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

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...

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

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.

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.

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.

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

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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.

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

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

Internalizing carbon costs in electricity markets: Using certificates in a load-based emissions trading scheme

International Nuclear Information System (INIS)

Gillenwater, Michael; Breidenich, Clare

2009-01-01

Several western states have considered developing a regulatory approach to reduce greenhouse gas (GHG) emissions from the electric power industry, referred to as a load-based (LB) cap-and-trade scheme. A LB approach differs from the traditional source-based (SB) cap-and-trade approach in that the emission reduction obligation is placed upon Load Serving Entities (LSEs), rather than electric generators. The LB approach can potentially reduce the problem of emissions leakage, relative to a SB system. For any of these proposed LB schemes to be effective, they must be compatible with modern, and increasingly competitive, wholesale electricity markets. LSE's are unlikely to know the emissions associated with their power purchases. Therefore, a key challenge for a LB scheme is how to assign emissions to each LSE. This paper discusses the problems with one model for assigning emissions under a LB scheme and proposes an alternative, using unbundled Generation Emission Attribute Certificates. By providing a mechanism to internalize an emissions price signal at the generator dispatch level, the tradable certificate model addresses both these problems and provides incentives identical to a SB scheme

Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation

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Chan-Uk Yeom

2017-10-01

Full Text Available This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK-based ELM to develop a systematic approach to generating if-then rules, while the conventional ELM operates without knowledge information. The TSK-ELM design includes a two-phase development. First, we generate an initial random-partition matrix and estimate cluster centers for random clustering. The obtained cluster centers are used to determine the premise parameters of fuzzy if-then rules. Next, the linear weights of the TSK fuzzy type are estimated using the least squares estimate (LSE method. These linear weights are used as the consequent parameters in the TSK-ELM design. The experiments were performed on short-term electricity-load data for forecasting. The electricity-load data were used to forecast hourly day-ahead loads given temperature forecasts; holiday information; and historical loads from the New England ISO. In order to quantify the performance of the forecaster, we use metrics and statistical characteristics such as root mean squared error (RMSE as well as mean absolute error (MAE, mean absolute percent error (MAPE, and R-squared, respectively. The experimental results revealed that the proposed method showed good performance when compared with a conventional ELM with four activation functions such sigmoid, sine, radial basis function, and rectified linear unit (ReLU. It possessed superior prediction performance and knowledge information and a small number of rules.

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

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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.

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

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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.

Forecasting Strategies for Predicting Peak Electric Load Days

Science.gov (United States)

Saxena, Harshit

Academic institutions spend thousands of dollars every month on their electric power consumption. Some of these institutions follow a demand charges pricing structure; here the amount a customer pays to the utility is decided based on the total energy consumed during the month, with an additional charge based on the highest average power load required by the customer over a moving window of time as decided by the utility. Therefore, it is crucial for these institutions to minimize the time periods where a high amount of electric load is demanded over a short duration of time. In order to reduce the peak loads and have more uniform energy consumption, it is imperative to predict when these peaks occur, so that appropriate mitigation strategies can be developed. The research work presented in this thesis has been conducted for Rochester Institute of Technology (RIT), where the demand charges are decided based on a 15 minute sliding window panned over the entire month. This case study makes use of different statistical and machine learning algorithms to develop a forecasting strategy for predicting the peak electric load days of the month. The proposed strategy was tested for a whole year starting May 2015 to April 2016 during which a total of 57 peak days were observed. The model predicted a total of 74 peak days during this period, 40 of these cases were true positives, hence achieving an accuracy level of 70 percent. The results obtained with the proposed forecasting strategy are promising and demonstrate an annual savings potential worth about $80,000 for a single submeter of RIT.

Investigation of efficiency of electric drive control system of excavator traction mechanism based on feedback on load

Science.gov (United States)

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

2018-05-01

The article presents the results of a study of the efficiency of the electric drive control system of the traction mechanism of a dragline based on the use of feedback on load in the traction cable. The investigations were carried out using a refined electromechanical model of the traction mechanism, which took into account not only the elastic elements of the gearbox, the backlashes in it and the changes in the kinematic parameters of the mechanism during operation, but also the mechanical characteristics of the electric drive and the features of its control system. By mathematical modeling of the transient processes of the electromechanical system, it is shown that the introduction of feedback on the load in the elastic element allows one to reduce the dynamic loads in the traction mechanism and to limit the elastic oscillations of the actuating mechanism in comparison with the standard control system. Fixed as a general decrease in the dynamic load of the nodes of traction mechanism in the modes of loading and latching of the bucket, and a decrease the operating time of the mechanism at maximum load. At the same time, undesirable phenomena in the operation of the electric drive were also associated with the increase in the recovery time of the steady-state value of the speed of the actuating mechanism under certain operating conditions, which can lead to a decrease in the reliability of the mechanical part and the productivity of the traction mechanism.

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.

Load profiles analysis for electricity market

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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.

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

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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.

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.

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.)

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....

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

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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

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)

Design and operational procedures for ORC-based systems coupled with internal combustion engines driving electrical generators at full and partial load

International Nuclear Information System (INIS)

Badescu, Viorel; Aboaltabooq, Mahdi Hatf Kadhum; Pop, Horatiu; Apostol, Valentin; Prisecaru, Malina; Prisecaru, Tudor

2017-01-01

Highlights: • Waste heat recovery from Internal Combustion Engines (ICEs). • Organic Ranking Cycle (ORC) systems driving Electric Generators (EGs). • ICE-EG partial load operation. • Optimum design geometry of ORC system. • Optimum operation of ORC system at partial EG load. - Abstract: This paper refers to recovering waste heat from the hot gases exhausted by internal combustion engines (ICEs) driving electric generators (EGs) at full and partial load. The topic is of particular interest for developing countries where electric grids are underdeveloped or missing and electricity is generated locally by using classical fuels. The heat recovery system is based on an Organic Rankine Cycle (ORC). A novel method is proposed for the optimum design of ORC-based systems operating in combination with ICE at partial EG loads. First, ORC-based systems coupled with ICEs operating at full EG load is treated. Specific results for the operation at full EG load are as follows: (i) the optimum superheating increment ranges between 30 and 40 °C, depending on the type of the working fluids; (ii) a pinch point temperature difference exits between the flue gas temperature and the working fluid at the evaporator inlet; (iii) the total area of the evaporator is very close to the total area of the condenser, a fact which facilitates manufacturing; (iv) the surface area of the preheater zone is about 75% of the total surface area, while those of the boiler zone and superheater zone is about 13.5% and 11.5%, respectively. Second, the case of the ORC-based systems coupled with ICEs operating at partial EG load is considered. Specific results for this case are as follows: (v) the net power may be maximized by optimizing the working fluid mass flow rate; (vi) when the ICE is coupled with an ORC-based system, the overall thermal efficiency of the combined system, η ICE-ORC , is higher than the thermal efficiency of the ICE operating alone. As an example, for the case treated here, �

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.

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.

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...

Real-Time Vehicle Energy Management System Based on Optimized Distribution of Electrical Load Power

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Yuefei Wang

2016-10-01

Full Text Available As a result of severe environmental pressure and stringent government regulations, refined energy management for vehicles has become inevitable. To improve vehicle fuel economy, this paper presents a bus-based energy management system for the electrical system of internal combustion engine vehicles. Both the model of an intelligent alternator and the model of a lead-acid battery are discussed. According to these models, the energy management for a vehicular electrical system is formulated as a global optimal control problem which aims to minimize fuel consumption. Pontryagin’s minimum principle is applied to solve the optimal control problem to realize a real-time control strategy for electrical energy management in vehicles. The control strategy can change the output of the intelligent alternator and the battery with the changes of electrical load and driving conditions in real-time. Experimental results demonstrate that, compared to the traditional open-loop control strategy, the proposed control strategy for vehicle energy management can effectively reduce fuel consumption and the fuel consumption per 100 km is decreased by approximately 1.7%.

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.

Minimization of Impact from Electric Vehicle Supply Equipment to the Electric Grid Using a Dynamically Controlled Battery Bank for Peak Load Shaving

Energy Technology Data Exchange (ETDEWEB)

Castello, Charles C [ORNL

2013-01-01

This research presents a comparison of two control systems for peak load shaving using local solar power generation (i.e., photovoltaic array) and local energy storage (i.e., battery bank). The purpose is to minimize load demand of electric vehicle supply equipment (EVSE) on the electric grid. A static and dynamic control system is compared to decrease demand from EVSE. Static control of the battery bank is based on charging and discharging to the electric grid at fixed times. Dynamic control, with 15-minute resolution, forecasts EVSE load based on data analysis of collected data. In the proposed dynamic control system, the sigmoid function is used to shave peak loads while limiting scenarios that can quickly drain the battery bank. These control systems are applied to Oak Ridge National Laboratory s (ORNL) solar-assisted electric vehicle (EV) charging stations. This installation is composed of three independently grid-tied sub-systems: (1) 25 EVSE; (2) 47 kW photovoltaic (PV) array; and (3) 60 kWh battery bank. The dynamic control system achieved the greatest peak load shaving, up to 34% on a cloudy day and 38% on a sunny day. The static control system was not ideal; peak load shaving was 14.6% on a cloudy day and 12.7% on a sunny day. Simulations based on ORNL data shows solar-assisted EV charging stations combined with the proposed dynamic battery control system can negate up to 89% of EVSE load demand on sunny days.

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.

Managing charging loads of electric vehicles by monetary incentives. A model-based optimization; Monetaere Anreize zur Steuerung der Ladelast von Elektrofahrzeugen. Eine modellgestuetzte Optimierung

Energy Technology Data Exchange (ETDEWEB)

Paetz, Alexandra-Gwyn; Kaschub, Thomas; Kopp, Martin; Jochem, Patrick; Fichtner, Wolf [Karlsruher Institut fuer Technologie, Karlsruhe (Germany). Inst. fuer Industriebetriebslehre und Industrielle Produktion

2013-03-15

Electric mobility is supposed to contribute to climate policy targets by reducing CO{sub 2}-emissions in the transportation sector. Increasing penetration rates of electric vehicles (EV) can lead to new challenges in the electricity sector, especially with regard to local distribution networks. Thus the management of charging loads is discussed as a key issue in energy economics. Due to their long parking times, high electricity and power demand, EV seem to be predestined for load management. Monetary incentives as dynamic pricing can be suitable for that: They reflect the current supply situation, pass the information to the consumers and can thus lead to a corresponding charging behaviour. In this article we analyse this interaction between dynamic pricing and charging loads. For this reason we have developed the optimization model DS-Opt+. It models a total number of 4,000 households in two residential areas of a major city with regard to its electricity demand, its mobility behaviour and its equipment of photovoltaic systems. Four different pricing models are tested for their effects on charging behaviour and thus the total load of the residential area. The results illustrate that only fairly high penetration rates of EV lead to remarkably higher electricity demand and require some load management. The tested dynamic pricing models are suitable for influencing charging loads; load-based tariffs are best in achieving a balanced load curve. In our analysis uncontrolled charging strategies are superior regarding a balanced load curve than controlled strategies by time-varying tariffs. Our results lead to several implications relevant for the energy industry and further research.

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 ...

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 ...

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.

Impacts of rising air temperatures on electric transmission ampacity and peak electricity load in the United States

Science.gov (United States)

Bartos, Matthew; Chester, Mikhail; Johnson, Nathan; Gorman, Brandon; Eisenberg, Daniel; Linkov, Igor; Bates, Matthew

2016-11-01

Climate change may constrain future electricity supply adequacy by reducing electric transmission capacity and increasing electricity demand. The carrying capacity of electric power cables decreases as ambient air temperatures rise; similarly, during the summer peak period, electricity loads typically increase with hotter air temperatures due to increased air conditioning usage. As atmospheric carbon concentrations increase, higher ambient air temperatures may strain power infrastructure by simultaneously reducing transmission capacity and increasing peak electricity load. We estimate the impacts of rising ambient air temperatures on electric transmission ampacity and peak per-capita electricity load for 121 planning areas in the United States using downscaled global climate model projections. Together, these planning areas account for roughly 80% of current peak summertime load. We estimate climate-attributable capacity reductions to transmission lines by constructing thermal models of representative conductors, then forcing these models with future temperature projections to determine the percent change in rated ampacity. Next, we assess the impact of climate change on electricity load by using historical relationships between ambient temperature and utility-scale summertime peak load to estimate the extent to which climate change will incur additional peak load increases. We find that by mid-century (2040-2060), increases in ambient air temperature may reduce average summertime transmission capacity by 1.9%-5.8% relative to the 1990-2010 reference period. At the same time, peak per-capita summertime loads may rise by 4.2%-15% on average due to increases in ambient air temperature. In the absence of energy efficiency gains, demand-side management programs and transmission infrastructure upgrades, these load increases have the potential to upset current assumptions about future electricity supply adequacy.

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

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.

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

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.

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)

Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System—A Case Study on Electrical Load Forecasting

Directory of Open Access Journals (Sweden)

Yunxuan Dong

2017-04-01

Full Text Available The process of modernizing smart grid prominently increases the complexity and uncertainty in scheduling and operation of power systems, and, in order to develop a more reliable, flexible, efficient and resilient grid, electrical load forecasting is not only an important key but is still a difficult and challenging task as well. In this paper, a short-term electrical load forecasting model, with a unit for feature learning named Pyramid System and recurrent neural networks, has been developed and it can effectively promote the stability and security of the power grid. Nine types of methods for feature learning are compared in this work to select the best one for learning target, and two criteria have been employed to evaluate the accuracy of the prediction intervals. Furthermore, an electrical load forecasting method based on recurrent neural networks has been formed to achieve the relational diagram of historical data, and, to be specific, the proposed techniques are applied to electrical load forecasting using the data collected from New South Wales, Australia. The simulation results show that the proposed hybrid models can not only satisfactorily approximate the actual value but they are also able to be effective tools in the planning of smart grids.

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

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.

Peak Electric Load Relief in Northern Manhattan

Directory of Open Access Journals (Sweden)

Hildegaard D. Link

2014-08-01

Full Text Available The aphorism “Think globally, act locally,” attributed to René Dubos, reflects the vision that the solution to global environmental problems must begin with efforts within our communities. PlaNYC 2030, the New York City sustainability plan, is the starting point for this study. Results include (a a case study based on the City College of New York (CCNY energy audit, in which we model the impacts of green roofs on campus energy demand and (b a case study of energy use at the neighborhood scale. We find that reducing the urban heat island effect can reduce building cooling requirements, peak electricity loads stress on the local electricity grid and improve urban livability.

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)

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....

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.

Multi nodal load forecasting in electric power systems using a radial basis neural network; Previsao de carga multinodal em sistemas eletricos de potencia usando uma rede neural de base radial

Energy Technology Data Exchange (ETDEWEB)

Altran, A.B.; Lotufo, A.D.P.; Minussi, C.R. [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Ilha Solteira, SP (Brazil). Dept. de Engenharia Eletrica], Emails: lealtran@yahoo.com.br, annadiva@dee.feis.unesp.br, minussi@dee.feis.unesp.br; Lopes, M.L.M. [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Ilha Solteira, SP (Brazil). Dept. de Matematica], E-mail: mara@mat.feis.unesp.br

2009-07-01

This paper presents a methodology for electrical load forecasting, using radial base functions as activation function in artificial neural networks with the training by backpropagation algorithm. This methodology is applied to short term electrical load forecasting (24 h ahead). Therefore, results are presented analyzing the use of radial base functions substituting the sigmoid function as activation function in multilayer perceptron neural networks. However, the main contribution of this paper is the proposal of a new formulation of load forecasting dedicated to the forecasting in several points of the electrical network, as well as considering several types of users (residential, commercial, industrial). It deals with the MLF (Multimodal Load Forecasting), with the same processing time as the GLF (Global Load Forecasting). (author)

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.

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.

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

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.

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.

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.

A Novel Hybrid Model Based on Extreme Learning Machine, k-Nearest Neighbor Regression and Wavelet Denoising Applied to Short-Term Electric Load Forecasting

Directory of Open Access Journals (Sweden)

Weide Li

2017-05-01

Full Text Available Electric load forecasting plays an important role in electricity markets and power systems. Because electric load time series are complicated and nonlinear, it is very difficult to achieve a satisfactory forecasting accuracy. In this paper, a hybrid model, Wavelet Denoising-Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EWKM, which combines k-Nearest Neighbor (KNN and Extreme Learning Machine (ELM based on a wavelet denoising technique is proposed for short-term load forecasting. The proposed hybrid model decomposes the time series into a low frequency-associated main signal and some detailed signals associated with high frequencies at first, then uses KNN to determine the independent and dependent variables from the low-frequency signal. Finally, the ELM is used to get the non-linear relationship between these variables to get the final prediction result for the electric load. Compared with three other models, Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EKM, Wavelet Denoising-Extreme Learning Machine (WKM and Wavelet Denoising-Back Propagation Neural Network optimized by k-Nearest Neighbor Regression (WNNM, the model proposed in this paper can improve the accuracy efficiently. New South Wales is the economic powerhouse of Australia, so we use the proposed model to predict electric demand for that region. The accurate prediction has a significant meaning.

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.

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.

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.

Designing the input vector to ANN-based models for short-term load forecast in electricity distribution systems

International Nuclear Information System (INIS)

Santos, P.J.; Martins, A.G.; Pires, A.J.

2007-01-01

The present trend to electricity market restructuring increases the need for reliable short-term load forecast (STLF) algorithms, in order to assist electric utilities in activities such as planning, operating and controlling electric energy systems. Methodologies such as artificial neural networks (ANN) have been widely used in the next hour load forecast horizon with satisfactory results. However, this type of approach has had some shortcomings. Usually, the input vector (IV) is defined in a arbitrary way, mainly based on experience, on engineering judgment criteria and on concern about the ANN dimension, always taking into consideration the apparent correlations within the available endogenous and exogenous data. In this paper, a proposal is made of an approach to define the IV composition, with the main focus on reducing the influence of trial-and-error and common sense judgments, which usually are not based on sufficient evidence of comparative advantages over previous alternatives. The proposal includes the assessment of the strictly necessary instances of the endogenous variable, both from the point of view of the contiguous values prior to the forecast to be made, and of the past values representing the trend of consumption at homologous time intervals of the past. It also assesses the influence of exogenous variables, again limiting their presence at the IV to the indispensable minimum. A comparison is made with two alternative IV structures previously proposed in the literature, also applied to the distribution sector. The paper is supported by a real case study at the distribution sector. (author)

Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory

Directory of Open Access Journals (Sweden)

Jun Yang

2015-03-01

Full Text Available In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G technique, electric vehicles (EVs can act as mobile energy storage units, which could be a solution for load frequency control (LFC in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances.

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.

Research on light rail electric load forecasting based on ARMA model

Science.gov (United States)

Huang, Yifan

2018-04-01

The article compares a variety of time series models and combines the characteristics of power load forecasting. Then, a light load forecasting model based on ARMA model is established. Based on this model, a light rail system is forecasted. The prediction results show that the accuracy of the model prediction is high.

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.

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.

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.

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

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.

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.

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.

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

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.

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.

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.

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.

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)

Future residential loads profiles : scenario-based analysis of high penetration of heavy loads and distributed generation

NARCIS (Netherlands)

Asare-Bediako, B.; Kling, W.L.; Ribeiro, P.F.

2014-01-01

Electric load profiles are useful for accurate load forecasting, network planning and optimal generation capacity. They represent electricity demand patterns and are to a large extent predictable. However, new and heavier loads (heat pumps and electric vehicles), distributed generation, and home

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.

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.

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.

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...

Analysis on learning curves of end-use appliances for the establishment of price-sensitivity load model in competitive electricity market

Energy Technology Data Exchange (ETDEWEB)

Hwang, Sung Wook; Kim, Jung Hoon [Hongik University (Korea); Song, Kyung Bin [Keimyung University (Korea); Choi, Joon Young [Jeonju University (Korea)

2001-07-01

The change of the electricity charge from cost base to price base due to the introduction to the electricity market competition causes consumer to choose a variety of charge schemes and a portion of loads to be affected by this change. Besides, it is required the index that consolidate the price volatility experienced on the power exchange with gaming and strategic bidding by suppliers to increase profits. Therefore, in order to find a mathematical model of the sensitively-responding to-price loads, the price-sensitive load model is needed. And the development of state-of- the-art technologies affects the electricity price, so the diffusion of high-efficient end-uses and these price affect load patterns. This paper shows the analysis on learning curves algorithms which is used to investigate the correlation of the end-uses' price and load patterns. (author). 6 refs., 4 figs., 4 tabs.

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.

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.

Optimal Dispatching of Active Distribution Networks Based on Load Equilibrium

Directory of Open Access Journals (Sweden)

Xiao Han

2017-12-01

Full Text Available This paper focuses on the optimal intraday scheduling of a distribution system that includes renewable energy (RE generation, energy storage systems (ESSs, and thermostatically controlled loads (TCLs. This system also provides time-of-use pricing to customers. Unlike previous studies, this study attempts to examine how to optimize the allocation of electric energy and to improve the equilibrium of the load curve. Accordingly, we propose a concept of load equilibrium entropy to quantify the overall equilibrium of the load curve and reflect the allocation optimization of electric energy. Based on this entropy, we built a novel multi-objective optimal dispatching model to minimize the operational cost and maximize the load curve equilibrium. To aggregate TCLs into the optimization objective, we introduced the concept of a virtual power plant (VPP and proposed a calculation method for VPP operating characteristics based on the equivalent thermal parameter model and the state-queue control method. The Particle Swarm Optimization algorithm was employed to solve the optimization problems. The simulation results illustrated that the proposed dispatching model can achieve cost reductions of system operations, peak load curtailment, and efficiency improvements, and also verified that the load equilibrium entropy can be used as a novel index of load characteristics.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Electricity Load Forecasting Using Support Vector Regression with Memetic Algorithms

Directory of Open Access Journals (Sweden)

Zhongyi Hu

2013-01-01

Full Text Available Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA based memetic algorithm (FA-MA to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature.

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.

A model of market power in electricity industries subject to peak load pricing

International Nuclear Information System (INIS)

Arellano, Maria-Soledad; Serra, Pablo

2007-01-01

This paper studies the exercise of market power in price-regulated electricity industries under peak-load pricing and merit order dispatching, but where investment decisions are taken by independent generating companies. Within this context, we show that producers can exercise market power by under-investing in base-load capacity, compared to the welfare-maximizing configuration. We also show that when there is free entry with an exogenous fixed entry cost that is later sunk, more intense competition results in higher welfare but fewer firms. (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.

