerability of power grids.

Electric load forecasting by seasonal recurrent SVR (support vector regression) with chaotic artificial bee colony algorithm

International Nuclear Information System (INIS)

Hong, Wei-Chiang

2011-01-01

Support vector regression (SVR), with hybrid chaotic sequence and evolutionary algorithms to determine suitable values of its three parameters, not only can effectively avoid converging prematurely (i.e., trapping into a local optimum), but also reveals its superior forecasting performance. Electric load sometimes demonstrates a seasonal (cyclic) tendency due to economic activities or climate cyclic nature. The applications of SVR models to deal with seasonal (cyclic) electric load forecasting have not been widely explored. In addition, the concept of recurrent neural networks (RNNs), focused on using past information to capture detailed information, is helpful to be combined into an SVR model. This investigation presents an electric load forecasting model which combines the seasonal recurrent support vector regression model with chaotic artificial bee colony algorithm (namely SRSVRCABC) to improve the forecasting performance. The proposed SRSVRCABC employs the chaotic behavior of honey bees which is with better performance in function optimization to overcome premature local optimum. A numerical example from an existed reference is used to elucidate the forecasting performance of the proposed SRSVRCABC model. The forecasting results indicate that the proposed model yields more accurate forecasting results than ARIMA and TF-ε-SVR-SA models. Therefore, the SRSVRCABC model is a promising alternative for electric load forecasting. -- Highlights: → Hybridizing the seasonal adjustment and the recurrent mechanism into an SVR model. → Employing chaotic sequence to improve the premature convergence of artificial bee colony algorithm. → Successfully providing significant accurate monthly load demand forecasting.

Energy Saving by Chopping off Peak Demand Using Day Light

Directory of Open Access Journals (Sweden)

Ashok Kumar Maitra

2011-08-01

Full Text Available An artificial intelligent technique has been implemented in this research using real time datas to calculate how much energy can be chopped from peak load demand. The results are based on real time data that are taken from power delivering centers. These datas do reflect the present condition of power and a solution to those critical conditions during the peak period. These are done in such a way such that helps in judicious scheduling of load. The time based load scheduling has been done so as to understand the basic criteria for solving power crisis during morning peak and early evening peak. The sunray availability and percentage of load that will use day light saving (DLS technique has been taken into account in this work. The results shows that about 0.5% to 1% of load can be shedded off from the peak load period which otherwise is reduction of power. Thus it otherwise also means that an equivalent amount of energy is saved which amounts to a large saving of national money. This result is obtained on monthly and even daily basis. Thus this paper justifies DLS gives a new renewable technique to save energy.

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

Directory of Open Access Journals (Sweden)

Jinchao Li

2018-01-01

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

Barriers to electricity load shift in companies: A survey-based exploration of the end-user perspective

International Nuclear Information System (INIS)

Olsthoorn, Mark; Schleich, Joachim; Klobasa, Marian

2015-01-01

As countries move toward larger shares of renewable electricity, the slow diffusion of active electricity load management should concern energy policy makers and users alike. Active load management can increase capacity factors and thereby reduce the need for new capacity, improve reliability, and lower electricity prices. This paper conceptually and empirically explores barriers to load shift in industry from an end-user perspective. An online survey, based on a taxonomy of barriers developed in the realm of energy efficiency, was carried out among manufacturing sites in mostly Southern Germany. Findings suggest that the most important barriers are risk of disruption of operations, impact on product quality, and uncertainty about cost savings. Of little concern are access to capital, lack of employee skills, and data security. Statistical tests suggest that companies for which electricity has higher strategic value rate financial and regulatory risk higher than smaller ones. Companies with a continuous production process report lower barrier scores than companies using batch or just-in-time production. A principal component analysis clusters the barriers and multivariate analysis with the factor scores confirms the prominence of technical risk as a barrier to load shift. The results provide guidance for policy making and future empirical studies. - Highlights: • We quantitatively assess barriers to load shift adoption among manufacturing firms. • Conceptually, we build on the literature on barriers to energy efficiency. • The most important barriers are interference with production and with product quality. • Companies with a continuous production process report lower barrier scores. • The barriers to load shift may be organized in distinct clusters via principal component analysis

Lightweight Battery Charge Regulator Used to Track Solar Array Peak Power

Science.gov (United States)

Soeder, James F.; Button, Robert M.

1999-01-01

A battery charge regulator based on the series-connected boost regulator (SCBR) technology has been developed for high-voltage spacecraft applications. The SCBR regulates the solar array power during insolation to prevent battery overcharge or undercharge conditions. It can also be used to provide regulated battery output voltage to spacecraft loads if necessary. This technology uses industry-standard dc-dc converters and a unique interconnection to provide size, weight, efficiency, fault tolerance, and modularity benefits over existing systems. The high-voltage SCBR shown in the photograph has demonstrated power densities of over 1000 watts per kilogram (W/kg). Using four 150-W dc-dc converter modules, it can process 2500 W of power at 120 Vdc with a minimum input voltage of 90 Vdc. Efficiency of the SCBR was 94 to 98 percent over the entire operational range. Internally, the unit is made of two separate SCBR s, each with its own analog control circuitry, to demonstrate the modularity of the technology. The analog controllers regulate the output current and incorporate the output voltage limit with active current sharing between the two units. They also include voltage and current telemetry, on/off control, and baseplate temperature sensors. For peak power tracking, the SCBR was connected to a LabView-based data acquisition system for telemetry and control. A digital control algorithm for tracking the peak power point of a solar array was developed using the principle of matching the source impedance with the load impedance for maximum energy transfer. The algorithm was successfully demonstrated in a simulated spacecraft electrical system at the Boeing PhantomWorks High Voltage Test Facility in Seattle, Washington. The system consists of a 42-string, high-voltage solar array simulator, a 77-cell, 80-ampere-hour (A-hr) nickel-hydrogen battery, and a constant power-load module. The SCBR and the LabView control algorithm successfully tracked the solar array peak

Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads

DEFF Research Database (Denmark)

Ergemen, Yunus Emre; Haldrup, Niels; Rodríguez-Caballero, Carlos Vladimir

to strong seasonal periodicity, and along the cross-sectional dimension, i.e. the hours of the day, there is a strong dependence which necessarily has to be accounted for in order to avoid spurious inference when focusing on the time series dependence alone. The long-range dependence is modelled in terms...... of a fractionally integrated panel data model and it is shown that both prices and loads consist of common factors with long memory and with loadings that vary considerably during the day. Due to the competitiveness of the Nordic power market the aggregate supply curve approximates well the marginal costs...... data approaches to analyse the time series and the cross-sectional dependence of hourly Nord Pool electricity spot prices and loads for the period 2000-2013. Hourly electricity prices and loads data are characterized by strong serial long-range dependence in the time series dimension in addition...

Projected costs of nuclear and conventional base load electricity generation in some IAEA Member States

International Nuclear Information System (INIS)

1990-09-01

The cost of nuclear and conventional electricity is one of the most important parameters for power system planning, and in particular for decisions on base load power projects. This study reviews the projected levelized electricity generation costs of the base load power generation options expected to be available in the medium term, using an agreed common economic methodology. Cost projections were obtained and evaluated for nuclear and fossil fuelled (mainly coal-fired) plants that could be commissioned in the mid- to late 1990s in 10 IAEA Member States. 27 refs, figs and tabs

Public policy analysis of energy efficiency and load management in changing electricity businesses

International Nuclear Information System (INIS)

Vine, Edward; Hamrin, Jan; Eyre, Nick; Crossley, David; Maloney, Michelle; Watt, Greg

2003-01-01

The focus of this paper is (1) the potential effectiveness of the reform of the electricity industry on promoting energy efficiency and load management, and (2) the potential effectiveness of new mechanisms for promoting energy efficiency and load management. Many countries are initiating reforms of their power sectors to stimulate private investment, increase operation and management efficiencies, and lower the cost of power. These countries are unbundling vertically integrated utilities into distinct generation, transmission, distribution and retail supply companies; introducing commercial management principles to government-owned monopolies; and in many cases transferring operation or ownership to private companies. Electric industry restructuring may force regulators and policy makers to re-examine existing mechanisms for promoting load management and energy efficiency. In some cases, electric industry restructuring replaces the long-standing relationship between a single monopoly provider and protected customer franchise with a new set of relationships among retail electricity suppliers and customers who may now be free to choose suppliers. In these types of situations, markets, not government regulators and utility monopolies, are seen as determining future energy production and consumption decisions. However, it is uncertain whether this type of restructuring will overcome important market barriers to energy efficiency that limit markets for energy-efficient products and services from functioning effectively. As a result of these barriers, a large, untapped potential for cost-effective energy-efficiency investments exists. Supporters of public policies argue that energy-efficiency programs are an appropriate government strategy to capture economic efficiencies that the market cannot secure unassisted

Public policy analysis of energy efficiency and load management in changing electricity business

Energy Technology Data Exchange (ETDEWEB)

Vine, E. [Lawrence Berkeley National Laboratory, Berkeley, CA (United States). Energy Analysis Dept.; Hamrin, J. [Centre for Resource Solutions (United States); Eyre, N. [Energy Savings Trust (United Kingdom); Crossley, D.; Maloney, M.; Watt, G. [Energy Futures Australia Pty Ltd (Australia)

2003-04-01

The focus of this paper is (1) the potential effectiveness of the reform of the electricity industry on promoting energy efficiency and load management, and (2) the potential effectiveness of new mechanisms for promoting energy efficiency and load management. Many countries are initiating reforms of their power sectors to stimulate private investment, increase operation and management efficiencies, and lower the cost of power. These countries are unbundling vertically integrated utilities into distinct generation, transmission, distribution and retail supply companies; introducing commercial management principles to government-owned monopolies; and in many cases transferring operation or ownership to private companies. Electric industry restructuring may force regulators and policy makers to re-examine existing mechanisms for promoting load management and energy efficiency. In some cases, electric industry restructuring replaces the long-standing relationship between a single monopoly provider and protected customer franchise with a new set of relationships among retail electricity suppliers and customers who may now be free to choose suppliers. In these types of situations, markets, not government regulators and utility monopolies, are seen as determining future energy production and consumption decisions. However, it is uncertain whether this type of restructuring will overcome important market barriers to energy efficiency that limit markets for energy-efficient products and services from functioning effectively. As a result of these barriers, a large, untapped potential for cost-effective energy-efficiency investments exists. Supporters of public policies argue that energy-efficiency programs are an appropriate government strategy to capture economic efficiencies that the market cannot secure unassisted. (author)

Public policy analysis of energy efficiency and load management in changing electricity businesses