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.

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

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.

Computation of the radiation Q of dielectric-loaded electrically small antennas in integral equation formulations

DEFF Research Database (Denmark)

Kim, Oleksiy S.

2016-01-01

A new technique for estimating the impedance frequency bandwidth of electrically small antennas loaded with magneto-dielectric material from a single-frequency simulation in a surface integral equation solver is presented. The estimate is based on the inverse of the radiation Q computed using newly...... derived expressions for the stored energy and the radiated power of arbitrary coupled electric and magnetic currents in free space....

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)

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...

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2006-07-15

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

Free vibration analysis of magneto-electro-elastic microbeams subjected to magneto-electric loads

Science.gov (United States)

Vaezi, Mohamad; Shirbani, Meisam Moory; Hajnayeb, Ali

2016-01-01

Different types of actuating and sensing mechanisms are used in new micro and nanoscale devices. Therefore, a new challenge is modeling electromechanical systems that use these mechanisms. In this paper, free vibration of a magnetoelectroelastic (MEE) microbeam is investigated in order to obtain its natural frequencies and buckling loads. The beam is simply supported at both ends. External electric and magnetic potentials are applied to the beam. By using the Hamilton's principle, the governing equations and boundary conditions are derived based on the Euler-Bernoulli beam theory. The equations are solved, analytically to obtain the natural frequencies of the MEE microbeam. Furthermore, the effects of external electric and magnetic potentials on the buckling of the beam are analyzed and the critical values of the potentials are obtained. Finally, a numerical study is conducted. It is found that the natural frequency can be tuned directly by changing the magnetic and electric potentials. Additionally, a closed form solution for the normalized natural frequency is derived, and buckling loads are calculated in a numerical example.

Equivalent electricity storage capacity of domestic thermostatically controlled loads

International Nuclear Information System (INIS)

Sossan, Fabrizio

2017-01-01

A method to quantify the equivalent storage capacity inherent the operation of thermostatically controlled loads (TCLs) is developed. Equivalent storage capacity is defined as the amount of power and electricity consumption which can be deferred or anticipated in time with respect to the baseline consumption (i.e. when no demand side event occurs) without violating temperature limits. The analysis is carried out for 4 common domestic TCLs: an electric space heating system, freezer, fridge, and electric water heater. They are simulated by applying grey-box thermal models identified from measurements. They describe the heat transfer of the considered TCLs as a function of the electric power consumption and environment conditions. To represent typical TCLs operating conditions, Monte Carlo simulations are developed, where models inputs and parameters are sampled from relevant statistical distributions. The analysis provides a way to compare flexible demand against competitive storage technologies. It is intended as a tool for system planners to assess the TCLs potential to support electrical grid operation. In the paper, a comparison of the storage capacity per unit of capital investment cost is performed considering the selected TCLs and two grid-connected battery storage systems (a 720 kVA/500 kWh lithium-ion unit and 15 kVA/120 kWh Vanadium flow redox) is performed. - Highlights: • The equivalent storage capacity of domestic TCLs is quantified • A comparison with battery-based storage technologies is performed • We derive metrics for system planners to plan storage in power system networks • Rule-of-thumb cost indicators for flexible demand and battery-based storage

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.

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

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)

Analytic model for ultrasound energy receivers and their optimal electric loads II: Experimental validation

Science.gov (United States)

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

2017-10-01

In this paper, we verify the two optimal electric load concepts based on the zero reflection condition and on the power maximization approach for ultrasound energy receivers. We test a high loss 1-3 composite transducer, and find that the measurements agree very well with the predictions of the analytic model for plate transducers that we have developed previously. Additionally, we also confirm that the power maximization and zero reflection loads are very different when the losses in the receiver are high. Finally, we compare the optimal load predictions by the KLM and the analytic models with frequency dependent attenuation to evaluate the influence of the viscosity.

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...

Self-Sensing of Position-Related Loads in Continuous Carbon Fibers-Embedded 3D-Printed Polymer Structures Using Electrical Resistance Measurement.

Science.gov (United States)

Luan, Congcong; Yao, Xinhua; Shen, Hongyao; Fu, Jianzhong

2018-03-27

Condition monitoring in polymer composites and structures based on continuous carbon fibers show overwhelming advantages over other potentially competitive sensing technologies in long-gauge measurements due to their great electromechanical behavior and excellent reinforcement property. Although carbon fibers have been developed as strain- or stress-sensing agents in composite structures through electrical resistance measurements, the electromechanical behavior under flexural loads in terms of different loading positions still lacks adequate research, which is the most common situation in practical applications. This study establishes the relationship between the fractional change in electrical resistance of carbon fibers and the external loads at different loading positions along the fibers' longitudinal direction. An approach for real-time monitoring of flexural loads at different loading positions was presented simultaneously based on this relationship. The effectiveness and feasibility of the approach were verified by experiments on carbon fiber-embedded three-dimensional (3D) printed thermoplastic polymer beam. The error in using the provided approach to monitor the external loads at different loading positions was less than 1.28%. The study fully taps the potential of continuous carbon fibers as long-gauge sensory agents and reinforcement in the 3D-printed polymer structures.

Self-Sensing of Position-Related Loads in Continuous Carbon Fibers-Embedded 3D-Printed Polymer Structures Using Electrical Resistance Measurement

Directory of Open Access Journals (Sweden)

Congcong Luan

2018-03-01

Full Text Available Condition monitoring in polymer composites and structures based on continuous carbon fibers show overwhelming advantages over other potentially competitive sensing technologies in long-gauge measurements due to their great electromechanical behavior and excellent reinforcement property. Although carbon fibers have been developed as strain- or stress-sensing agents in composite structures through electrical resistance measurements, the electromechanical behavior under flexural loads in terms of different loading positions still lacks adequate research, which is the most common situation in practical applications. This study establishes the relationship between the fractional change in electrical resistance of carbon fibers and the external loads at different loading positions along the fibers’ longitudinal direction. An approach for real-time monitoring of flexural loads at different loading positions was presented simultaneously based on this relationship. The effectiveness and feasibility of the approach were verified by experiments on carbon fiber-embedded three-dimensional (3D printed thermoplastic polymer beam. The error in using the provided approach to monitor the external loads at different loading positions was less than 1.28%. The study fully taps the potential of continuous carbon fibers as long-gauge sensory agents and reinforcement in the 3D-printed polymer structures.

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)

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)

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...

The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

Science.gov (United States)

Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

2017-08-01

The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

Short-term Power Load Forecasting Based on Balanced KNN

Science.gov (United States)

Lv, Xianlong; Cheng, Xingong; YanShuang; Tang, Yan-mei

2018-03-01

To improve the accuracy of load forecasting, a short-term load forecasting model based on balanced KNN algorithm is proposed; According to the load characteristics, the historical data of massive power load are divided into scenes by the K-means algorithm; In view of unbalanced load scenes, the balanced KNN algorithm is proposed to classify the scene accurately; The local weighted linear regression algorithm is used to fitting and predict the load; Adopting the Apache Hadoop programming framework of cloud computing, the proposed algorithm model is parallelized and improved to enhance its ability of dealing with massive and high-dimension data. The analysis of the household electricity consumption data for a residential district is done by 23-nodes cloud computing cluster, and experimental results show that the load forecasting accuracy and execution time by the proposed model are the better than those of traditional forecasting algorithm.

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

Electricity pricing and load dispatching in deregulated electricity market

International Nuclear Information System (INIS)

Geerli; Niioka, S.; Yokoyama, R.

2003-01-01

A rapid move to a market-based electric power industry will significantly alter the structure of electricity pricing and system operation. In this paper, we consider a game of negotiation in the electricity market, involving electric utilities, independent power producers (IPPs) and large-scale customers. We analyze the two-level game strategies for the negotiation process between utilities, IPPs and customers. These have been previously recognized as a way to come up with a rational decision for competitive markets, in which players intend to maximize their own profits. The derived operation rules based on competition can be viewed as an extension of the conventional equal incremental cost method for the deregulated power system. The proposed approach was applied to several systems to verify its effectiveness. (Author)

Research of Impact Load in Large Electrohydraulic Load Simulator

Directory of Open Access Journals (Sweden)

Yongguang Liu

2014-01-01

Full Text Available The stronger impact load will appear in the initial phase when the large electric cylinder is tested in the hardware-in-loop simulation. In this paper, the mathematical model is built based on AMESim, and then the reason of the impact load is investigated through analyzing the changing tendency of parameters in the simulation results. The inhibition methods of impact load are presented according to the structural invariability principle and applied to the actual system. The final experimental result indicates that the impact load is inhibited, which provides a good experimental condition for the electric cylinder and promotes the study of large load simulator.

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.

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.

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.

Measurements and simulations for peak electrical load reduction in cooling dominated climate

International Nuclear Information System (INIS)

Sadineni, Suresh B.; Boehm, Robert F.

2012-01-01

Peak electric demand due to cooling load in the Desert Southwest region of the US has been an issue for the electrical energy suppliers. To address this issue, a consortium has been formed between the University of Nevada Las Vegas, Pulte Homes (home builder) and NV Energy (local utility) in order to reduce the peak load by more than 65%. The implemented strategies that were used to accomplish that goal consist of energy efficiency in homes, onsite electricity generation through roof integrated PV, direct load control, and battery storage at the substation level. The simulation models developed using building energy analysis software were validated against measured data. The electrical energy demand for the upgraded home during peak period (1:00–7:00 PM) decreased by approximately 37% and 9% compared to a code standard home of the same size, due to energy efficiency and PV generation, respectively. The total decrease in electrical demand due to energy efficiency and PV generation during the peak period is 46%. Additionally, a 2.2 °C increase in thermostat temperature from 23.9 °C to 26.1 °C between 4:00 PM and 7:00 PM has further decreased the average demand during the peak period by 69% of demand from a standard home. -- Highlights: ► A study to demonstrate peak load reductions of 65% at the substation. ► A new residential energy efficient community named Villa Trieste is being developed. ► The peak demand from the homes has decreased by 37% through energy efficiency. ► A 1.8 kWp system along with energy efficiency measures decreased peak by 46%.

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.

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.

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...

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).

Simple Models for Model-based Portfolio Load Balancing Controller Synthesis

DEFF Research Database (Denmark)

Edlund, Kristian Skjoldborg; Mølbak, Tommy; Bendtsen, Jan Dimon

2010-01-01

of generation units existing in an electrical power supply network, for instance in model-based predictive control or declarative control schemes. We focus on the effectuators found in the Danish power system. In particular, the paper presents models for boiler load, district heating, condensate throttling...

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...

Renewable energy the best remedy for electrical load shedding in Pakistan

International Nuclear Information System (INIS)

Bhutta, S.M.

2011-01-01

Average 33% time of daily electrical load shedding in Pakistan is most serious as it has affected all activities. Industries are crippled, commercial, official activities and daily life is being deteriorated Total loss to Export is 1.3 and oil import bill is $ 9 Billion. If appropriate actions are not taken immediately; the situation is going to get worse when people will fight for every watt of electricity. The impounding crises are not foreseen and its gravity is not yet properly realized by the decision makers. Politics and several lobbies work against construction of major projects of hydel power and baseless controversies have been created. Pakistan is blessed with abundant renewable energy i.e. 2.9 million MW solar, tidal, wind 346,000 MW and 59,000 MW potentials of hydro electricity. Analysis of the reasons for the slow and no growth of these vital renewable potentials in Pakistan indicate that there are barriers which need to be mitigated to take immediate benefits to overcome menace of load shedding. Local R and D, Design, manufacturing, installation and feasibility study capabilities are negligible. Institutional capabilities in most of the organizations can at best be ranked as average or weak. Other impediments and barriers that continue to hamper the load shedding are losses, attitude in the promotion of renewable and hydro power projects include: lack of serious attempts to mitigate the barriers, integrate the programs with profitability; inadequate evaluation of resources; non availability of reliable baseline data; and lack of coordination among the relevant agencies; weak institutional arrangements for renewable energy promotion; absence of fiscal and financing mechanisms; lack of understanding, awareness, information and outreach; uneven allocation of resources; lack of appropriate quality management, monitoring and evaluation programs; and need of attractive policy framework and legislative support, building consensus among people and provinces

Study on Electricity Business Expansion and Electricity Sales Based on Seasonal Adjustment

Science.gov (United States)

Zhang, Yumin; Han, Xueshan; Wang, Yong; Zhang, Li; Yang, Guangsen; Sun, Donglei; Wang, Bolun

2017-05-01

[1] proposed a novel analysis and forecast method of electricity business expansion based on Seasonal Adjustment, we extend this work to include the effect the micro and macro aspects, respectively. From micro aspect, we introduce the concept of load factor to forecast the stable value of electricity consumption of single new consumer after the installation of new capacity of the high-voltage transformer. From macro aspects, considering the growth of business expanding is also stimulated by the growth of electricity sales, it is necessary to analyse the antecedent relationship between business expanding and electricity sales. First, forecast electricity consumption of customer group and release rules of expanding capacity, respectively. Second, contrast the degree of fitting and prediction accuracy to find out the antecedence relationship and analyse the reason. Also, it can be used as a contrast to observe the influence of customer group in different ranges on the prediction precision. Finally, Simulation results indicate that the proposed method is accurate to help determine the value of expanding capacity and electricity consumption.

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.

Deep Neural Network Based Demand Side Short Term Load Forecasting

Directory of Open Access Journals (Sweden)

Seunghyoung Ryu

2016-12-01

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

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.

Prioritized rule based load management technique for residential building powered by PV/battery system

Directory of Open Access Journals (Sweden)

T.R. Ayodele

2017-06-01

Full Text Available In recent years, Solar Photovoltaic (PV system has presented itself as one of the main solutions to the electricity poverty plaguing the majority of buildings in rural communities with solar energy potential. However, the stochasticity associated with solar PV power output owing to vagaries in weather conditions is a major challenge in the deployment of the systems. This study investigates approach for maximizing the benefits of a Stand-Alone Photovoltaic-Battery (SAPVB system via techniques that provide for optimum energy gleaning and management. A rule-based load management scheme is developed and tested for a residential building. The approach allows load prioritizing and shifting based on certain rules. To achieve this, the residential loads are classified into Critical Loads (CLs and Uncritical Loads (ULs. The CLs are given higher priority and therefore are allowed to operate at their scheduled time while the ULs are of less priority, hence can be shifted to a time where there is enough electric power generation from the PV arrays rather than the loads being operated at the time period set by the user. Four scenarios were created to give insight into the applicability of the proposed rule based load management scheme. The result revealed that when the load management technique is not utilized as in the case of scenario 1 (Base case, the percentage satisfaction of the critical and uncritical loads by the PV system are 49.8% and 23.7%. However with the implementation of the load management scheme in scenarios 2, 3 and 4, the percentage satisfaction of the loads (CLs, ULs are (93.8%, 74.2%, (90.9%, 70.1% and (87.2%, 65.4% for scenarios 2, 3 and 4, respectively.

Distributed Smart Device for Monitoring, Control and Management of Electric Loads in Domotic Environments

Directory of Open Access Journals (Sweden)

Carlos Perez-Vidal

2012-04-01

Full Text Available This paper presents a microdevice for monitoring, control and management of electric loads at home. The key idea is to compact the electronic design as much as possible in order to install it inside a Schuko socket. Moreover, the electronic Schuko socket (electronic microdevice + Schuko socket has the feature of communicating with a central unit and with other microdevices over the existing powerlines. Using the existing power lines, the proposed device can be installed in new buildings or in old ones. The main use of this device is to monitor, control and manage electric loads to save energy and prevent accidents produced by different kind of devices (e.g., iron used in domestic tasks. The developed smart device is based on a single phase multifunction energy meter manufactured by Analog Devices (ADE7753 to measure the consumption of electrical energy and thento transmit it using a serial interface. To provide current measurement information to the ADE7753, an ultra flat SMD open loop integrated circuit current transducer based on the Hall effect principle manufactured by Lem (FHS-40P/SP600 has been used. Moreover, each smart device has a PL-3120 smart transceiver manufactured by LonWorks to execute the user’s program, to communicate with the ADE7753 via serial interface and to transmit information to the central unit via powerline communication. Experimental results show the exactitude of the measurements made using the developed smart device.

Distributed smart device for monitoring, control and management of electric loads in domotic environments.

Science.gov (United States)

Morales, Ricardo; Badesa, Francisco J; García-Aracil, Nicolas; Perez-Vidal, Carlos; Sabater, Jose María

2012-01-01

This paper presents a microdevice for monitoring, control and management of electric loads at home. The key idea is to compact the electronic design as much as possible in order to install it inside a Schuko socket. Moreover, the electronic Schuko socket (electronic microdevice + Schuko socket) has the feature of communicating with a central unit and with other microdevices over the existing powerlines. Using the existing power lines, the proposed device can be installed in new buildings or in old ones. The main use of this device is to monitor, control and manage electric loads to save energy and prevent accidents produced by different kind of devices (e.g., iron) used in domestic tasks. The developed smart device is based on a single phase multifunction energy meter manufactured by Analog Devices (ADE7753) to measure the consumption of electrical energy and then to transmit it using a serial interface. To provide current measurement information to the ADE7753, an ultra flat SMD open loop integrated circuit current transducer based on the Hall effect principle manufactured by Lem (FHS-40P/SP600) has been used. Moreover, each smart device has a PL-3120 smart transceiver manufactured by LonWorks to execute the user's program, to communicate with the ADE7753 via serial interface and to transmit information to the central unit via powerline communication. Experimental results show the exactitude of the measurements made using the developed smart device.

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....

Load management: Model-based control of aggregate power for populations of thermostatically controlled loads

International Nuclear Information System (INIS)

Perfumo, Cristian; Kofman, Ernesto; Braslavsky, Julio H.; Ward, John K.

2012-01-01

Highlights: ► Characterisation of power response of a population of air conditioners. ► Implementation of demand side management on a group of air conditioners. ► Design of a controller for the power output of a group of air conditioners. ► Quantification of comfort impact of demand side management. - Abstract: Large groups of electrical loads can be controlled as a single entity to reduce their aggregate power demand in the electricity network. This approach, known as load management (LM) or demand response, offers an alternative to the traditional paradigm in the electricity market, where matching supply and demand is achieved solely by regulating how much generation is dispatched. Thermostatically controlled loads (TCLs), such as air conditioners (ACs) and fridges, are particularly suitable for LM, which can be implemented using feedback control techniques to regulate their aggregate power. To achieve high performance, such feedback control techniques require an accurate mathematical model of the TCL aggregate dynamics. Although such models have been developed, they appear too complex to be effectively used in control design. In this paper we develop a mathematical model aimed at the design of a model-based feedback control strategy. The proposed model analytically characterises the aggregate power response of a population of ACs to a simultaneous step change in temperature set points. Based on this model, we then derive, and completely parametrise in terms of the ACs ensemble properties, a reduced-order mathematical model to design an internal-model controller that regulates aggregate power by broadcasting temperature set-point offset changes. The proposed controller achieves high LM performance provided the ACs are equipped with high resolution thermostats. With coarser resolution thermostats, which are typical in present commercial and residential ACs, performance deteriorates significantly. This limitation is overcome by subdividing the population

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...

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)

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.

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.

Crack density and electrical resistance in indium-tin-oxide/polymer thin films under cyclic loading

KAUST Repository

Mora Cordova, Angel

2014-11-01

Here, we propose a damage model that describes the degradation of the material properties of indium-tin-oxide (ITO) thin films deposited on polymer substrates under cyclic loading. We base this model on our earlier tensile test model and show that the new model is suitable for cyclic loading. After calibration with experimental data, we are able to capture the stress-strain behavior and changes in electrical resistance of ITO thin films. We are also able to predict the crack density using calibrations from our previous model. Finally, we demonstrate the capabilities of our model based on simulations using material properties reported in the literature. Our model is implemented in the commercially available finite element software ABAQUS using a user subroutine UMAT.[Figure not available: see fulltext.].

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.

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...

Adaptive algorithm for predicting increases in central loads of electrical energy systems

Energy Technology Data Exchange (ETDEWEB)

Arbachyauskene, N A; Pushinaytis, K V

1982-01-01

An adaptive algorithm for predicting increases in central loads of the electrical energy system is suggested for the task of evaluating the condition. The algorithm is based on the Kalman filter. In order to calculate the coefficient of intensification, the a priori assigned noise characteristics with low accuracy are used only in the beginning of the calculation. Further, the coefficient of intensification is calculated from the innovation sequence. This approach makes it possible to correct errors in the assignment of the statistical noise characteristics and to follow their changes. The algorithm is experimentally verified.

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.

Electric Vehicle Based Battery Storages for Future Power System Regulation Services

DEFF Research Database (Denmark)

Pillai, Jayakrishnan Radhakrishna; Bak-Jensen, Birgitte

2009-01-01

supplying the reserve power requirements. This limited regulation services from conventional generators in the future power system calls for other new reserve power solutions like Electric Vehicle (EV) based battery storages. A generic aggregated EV based battery storage for long-term dynamic load frequency...

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

Effect of graphite loading on the electrical and mechanical properties of Poly (Ethylene Oxide)/Poly (Vinyl Chloride) polymer films

Science.gov (United States)

Hajar, M. D. S.; Supri, A. G.; Hanif, M. P. M.; Yazid, M. I. M.

2017-10-01

In this study, films consisting of a blend of poly (ethylene oxide)/poly (vinyl chloride) (PEO/PVC) and a conductive filler, graphite were prepared and characterized for their mechanical and electrical properties. Solid polymer blend films based on PEO/PVC (50/50 wt%/wt%) with different graphite loading were prepared by using solution casting technique. Electrical conductivity results discovered the conductivity increased with increasing of filler loading. However, increasing amount of graphite loading led to a decreased in tensile strength and young’s modulus of PEO/PVC/Graphite polymer films. The dispersion of graphite and mechanism of conductive path in the polymer films were also investigated by scanning electron microscopy (SEM). The morphology of the PEO/PVC/Graphite polymer films shows that agglomeration occurred to complete the connection of conductive path, thus improving the conductivity behavior of the polymer films.

Nationwide impact and vehicle to grid application of electric vehicles mobility using an activity based model

OpenAIRE

Álvaro, Roberto; González, Jairo; Fraile Ardanuy, José Jesús; Knapen, Luk; Janssens, Davy

2013-01-01

This paper describes the impact of electric mobility on the transmission grid in Flanders region (Belgium), using a micro-simulation activity based models. These models are used to provide temporal and spatial estimation of energy and power demanded by electric vehicles (EVs) in different mobility zones. The increment in the load demand due to electric mobility is added to the background load demand in these mobility areas and the effects over the transmission substations are analyzed. From t...

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.

The effects of variable renewable electricity on energy efficiency and full load hours of fossil-fired power plants in the European Union

NARCIS (Netherlands)

de Groot, Mats; Crijns-Graus, Wina; Harmsen, Robert

2017-01-01

This study focused on the effects of variable renewable electricity (VRE) on full load hours and energy efficiency of fossil-fired power generation in the European Union from 1990-2014. Member states were aggregated into three groups based on the level of VRE penetration. Average full load hours are

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

Application of high-resolution domestic electricity load profiles in network modelling

DEFF Research Database (Denmark)

Marszal, Anna Joanna; Mendaza, Iker Diaz de Cerio; Heiselberg, Per Kvols

2016-01-01

the generated profiles are inputted in a low-voltage network model created in DIgSILENT PowerFactory. By means of employing 1 hour based demand and generation profiles in during dynamic studies, the representation of the local power system performance might sometimes not be as accurate as needed. In the test...... with modeling when 1-minute domestic electricity demand and generation profiles are used as inputs. The analysis is done with a case study of low-voltage network located in Northern Denmark. The analysis includes two parts. The first part focuses on modeling the domestic demands and on-site generation in 1......-minute resolution. The load profiles of the household appliances are created using a bottom-up model, which uses the 1-minute cycle power use characteristics of a single appliance as the main building block. The profiles of heavy electric appliances, such as heat pump, are not included in the above...

Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm

Directory of Open Access Journals (Sweden)

Bao Wang

2012-11-01

Full Text Available The accuracy of annual electric load forecasting plays an important role in the economic and social benefits of electric power systems. The least squares support vector machine (LSSVM has been proven to offer strong potential in forecasting issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. As a novel meta-heuristic and evolutionary algorithm, the fruit fly optimization algorithm (FOA has the advantages of being easy to understand and fast convergence to the global optimal solution. Therefore, to improve the forecasting performance, this paper proposes a LSSVM-based annual electric load forecasting model that uses FOA to automatically determine the appropriate values of the two parameters for the LSSVM model. By taking the annual electricity consumption of China as an instance, the computational result shows that the LSSVM combined with FOA (LSSVM-FOA outperforms other alternative methods, namely single LSSVM, LSSVM combined with coupled simulated annealing algorithm (LSSVM-CSA, generalized regression neural network (GRNN and regression model.

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.

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....

A New Approach to Detection of Systematic Errors in Secondary Substation Monitoring Equipment Based on Short Term Load Forecasting

Directory of Open Access Journals (Sweden)

Javier Moriano

2016-01-01

Full Text Available In recent years, Secondary Substations (SSs are being provided with equipment that allows their full management. This is particularly useful not only for monitoring and planning purposes but also for detecting erroneous measurements, which could negatively affect the performance of the SS. On the other hand, load forecasting is extremely important since they help electricity companies to make crucial decisions regarding purchasing and generating electric power, load switching, and infrastructure development. In this regard, Short Term Load Forecasting (STLF allows the electric power load to be predicted over an interval ranging from one hour to one week. However, important issues concerning error detection by employing STLF has not been specifically addressed until now. This paper proposes a novel STLF-based approach to the detection of gain and offset errors introduced by the measurement equipment. The implemented system has been tested against real power load data provided by electricity suppliers. Different gain and offset error levels are successfully detected.

Short-Term Multiple Forecasting of Electric Energy Loads for Sustainable Demand Planning in Smart Grids for Smart Homes

Directory of Open Access Journals (Sweden)

Adeshina Y. Alani

2017-10-01

Full Text Available Energy consumption in the form of fuel or electricity is ubiquitous globally. Among energy types, electricity is crucial to human life in terms of cooking, warming and cooling of shelters, powering of electronic devices as well as commercial and industrial operations. Users of electronic devices sometimes consume fluctuating amounts of electricity generated from smart-grid infrastructure owned by the government or private investors. However, frequent imbalance is noticed between the demand and supply of electricity, hence effective planning is required to facilitate its distribution among consumers. Such effective planning is stimulated by the need to predict future consumption within a short period. Although several interesting classical techniques have been used for such predictions, they still require improvement for the purpose of reducing significant predictive errors when used for short-term load forecasting. This research develops a near-zero cooperative probabilistic scenario analysis and decision tree (PSA-DT model to address the lacuna of enormous predictive error faced by the state-of-the-art models. The PSA-DT is based on a probabilistic technique in view of the uncertain nature of electricity consumption, complemented by a DT to reinforce the collaboration of the two techniques. Based on detailed experimental analytics on residential, commercial and industrial data loads, the PSA-DT model outperforms the state-of-the-art models in terms of accuracy to a near-zero error rate. This implies that its deployment for electricity demand planning will be of great benefit to various smart-grid operators and homes.

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Power load prediction based on GM (1,1)

Science.gov (United States)

Wu, Di

2017-05-01

Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

Short-term forecasting of individual household electricity loads with investigating impact of data resolution and forecast horizon

Directory of Open Access Journals (Sweden)

Yildiz Baran

2018-01-01

Full Text Available Smart grid components such as smart home and battery energy management systems, high penetration of renewable energy systems, and demand response activities, require accurate electricity demand forecasts for the successful operation of the electricity distribution networks. For example, in order to optimize residential PV generation and electricity consumption and plan battery charge-discharge regimes by scheduling household appliances, forecasts need to target and be tailored to individual household electricity loads. The recent uptake of smart meters allows easier access to electricity readings at very fine resolutions; hence, it is possible to utilize this source of available data to create forecast models. In this paper, models which predominantly use smart meter data alongside with weather variables, or smart meter based models (SMBM, are implemented to forecast individual household loads. Well-known machine learning models such as artificial neural networks (ANN, support vector machines (SVM and Least-Square SVM are implemented within the SMBM framework and their performance is compared. The analysed household stock consists of 14 households from the state of New South Wales, Australia, with at least a year worth of 5 min. resolution data. In order for the results to be comparable between different households, our study first investigates household load profiles according to their volatility and reveals the relationship between load standard deviation and forecast performance. The analysis extends previous research by evaluating forecasts over four different data resolution; 5, 15, 30 and 60 min, each resolution analysed for four different horizons; 1, 6, 12 and 24 h ahead. Both, data resolution and forecast horizon, proved to have significant impact on the forecast performance and the obtained results provide important insights for the operation of various smart grid applications. Finally, it is shown that the load profile of some

Short-term forecasting of individual household electricity loads with investigating impact of data resolution and forecast horizon

Science.gov (United States)

Yildiz, Baran; Bilbao, Jose I.; Dore, Jonathon; Sproul, Alistair B.

2018-05-01

Smart grid components such as smart home and battery energy management systems, high penetration of renewable energy systems, and demand response activities, require accurate electricity demand forecasts for the successful operation of the electricity distribution networks. For example, in order to optimize residential PV generation and electricity consumption and plan battery charge-discharge regimes by scheduling household appliances, forecasts need to target and be tailored to individual household electricity loads. The recent uptake of smart meters allows easier access to electricity readings at very fine resolutions; hence, it is possible to utilize this source of available data to create forecast models. In this paper, models which predominantly use smart meter data alongside with weather variables, or smart meter based models (SMBM), are implemented to forecast individual household loads. Well-known machine learning models such as artificial neural networks (ANN), support vector machines (SVM) and Least-Square SVM are implemented within the SMBM framework and their performance is compared. The analysed household stock consists of 14 households from the state of New South Wales, Australia, with at least a year worth of 5 min. resolution data. In order for the results to be comparable between different households, our study first investigates household load profiles according to their volatility and reveals the relationship between load standard deviation and forecast performance. The analysis extends previous research by evaluating forecasts over four different data resolution; 5, 15, 30 and 60 min, each resolution analysed for four different horizons; 1, 6, 12 and 24 h ahead. Both, data resolution and forecast horizon, proved to have significant impact on the forecast performance and the obtained results provide important insights for the operation of various smart grid applications. Finally, it is shown that the load profile of some households vary

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...

Nonintrusive Load Monitoring Based on Advanced Deep Learning and Novel Signature

Directory of Open Access Journals (Sweden)

Jihyun Kim

2017-01-01

Full Text Available Monitoring electricity consumption in the home is an important way to help reduce energy usage. Nonintrusive Load Monitoring (NILM is existing technique which helps us monitor electricity consumption effectively and costly. NILM is a promising approach to obtain estimates of the electrical power consumption of individual appliances from aggregate measurements of voltage and/or current in the distribution system. Among the previous studies, Hidden Markov Model (HMM based models have been studied very much. However, increasing appliances, multistate of appliances, and similar power consumption of appliances are three big issues in NILM recently. In this paper, we address these problems through providing our contributions as follows. First, we proposed state-of-the-art energy disaggregation based on Long Short-Term Memory Recurrent Neural Network (LSTM-RNN model and additional advanced deep learning. Second, we proposed a novel signature to improve classification performance of the proposed model in multistate appliance case. We applied the proposed model on two datasets such as UK-DALE and REDD. Via our experimental results, we have confirmed that our model outperforms the advanced model. Thus, we show that our combination between advanced deep learning and novel signature can be a robust solution to overcome NILM’s issues and improve the performance of load identification.

Long-term monitoring FBG-based cable load sensor

Science.gov (United States)

Zhang, Zhichun; Zhou, Zhi; Wang, Chuan; Ou, Jinping

2006-03-01

Stay cables are the main load-bearing components of stayed-cable bridges. The cables stress status is an important factor to the stayed-cable bridge structure safety evaluation. So it's very important not only to the bridge construction, but also to the long-term safety evaluation for the bridge structure in-service. The accurate measurement for cable load depends on an effective sensor, especially to meet the long time durability and measurement demand. FBG, for its great advantage of corrosion resistance, absolute measurement, high accuracy, electro-magnetic resistance, quasi-distribution sensing, absolute measurement and so on, is the most promising sensor, which can cater for the cable force monitoring. In this paper, a load sensor has been developed, which is made up of a bushing elastic supporting body, 4 FBGs uniformly-spaced attached outside of the bushing supporting body, and a temperature compensation FBG for other four FBGs, moreover a cover for protection of FBGs. Firstly, the sensor measuring principle is analyzed, and relationship equation of FBG wavelength shifts and extrinsic load has also been gotten. And then the sensor calibration experiments of a steel cable stretching test with the FBG load sensor and a reference electric pressure sensor is finished, and the results shows excellent linearity of extrinsic load and FBG wavelength shifts, and good repeatability, which indicates that such kind of FBG-based load sensor is suitable for load measurement, especially for long-term, real time monitoring of stay-cables.

A bankruptcy problem approach to load-shedding in multiagent-based microgrid operation.

Science.gov (United States)

Kim, Hak-Man; Kinoshita, Tetsuo; Lim, Yujin; Kim, Tai-Hoon

2010-01-01

A microgrid is composed of distributed power generation systems (DGs), distributed energy storage devices (DSs), and loads. To maintain a specific frequency in the islanded mode as an important requirement, the control of DGs' output and charge action of DSs are used in supply surplus conditions and load-shedding and discharge action of DSs are used in supply shortage conditions. Recently, multiagent systems for autonomous microgrid operation have been studied. Especially, load-shedding, which is intentional reduction of electricity use, is a critical problem in islanded microgrid operation based on the multiagent system. Therefore, effective schemes for load-shedding are required. Meanwhile, the bankruptcy problem deals with dividing short resources among multiple agents. In order to solve the bankruptcy problem, division rules, such as the constrained equal awards rule (CEA), the constrained equal losses rule (CEL), and the random arrival rule (RA), have been used. In this paper, we approach load-shedding as a bankruptcy problem. We compare load-shedding results by above-mentioned rules in islanded microgrid operation based on wireless sensor network (WSN) as the communication link for an agent's interactions.

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.

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

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.

A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow

Directory of Open Access Journals (Sweden)

Paulo Maciel

2013-07-01

Full Text Available Energy consumption is a matter of common concern in the world today. Research demonstrates that as a consequence of the constantly evolving and expanding field of information technology, data centers are now major consumers of electrical energy. Such high electrical energy consumption emphasizes the issues of sustainability and cost. Against this background, the present paper proposes a power load distribution algorithm (PLDA to optimize energy distribution of data center power infrastructures. The PLDA, which is based on the Ford-Fulkerson algorithm, is supported by an environment called ASTRO, capable of performing the integrated evaluation of dependability, cost and sustainability. More specifically, the PLDA optimizes the flow distribution of the energy flow model (EFM. EFMs are responsible for estimating sustainability and cost issues of data center infrastructures without crossing the restrictions of the power capacity that each device can provide (power system or extract (cooling system. Additionally, a case study is presented that analyzed seven data center power architectures. Significant results were observed, achieving a reduction in power consumption of up to 15.5%.

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)

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.

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

Science.gov (United States)

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

2016-01-01

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

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...

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....

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

Economic MPC based on LPV model for thermostatically controlled loads

DEFF Research Database (Denmark)

Zemtsov, Nikita; Hlava, Jaroslav; Frantsuzova, Galina

2017-01-01

Rapid increase of the renewable energy share in electricity production requires optimization and flexibility of the power consumption side. Thermostatically controlled loads (TCLs) have a large potential for regulation service provision. Economic model predictive control (MPC) is an advanced...... control method which can be used to syncronize the power consumption with undispatchable renewable electricity production. Thermal behavior of TCLs can be described by linear models based on energy balance of the system. In some cases, parameters of the model may be time-varying. In this work, we present...... a modified economic MPC based on linear parameter-varying model. In particular, we provide an exact transformation from a standard economic MPC formulation to a linear program. We assume that the variables influencing the model parameters are known (predictable) for the prediction horizon of the controller...

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

Energy Technology Data Exchange (ETDEWEB)

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

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.

Real-Time Vehicle Energy Management System Based on Optimized Distribution of Electrical Load Power

OpenAIRE

Yuefei Wang; Hao Hu; Li Zhang; Nan Zhang; Xuhui Sun

2016-01-01

As a result of severe environmental pressure and stringent government regulations, refined energy management for vehicles has become inevitable. To improve vehicle fuel economy, this paper presents a bus-based energy management system for the electrical system of internal combustion engine vehicles. Both the model of an intelligent alternator and the model of a lead-acid battery are discussed. According to these models, the energy management for a vehicular electrical system is formulated as ...

A Hybrid Seasonal Mechanism with a Chaotic Cuckoo Search Algorithm with a Support Vector Regression Model for Electric Load Forecasting

Directory of Open Access Journals (Sweden)

Yongquan Dong

2018-04-01

Full Text Available Providing accurate electric load forecasting results plays a crucial role in daily energy management of the power supply system. Due to superior forecasting performance, the hybridizing support vector regression (SVR model with evolutionary algorithms has received attention and deserves to continue being explored widely. The cuckoo search (CS algorithm has the potential to contribute more satisfactory electric load forecasting results. However, the original CS algorithm suffers from its inherent drawbacks, such as parameters that require accurate setting, loss of population diversity, and easy trapping in local optima (i.e., premature convergence. Therefore, proposing some critical improvement mechanisms and employing an improved CS algorithm to determine suitable parameter combinations for an SVR model is essential. This paper proposes the SVR with chaotic cuckoo search (SVRCCS model based on using a tent chaotic mapping function to enrich the cuckoo search space and diversify the population to avoid trapping in local optima. In addition, to deal with the cyclic nature of electric loads, a seasonal mechanism is combined with the SVRCCS model, namely giving a seasonal SVR with chaotic cuckoo search (SSVRCCS model, to produce more accurate forecasting performances. The numerical results, tested by using the datasets from the National Electricity Market (NEM, Queensland, Australia and the New York Independent System Operator (NYISO, NY, USA, show that the proposed SSVRCCS model outperforms other alternative models.

An efficient approach for electric load forecasting using distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network) neural network

International Nuclear Information System (INIS)

Cai, Yuan; Wang, Jian-zhou; Tang, Yun; Yang, Yu-chen

2011-01-01

This paper presents a neural network based on adaptive resonance theory, named distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network), applied to the electric load forecasting problem. The distributed ART combines the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multi-layer perceptions. The HS-ARTMAP, a hybrid of an RBF (Radial Basis Function)-network-like module which uses hyper-sphere basis function substitute the Gaussian basis function and an ART-like module, performs incremental learning capabilities in function approximation problem. The HS-ARTMAP only receives the compressed distributed coding processed by distributed ART to deal with the proliferation problem which ARTMAP (adaptive resonance theory map) architecture often encounters and still performs well in electric load forecasting. To demonstrate the performance of the methodology, data from New South Wales and Victoria in Australia are illustrated. Results show that the developed method is much better than the traditional BP and single HS-ARTMAP neural network. -- Research highlights: → The processing of the presented network is based on compressed distributed data. It's an innovation among the adaptive resonance theory architecture. → The presented network decreases the proliferation the Fuzzy ARTMAP architectures usually encounter. → The network on-line forecasts electrical load accurately, stably. → Both one-period and multi-period load forecasting are executed using data of different cities.

A Bankruptcy Problem Approach to Load-shedding in Multiagent-based Microgrid Operation

Directory of Open Access Journals (Sweden)

Yujin Lim

2010-09-01

Full Text Available A microgrid is composed of distributed power generation systems (DGs, distributed energy storage devices (DSs, and loads. To maintain a specific frequency in the islanded mode as an important requirement,  the control of DGs’ output and charge action of DSs are used in supply surplus conditions and load-shedding and discharge action of DSs are used in supply shortage conditions. Recently, multiagent systems for autonomous microgrid operation have been studied. Especially, load-shedding, which is intentional reduction of electricity use, is a critical problem in islanded microgrid operation based on the multiagent system. Therefore, effective schemes for load-shedding are required. Meanwhile, the bankruptcy problem deals with dividing short resources among multiple agents. In order to solve the bankruptcy problem, division rules, such as the constrained equal awards rule (CEA, the constrained equal losses rule (CEL, and the random arrival rule (RA, have been used. In this paper, we approach load-shedding as a bankruptcy problem. We compare load-shedding results by above-mentioned rules in islanded microgrid operation based on wireless sensor network (WSN as the communication link for an agent’s interactions.

New approaches to provide ride-through for critical loads in electric power distribution systems

Science.gov (United States)

Montero-Hernandez, Oscar C.

2001-07-01

The extensive use of electronic circuits has enabled modernization, automation, miniaturization, high quality, low cost, and other achievements regarding electric loads in the last decades. However, modern electronic circuits and systems are extremely sensitive to disturbances from the electric power supply. In fact, the rate at which these disturbances happen is considerable as has been documented in recent years. In response to the power quality concerns presented previously, this dissertation is proposing new approaches to provide ride-through for critical loads during voltage disturbances with emphasis on voltage sags. In this dissertation, a new approach based on an AC-DC-AC system is proposed to provide ride-through for critical loads connected in buildings and/or an industrial system. In this approach, a three-phase IGBT inverter with a built in Dc-link voltage regulator is suitably controlled along with static by-pass switches to provide continuous power to critical loads. During a disturbance, the input utility source is disconnected and the power from the inverter is connected to the load. The remaining voltage in the AC supply is converted to DC and compensated before being applied to the inverter and the load. After detecting normal utility conditions, power from the utility is restored to the critical load. In order to achieve an extended ride-through capability a second approach is introduced. In this case, the Dc-link voltage regulator is performed by a DC-DC Buck-Boost converter. This new approach has the capability to mitigate voltage variations below and above the nominal value. In the third approach presented in this dissertation, a three-phase AC to AC boost converter is investigated. This converter provides a boosting action for the utility input voltages, right before they are applied to the load. The proposed Pulse Width Modulation (PWM) control strategy ensures independent control of each phase and compensates for both single-phase or poly

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.

electrical load survey electrical load survey and forecast

African Journals Online (AJOL)

eobe

scattered nature of the area and low load factor. In this ... employment and allow decentralized production of the ... and viable concept from energy production and .... VII Yr. ×. kWh. VIII Yr. ×. kWh. IX Yr. ×. kWh. X Yr. ×. kWh. 1. Residential. 147.

Prediction of crack density and electrical resistance changes in indium tin oxide/polymer thin films under tensile loading

KAUST Repository

Mora Cordova, Angel

2014-06-11

We present unified predictions for the crack onset strain, evolution of crack density, and changes in electrical resistance in indium tin oxide/polymer thin films under tensile loading. We propose a damage mechanics model to quantify and predict such changes as an alternative to fracture mechanics formulations. Our predictions are obtained by assuming that there are no flaws at the onset of loading as opposed to the assumptions of fracture mechanics approaches. We calibrate the crack onset strain and the damage model based on experimental data reported in the literature. We predict crack density and changes in electrical resistance as a function of the damage induced in the films. We implement our model in the commercial finite element software ABAQUS using a user subroutine UMAT. We obtain fair to good agreement with experiments. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

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.)

Analysis of the reactive power consumption and the harmonics in the network by the non-linear electrical loads

Energy Technology Data Exchange (ETDEWEB)

Cogo, Joao Roberto [Escola Federal de Engenharia de Itajuba, MG (Brazil)

1994-12-31

The non linear electrical loads can give rise to a number of disturbances in electrical power networks. Among them, the high consumption of relative power is to be noted and so is the several harmonic components which may be injected in the industry system and very often in the utility system. So, by using appropriate technical considerations, as well as measurements in typical special electrical loads, such negative effects are analyzed and ways of minimizing them are suggested. (author) 3 refs., 11 figs., 6 tabs.

A flexible control strategy of plug-in electric vehicles operating in seven modes for smoothing load power curves in smart grid

International Nuclear Information System (INIS)

Khemakhem, Siwar; Rekik, Mouna; Krichen, Lotfi

2017-01-01

Plug-in electric vehicles (PEVs) seem to be an interesting new electrical load for improving the reliability of smart grid. The purpose of this work is to investigate a supervision strategy based on regulated charging of PEVs in order to guarantee an optimized power management of the system and consequently a flatter power demand curve. The system mainly includes PEVs powered by a Lithium-ion battery ensuring the charging and discharging operations of these PEVs at home and a daily load power demanded by home appliances. The purpose of the considered strategy is to detect the connection status of each PEV and to establish the priority order between these PEVs with certain flexibility which results in managing the PEVs through seven operating modes. The response of the control algorithm enables to ensure the power flow exchange between the PEVs and the electrical grid, especially at rush hours, and to minimize load power variance aiming to achieve the smoothness for the power demand curve and to reduce the stress of the electrical grid. The simulation results are presented in order to illustrate the efficiency of this power control approach. - Highlights: • A flexible power management algorithm of Plug-in electric vehicle is proposed. • This control can be applied for any home equipped with two PEVs. • The response is to ensure the power flow exchange between PEVs and power grid. • The main contribution is to achieve the smoothness for the daily power demand curve.

Knowledge-Based System to Support Plug Load Management

Data.gov (United States)

National Aeronautics and Space Administration — Electrical plug loads comprise an increasingly larger share of building energy consumption as improvements have been made to Heating, Ventilation, and Air...

Advantages of geosynchronous solar power satellites for terrestrial base-load electrical supply compared to other renewable energy sources - or why civilization needs solar power satellites

Energy Technology Data Exchange (ETDEWEB)

Strickland, J.K. Jr. [Texas Univ., Austin, TX (United States)

1998-06-01

The arguments in favour of using solar power satellites for primary base-load electrical supply are presented and compared with the advantages and drawbacks of other renewable energy sources, especially ground solar and wind systems. Popular misconceptions about energy use and the importation of space solar energy to the Earth`s surface are examined and discounted. Finally an optimal mix of space solar (focusing on geosynchronous solar power satellites), ground solar, and other energy sources is described which, it is argued, would be capable to meet future global energy demand. (UK)

Climate Control Load Reduction Strategies for Electric Drive Vehicles in Cold Weather: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jeffers, Matthew; Chaney, Lawrence; Rugh, John

2016-03-31

When operated, the climate control system is the largest auxiliary load on a vehicle. This load has significant impact on fuel economy for conventional and hybrid vehicles, and it drastically reduces the driving range of all electric vehicles (EVs). Heating is even more detrimental to EV range than cooling because no engine waste heat is available. Reducing the thermal loads on the heating, ventilating, and air conditioning system will extend driving range and increase the market penetration of EVs. Researchers at the National Renewable Energy Laboratory have evaluated strategies for vehicle climate control load reduction with special attention toward grid connected electric vehicles. Outdoor vehicle thermal testing and computational modeling were used to assess potential strategies for improved thermal management and to evaluate the effectiveness of thermal load reduction technologies. A human physiology model was also used to evaluate the impact on occupant thermal comfort. Experimental evaluations of zonal heating strategies demonstrated a 5.5% to 28.5% reduction in cabin heating energy over a 20-minute warm-up. Vehicle simulations over various drive cycles show a 6.9% to 18.7% improvement in EV range over baseline heating using the most promising zonal heating strategy investigated. A national-level analysis was conducted to determine the overall national impact. If all vehicles used the best zonal strategy, the range would be improved by 7.1% over the baseline heating range. This is a 33% reduction in the range penalty for heating.

Voltage Stability Control of Electrical Network Using Intelligent Load Shedding Strategy Based on Fuzzy Logic

Directory of Open Access Journals (Sweden)

Houda Jouini

2010-01-01

Full Text Available As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several preventive and curative means are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we try to propose an intelligent load shedding strategy as a new approach based on fuzzy controllers. This strategy was founded on the calculation of generated power sensitivity degree related to those injected at different network buses. During the fault phase, fuzzy controller algorithms generate monitor vectors ensuring a precalculated load shedding ratio in the purpose to reestablish the power balance and conduct the network to a new steady state.

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

Directory of Open Access Journals (Sweden)

S. Saravanan

2012-07-01

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

MODEL FOR ELECTRIC LOAD OF COMMUNITY HOUSING PROJECTS TO INVESTIGATE “GENERATOR – ACCUMULATOR – CONSUMER” SYSTEM WHILE USING MONTE-CARLO METHOD

Directory of Open Access Journals (Sweden)

K. V. Dobrego

2017-01-01

Full Text Available Nowadays we observe rather rapid growth of energy accumulators market. There are prerequisites to their extensive application in Belarus. In spite of technology development problems pertaining to optimization of electric power and their operation under conditions of specific systems “generator – accumulator – consumer” (GAC have not obtained proper consideration. At the same time tuning and optimization of the GAC system may provide competitive advantages to various accumulating systems because application of accumulator batteries in non-optimal charge – discharge conditions reduces its operating resource. Optimization of the GAC system may include utilization of hybrid accumulator systems together with heterogeneous chemical and mechanical accumulators, tuning of system controller parameters etc. Research papers present a great number of empirical and analytical methods for calculation of electric loads. These methods use the following parameters as initial data: time-averaged values of actual electric power consumption, averaged apartment electric loads, empirical and statistical form coefficients, coefficients of maximum electric load for a group of uniform consumers. However such models do not meet the requirements of detailed simulation of relatively small system operation when the simulation must correspond to non-stationary, non-averaged, stochastic load nature. The paper provides a simple approach to the detailed simulation of electric loads in regard to small projects such as multi-unit apartment building or small agricultural farm. The model is formulated both in physical and algorithmic terms that make it possible to be easily realized in any programming environment. The paper presents convergence of integral electric power consumption, which is set by the model, to statistically averaged parameters. Autocorrelation function has been calculated in the paper that shows two scales for autocorrelation of simulated load diagrams

Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model

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Yanting Du

2018-02-01

Full Text Available In order to estimate the diesel particulate filter (DPF soot load and improve the accuracy of regeneration timing, a novel method based on an equivalent circuit model is proposed based on the electric-fluid analogy. This proposed method can reduce the impact of the engine transient operation on the soot load, accurately calculate the flow resistance, and improve the estimation accuracy of the soot load. Firstly, the least square method is used to identify the flow resistance based on the World Harmonized Transient Cycle (WHTC test data, and the relationship between flow resistance, exhaust temperature and soot load is established. Secondly, the online estimation of the soot load is achieved by using the dual extended Kalman filter (DEKF. The results show that this method has good convergence and robustness with the maximal absolute error of 0.2 g/L at regeneration timing, which can meet engineering requirements. Additionally, this method can estimate the soot load under engine transient operating conditions and avoids a large number of experimental tests, extensive calibration and the analysis of complex chemical reactions required in traditional methods.

Short-term load and wind power forecasting using neural network-based prediction intervals.

Science.gov (United States)

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2014-02-01

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

A neutral network based technique for short-term forecasting of anomalous load periods

Energy Technology Data Exchange (ETDEWEB)

Sforna, M [ENEL, s.p.a, Italian Power Company (Italy); Lamedica, R; Prudenzi, A [Rome Univ. ` La Sapienza` , Rome (Italy); Caciotta, M; Orsolini Cencelli, V [Rome Univ. III, Rome (Italy)

1995-01-01

The paper illustrates a part of the research activity conducted by authors in the field of electric Short Term Load Forecasting (STLF) based on Artificial Neural Network (ANN) architectures. Previous experiences with basic ANN architectures have shown that, even though these architecture provide results comparable with those obtained by human operators for most normal days, they evidence some accuracy deficiencies when applied to `anomalous` load conditions occurring during holidays and long weekends. For these periods a specific procedure based upon a combined (unsupervised/supervised) approach has been proposed. The unsupervised stage provides a preventive classification of the historical load data by means of a Kohonen`s Self Organizing Map (SOM). The supervised stage, performing the proper forecasting activity, is obtained by using a multi-layer percept ron with a back propagation learning algorithm similar to the ones above mentioned. The unconventional use of information deriving from the classification stage permits the proposed procedure to obtain a relevant enhancement of the forecast accuracy for anomalous load situations.

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.

A novel approach for UI charge reduction using AMI based load prioritization in smart grid

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Avani Pujara

2017-09-01

Full Text Available System frequency is vital part for power system balance. As per India Electricity Grid code frequency should be in the range of 49.5 Hz–50.5 Hz. Deviation from above mentioned range is charged as Unscheduled Interchange (UI charge. This paper proposes a new method for load and frequency control based on control of third parameter of three-part Availability Based Tariff (ABT i.e. Unscheduled Interchange charges. New circuit is designed considering prioritization of load and using Advanced Metering Infrastructure (AMI under Smart Grid environment.

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

Effect of blade flutter and electrical loading on small wind turbine noise

Science.gov (United States)

The effect of blade flutter and electrical loading on the noise level of two different size wind turbines was investigated at the Conservation and Production Research Laboratory (CPRL) near Bushland, TX. Noise and performance data were collected on two blade designs tested on a wind turbine rated a...

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

Lambda-Based Data Processing Architecture for Two-Level Load Forecasting in Residential Buildings

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Gde Dharma Nugraha

2018-03-01

Full Text Available Building energy management systems (BEMS have been intensively used to manage the electricity consumption of residential buildings more efficiently. However, the dynamic behavior of the occupants introduces uncertainty problems that affect the performance of the BEMS. To address this uncertainty problem, the BEMS may implement load forecasting as one of the BEMS modules. Load forecasting utilizes historical load data to compute model predictions for a specific time in the future. Recently, smart meters have been introduced to collect electricity consumption data. Smart meters not only capture aggregation data, but also individual data that is more frequently close to real-time. The processing of both smart meter data types for load forecasting can enhance the performance of the BEMS when confronted with uncertainty problems. The collection of smart meter data can be processed using a batch approach for short-term load forecasting, while the real-time smart meter data can be processed for very short-term load forecasting, which adjusts the short-term load forecasting to adapt to the dynamic behavior of the occupants. This approach requires different data processing techniques for aggregation and individual of smart meter data. In this paper, we propose Lambda-based data processing architecture to process the different types of smart meter data and implement the two-level load forecasting approach, which combines short-term and very short-term load forecasting techniques on top of our proposed data processing architecture. The proposed approach is expected to enhance the BEMS to address the uncertainty problem in order to process data in less time. Our experiment showed that the proposed approaches improved the accuracy by 7% compared to a typical BEMS with only one load forecasting technique, and had the lowest computation time when processing the smart meter data.

A pattern recognition methodology for evaluation of load profiles and typical days of large electricity customers

International Nuclear Information System (INIS)

Tsekouras, G.J.; Kotoulas, P.B.; Tsirekis, C.D.; Dialynas, E.N.; Hatziargyriou, N.D.

2008-01-01

This paper describes a pattern recognition methodology for the classification of the daily chronological load curves of each large electricity customer, in order to estimate his typical days and his respective representative daily load profiles. It is based on pattern recognition methods, such as k-means, self-organized maps (SOM), fuzzy k-means and hierarchical clustering, which are theoretically described and properly adapted. The parameters of each clustering method are properly selected by an optimization process, which is separately applied for each one of six adequacy measures. The results can be used for the short-term and mid-term load forecasting of each consumer, for the choice of the proper tariffs and the feasibility studies of demand side management programs. This methodology is analytically applied for one medium voltage industrial customer and synoptically for a set of medium voltage customers of the Greek power system. The results of the clustering methods are presented and discussed. (author)

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.

Are daily and weekly load and spot price dynamics in Australia's National Electricity Market governed by episodic nonlinearity?

International Nuclear Information System (INIS)

Wild, Phillip; Hinich, Melvin J.; Foster, John

2010-01-01

In this article, we use half hourly spot electricity prices and load data for the National Electricity Market (NEM) of Australia for the period from December 1998 to June 2009 to test for episodic nonlinearity in the dynamics governing daily and weekly cycles in load and spot price time series data. We apply the portmanteau correlation, bicorrelation and tricorrelation tests introduced in Hinich (1996) to the time series of half hourly spot prices and load demand from 7/12/1998 to 30/06/2009 using a FORTRAN 95 program. We find the presence of significant third and fourth-order (nonlinear) serial dependence in the weekly load and spot price data in particular, but to a much more marginal extent, in the daily data. (author)

Assessing the influence of the temporal resolution of electrical load and PV generation profiles on self-consumption and sizing of PV-battery systems

International Nuclear Information System (INIS)

Beck, T.; Kondziella, H.; Huard, G.; Bruckner, T.

2016-01-01

Highlights: • MILP optimization model for operation and investment of PV-battery systems. • Use of high resolution (10 s) electrical household load and PV generation profiles. • Analysis of influence of temporal resolution on self-consumption and optimal sizing. • Electrical load profile characteristics influence required temporal resolution. - Abstract: The interest in self-consumption of electricity generated by rooftop photovoltaic systems has grown in recent years, fueled by decreasing levelized costs of electricity and feed-in tariffs as well as increasing end customer electricity prices in the residential sector. This also fostered research on grid-connected PV-battery storage systems, which are a promising technology to increase self-consumption. In this paper a mixed-integer linear optimization model of a PV-battery system that minimizes the total discounted operating and investment costs is developed. The model is employed to study the effect of the temporal resolution of electrical load and PV generation profiles on the rate of self-consumption and the optimal sizing of PV and PV-battery systems. In contrast to previous studies high resolution (10 s) measured input data for both PV generation and electrical load profiles is used for the analysis. The data was obtained by smart meter measurements in 25 different households in Germany. It is shown that the temporal resolution of load profiles is more critical for the accuracy of the determination of self-consumption rates than the resolution of the PV generation. For PV-systems without additional storage accurate results can be obtained by using 15 min solar irradiation data. The required accuracy for the electrical load profiles depends strongly on the load profile characteristics. While good results can be obtained with 60 s for all electrical load profiles, 15 min data can still be sufficient for load profiles that do not exhibit most of their electricity consumption at power levels above 2 k

Properties of single-walled carbon nanotube-based aerogels as a function of nanotube loading

International Nuclear Information System (INIS)

Worsley, Marcus A.; Pauzauskie, Peter J.; Kucheyev, Sergei O.; Zaug, Joseph M.; Hamza, Alex V.; Satcher, Joe H.; Baumann, Theodore F.

2009-01-01

Here, we present the synthesis and characterization of low-density single-walled carbon nanotube-based aerogels (SWNT-CA). Aerogels with varying nanotube loading (0-55 wt.%) and density (20-350 mg cm -3 ) were fabricated and characterized by four-probe method, electron microscopy, Raman spectroscopy and nitrogen porosimetry. Several properties of the SWNT-CAs were highly dependent upon nanotube loading. At nanotube loadings of 55 wt.%, shrinkage of the aerogel monoliths during carbonization and drying was almost completely eliminated. Electrical conductivities are improved by an order of magnitude for the SWNT-CA (55 wt.% nanotubes) compared to those of foams without nanotubes. Surface areas as high as 184 m 2 g -1 were achieved for SWNT-CAs with greater than 20 wt.% nanotube loading.

Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads

Science.gov (United States)

Parlos, Alexander G.; Toliyat, Hamid A.

2005-01-01

An end-of-life prediction system developed for electric machines and their loads could be used in integrated vehicle health monitoring at NASA and in other government agencies. This system will provide on-line, real-time condition assessment and end-of-life prediction of electric machines (e.g., motors, generators) and/or their loads of mechanically coupled machinery (e.g., pumps, fans, compressors, turbines, conveyor belts, magnetic levitation trains, and others). In long-duration space flight, the ability to predict the lifetime of machinery could spell the difference between mission success or failure. Therefore, the system described here may be of inestimable value to the U.S. space program. The system will provide continuous monitoring for on-line condition assessment and end-of-life prediction as opposed to the current off-line diagnoses.

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

The rule of nuclear power in the base-load portfolio optimization process

International Nuclear Information System (INIS)

Desiata, L.; D'Alberti, F.

2007-01-01

The pursuit of optimal portfolios, maximizing long-term profitability, is the main strategic challenge faced by electricity producers nowadays. Investment decisions, worth billions of euros, are affected by spot factors (such as current fuel prices volatility) that often lead to unbalanced generation mixes. Our analysis presents a statistical-financial approach that highlights the role of nuclear within the base-load portfolio optimisation process [it

Method of bringing nuclear power plant to fractional electrical load conditions

International Nuclear Information System (INIS)

Iljunin, V.G.; Kuznetsoy, I.A.; Murogov, V.M.; Shmelev, A.N.

1978-01-01

A method is described of bringing a nuclear power plant to fractional electric load conditions, which power plant comprises at least two nuclear reactors, at least one nuclear reactor being a breeder and both reactors transferring heat to the turbine working substance, consisting in that the consumption of the turbine working substance is reduced in accordance with a predetermined fractional load. At the same time, the amount of heat being transferred from the nuclear reactors to the turbine working substance is reduced, for which purpose the reactors are included in autonomous cooling circuits to successively transfer heat to the turbine working substance. The breeding reactor is included in the cooling circuit with a lower coolant temperature, the temperature of the coolant at the inlet and outlet of the breeder being reduced to a level ensuring the operation of the nuclear power plant in predetermined fractional load conditions, due to which the power of the breeder is increased, and afterheat is removed

The influence of the structure of the metal load removal from liquid steel in electric arc furnaces

Science.gov (United States)

Pǎcurar, Cristina; Hepuť, Teodor; Crisan, Eugen

2016-06-01

One of the main technical and economic indicators in the steel industry and steel respectively the development it is the removal of liquid steel. This indicator depends on several factors, namely technology: the structure and the quality metal load, the degree of preparedness of it, and the content of non-metallic material accompanying the unit of drawing up, the technology for the elaboration, etc. research has been taken into account in drawing up steel electric arc furnace type spring EBT (Electric Bottom taping), seeking to load and removing components of liquid steel. Metal load has been composed of eight metal grades, in some cases with great differences in terms of quality. Data obtained were processed in the EXCEL spreadsheet programs and MATLAB, the results obtained being presented both graphically and analytically. On the basis of the results obtained may opt for a load optimal structure metal.

A New Neural Network Approach to Short Term Load Forecasting of Electrical Power Systems

Directory of Open Access Journals (Sweden)

Farshid Keynia

2011-03-01

Full Text Available Short-term load forecast (STLF is an important operational function in both regulated power systems and deregulated open electricity markets. However, STLF is not easy to handle due to the nonlinear and random-like behaviors of system loads, weather conditions, and social and economic environment variations. Despite the research work performed in the area, more accurate and robust STLF methods are still needed due to the importance and complexity of STLF. In this paper, a new neural network approach for STLF is proposed. The proposed neural network has a novel learning algorithm based on a new modified harmony search technique. This learning algorithm can widely search the solution space in various directions, and it can also avoid the overfitting problem, trapping in local minima and dead bands. Based on this learning algorithm, the suggested neural network can efficiently extract the input/output mapping function of the forecast process leading to high STLF accuracy. The proposed approach is tested on two practical power systems and the results obtained are compared with the results of several other recently published STLF methods. These comparisons confirm the validity of the developed approach.

The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use. A review

International Nuclear Information System (INIS)

Newsham, Guy R.; Bowker, Brent G.

2010-01-01

Peak demand for electricity in North America is expected to grow, challenging electrical utilities to supply this demand in a cost-effective, reliable manner. Therefore, there is growing interest in strategies to reduce peak demand by eliminating electricity use, or shifting it to non-peak times. This strategy is commonly called 'demand response'. In households, common strategies are time-varying pricing, which charge more for energy use on peak, or direct load control, which allows utilities to curtail certain loads during high demand periods. We reviewed recent North American studies of these strategies. The data suggest that the most effective strategy is a critical peak price (CPP) program with enabling technology to automatically curtail loads on event days. There is little evidence that this causes substantial hardship for occupants, particularly if they have input into which loads are controlled and how, and have an override option. In such cases, a peak load reduction of at least 30% is a reasonable expectation. It might be possible to attain such load reductions without enabling technology by focusing on household types more likely to respond, and providing them with excellent support. A simple time-of-use (TOU) program can only expect to realise on-peak reductions of 5%. (author)

Usage monitoring of electrical devices in a smart home.

Science.gov (United States)

Rahimi, Saba; Chan, Adrian D C; Goubran, Rafik A

2011-01-01

Profiling the usage of electrical devices within a smart home can be used as a method for determining an occupant's activities of daily living. A nonintrusive load monitoring system monitors the electrical consumption at a single electrical source (e.g., main electric utility service entry) and the operating schedules of individual devices are determined by disaggregating the composite electrical consumption waveforms. An electrical device's load signature plays a key role in nonintrusive load monitoring systems. A load signature is the unique electrical behaviour of an individual device when it is in operation. This paper proposes a feature-based model, using the real power and reactive power as features for describing the load signatures of individual devices. Experimental results for single device recognition for 7 devices show that the proposed approach can achieve 100% classification accuracy with discriminant analysis using Mahalanobis distances.

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)

Fully-distributed Load Frequency Control Strategy in an Islanded Microgrid Considering Plug-In Electric Vehicles

Directory of Open Access Journals (Sweden)

Xiao Qi

2018-06-01

Full Text Available With large-scale integration of electric vehicles, this paper investigates the load frequency control problem in an islanded microgrid with plug-in electric vehicles (PEVs, which can be regarded as mobile battery energy storages to provide a valuable contribution to frequency regulation. A novel fully-distributed control strategy is proposed to achieve fast frequency regulation of islanded microgrids and effective coordination control of distributed energy sources. Firstly, distributed control based on an improved linear active disturbance rejection algorithm is realized through a multi-agent system, and it greatly enhances the anti-disturbance capability of the microgrid. Then, in order to guarantee the effectiveness of PEVs in frequency regulation, PEVs are controlled following the controllable power rate (CPR calculated from the consensus-based multi-agent system. Furthermore, the system control construction in this paper is well designed to avoid the negative effects caused by system communication time delay. Finally, numerical simulations under different disturbances are carried out to demonstrate the effectiveness of the proposed control strategy in comparison with other previous control strategies.

The Effect of Electric Load Profiles on the Performance of Off-Grid Residential Hybrid Renewable Energy Systems

Directory of Open Access Journals (Sweden)

Stephen Treado

2015-10-01

Full Text Available This paper investigates the energy performance of off-grid residential hybrid renewable electric power systems, particularly the effect of electric load profiles on the ability to harvest available solar energy and avoid the consumption of auxiliary energy in the form of propane. The concepts are illustrated by an analysis of the energy performance of electric and propane-fired refrigerators. Off-grid electric power systems frequently incorporate a renewable source, such as wind or solar photovoltaic (PV, with a back-up power provided by a propane fueled motor/generator. Among other design decisions, residential consumers face the choice of employing an electric refrigerator with a conventional vapor compression refrigeration system, or a fuel-fired refrigerator operating as an absorption refrigeration system. One interesting question is whether it is more advantageous from an energy perspective to use electricity to run the refrigerator, which might be provided by some combination of the PV and propane motor/generator, thereby taking advantage of the relatively higher electric refrigerator Coefficient of Performance (COP and free solar energy but having to accept a low electrical conversion efficiency of the motor/generator, or use thermal energy from the combustion of propane to produce the refrigeration effect via an absorption system, albeit with a much lower COP. The analysis is complicated by the fact that most off-grid renewable electrical power systems utilize a battery bank to provide electrical power when it is not available from the wind turbine or PV system, so the state of charge of the battery bank will have a noticeable impact on what energy source is available at any moment in time. Daily electric load profiles combined with variable solar energy input determine the state of charge of the battery bank, with the degree of synchronization between the two being a critical factor in determining performance. The annual energy usage

Systems and methods for providing power to a load based upon a control strategy

Science.gov (United States)

Perisic, Milun; Kajouke, Lateef A; Ransom, Ray M

2013-12-24

Systems and methods are provided for an electrical system. The electrical system includes a load, an interface configured to receive a voltage from a voltage source, and a controller configured to receive the voltage from the voltage source through the interface and to provide a voltage and current to the load. Wherein, when the controller is in a constant voltage mode, the controller provides a constant voltage to the load, when the controller is in a constant current mode, the controller provides a constant current to the load, and when the controller is in a constant power mode, the controller provides a constant power to the load.

Muscle electrical activity during exercises with and without load executed on dry land and in an aquatic environment

Directory of Open Access Journals (Sweden)

Indira Nayra Paz Santos

Full Text Available Introduction Muscle activity in the aquatic environment was investigated using electromyographic analyses. The physical properties of water and the resistance used may influence the response of the muscle during exercise. The objective of this study was to evaluate the electrical activity in water and on the floor during flexion and knee extension exercises with and without load and aimed at understanding the muscular response while performing resistance exercises in water. Methods The sample consisted of 14 volunteers between 18 and 35 years old who were subjected to active exercises involving knee flexion and extension with and without load on the floor and in water. Electromyography was performed during the movement. Results A significant increase was found in the electrical activity of the rectus femoris muscle during exercises on the floor. The biceps femoris muscle showed increased electromyographic activity when resistance was used. A significant increase was found in the electrical activity of the rectus femoris muscle compared with exercises with and without load and the moment of rest in immersion. The electrical activity of the rectus and biceps femoris muscles was reduced in exercises with load and without load in a therapy pool compared with on the floor. Conclusion There was a reduction of the electromyographic activity in the aquatic environment compared with that on the ground, which could be attributed to the effects from hot water. Therefore, it is believed that resistance exercises can be performed early in a therapy pool, which will facilitate the prevention and treatment of musculoskeletal disorders.

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

DEFF Research Database (Denmark)

Vlachogiannis, Ioannis (John)

2009-01-01

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

Modeling of plug-in electric vehicle travel patterns and charging load based on trip chain generation

Science.gov (United States)

Wang, Dai; Gao, Junyu; Li, Pan; Wang, Bin; Zhang, Cong; Saxena, Samveg

2017-08-01

Modeling PEV travel and charging behavior is the key to estimate the charging demand and further explore the potential of providing grid services. This paper presents a stochastic simulation methodology to generate itineraries and charging load profiles for a population of PEVs based on real-world vehicle driving data. In order to describe the sequence of daily travel activities, we use the trip chain model which contains the detailed information of each trip, namely start time, end time, trip distance, start location and end location. A trip chain generation method is developed based on the Naive Bayes model to generate a large number of trips which are temporally and spatially coupled. We apply the proposed methodology to investigate the multi-location charging loads in three different scenarios. Simulation results show that home charging can meet the energy demand of the majority of PEVs in an average condition. In addition, we calculate the lower bound of charging load peak on the premise of lowest charging cost. The results are instructive for the design and construction of charging facilities to avoid excessive infrastructure.

Advances in electric power and energy systems load and price forecasting

CERN Document Server

2017-01-01

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

Hierarchical Load Tracking Control of a Grid-connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

DEFF Research Database (Denmark)

Li, Yonghui; Wu, Qiuwei; Zhu, Haiyu

2015-01-01

efficiency operation obtained at different active power output levels, a hierarchical load tracking control scheme for the grid-connected SOFC was proposed to realize the maximum electrical efficiency operation with the stack temperature bounded. The hierarchical control scheme consists of a fast active...... power control and a slower stack temperature control. The active power control was developed by using a decentralized control method. The efficiency of the proposed hierarchical control scheme was demonstrated by case studies using the benchmark SOFC dynamic model......Based on the benchmark solid oxide fuel cell (SOFC) dynamic model for power system studies and the analysis of the SOFC operating conditions, the nonlinear programming (NLP) optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject...

Software for optimal selection of places for installation of balancing devices in 0,4 kV electric power systems loaded with electric motors

Directory of Open Access Journals (Sweden)

Romanova Victoria

2017-01-01

Full Text Available This publication considers the issues of development of the software program for designing of 0,4 kV power supply systems with motor-actuated load under voltage unsymmetry conditions (using the example of the Trans-Baikal Territory. Voltage unsymmetry is practically constant phenomenon in the electric power networks of different voltage types. Voltage unsymmetry effects significantly the electric power consumers, including the supply mains itself. It has especially negative impact on the electrical equipment operation process and its lifetime. The urgency of the problem is confirmed by multiple research on the same topic and by significant number of damages suffered by the electric power consumers staying in service (especially in the Trans-Baikal Territory and in the Far-East regions. Voltage unsymmetry causes economic loss and reduction of the electromagnetic interference value by the voltage unsymmetry coefficient in negative-phase sequence (K2U gives inevitable economic effect accordingly. However, the payback period for the activities aimed at reduction of electromagnetic interference, will vary from some months to several years. The more accurate value of the payback period may be obtained using the developed software program. The developed software design program is implemented by means of the programming language C# in Microsoft Visual Studio environment, using the built-in cross-platform database SQLite. The software program shall allow making quick and accurate calculation of the power losses, to determine the economic feasibility of provision special measures for removal of the voltage unsymmetry, for determination of optimal application and location of the balancing devices. The software implementation in power systems loaded with electric motors will improve reliability and efficiency of asynchronous motors. The software is of interest for developers of projects on power supply systems for regions with non-linear loads.

Runoff load estimation of particulate and dissolved nitrogen in Lake Inba watershed using continuous monitoring data on turbidity and electric conductivity.

Science.gov (United States)

Kim, J; Nagano, Y; Furumai, H

2012-01-01

Easy-to-measure surrogate parameters for water quality indicators are needed for real time monitoring as well as for generating data for model calibration and validation. In this study, a novel linear regression model for estimating total nitrogen (TN) based on two surrogate parameters is proposed based on evaluation of pollutant loads flowing into a eutrophic lake. Based on their runoff characteristics during wet weather, electric conductivity (EC) and turbidity were selected as surrogates for particulate nitrogen (PN) and dissolved nitrogen (DN), respectively. Strong linear relationships were established between PN and turbidity and DN and EC, and both models subsequently combined for estimation of TN. This model was evaluated by comparison of estimated and observed TN runoff loads during rainfall events. This analysis showed that turbidity and EC are viable surrogates for PN and DN, respectively, and that the linear regression model for TN concentration was successful in estimating TN runoff loads during rainfall events and also under dry weather conditions.

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

Directory of Open Access Journals (Sweden)

Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

Decentralized Electric Vehicle Charging Strategies for Reduced Load Variation and Guaranteed Charge Completion in Regional Distribution Grids

Directory of Open Access Journals (Sweden)

Weige Zhang

2017-01-01

Full Text Available A novel, fully decentralized strategy to coordinate charge operation of electric vehicles is proposed in this paper. Based on stochastic switching control of on-board chargers, this strategy ensures high-efficiency charging, reduces load variations to the grid during charging periods, achieves charge completion with high probability, and accomplishes approximate “valley-filling”. Further improvements on the core strategy, including individualized power management, adaptive strategies, and battery support systems, are introduced to further reduce power fluctuation variances and to guarantee charge completion. Stochastic analysis is performed to establish the main properties of the strategies and to quantitatively show the performance improvements. Compared with the existing decentralized charging strategies, the strategies proposed in this paper can be implemented without any information exchange between grid operators and electric vehicles (EVs, resulting in a communications cost reduction. Additionally, it is shown that by using stochastic charging rules, a grid-supporting battery system with a very small energy capacity can achieve substantial reduction of EV load fluctuations with high confidence. An extensive set of simulations and case studies with real-world data are used to demonstrate the benefits of the proposed strategies.

Improving the principles of short-term electric load forecasting of the Irkutsk region

Directory of Open Access Journals (Sweden)

Kornilov Vladimir

2017-01-01

Full Text Available Forecasting of electric load (EL is an important task for both electric power entities and large consumers of electricity [1]. Large consumers are faced with the need to compose applications for the planned volume of EL, and the deviation of subsequent real consumption from previously announced leads to the appearance of penalties from the wholesale market. In turn, electricity producers are interested in forecasting the demand for electricity for prompt response to its fluctuations and for the purpose of optimal infrastructure development. The most difficult and urgent task is the hourly forecasting of EL, which is extremely important for the successful solution of problems of optimization of generating capacities, minimization of power losses, dispatching control, security assessment of power supply, etc. Ultimately, such forecasts allow optimizing the cash costs for electricity and fuel or water consumption during generation. This paper analyzes the experience of the branch of JSC "SO UPS" Irkutsk Regional Dispatch Office of the procedure for short-term forecasting of the EL of the Irkutsk region.

Load research manual. Volume 1. Load research procedures

Energy Technology Data Exchange (ETDEWEB)

Brandenburg, L.; Clarkson, G.; Grund, Jr., C.; Leo, J.; Asbury, J.; Brandon-Brown, F.; Derderian, H.; Mueller, R.; Swaroop, R.

1980-11-01

This three-volume manual presents technical guidelines for electric utility load research. Special attention is given to issues raised by the load data reporting requirements of the Public Utility Regulatory Policies Act of 1978 and to problems faced by smaller utilities that are initiating load research programs. In Volumes 1 and 2, procedures are suggested for determining data requirements for load research, establishing the size and customer composition of a load survey sample, selecting and using equipment to record customer electricity usage, processing data tapes from the recording equipment, and analyzing the data. Statistical techniques used in customer sampling are discussed in detail. The costs of load research also are estimated, and ongoing load research programs at three utilities are described. The manual includes guides to load research literature and glossaries of load research and statistical terms.

VOLTTRON-Based System for Providing Ancillary Services with Residential Building Loads

Energy Technology Data Exchange (ETDEWEB)

Jin, Xin

2016-07-01

Ancillary services entail controlled modulation of building equipment to maintain a stable balance of generation and load in the power system. Ancillary services include frequency regulation and contingency reserves, whose acting time ranges from several seconds to several minutes. Many pilot studies have been implemented to use industrial loads to provide ancillary services, and some have explored services from commercial building loads or electric vehicle charging loads. Residential loads, such as space conditioning and water heating, represent a largely untapped resource for providing ancillary services. The residential building sector accounts for a significant fraction of the total electricity use in the United States. Many loads in residential buildings are flexible and could potentially be curtailed or shifted at the request of the grid. However, there are many barriers that prevent residential loads being widely used for ancillary services. One of the major technical barriers is the lack of communication capabilities between end-use devices and the grid. End-use devices need to be able to receive the automatic generation control (AGC) signal from the grid operator and supply certain types of telemetry to verify response. With the advance of consumer electronics, communication-enabled, or 'connected,' residential equipment has emerged to overcome the communication barrier. However, these end-use devices have introduced a new interoperability challenge due to the existence of numerous standards and communication protocols among different end devices. In this paper, we present a VOLTTRON-based system that overcomes these technical challenges and provides ancillary services with residential loads. VOLTTRON is an open-source control and sensing platform for building energy management, facilitating interoperability solutions for end devices. We have developed drivers to communicate and control different types of end devices through standard-based

Three phase load flow; Fluxo de carga trifasico

Energy Technology Data Exchange (ETDEWEB)

Zago, Maria Goretti

1992-12-01

The phase model which is used in the analysis and planning of electric power system is based on the hypothesis that both the transmission system and load are equilibrated. Such a system, which presents the advantage of being simple,presents satisfactory results in several cases, however, for certain applications this system is inadequate. this work presents an alternative method based on three-phase load flow which an be applied to electric power distribution networks 19 refs., 25 figs., 24 tabs.

Non-intrusive appliance load monitoring system based on a modern kWh-meter

Energy Technology Data Exchange (ETDEWEB)

Pihala, H. [VTT Energy, Espoo (Finland). Energy Systems

1998-12-01

Non-intrusive appliance load monitoring (NIALM) is a fairly new method to estimate load profiles of individual electric appliances in a small building, like a household, by monitoring the whole load at a single point with one recording device without sub-meters. Appliances have special electrical characteristics, the positive and negative active and reactive power changes during the time they are switched on or off. These changes are called events and are detected with a monitoring device called an event recorder. Different NIALM-concepts developed in Europe and in the United States are generally discussed. The NIALM-concept developed in this study is based on a 3-phase, power quality monitoring kWh-meter and unique load identification algorithms. This modern kWh-meter with a serial data bus to a laptop personal computer is used as die event recorder. The NIALM-concept of this presentation shows for the first time how a kWh-meter can be used at the same time for billing, power quality and appliance end-use monitoring. An essential part of the developed NIALM-system prototype is the software of load identification algorithms which runs in an off-line personal computer. These algorithms are able to identify, with a certain accuracy, both two-state and multi-state appliances. This prototype requires manual-setup in which the naming of appliances is performed. The results of the prototype NIALMS were verified in a large, single family detached house and they were compared to the results of other prototypes in France and the United States, although this comparison is difficult because of different supply systems, appliance stock and number of tested sites. Different applications of NIALM are discussed. Gathering of load research data, verification of DSM-programs, home automation, failure analysis of appliances and security surveillance of buildings are interesting areas of NIALM. Both utilities and customers can benefit from these applications. It is possible to

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.

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...

Electrical properties of multiphase composites based on carbon nanotubes and an optimized clay content

Science.gov (United States)

Egiziano, Luigi; Lamberti, Patrizia; Spinelli, Giovanni; Tucci, Vincenzo; Guadagno, Liberata; Vertuccio, Luigi

2016-05-01

The experimental results concerning the characterization of a multiphase nanocomposite systems based on epoxy matrix, loaded with different amount of multi-walled carbon nanotubes (MWCNTs) and an optimized Hydrotalcite (HT) clay content (i.e. 0.6 wt%), duly identified by an our previous theoretical study based on Design of Experiment (DoE), are presented. Dynamic-mechanical analysis (DMA) reveal that even the introduction of higher HT loading (up to 1%wt) don't affect significantly the mechanical properties of the nanocomposites while morphological investigations show an effective synergy between clay and carbon nanotubes that leads to peculiar micro/nanostructures that favor the creation of the electrical conductive network inside the insulating resin. An electrical characterization is carried out in terms of DC electrical conductivity, percolation threshold (EPT) and frequency response in the range 10Hz-1MHz. In particular, the measurements of the DC conductivity allow to obtain the typical "percolation" curve also found for classical CNT-polymer mixtures and a value of about 2 S/m for the electrical conductivity is achieved at the highest considered CNTs concentration (i.e. 1 wt%). The results suggest that multiphase nanocomposites obtained incorporating dispersive nanofillers, in addition to the conductive one, may be a valid alternative to the polymer blends, to improve the properties of the polymeric materials thus able to meet high demands, particularly concerning their mechanical and thermal stability and electrical features required in the aircraft engineering.

Short-Term Fuzzy Load Forecasting Model Using Genetic–Fuzzy and Ant Colony–Fuzzy Knowledge Base Optimization

Directory of Open Access Journals (Sweden)

Murat Luy

2018-05-01

Full Text Available The estimation of hourly electricity load consumption is highly important for planning short-term supply–demand equilibrium in sources and facilities. Studies of short-term load forecasting in the literature are categorized into two groups: classical conventional and artificial intelligence-based methods. Artificial intelligence-based models, especially when using fuzzy logic techniques, have more accurate load estimations when datasets include high uncertainty. However, as the knowledge base—which is defined by expert insights and decisions—gets larger, the load forecasting performance decreases. This study handles the problem that is caused by the growing knowledge base, and improves the load forecasting performance of fuzzy models through nature-inspired methods. The proposed models have been optimized by using ant colony optimization and genetic algorithm (GA techniques. The training and testing processes of the proposed systems were performed on historical hourly load consumption and temperature data collected between 2011 and 2014. The results show that the proposed models can sufficiently improve the performance of hourly short-term load forecasting. The mean absolute percentage error (MAPE of the monthly minimum in the forecasting model, in terms of the forecasting accuracy, is 3.9% (February 2014. The results show that the proposed methods make it possible to work with large-scale rule bases in a more flexible estimation environment.

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.

Economics of coal-based electricity generation

Energy Technology Data Exchange (ETDEWEB)

Hemming, D F; Johnston, R; Teper, M

1979-01-01

The report deals with base-load electricity generation from coal and compares the economics of four alternative technologies: conventional pulverised-fuel (PF) boiler with steam cycle; atmospheric fluidised-bed (AFB) boiler with steam cycle; pressurised fluidised-bed (PFB) boiler with combined cycle; and integrated air-blown coal gasification with combined cycle systems are compared for both a high sulphur (3.5%) coal with environmental regulations requiring 85% sulphur removal, and for a low sulphur coal without sulphur removal. The results indicate that there is no single clear 'winner' among the advanced technologies. The optimum system depends on coal price, required rate-of-return, sulphur content of the coal, taxation regime etc. (34 refs.) (Available from IEA Coal Research, Economic Assessment Service)

Electricity Purchase Optimization Decision Based on Data Mining and Bayesian Game

Directory of Open Access Journals (Sweden)

Yajing Gao

2018-04-01

Full Text Available The openness of the electricity retail market results in the power retailers facing fierce competition in the market. This article aims to analyze the electricity purchase optimization decision-making of each power retailer with the background of the big data era. First, in order to guide the power retailer to make a purchase of electricity, this paper considers the users’ historical electricity consumption data and a comprehensive consideration of multiple factors, then uses the wavelet neural network (WNN model based on “meteorological similarity day (MSD” to forecast the user load demand. Second, in order to guide the quotation of the power retailer, this paper considers the multiple factors affecting the electricity price to cluster the sample set, and establishes a Genetic algorithm- back propagation (GA-BP neural network model based on fuzzy clustering (FC to predict the short-term market clearing price (MCP. Thirdly, based on Sealed-bid Auction (SA in game theory, a Bayesian Game Model (BGM of the power retailer’s bidding strategy is constructed, and the optimal bidding strategy is obtained by obtaining the Bayesian Nash Equilibrium (BNE under different probability distributions. Finally, a practical example is proposed to prove that the model and method can provide an effective reference for the decision-making optimization of the sales company.

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

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

International Nuclear Information System (INIS)

Wang, Yong; Li, Lin

2013-01-01

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

We Need to Talk... Developing Communicating Power Supplies to Monitor & Control Miscellaneous Electric Loads

Energy Technology Data Exchange (ETDEWEB)

Weber, Andrew; Lanzisera, Steven; Liao, Anna; Meier, Alan

2014-08-11

Plug loads represent 30percent of total electricity use in residential buildings. Significant energy savings would result from an accurate understanding of which miscellaneous electric devices are using energy, at what time, and in what quantity. Commercially available plug load monitoring and control solutions replace or limit the attached device's native controls - forcing the user to adapt to a separate set of controls associated with the monitoring and control hardware. A better solution is integration of these capabilities at the power supply level. In this paper, we demonstrate a method achieving this integration. Our solution allows unobtrusive power monitoring and control while retaining native device control features. Further, our prototype enables intelligent behaviors by allowing devices to respond to the state of one another automatically. The CPS enables energy savings while demonstrating an added level of functionality to the user. If CPS technology became widespread in devices, a combination of automated and human interactive solutions would enable high levels of energy savings in buildings.

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)

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

Science.gov (United States)

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

2016-04-01

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

Morphological and electrical properties of epoxy-based composites reinforced with exfoliated graphite

Energy Technology Data Exchange (ETDEWEB)

Lamberti, Patrizia; Spinelli, Giovanni, E-mail: gspinelli@unisa.it; Tucci, Vincenzo [Department of Information and Electrical Engineering and Applied Mathematics University of Salerno, Via Giovanni Paolo II, Fisciano (Italy); Guadagno, Liberata; Raimondo, Marialuigia; Vertuccio, Luigi [Department of Industrial Engineering University of Salerno, Via Giovanni Paolo II, Fisciano (Italy)

2016-05-18

An experimental study has been carried out to prepare and characterize epoxy/amine-based composites filled with different percentages of partially exfoliated graphite (i.e. pEG) particles having an exfoliation degree of 56% in order to analyze the effect of the filler amounts on the electrical properties of the resulting nanocomposites. Moreover, in order to fully investigate the direct relationship between the physical properties of the employed filler and the results of the electrical characterization, a structural and morphological characterization of the pEG samples is carried out by means of various type of analysis such as X-ray diffraction patterns, micro-Raman and Scanning Electron Microscopy (SEM) images. The DC electrical characterization reveals a percolation thresholds (EPT) that falls in the range [2–3] wt% and an electrical conductivity of about 0.66 S/m at the highest filler loading (6.5 wt%). From the analysis of the percolative curve it is possible to derive the percolation law parameters and in particular the critical exponent t, whose value (i.e. 1.2) reflects an effective 2D organization of the percolating structure consistent with the type of filler used (2-dimensional). Finally, an extensive analysis concerning the electrical properties in the frequency domain has been carried out in order to evaluate the effectiveness of pEG-loaded composites in terms of electromagnetic interference compatibility (EMC) and their applicability as radar absorbers materials (RAMs).

Security attack detection algorithm for electric power gis system based on mobile application

Science.gov (United States)

Zhou, Chao; Feng, Renjun; Wang, Liming; Huang, Wei; Guo, Yajuan

2017-05-01

Electric power GIS is one of the key information technologies to satisfy the power grid construction in China, and widely used in power grid construction planning, weather, and power distribution management. The introduction of electric power GIS based on mobile applications is an effective extension of the geographic information system that has been widely used in the electric power industry. It provides reliable, cheap and sustainable power service for the country. The accurate state estimation is the important conditions to maintain the normal operation of the electric power GIS. Recent research has shown that attackers can inject the complex false data into the power system. The injection attack of this new type of false data (load integrity attack LIA) can successfully bypass the routine detection to achieve the purpose of attack, so that the control center will make a series of wrong decision. Eventually, leading to uneven distribution of power in the grid. In order to ensure the safety of the electric power GIS system based on mobile application, it is very important to analyze the attack mechanism and propose a new type of attack, and to study the corresponding detection method and prevention strategy in the environment of electric power GIS system based on mobile application.

Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

Directory of Open Access Journals (Sweden)

Wang Chao

2016-03-01

Full Text Available Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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.

A Permutation Importance-Based Feature Selection Method for Short-Term Electricity Load Forecasting Using Random Forest

Directory of Open Access Journals (Sweden)

Nantian Huang

2016-09-01

Full Text Available The prediction accuracy of short-term load forecast (STLF depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF-based feature selection method for STLF is proposed. First, 243 related features were extracted from historical load data and the time information of prediction points to form the original feature set. Subsequently, the original feature set was used to train an RF as the original model. After the training process, the prediction error of the original model on the test set was recorded and the permutation importance (PI value of each feature was obtained. Then, an improved sequential backward search method was used to select the optimal forecasting feature subset based on the PI value of each feature. Finally, the optimal forecasting feature subset was used to train a new RF model as the final prediction model. Experiments showed that the prediction accuracy of RF trained by the optimal forecasting feature subset was higher than that of the original model and comparative models based on support vector regression and artificial neural network.

A Mobile-based Platform for Big Load Profiles Data Analytics in Non-Advanced Metering Infrastructures

Directory of Open Access Journals (Sweden)

Moussa Sherin

2016-01-01

Full Text Available With the rapidly increase of electricity demand around the world due to industrialization and urbanization, this turns the availability of precise knowledge about the consumption patterns of consumers to a valuable asset for electricity providers, given the current competitive electricity market. This would allow them to provide satisfactory services in time of load peaks and to control fraud and abuse cases. Despite of this crucial necessity, this is currently very hard to achieve in many developing countries since smart meters or advanced metering infrastructures (AMIs are not yet settled there to monitor and report energy usages. Whereas the communication and information technologies have widely emerged in such nations, allowing the enormous spread of smart devices among population. In this paper, we present mobile-based BLPDA, a novel platform for big data analytics of consumerss’ load profiles (LPs in the absence of AMIs’ establishment. The proposed platform utilizes mobile computing in order to collect the consumptions of consumers, build their LPs, and analyze the aggregated usages data. Thus, allowing electricity providers to have better vision for an enhanced decision making process. The experimental results emphasize the effectiveness of our platform as an adequate alternative for AMIs in developing countries with minimal cost.

An annual framework for clustering-based pricing for an electricity retailer

International Nuclear Information System (INIS)

Mahmoudi-Kohan, N.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.

2010-01-01

In the competitive environment, it is necessary for a retailer to increase his/her profit as much as possible. There are few researches focused on the subjects related to the retailer and the retail market. In addition, those researches have mostly focused on the participation of the retailer in the wholesale market. In order to determine the optimal selling price, the knowledge of how and when consumers use electricity is essential to the retailer. This type of information can be found in load profiles of customers. In this paper, an annual framework for optimal price offering by a retailer is proposed which is based on clustering technique. For this purpose, load profiles of customers are used as their consumption patterns. Also, a profit function is defined as the objective of optimization problem based on the load profile considering conditional value at risk (CVaR) for risk modeling. Also, a new acceptance function is proposed to overcome drawbacks of the traditional ones. The objective function is a mixed-integer nonlinear problem which is solved by GAMS software. (author)

An assessment of household electricity load curves and corresponding CO2 marginal abatement cost curves for Gujarat state, India

International Nuclear Information System (INIS)

Garg, Amit; Shukla, P.R.; Maheshwari, Jyoti; Upadhyay, Jigeesha

2014-01-01

Gujarat, a large industrialized state in India, consumed 67 TWh of electricity in 2009–10, besides experiencing a 4.5% demand–supply short-fall. Residential sector accounted for 15% of the total electricity consumption. We conducted load research survey across 21 cities and towns of the state to estimate residential electricity load curves, share of appliances by type and usage patterns for all types of household appliances at utility, geographic, appliance, income and end-use levels. The results indicate that a large scope exists for penetration of energy efficient devices in residential sector. Marginal Abatement Cost (MAC) curves for electricity and CO 2 were generated to analyze relative attractiveness of energy efficient appliance options. Results indicate that up to 7.9 TWh of electricity can be saved per year with 6.7 Mt-CO 2 emissions mitigation at negative or very low CO 2 prices of US$ 10/t-CO 2 . Despite such options existing, their penetration is not realized due to myriad barriers such as financial, institutional or awareness and therefore cannot be taken as baseline options for CO 2 emission mitigation regimes. - Highlights: • Residential sector provides focused mitigation opportunities. • Energy efficient space cooling is the main technology transition required. • Almost 26% residential load could be reduced by DSM measures. • Myriad barriers limit penetration of negative marginal cost efficient options

ANALYSIS OF ENERGY EFFICIENCY OF OPERATING MODES OF ELECTRICAL SYSTEMS WITH THE TRACTION LOADS

Directory of Open Access Journals (Sweden)

V. E. Bondarenko

2017-03-01

Full Text Available Innovative scenarios of reliable energy supply of transportation process aimed at reducing the specific energy consumption and increase energy efficiency of the systems of electric traction. The paper suggests innovative energy saving directions in traction networks of railways and new circuit solutions accessing traction substations in energy systems networks, ensure energy security of the transportation process. To ensure the energy security of rail transport special schemes were developed to propose the concept of external power traction substations, which would increase the number of connections to the networks of 220 – 330 kV, as well as the creation of transport and energy corridors, development of its own supply of electric networks of 110 kV substations and mobile RP-110 kV of next generation. Therefore, the investment program of the structures owned by the Ukrainian Railways (Ukrzaliznytsia need to be synchronized in their technological characteristics, as well as the criteria of reliability and quality of power supply with the same external energy investment programs. It is found that without any load on left or right supplying arm one of two less loaded phases of traction transformer begins generating specific modes in the supplying three-phase line. Thus, modes of mobile substation cause leakage in one of the phases of the supply line of traction transformers of active-capacitive current, and as a result generating energy in the main power line of 154 kV, which is fixed and calculated by electricity meters. For these three phase mode supply network is necessary to use 1st algorithm, i.e. taking into account the amount of electricity as the energy in all phases. For effective application of reactive power compensation devices in the AC traction power supply systems it is proposed to develop regulatory documentation on necessity of application and the order of choice of parameters and placement of compensation systems taking into

Electronic load as part of the test complex of the power processing unit of electric and plasma propulsion

OpenAIRE

Chubov, S. V.; Soldatov, Aleksey Ivanovich

2017-01-01

This article provides the advantages and technical solutions for the use of electronic loads as part of a testing complex of power and management systems of electric and plasma propulsion of three types. The paper shows the parameters that were applied to select the electronic loads and describes their functionality.

A case study review of technical and technology issues for transition of a utility load management program to provide system reliability resources in restructured electricity markets

Energy Technology Data Exchange (ETDEWEB)

Weller, G.H.

2001-07-15

Utility load management programs--including direct load control and interruptible load programs--were employed by utilities in the past as system reliability resources. With electricity industry restructuring, the context for these programs has changed; the market that was once controlled by vertically integrated utilities has become competitive, raising the question: can existing load management programs be modified so that they can effectively participate in competitive energy markets? In the short run, modified and/or improved operation of load management programs may be the most effective form of demand-side response available to the electricity system today. However, in light of recent technological advances in metering, communication, and load control, utility load management programs must be carefully reviewed in order to determine appropriate investments to support this transition. This report investigates the feasibility of and options for modifying an existing utility load management system so that it might provide reliability services (i.e. ancillary services) in the competitive markets that have resulted from electricity industry restructuring. The report is a case study of Southern California Edison's (SCE) load management programs. SCE was chosen because it operates one of the largest load management programs in the country and it operates them within a competitive wholesale electricity market. The report describes a wide range of existing and soon-to-be-available communication, control, and metering technologies that could be used to facilitate the evolution of SCE's load management programs and systems to provision of reliability services. The fundamental finding of this report is that, with modifications, SCE's load management infrastructure could be transitioned to provide critical ancillary services in competitive electricity markets, employing currently or soon-to-be available load control technologies.

Load levelling measures being tackled by shikoku Electric Power Co. Inc.; Shikoku Denryoku Kabushi Kaisha no fuka heijunka eno torikumi

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-11-01

For the electric power companies, the activity of pushing forward the load levelling contributes greatly to the curtailment of cost by means of effective formation and utilization of facilities. It is planned to take up more positive activities with a target of 3% improvement in the load factor in ten years. Concrete measures for further promotion of load levelling are the diversity of the rate menu of appraising the load levelling effort of the customers and the promotion of the spread of equipment and systems relating to load levelling such as electric water heating apparatuses and thermal energy storage air conditioning systems. The rate system has been reviewed taking the opportunity of rate revision made in January, 1996. Particularly, further load shift to midnight time zone is expected as a result of better rate incentive for customers which is brought about by large reduction of the rate level due to the cost reduction effect accompanying the improvement in atomic power generation ratio. Outlines are given on the fields relating to general households, business, dwellings, buildings, and industry. 3 figs., 1 tab.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

OpenAIRE

Duarte, Jorge; Fred, Ana; Rodrigues, Fátima; Duarte, João; Ramos, Sérgio; Vale, Zita

2007-01-01

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity ...

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.

The effect of load and thickness variation on stress analysis of monocoque frame of electric city car using FEM

Science.gov (United States)

Makhrojan, Agus; Suprihadi, Agus; Budi, Sigit Setijo; Jamari, J.; Ismail, Rifky

2017-01-01

The electric car is transportation which growing and constantly put through improvisation vehicle design. One of the structural components of the electric car which holds a major role is a frame. The purpose of this study is to get monocoque frame design which lightweight and powerful for a city car with two passengers that was able to improve the efficiency of the battery voltage source. Monocoque frame should be able to accept the normal loads such as the weight of batteries, passenger, and body. The most important thing, monocoque frame should also be able to protect the driver and passengers in the event of a collision. Mild steel was chosen for the design because it is easy to obtain and reasonable price as well as easy to shaped for two-seater electric car. FEM (finite element method) was used to determine stress determination and rigidity of the monocoque frame when receiving a static load. The results show that the monocoque frame was still able to withstand the required loads with minimal deflection.

Assessment of high temperature nuclear energy storage systems for the production of intermediate and peak-load electric power

International Nuclear Information System (INIS)

Fox, E.C.; Fuller, L.C.; Silverman, M.D.

1977-01-01

Increased cost of energy, depletion of domestic supplies of oil and natural gas, and dependence on foreign suppliers, have led to an investigation of energy storage as a means to displace the use of oil and gas presently being used to generate intermediate and peak-load electricity. Dedicated nuclear thermal energy storage is investigated as a possible alternative. An evaluation of thermal storage systems is made for several reactor concepts and economic comparisons are presented with conventional storage and peak power producing systems. It is concluded that dedicated nuclear storage has a small but possible useful role in providing intermediate and peak-load electric power

Nanopowder synthesis based on electric explosion technology

Science.gov (United States)

Kryzhevich, D. S.; Zolnikov, K. P.; Korchuganov, A. V.; Psakhie, S. G.

2017-10-01

A computer simulation of the bicomponent nanoparticle formation during the electric explosion of copper and nickel wires was carried out. The calculations were performed in the framework of the molecular dynamics method using many-body potentials of interatomic interaction. As a result of an electric explosion of dissimilar metal wires, bicomponent nanoparticles having different stoichiometry and a block structure can be formed. It is possible to control the process of destruction and the structure of the formed bicomponent nanoparticles by varying the distance between the wires and the loading parameters.

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.

An energy estimation framework for event-based methods in Non-Intrusive Load Monitoring

International Nuclear Information System (INIS)

Giri, Suman; Bergés, Mario

2015-01-01

Highlights: • Energy estimation is NILM has not yet accounted for complexity of appliance models. • We present a data-driven framework for appliance modeling in supervised NILM. • We test the framework on 3 houses and report average accuracies of 5.9–22.4%. • Appliance models facilitate the estimation of energy consumed by the appliance. - Abstract: Non-Intrusive Load Monitoring (NILM) is a set of techniques used to estimate the electricity consumed by individual appliances in a building from measurements of the total electrical consumption. Most commonly, NILM works by first attributing any significant change in the total power consumption (also known as an event) to a specific load and subsequently using these attributions (i.e. the labels for the events) to estimate energy for each load. For this last step, most published work in the field makes simplifying assumptions to make the problem more tractable. In this paper, we present a framework for creating appliance models based on classification labels and aggregate power measurements that can help to relax many of these assumptions. Our framework automatically builds models for appliances to perform energy estimation. The model relies on feature extraction, clustering via affinity propagation, perturbation of extracted states to ensure that they mimic appliance behavior, creation of finite state models, correction of any errors in classification that might violate the model, and estimation of energy based on corrected labels. We evaluate our framework on 3 houses from standard datasets in the field and show that the framework can learn data-driven models based on event labels and use that to estimate energy with lower error margins (e.g., 1.1–42.3%) than when using the heuristic models used by others

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.

Effective use of electric power facilities and promotion of energy conservation

International Nuclear Information System (INIS)

Tokumitsu, Iwao

1999-01-01

The capacity of Japan's commercial electric power facilities has been increased to more than 200 million kw. In order to provide a stable supply of electric power to meet constantly fluctuaring electric power demands, Japan's power plants generate electricity using an optimal combination of facilities, with nuclear power and coal-fired thermoelectric power providing the base load supply. In the use of electric power, moreover, measures are being implemented to reduce generation costs, conserve energy, and cut carbon dioxide emissions by reducing maximum output and equalizing the load. This report presents information concerning measures for improving the efficiency of electric power facilities operation, equalizing the load and promoting energy conservation. (author)

Direct participation of electrical loads in the California independent system operator markets during the Summer of 2000

International Nuclear Information System (INIS)

Marnay, Chris; Hamachi, Kristina S.; Khavkin, Mark; Siddiqui, Afzal S.

2001-01-01

California's restructured electricity markets opened on 1 April 1998. The former investor-owned utilities were functionally divided into generation, transmission, and distribution activities, all of their gas-fired generating capacity was divested, and the retail market was opened to competition. To ensure that small customers shared in the expected benefit of lower prices, the enabling legislation mandated a 10% rate cut for all customers, which was implemented in a simplistic way that fossilized 1996 tariff structures. Rising fuel and environmental compliance costs, together with a reduced ability to import electricity, numerous plant outages, and exercise of market power by generators drove up wholesale electricity prices steeply in 2000, while retail tariffs remained unchanged. One of the distribution/supply companies entered bankruptcy in April 2001, and another was insolvent. During this period, two sets of interruptible load programs were in place, longstanding ones organized as special tariffs by the distribution/supply companies and hastily established ones run directly by the California Independent System Operator (CAISO). The distribution/supply company programs were effective at reducing load during the summer of 2000, but because of the high frequency of outages required by a system on the brink of failure, customer response declined and many left the tariff. The CAISO programs failed to attract enough participation to make a significant difference to the California supply demand imbalance. The poor performance of direct load participation in California's markets reinforces the argument for accurate pricing of electricity as a stimulus to energy efficiency investment and as a constraint on market volatility

Finite element-based limit load of piping branch junctions under combined loadings

International Nuclear Information System (INIS)

Xuan Fuzhen; Li Peining

2004-01-01

The limit load is an important input parameter in engineering defect-assessment procedures and strength design. In the present work, a total of 100 different piping branch junction models for the limit load calculation were performed under combined internal pressure and moments in use of non-linear finite element (FE) method. Three different existing accumulation rules for limit load, i.e., linear equation, parabolic equation and quadratic equation were discussed on the basis of FE results. A novel limit load solution was developed based on detailed three-dimensional FE limit analyses which accommodated the geometrical parameter influence, together with analytical solutions based on equilibrium stress fields. Finally, six experimental results were provided to justify the presented equation. According to the FE limit analysis, limit load interaction of the piping tees under combined pressure and moments has a relationship with the geometrical parameters, especially with the diameter ratio d/D. The predicted limit loads from the presented formula are very close to the experimental data. The resulting limit load solution is given in a closed form, and thus can be easily used in practice

Electric terminal performance and characterization of solid oxide fuel cells and systems

Science.gov (United States)

Lindahl, Peter Allan

Solid Oxide Fuel Cells (SOFCs) are electrochemical devices which can effect efficient, clean, and quiet conversion of chemical to electrical energy. In contrast to conventional electricity generation systems which feature multiple discrete energy conversion processes, SOFCs are direct energy conversion devices. That is, they feature a fully integrated chemical to electrical energy conversion process where the electric load demanded of the cell intrinsically drives the electrochemical reactions and associated processes internal to the cell. As a result, the cell's electric terminals provide a path for interaction between load side electric demand and the conversion side processes. The implication of this is twofold. First, the magnitude and dynamic characteristics of the electric load demanded of the cell can directly impact the long-term efficacy of the cell's chemical to electrical energy conversion. Second, the electric terminal response to dynamic loads can be exploited for monitoring the cell's conversion side processes and used in diagnostic analysis and degradation-mitigating control schemes. This dissertation presents a multi-tier investigation into this electric terminal based performance characterization of SOFCs through the development of novel test systems, analysis techniques and control schemes. First, a reference-based simulation system is introduced. This system scales up the electric terminal performance of a prototype SOFC system, e.g. a single fuel cell, to that of a full power-level stack. This allows realistic stack/load interaction studies while maintaining explicit ability for post-test analysis of the prototype system. Next, a time-domain least squares fitting method for electrochemical impedance spectroscopy (EIS) is developed for reduced-time monitoring of the electrochemical and physicochemical mechanics of the fuel cell through its electric terminals. The utility of the reference-based simulator and the EIS technique are demonstrated

Radio-frequency electrical design of the WEST long pulse and load-resilient ICRH launchers

Energy Technology Data Exchange (ETDEWEB)

Helou, Walid, E-mail: walid.helou@cea.fr [CEA, IRFM, F-13108 St-Paul-Lez-Durance (France); Colas, Laurent; Hillairet, Julien [CEA, IRFM, F-13108 St-Paul-Lez-Durance (France); Milanesio, Daniele [Department of Electronics, Politecnico di Torino, Torino (Italy); Mollard, Patrick [CEA, IRFM, F-13108 St-Paul-Lez-Durance (France); Argouarch, Arnaud [CEA DAM/DIF/DP2I, Bruyère le Chatel (France); Berger-By, Gilles; Bernard, Jean-Michel [CEA, IRFM, F-13108 St-Paul-Lez-Durance (France); Chen, Zhaoxi [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Delaplanche, Jean-Marc [CEA, IRFM, F-13108 St-Paul-Lez-Durance (France); Dumortier, Pierre; Durodié, Frédéric [Laboratoire de physique des plasmas de l’ERM, Laboratorium voor plasmafysica van de KMS – (LPP-ERM/KMS), Ecole royale militaire–Koninklijke militaire school, BE-1000 Brussels (Belgium); Ekedahl, Annika; Fedorczak, Nicolas; Ferlay, Fabien; Goniche, Marc [CEA, IRFM, F-13108 St-Paul-Lez-Durance (France); Jacquot, Jonathan [Max-Planck Institut für Plasmaphysik, Boltzmannstraße 2, 85748 Garching (Germany); Joffrin, Emmanuel; Litaudon, Xavier; Lombard, Gilles [CEA, IRFM, F-13108 St-Paul-Lez-Durance (France); and others

2015-10-15

Highlights: • Three new ion cyclotron resonance heating launchers designed for WEST. • Operation at 3 MW/launcher for 30 s and 1 MW/launcher for 1000 s on H-mode plasmas. • Unique combination of continuous-wave operation at high power and load tolerance. • International team led by the CEA/IRFM. • RF design performed using electromagnetic solvers and electric circuit calculations. - Abstract: Three new ion cyclotron resonance heating (ICRH) launchers have been designed for the WEST project (W-Tungsten Environment in Steady-state Tokamak) in order to operate at 3 MW/launcher for 30 s and 1 MW/launcher for 1000 s on H-mode plasmas. These new launchers will be to date the first ICRH launchers to offer the unique combination of continuous-wave (CW) operation at high power and load tolerance capabilities for coupling on H-mode edge. The radio-frequency (RF) design optimization process has been carried out using full-wave electromagnetic solvers combined with electric circuit calculations. Cavity modes occurring between the launchers structures and the vacuum vessel ports have been evaluated and cleared out.

A 100% renewable electricity mix? Analyses and optimisations. Testing the boundaries of renewable energy-based electricity development in metropolitan France by 2050

International Nuclear Information System (INIS)

Dubilly, Anne-Laure; Fournie, Laurent; Chiche, Alice; Faure, Nathalie; Bardet, Regis; Alais, Jean-Christophe; Girard, Robin; Bossavy, Arthur; Le Gars, Loic; Biau, Jean-Baptiste; Piqueras, Ugo; Peyrusse, Colombe

2015-10-01

In 2013, ADEME published its energy and climate scenarios for the period 2030 to 2050, suggesting possible avenues to achieve a four-fold reduction in greenhouse-gas emissions by 2050 by cutting energy consumption by half and deploying renewable energy sources for electricity generation on a substantial scale. Both of these objectives were the basis for targets set by the President of France and subsequently adopted by Parliament in the Energy Transition Law to promote green growth. With this new study, ADEME submits an exploratory scientific prospective study. Questions of balance between production and demand and cost efficiency of renewable-based electricity mixes are investigated through an advanced optimisation. The electricity mixes are theoretical: they are created from scratch and do not take into account the current situation or the path needed to achieve a 100% renewable-based electricity system. It aims at highlighting the technical measures to be implemented (strengthening grids, load shedding and storage) to support a policy of growth in renewable electricity technologies. It is also be used to identify the key factors for developing renewable technologies at lower cost such as lower costs of technologies, demand-side management, development of flexibility, support of R and D of least-mature technologies and the social acceptance of renewable electricity installations. (authors)

Real-time electricity pricing mechanism in China based on system dynamics

International Nuclear Information System (INIS)

He, Yongxiu; Zhang, Jixiang

2015-01-01

Highlights: • The system dynamics is used to research the real-time electricity pricing mechanism. • Four kinds of the real-time electricity pricing models are carried out and simulated. • It analysed the electricity price, the user satisfaction and the social benefits under the different models. • Market pricing is the trend of the real-time electricity pricing mechanism. • Initial development path of the real-time price mechanism for China is designed between 2015 and 2030. - Abstract: As an important means of demand-side response, the reasonable formulation of the electricity price mechanism will have an important impact on the balance between the supply and demand of electric power. With the introduction of Chinese intelligence apparatus and the rapid development of smart grids, real-time electricity pricing, as the frontier electricity pricing mechanism in the smart grid, will have great significance on the promotion of energy conservation and the improvement of the total social surplus. From the perspective of system dynamics, this paper studies different real-time electricity pricing mechanisms based on load structure, cost structure and bidding and analyses the situation of user satisfaction and the total social surplus under different pricing mechanisms. Finally, through the comparative analysis of examples under different real-time pricing scenarios, this paper aims to explore and design the future dynamic real-time electricity pricing mechanism in China, predicts the dynamic real-time pricing level and provides a reference for real-time electricity price promotion in the future

Observer-Based Load Frequency Control for Island Microgrid with Photovoltaic Power

Directory of Open Access Journals (Sweden)

Chaoxu Mu

2017-01-01

Full Text Available As renewable energy is widely integrated into the power system, the stochastic and intermittent power generation from renewable energy may cause system frequency deviating from the prescribed level, especially for a microgrid. In this paper, the load frequency control (LFC of an island microgrid with photovoltaic (PV power and electric vehicles (EVs is investigated, where the EVs can be treated as distributed energy storages. Considering the disturbances from load change and PV power, an observer-based integral sliding mode (OISM controller is designed to regulate the frequency back to the prescribed value, where the neural network observer is used to online estimate the PV power. Simulation studies on a benchmark microgrid system are presented to illustrate the effectiveness of OISM controller, and comparative results also demonstrate that the proposed method has a superior performance for stabilizing the frequency over the PID control.

Active load current sharing in fuel cell and battery fed DC motor drive for electric vehicle application

International Nuclear Information System (INIS)

Pany, Premananda; Singh, R.K.; Tripathi, R.K.

2016-01-01

Highlights: • Load current sharing in FC and battery fed dc drive. • Active current sharing control using LabVIEW. • Detail hardware implementation. • Controller performance is verified through MATLAB simulation and experimental results. - Abstract: In order to reduce the stress on fuel cell based hybrid source fed electric drive system the controller design is made through active current sharing (ACS) technique. The effectiveness of the proposed ACS technique is tested on a dc drive system fed from fuel cell and battery energy sources which enables both load current sharing and source power management. High efficiency and reliability of the hybrid system can be achieved by proper energy conversion and management of power to meet the load demand in terms of required voltage and current. To overcome the slow dynamics feature of FC, a battery bank of adequate power capacity has to be incorporated as FC voltage drops heavily during fast load demand. The controller allows fuel cell to operate in normal load region and draw the excess power from battery. In order to demonstrate the performance of the drive using ACS control strategy different modes of operation of the hybrid source with the static and dynamic behavior of the control system is verified through simulation and experimental results. This control scheme is implemented digitally in LabVIEW with PCI 6251 DAQ I/O interface card. The efficacy of the controller performance is demonstrated in system changing condition supplemented by experimental validation.

Load research manual. Volume 2. Fundamentals of implementing load research procedures

Energy Technology Data Exchange (ETDEWEB)

Brandenburg, L.; Clarkson, G.; Grund, Jr., C.; Leo, J.; Asbury, J.; Brandon-Brown, F.; Derderian, H.; Mueller, R.; Swaroop, R.

1980-11-01

This three-volume manual presents technical guidelines for electric utility load research. Special attention is given to issues raised by the load data reporting requirements of the Public Utility Regulatory Policies Act of 1978 and to problems faced by smaller utilities that are initiating load research programs. In Volumes 1 and 2, procedures are suggested for determining data requirements for load research, establishing the size and customer composition of a load survey sample, selecting and using equipment to record customer electricity usage, processing data tapes from the recording equipment, and analyzing the data. Statistical techniques used in customer sampling are discussed in detail. The costs of load research also are estimated, and ongoing load research programs at three utilities are described. The manual includes guides to load research literature and glossaries of load research and statistical terms.

A New Strategy for Short-Term Load Forecasting

Directory of Open Access Journals (Sweden)

Yi Yang

2013-01-01

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

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

Field data collection of miscellaneous electrical loads in Northern California: Initial results

Energy Technology Data Exchange (ETDEWEB)

Greenblatt, Jeffery B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.; Pratt, Stacy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.; Willem, Henry [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.; Claybaugh, Erin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.; Desroches, Louis-Benoit [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.; Beraki, Bereket [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.; Nagaraju, Mythri [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.; Price, Sarah K. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.; Young, Scott J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Energy Analysis and Environmental Impacts Dept.

2013-02-25

This report describes efforts to measure energy use of miscellaneous electrical loads (MELs) in 880 San Francisco Bay Area homes during the summer of 2012. Ten regions were selected for metering: Antioch, Berkeley, Fremont, Livermore, Marin County (San Rafael, Novato, Fairfax, and Mill Valley), Oakland/Emeryville, Pleasanton, Richmond, San Leandro, and Union City. The project focused on three major categories of devices: entertainment (game consoles, set-top boxes, televisions and video players), home office (computers, monitors and network equipment), and kitchen plug-loads (coffee/espresso makers, microwave ovens/toaster ovens/toasters, rice/slow cookers and wine chillers). These categories were important to meter because they either dominated the estimated overall energy use of MELs, are rapidly changing, or there are very little energy consumption data published. A total of 1,176 energy meters and 143 other sensors were deployed, and 90% of these meters and sensors were retrieved. After data cleaning, we obtained 711 valid device energy use measurements, which were used to estimate, for a number of device subcategories, the average time spent in high power, low power and “off” modes, the average energy use in each mode, and the average overall energy use. Consistent with observations made in previous studies, we find on average that information technology (IT) devices (home entertainment and home office equipment) consume more energy (15.0 and 13.0 W, respectively) than non-IT devices (kitchen plug-loads; 4.9 W). Opportunities for energy savings were identified in almost every device category, based on the time spent in various modes and/or the power levels consumed in those modes. Future reports will analyze the collected data in detail by device category and compare results to those obtained from prior studies.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Electrical energy consumption control apparatuses and electrical energy consumption control methods

Science.gov (United States)

Hammerstrom, Donald J.

2012-09-04

Electrical energy consumption control apparatuses and electrical energy consumption control methods are described. According to one aspect, an electrical energy consumption control apparatus includes processing circuitry configured to receive a signal which is indicative of current of electrical energy which is consumed by a plurality of loads at a site, to compare the signal which is indicative of current of electrical energy which is consumed by the plurality of loads at the site with a desired substantially sinusoidal waveform of current of electrical energy which is received at the site from an electrical power system, and to use the comparison to control an amount of the electrical energy which is consumed by at least one of the loads of the site.

Analysis of electrical circuits with variable load regime parameters projective geometry method

CERN Document Server

Penin, A

2015-01-01

This book introduces electric circuits with variable loads and voltage regulators. It allows to define invariant relationships for various parameters of regime and circuit sections and to prove the concepts characterizing these circuits. Generalized equivalent circuits are introduced. Projective geometry is used for the interpretation of changes of operating regime parameters. Expressions of normalized regime parameters and their changes are presented. Convenient formulas for the calculation of currents are given. Parallel voltage sources and the cascade connection of multi-port networks are d

Development of methods for evaluation of electricity saving and load levelling measures. Part 2: The planning and implementation of a power conservation campaign

Energy Technology Data Exchange (ETDEWEB)

Storm Soerensen, M.; Madsen, P.K. [NESA A/S, Research and Development Dept. (Denmark)

1997-12-01

In recent years many campaigns and projects have been carried out with the purpose of reducing the energy consumption. Simultaneously a lot of economic and structural changes are taking place in society in general; changes which also affect the size of the electricity consumption. Furthermore, there is a trend towards increased use of wind mills and decentral combined heating and power plants, which affects the electricity load of the local area. It is difficult to identify and separate the effect of each of these attitude-adjusting activities. The project `Development of methods for evaluation of the effect of electricity saving and load levelling measures` focuses on two different methods which, on different levels, can be used to determine the impact of different different activities on the electricity consumption. Both methods are based on mathematical statistics, and they consist of an analysis of historical data and a test campaign which will make it possible to test specific activities in a comparatively small scale. The historical part covers the years 1974 to 1994 and include such variables as: demography, economic factors, climatic conditions, periods of electricity saving campaigns, the start of billing according to time of day tariff etc. The wish to be able to measure the extent of these energy saving and load reducing initiatives resulted in a test campaign which was carried out under very restricted conditions starting in the fall of 1996. If the effect of the test campaign can be measured and as a consequence of this a method can be estimated, it will be possible to place models which can measure the effect of future campaigns. The primary object of the campaign is not the size of the electricity savings of the individual customer, but rather to obtain total savings for the entire group of customers. The test has been structured in a way which makes it possible to perform an analysis of the effect of the campaign by use of analysis of intervention

Power Load Prediction Based on Fractal Theory

OpenAIRE

Jian-Kai, Liang; Cattani, Carlo; Wan-Qing, Song

2015-01-01

The basic theories of load forecasting on the power system are summarized. Fractal theory, which is a new algorithm applied to load forecasting, is introduced. Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting. According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and...

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.

Electric drives

CERN Document Server

Boldea, Ion

2005-01-01

ENERGY CONVERSION IN ELECTRIC DRIVESElectric Drives: A DefinitionApplication Range of Electric DrivesEnergy Savings Pay Off RapidlyGlobal Energy Savings Through PEC DrivesMotor/Mechanical Load MatchMotion/Time Profile MatchLoad Dynamics and StabilityMultiquadrant OperationPerformance IndexesProblemsELECTRIC MOTORS FOR DRIVESElectric Drives: A Typical ConfigurationElectric Motors for DrivesDC Brush MotorsConventional AC MotorsPower Electronic Converter Dependent MotorsEnergy Conversion in Electric Motors/GeneratorsPOWER ELECTRONIC CONVERTERS (PECs) FOR DRIVESPower Electronic Switches (PESs)The

Anisotropy of domain switching in prepoled lead titanate zirconate ceramics under multiaxial electrical loading

Science.gov (United States)

Liu, Yuan-Ming; Li, Fa-Xin; Fang, Dai-Ning

2007-01-01

The authors report an observation of anisotropic domain switching process in prepoled lead titanate zirconate (PZT) ceramics under multiaxial electrical loading. Prepoled PZT blocks were obliquely cut to apply an electric field at discrete angles θ (0°-180°) to the initial poling direction. Both the coercive field and switchable polarization are found to decrease significantly when sinθ increases from zero to unity. The measured strain curves show that most domains that accomplished 180° domain switching actually experienced two successive 90° switching. The oriented domain texture after poling plus the induced nonuniform stress are used to explain the observed domain switching anisotropy.

On load flow control in electric power systems

Energy Technology Data Exchange (ETDEWEB)

Herbig, Arnim

2000-01-01

This dissertation deals with the control of active power flow, or load flow in electric power systems. During the last few years, interest in the possibilities to control the active power flows in transmission systems has increased significantly. There is a number of reasons for this, coming both from the application side - that is, from power system operations - and from the technological side. where advances in power electronics and related technologies have made new system components available. Load flow control is by nature a multi-input multi-output problem, since any change of load flow in one line will be complemented by changes in other lines. Strong cross-coupling between controllable components is to be expected, and the possibility of adverse interactions between these components cannot be rejected straightaway. Interactions with dynamic phenomena in the power system are also a source of concern. Three controllable components are investigated in this thesis, namely the controlled series capacitor (CSC), the phase angle regulator (PAR), and the unified power flow controller (UPFC). Properties and characteristics of these devices axe investigated and discussed. A simple control strategy is proposed. This strategy is then analyzed extensively. Mathematical methods and physical knowledge about the pertinent phenomena are combined, and it is shown that this control strategy can be used for a fairly general class of devices. Computer simulations of the controlled system provide insight into the system behavior in a system of reasonable size. The robustness and stability of the control system are discussed as are its limits. Further, the behavior of the control strategy in a system where the modeling allows for dynamic phenomena are investigated with computer simulations. It is discussed under which circumstances the control action has beneficial or detrimental effect on the system dynamics. Finally, a graphical approach for analyzing the effect of controllers

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.

Load-redistribution strategy based on time-varying load against cascading failure of complex network

International Nuclear Information System (INIS)

Liu Jun; Shi Xin; Wang Kai; Shi Wei-Ren; Xiong Qing-Yu

2015-01-01

Cascading failure can cause great damage to complex networks, so it is of great significance to improve the network robustness against cascading failure. Many previous existing works on load-redistribution strategies require global information, which is not suitable for large scale networks, and some strategies based on local information assume that the load of a node is always its initial load before the network is attacked, and the load of the failure node is redistributed to its neighbors according to their initial load or initial residual capacity. This paper proposes a new load-redistribution strategy based on local information considering an ever-changing load. It redistributes the loads of the failure node to its nearest neighbors according to their current residual capacity, which makes full use of the residual capacity of the network. Experiments are conducted on two typical networks and two real networks, and the experimental results show that the new load-redistribution strategy can reduce the size of cascading failure efficiently. (paper)

Security cost analysis in electricity markets based on voltage security criteria and Web-based implementation

International Nuclear Information System (INIS)

Chen, H.

2003-01-01

This paper presents an efficient and transparent method for electricity market operators to analyze transaction security costs and to quantify the correlation between market operation and power system operation. Rescheduling and take-risk strategies were proposed and discussed with reference to transaction impact computations, thermal and voltage limits and voltage stability criteria. The rescheduling method is associated with an iterative generation dispatch or load curtailment approach to minimize the amount of rescheduling. The take-risk method considered operating risks to facilitate transactions. The SATC concept was also proposed to accurately evaluate transmission congestion. The impact of transaction was calculated using a new sensitivity formula to find the most effective rescheduling direction and the most effective cost distribution. A new pricing method called Nodal Congestion Price was also proposed to determine proper price signals. The paper also presents an Artificial Neural Network (ANN) based short term load forecasting method that considers the effect of price on the load. A web-based prototype was implemented to allow all market participants access to the proposed analysis and pricing techniques. Several case studies have validated the effectiveness of the proposed method which would help independent system operators in determining congestion prices, coordinate transactions and make profitable market decisions

A robust internet-based auction to procure electricity forwards

International Nuclear Information System (INIS)

Woo, C.K.; Lloyd, D.; Borden, M.; Warrington, R.; Baskette, C.

2004-01-01

Securing forward contracts to manage procurement-cost risk is an intuitively appealing and economically reasonable strategy for a load-serving local distribution company (LDC) in today's volatile electricity marketplace. However, knowing what to buy does not guarantee least-cost implementation. The forward-contract price quoted by a prospective seller may not be the 'best deal' that an LDC could have obtained, especially when the forward contract desired by the LDC is not actively traded. This paper reports the results from five internet-based auctions for electricity forward contracts with non-firm delivery and varying hourly quantities held monthly by a Florida municipal utility (MU) from September 2002 to January 2003. The results confirm that a multi-round auction design is robust in realizing competitive price offers made by credit-worthy sellers, time-efficient contracting, and consistent cost savings to the MU. Thus, the Anglo-Dutch auction described herein is a reasonable substitute for generation ownership by an LDC. (author)

Wavelet-based information filtering for fault diagnosis of electric drive systems in electric ships.

Science.gov (United States)

Silva, Andre A; Gupta, Shalabh; Bazzi, Ali M; Ulatowski, Arthur

2017-09-22

Electric machines and drives have enjoyed extensive applications in the field of electric vehicles (e.g., electric ships, boats, cars, and underwater vessels) due to their ease of scalability and wide range of operating conditions. This stems from their ability to generate the desired torque and power levels for propulsion under various external load conditions. However, as with the most electrical systems, the electric drives are prone to component failures that can degrade their performance, reduce the efficiency, and require expensive maintenance. Therefore, for safe and reliable operation of electric vehicles, there is a need for automated early diagnostics of critical failures such as broken rotor bars and electrical phase failures. In this regard, this paper presents a fault diagnosis methodology for electric drives in electric ships. This methodology utilizes the two-dimensional, i.e. scale-shift, wavelet transform of the sensor data to filter optimal information-rich regions which can enhance the diagnosis accuracy as well as reduce the computational complexity of the classifier. The methodology was tested on sensor data generated from an experimentally validated simulation model of electric drives under various cruising speed conditions. The results in comparison with other existing techniques show a high correct classification rate with low false alarm and miss detection rates. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Preparatory Work for a Scenario-Based Electricity Expansion Plan for North Korea after Hypothetical Reunification using WASP-IV

Energy Technology Data Exchange (ETDEWEB)

Kim, Young Joo; Chang, Choong Koo [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

2014-10-15

It is noteworthy that North Korean government itself has demanded other parties' cooperation in the field of power sector as the top priority to deal with North Korean own economic issues. In this light, the researcher consider that how to build power capacity in North Korean area after reunification needs to be studied with priority. A scenario-based approach is being adopted, and three scenarios are proposed: Scenario increasing capacity at 2.4% annual rate, Imitating South Korean electricity expansion history, and reaching 80% of South Korean Annual Peak Load in 35 years. In order to carry out the research, WASP-IV (Wien Automation System Planning-IV) code developed by IAEA is, with reasonable assumptions, being executed. Annual Peak Load prediction for each scenario, load duration curve, and existing power generating facilities in North Korea are presented herein. This research is being conducted as a preparatory work for the further study. IAEA's WASP-IV is adopted for a scenario-based electricity expansion plan for North Korea after hypothetical reunification between Koreas. Input data including Annual Peak Load, load duration curve, and existing facilities are built and presented. Additional future research includes inputting candidate plants data, cost data such as construction period, operation and maintenance costs, and fuel costs, as well as decommissioning of aged power plants in North Korea to complete WASP-IV execution. Assuming reunification, electricity expansion plan would need to integrate North and South Koreas demands and facilities. However, this research narrows down its scope to North Korean demand and facilities only. Such integrated simulation could be the topic for the later research. This work was supported by the 2014 Research Fund of the KINGS.

Preparatory Work for a Scenario-Based Electricity Expansion Plan for North Korea after Hypothetical Reunification using WASP-IV

International Nuclear Information System (INIS)

Kim, Young Joo; Chang, Choong Koo

2014-01-01

It is noteworthy that North Korean government itself has demanded other parties' cooperation in the field of power sector as the top priority to deal with North Korean own economic issues. In this light, the researcher consider that how to build power capacity in North Korean area after reunification needs to be studied with priority. A scenario-based approach is being adopted, and three scenarios are proposed: Scenario increasing capacity at 2.4% annual rate, Imitating South Korean electricity expansion history, and reaching 80% of South Korean Annual Peak Load in 35 years. In order to carry out the research, WASP-IV (Wien Automation System Planning-IV) code developed by IAEA is, with reasonable assumptions, being executed. Annual Peak Load prediction for each scenario, load duration curve, and existing power generating facilities in North Korea are presented herein. This research is being conducted as a preparatory work for the further study. IAEA's WASP-IV is adopted for a scenario-based electricity expansion plan for North Korea after hypothetical reunification between Koreas. Input data including Annual Peak Load, load duration curve, and existing facilities are built and presented. Additional future research includes inputting candidate plants data, cost data such as construction period, operation and maintenance costs, and fuel costs, as well as decommissioning of aged power plants in North Korea to complete WASP-IV execution. Assuming reunification, electricity expansion plan would need to integrate North and South Koreas demands and facilities. However, this research narrows down its scope to North Korean demand and facilities only. Such integrated simulation could be the topic for the later research. This work was supported by the 2014 Research Fund of the KINGS

46 CFR 169.689 - Demand loads.

Science.gov (United States)

2010-10-01

... 46 Shipping 7 2010-10-01 2010-10-01 false Demand loads. 169.689 Section 169.689 Shipping COAST... Electrical Electrical Installations on Vessels of 100 Gross Tons and Over § 169.689 Demand loads. Demand loads must meet § 111.60-7 of this chapter except that smaller demand loads for motor feeders are...

Status of load management

Energy Technology Data Exchange (ETDEWEB)

Juchymenko, A

1983-08-01

A summary is presented of the status of load management, defined as any activity by an electric utility to affect the size and characteristics of its load. Load management is currently viewed by electric utilities as an important tool for marketing electricity in a competitive fuel situation. A major aim of the National Energy Program is to reduce Canada's dependence on oil by 1990 to 10% of the energy used by all markets. As a result, electricity may play a greater role in the supply of primary energy. Research in load management has been directed mostly towards the residential market, especially direct control of domestic hot water heaters and air conditioners. Studies conducted in Canada and the U.S. to determine user's receptiveness to direct control of loads and thermal energy storage systems indicate that these load management techniques are in most cases not acceptable to customers, who prefer voluntary reduction in demand. The potential exists in the industrial market to use load management to assist in electrifying many of the fossil fuel-fired processes at competitive energy prices. Some of the more important applications include an industrial heat pump to heat liquids to 120{degree}C, induction heating for melting and heat treating of metals, and mechanical vapor recompression equipment to produce proces steam. 21 refs., 2 figs., 2 tabs.

Balance control of grid currents for UPQC under unbalanced loads based on matching-ratio compensation algorithm

DEFF Research Database (Denmark)

Zhao, Xiaojun; Zhang, Chunjiang; Chai, Xiuhui

2018-01-01

In three-phase four-wire systems, unbalanced loads can cause grid currents to be unbalanced, and this may cause the neutral point potential on the grid side to shift. The neutral point potential shift will worsen the control precision as well as the performance of the threephase four-wire unified...... fluctuations, and elaborates the interaction between unbalanced grid currents and DC bus voltage fluctuations; two control strategies of UPQC under three-phase stationary coordinate based on the MCA are given, and finally, the feasibility and effectiveness of the proposed control strategy are verified...... power quality conditioner (UPQC), and it also leads to unbalanced three-phase output voltage, even causing damage to electric equipment. To deal with unbalanced loads, this paper proposes a matching-ratio compensation algorithm (MCA) for the fundamental active component of load currents...

Probabilistic modeling of nodal electric vehicle load due to fast charging stations

DEFF Research Database (Denmark)

Tang, Difei; Wang, Peng; Wu, Qiuwei

2016-01-01

In order to reduce greenhouse gas emission and fossil fuel dependence, Electric Vehicle (EV) has drawn increasing attention due to its zero emission and high efficiency. However, new problems such as range anxiety, long charging duration and high charging power may threaten the safe and efficient...... station into consideration. Fuzzy logic inference system is applied to simulate the charging decision of EV drivers at fast charging station. Due to increasing EV loads in power system, the potential traffic congestion in fast charging stations is modeled and evaluated by queuing theory with spatial...

Electric vehicle system for charging and supplying electrical power

Science.gov (United States)

Su, Gui Jia

2010-06-08

A power system that provides power between an energy storage device, an external charging-source/load, an onboard electrical power generator, and a vehicle drive shaft. The power system has at least one energy storage device electrically connected across a dc bus, at least one filter capacitor leg having at least one filter capacitor electrically connected across the dc bus, at least one power inverter/converter electrically connected across the dc bus, and at least one multiphase motor/generator having stator windings electrically connected at one end to form a neutral point and electrically connected on the other end to one of the power inverter/converters. A charging-sourcing selection socket is electrically connected to the neutral points and the external charging-source/load. At least one electronics controller is electrically connected to the charging-sourcing selection socket and at least one power inverter/converter. The switch legs in each of the inverter/converters selected by the charging-source/load socket collectively function as a single switch leg. The motor/generators function as an inductor.

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.

Decoupling Weather Influence from User Habits for an Optimal Electric Load Forecast System

Directory of Open Access Journals (Sweden)

Luca Massidda

2017-12-01

Full Text Available The balance between production and consumption in a smart grid with high penetration of renewable sources and in the presence of energy storage systems benefits from an accurate load prediction. A general approach to load forecasting is not possible because of the additional complication due to the increasing presence of distributed and usually unmeasured photovoltaic production. Various methods are proposed in the literature that can be classified into two classes: those that predict by separating the portion of load due to consumption habits from the part of production due to local weather conditions, and those that attempt to predict the load as a whole. The characteristic that should lead to a preference for one approach over another is obviously the percentage of penetration of distributed production. The study site discussed in this document is the grid of Borkum, an island located in the North Sea. The advantages in terms of reducing forecasting errors for the electrical load, which can be obtained by using weather information, are explained. In particular, when comparing the results of different approaches gradually introducing weather forecasts, it is clear that the correct functional dependency of production has to be taken into account in order to obtain maximum yield from the available information. Where possible, this approach can significantly improve the quality of the forecasts, which in turn can improve the balance of a network—especially if energy storage systems are in place.

The analysis and compensation of errors of precise simple harmonic motion control under high speed and large load conditions based on servo electric cylinder

Science.gov (United States)

Ma, Chen-xi; Ding, Guo-qing

2017-10-01

Simple harmonic waves and synthesized simple harmonic waves are widely used in the test of instruments. However, because of the errors caused by clearance of gear and time-delay error of FPGA, it is difficult to control servo electric cylinder in precise simple harmonic motion under high speed, high frequency and large load conditions. To solve the problem, a method of error compensation is proposed in this paper. In the method, a displacement sensor is fitted on the piston rod of the electric cylinder. By using the displacement sensor, the real-time displacement of the piston rod is obtained and fed back to the input of servo motor, then a closed loop control is realized. There is compensation of pulses in the next period of the synthetic waves. This paper uses FPGA as the processing core. The software mainly comprises a waveform generator, an Ethernet module, a memory module, a pulse generator, a pulse selector, a protection module, an error compensation module. A durability of shock absorbers is used as the testing platform. The durability mainly comprises a single electric cylinder, a servo motor for driving the electric cylinder, and the servo motor driver.

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).

Monitoring the ammonia loading of zeolite-based ammonia SCR catalysts by a microwave method

Energy Technology Data Exchange (ETDEWEB)

Reiss, S.; Schoenauer, D.; Hagen, G.; Moos, R. [University of Bayreuth, Department of Functional Materials, Bayreuth (Germany); Fischerauer, G. [University of Bayreuth, Department of Metrology and Control, Bayreuth (Germany)

2011-05-15

Exhaust gas aftertreatment systems, which reduce nitrogen oxide emissions of heavy-duty diesel engines, commonly use a selective catalytic reduction (SCR) catalyst. Currently, emissions are controlled by evaluating NO{sub x} or NH{sub 3} in the gas phase downstream the catalyst and calculating the NH{sub 3} loading via a chemical storage model. Here, a microwave-cavity perturbation method is proposed in which electromagnetic waves are excited by probe feeds and the reflected signals are measured. At distinct resonance frequencies, the reflection coefficient shows a pronounced minimum. These resonance frequencies depend almost linearly on the NH{sub 3} loading of a zeolite-based SCR catalyst. Since the NH{sub 3} loading-dependent electrical properties of the catalyst material itself are measured, the amount of stored ammonia can be determined directly and in situ. The cross-sensitivity towards water can be reduced almost completely by selecting an appropriate frequency range. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Theoretical Studying the Cyclic Loading of Electric Drive Parts of the Stand duo-160

Directory of Open Access Journals (Sweden)

A. A. Maltsev

2015-01-01

Full Text Available An electric drive of work rolls of the single-stand rolling mill duo-160 located in the laboratory of Bauman Moscow State Technical University (BMSTU is selected as an object of the theoretical study. After the work rolls have gripped the work-piece the torsional vibrations occur in the drive; a 5-mass dynamic model is built to determine their forms and frequencies. Equations of torsionalvibration movement of masses with time are based on the Lagrange equations of type II. The paper identifies intrinsic moments of inertia and angular stiffness of parts and units of the electric drive. The graphs of the moments of elastic forces are built taking into consideration the dampers and backlashes. A revealed transition process has shown that given amplitudes of the cyclic shear stresses arising in dangerous section of the most loaded top spindle do not exceed the limit of its endurance in this section. In case of excess revealed, it would lead to accumulation of fatigue damage in the spindle metal and to formation of fatigue crack that most probably would appear near the shaft surface rather than in the metal mass. With further using the electric drive this micro-crack would be gradually evolved into macro-crack, the working cross-sectional area of the shaft would be reduced so that there would be a spindle failure and on the surface of a fatigue fracture of its shaft a strongly marked crack growth zone and a completely broken zone would be observed.

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 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 Electrical Resistivity and Acoustic Emission Response Law and Damage Evolution of Limestone in Brazilian Split Test

Directory of Open Access Journals (Sweden)

Xinji Xu

2016-01-01

Full Text Available The Brazilian split test was performed on two groups of limestone samples with loading directions vertical and parallel to the bedding plane, and the response laws of the electrical resistivity and acoustic emission (AE in the two loading modes were obtained. The test results showed that the Brazilian split test with loading directions vertical and parallel to the bedding showed obviously different results and anisotropic characteristics. On the basis of the response laws of the electrical resistivity and AE, the damage variables based on the electrical resistivity and AE properties were modified, and the evolution laws of the damage variables in the Brazilian split test with different loading directions were obtained. It was found that the damage evolution laws varied with the loading direction. Specifically, in the time-varying curve of the damage variable with the loading direction vertical to the bedding, the damage variable based on electrical resistivity properties showed an obvious damage weakening stage while that based on AE properties showed an abrupt increase under low load.

Kinetics of Domain Switching by Mechanical and Electrical Stimulation in Relaxor-Based Ferroelectrics

Science.gov (United States)

Chen, Zibin; Hong, Liang; Wang, Feifei; An, Xianghai; Wang, Xiaolin; Ringer, Simon; Chen, Long-Qing; Luo, Haosu; Liao, Xiaozhou

2017-12-01

Ferroelectric materials have been extensively explored for applications in high-density nonvolatile memory devices because of their ferroelectric-ferroelastic domain-switching behavior under electric loading or mechanical stress. However, the existence of ferroelectric and ferroelastic backswitching would cause significant data loss, which affects the reliability of data storage. Here, we apply in situ transmission electron microscopy and phase-field modeling to explore the unique ferroelastic domain-switching kinetics and the origin of this in relaxor-based Pb (Mg1 /3Nb2 /3)O3-33 % PbTiO3 single-crystal pillars under electrical and mechanical stimulations. Results showed that the electric-mechanical hysteresis loop shifted for relaxor-based single-crystal pillars because of the low energy levels of domains in the material and the constraint on the pillars, resulting in various mechanically reversible and irreversible domain-switching states. The phenomenon can potentially be used for advanced bit writing and reading in nonvolatile memories, which effectively overcomes the backswitching problem and broadens the types of ferroelectric materials for nonvolatile memory applications.

Optimal Overcurrent Relay Coordination in Presence of Inverter-based Wind Farms and Electrical Energy Storage Devices

DEFF Research Database (Denmark)

Javadi, Mohammad Sadegh; Esmaeel Nezhad, Ali; Anvari-Moghaddam, Amjad

2018-01-01

This paper investigates the coordination problem of overcurrent relays (OCRs) in presence of wind power generation and electrical energy storage (EES) systems. As the injected short-circuit current of inverter-based devices connected to the electrical grid is a function of the power electronic...... mainly matter for the EES system operating in either charging or discharging modes, as well. This paper evaluates different operation strategies considering the variations of the load demand and the presence of large-scale wind farms as well as an EES system, while validating the suggested method...

Electrical distribution system management

International Nuclear Information System (INIS)

Hajos, L.; Mortarulo, M.; Chang, K.; Sparks, T.

1990-01-01

This paper reports that maintenance of electrical system data is essential to the operation, maintenance, and modification of a nuclear station. Load and equipment changes affect equipment sizing, available short-circuit currents and protection coordination. System parameters must be maintained in a controlled manner to enable evaluation of proposed modifications and provide adequate verification and traceability. For this purpose, Public Service Electric and Gas Company has implemented a Verified and Validated Electric Distribution System Management (EDSM) program at the Hope Creek and Salem Nuclear Power Stations. EDSM program integrates computerized configuration management of electrical systems with calculational software the Technical Standard procedures. The software platform is PC-based. The Database Manager and Calculational programs have been linked together through a user friendly menu system. The database management nodule enable s assembly and maintenance of databases for individual loads, buses, and branches within the electrical systems with system access and approval controlled through electronic security incorporated within the database manger. Reports drawn from the database serve as the as-built and/or as-designed record of the system configurations. This module also creates input data files of network parameters in a format readable by the calculational modules. Calculations modules provide load flow, voltage drop, motor starting, and short-circuit analyses, as well as dynamic analyses of bus transfers

76 FR 66220 - Automatic Underfrequency Load Shedding and Load Shedding Plans Reliability Standards

Science.gov (United States)

2011-10-26

.... I. Background A. Underfrequency Load Shedding 4. An interconnected electric power system must... generation and load within an interconnected electric power system is shown in the frequency of the system.\\4... Reliability Standards for the Bulk-Power System, Order No. 693, FERC Stats. & Regs. ] 31,242, order on reh'g...

Analysing socioeconomic diversity and scaling effects on residential electricity load profiles in the context of low carbon technology uptake

International Nuclear Information System (INIS)

McKenna, R.; Hofmann, L.; Merkel, E.; Fichtner, W.; Strachan, N.

2016-01-01

Adequately accounting for interactions between Low Carbon Technologies (LCTs) at the building level and the overarching energy system means capturing the granularity associated with decentralised heat and power supply in residential buildings. The approach presented here adds novelty in terms of a realistic socioeconomic differentiation by employing dwelling/household archetypes (DHAs) and neighbourhood clusters at the Output Area (OA) level. These archetypes are combined with a mixed integer linear program (MILP) to generate optimum (minimum cost) technology configurations and operation schedules. Even in the baseline case, without any LCT penetration, a substantial deviation from the standard load profile (SLP) is encountered, suggesting that for some neighbourhoods this profile is not appropriate. With the application of LCTs, including heat pumps, micro-CHP and photovoltaic (PV), this effect is much stronger, including more negative residual load, more variability, and higher ramps with increased LCT penetration, and crucially different between neighbourhood clusters. The main policy implication of the study is the importance of understanding electrical load profiles at the neighbourhood level, because of the consequences they have for investment in the overarching energy system, including transmission and distribution infrastructure, and centralised generation plant. Further work should focus on attaining a superior socioeconomic differentiation between households. - Highlights: • Low carbon technologies (LCTs) for heat/electricity in residential buildings. • Socioeconomic effects and interactions with overarching energy system. • Building thermal/electrical model combined with optimisation. • Significant differences between neighbourhood load profiles. • Policy implications: support for LCTs and investment in infrastructure.

Calculation of cooling internal circuits loss of load curve in giant electric machines; Calculo da curva de perda de carga dos circuitos axiais internos de refrigeracao de maquinas eletricas gigantes

Energy Technology Data Exchange (ETDEWEB)

Silva, Hilton Penha [Parana Univ., Curitiba, PR (Brazil). Dept. de Engenharia Mecanica. Dept. de Engenharia do Produto; Passos, Alex Sandro Barbosa [Parana Univ., Curitiba, PR (Brazil). Dept. de Engenharia Mecanica. Dept. de Pesquisa e Desenvolvimento do Produto

2001-07-01

This article describes a method for calculation of the loss of load curve for the ventilation axial circuits. The method assumes the ventilation circuit representation in a way similar to the electrical circuits. The great difficulty of circuit solution resides in the non linearity of the loss of load resistances and the equations relating the pressures and flows. The method is based on the association of the resistance curves of loss of load in a such way that, when the resistance curve of the total circuit loss of load is obtained, the blower operation point can be easily obtained and, consequently, the individual flows for each section of the circuit.

A load factor based mean-variance analysis for fuel diversification

Energy Technology Data Exchange (ETDEWEB)

Gotham, Douglas; Preckel, Paul; Ruangpattana, Suriya [State Utility Forecasting Group, Purdue University, West Lafayette, IN (United States); Muthuraman, Kumar [McCombs School of Business, University of Texas, Austin, TX (United States); Rardin, Ronald [Department of Industrial Engineering, University of Arkansas, Fayetteville, AR (United States)

2009-03-15

Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (Markowitz, H., 1952. Portfolio selection. Journal of Finance 7(1) 77-91). However the standard mean-variance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also illustrate the approach using data for the state of Indiana and demonstrate the ability of the model in providing useful insights. (author)

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.

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.

40 CFR 92.106 - Equipment for loading the engine.

Science.gov (United States)

2010-07-01

...: electrical resistance load bank; fans or other means for cooling of the load bank; wattmeter, including phase... electrical shunt and voltmeter is allowed for current measurement); meter(s) to measure the voltage across... locomotives are equipped with an internal electrical resistance load bank and fans for cooling of the load...

Optimal load scheduling in commercial and residential microgrids

Science.gov (United States)

Ganji Tanha, Mohammad Mahdi

Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants' comfort level, and microgrid operation constraints. The CBOLS' objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying single-unit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.

System and method to determine electric motor efficiency using an equivalent circuit

Science.gov (United States)

Lu, Bin [Kenosha, WI; Habetler, Thomas G [Snellville, GA

2011-06-07

A system and method for determining electric motor efficiency includes a monitoring system having a processor programmed to determine efficiency of an electric motor under load while the electric motor is online. The determination of motor efficiency is independent of a rotor speed measurement. Further, the efficiency is based on a determination of stator winding resistance, an input voltage, and an input current. The determination of the stator winding resistance occurs while the electric motor under load is online.

Analysis for Involvement of TPP Operating in Accordance with Heating Schedule to Passing Through Failures of Electric Load Schedules

Directory of Open Access Journals (Sweden)

V. I. Nazarov

2013-01-01

Full Text Available The paper describes technical and economic evaluation of various methods pertaining to passing through failures of electric load at TPP which is operating in accordance with heating schedule.

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

International Nuclear Information System (INIS)

Bowcock, S.; Miller, D.

1992-01-01

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

Development of an Energy-Savings Calculation Methodology for Residential Miscellaneous Electric Loads: Preprint

Energy Technology Data Exchange (ETDEWEB)

Hendron, R.; Eastment, M.

2006-08-01

In order to meet whole-house energy savings targets beyond 50% in residential buildings, it will be essential that new technologies and systems approaches be developed to address miscellaneous electric loads (MELs). These MELs are comprised of the small and diverse collection of energy-consuming devices found in homes, including what are commonly known as plug loads (televisions, stereos, microwaves), along with all hard-wired loads that do not fit into other major end-use categories (doorbells, security systems, garage door openers). MELs present special challenges because their purchase and operation are largely under the control of the occupants. If no steps are taken to address MELs, they can constitute 40-50% of the remaining source energy use in homes that achieve 60-70% whole-house energy savings, and this percentage is likely to increase in the future as home electronics become even more sophisticated and their use becomes more widespread. Building America (BA), a U.S. Department of Energy research program that targets 50% energy savings by 2015 and 90% savings by 2025, has begun to identify and develop advanced solutions that can reduce MELs.

Artificial intelligence in short term electric load forecasting: a state-of-the-art survey for the researcher

Energy Technology Data Exchange (ETDEWEB)

Metaxiotis, K.; Kagiannas, A.; Askounis, D.; Psarras, J. [National Technical University of Athens, Zografou (Turkey). Dept. of Electrical and Computer Engineering

2003-06-01

Intelligent solutions, based on artificial intelligence (AI) technologies, to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. AI-based systems are being developed and deployed worldwide in myriad applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. This paper provides an overview for the researcher of AI technologies, as well as their current use in the field of short term electric load forecasting (STELF). The history of AI in STELF is outlined, leading to a discussion of the various approaches as well as the current research directions. The paper concludes by sharing thoughts and estimations on AI future prospects in this area. This review reveals that although still regarded as a novel methodology, AI technologies are shown to have matured to the point of offering real practical benefits in many of their applications. (Author)

An implementation of particle swarm optimization to evaluate optimal under-voltage load shedding in competitive electricity markets

Science.gov (United States)

Hosseini-Bioki, M. M.; Rashidinejad, M.; Abdollahi, A.

2013-11-01

Load shedding is a crucial issue in power systems especially under restructured electricity environment. Market-driven load shedding in reregulated power systems associated with security as well as reliability is investigated in this paper. A technoeconomic multi-objective function is introduced to reveal an optimal load shedding scheme considering maximum social welfare. The proposed optimization problem includes maximum GENCOs and loads' profits as well as maximum loadability limit under normal and contingency conditions. Particle swarm optimization (PSO) as a heuristic optimization technique, is utilized to find an optimal load shedding scheme. In a market-driven structure, generators offer their bidding blocks while the dispatchable loads will bid their price-responsive demands. An independent system operator (ISO) derives a market clearing price (MCP) while rescheduling the amount of generating power in both pre-contingency and post-contingency conditions. The proposed methodology is developed on a 3-bus system and then is applied to a modified IEEE 30-bus test system. The obtained results show the effectiveness of the proposed methodology in implementing the optimal load shedding satisfying social welfare by maintaining voltage stability margin (VSM) through technoeconomic analyses.

Prediction of crack density and electrical resistance changes in indium tin oxide/polymer thin films under tensile loading

KAUST Repository

Mora Cordova, Angel; Khan, Kamran; El Sayed, Tamer

2014-01-01

We present unified predictions for the crack onset strain, evolution of crack density, and changes in electrical resistance in indium tin oxide/polymer thin films under tensile loading. We propose a damage mechanics model to quantify and predict

Electrical appliance energy consumption control methods and electrical energy consumption systems

Science.gov (United States)

Donnelly, Matthew K [Kennewick, WA; Chassin, David P [Pasco, WA; Dagle, Jeffery E [Richland, WA; Kintner-Meyer, Michael [Richland, WA; Winiarski, David W [Kennewick, WA; Pratt, Robert G [Kennewick, WA; Boberly-Bartis, Anne Marie [Alexandria, VA

2006-03-07

Electrical appliance energy consumption control methods and electrical energy consumption systems are described. In one aspect, an electrical appliance energy consumption control method includes providing an electrical appliance coupled with a power distribution system, receiving electrical energy within the appliance from the power distribution system, consuming the received electrical energy using a plurality of loads of the appliance, monitoring electrical energy of the power distribution system, and adjusting an amount of consumption of the received electrical energy via one of the loads of the appliance from an initial level of consumption to an other level of consumption different than the initial level of consumption responsive to the monitoring.

Electrical appliance energy consumption control methods and electrical energy consumption systems

Science.gov (United States)

Donnelly, Matthew K [Kennewick, WA; Chassin, David P [Pasco, WA; Dagle, Jeffery E [Richland, WA; Kintner-Meyer, Michael [Richland, WA; Winiarski, David W [Kennewick, WA; Pratt, Robert G [Kennewick, WA; Boberly-Bartis, Anne Marie [Alexandria, VA

2008-09-02

Electrical appliance energy consumption control methods and electrical energy consumption systems are described. In one aspect, an electrical appliance energy consumption control method includes providing an electrical appliance coupled with a power distribution system, receiving electrical energy within the appliance from the power distribution system, consuming the received electrical energy using a plurality of loads of the appliance, monitoring electrical energy of the power distribution system, and adjusting an amount of consumption of the received electrical energy via one of the loads of the appliance from an initial level of consumption to an other level of consumption different than the initial level of consumption responsive to the monitoring.

Neural network-based voltage regulator for an isolated asynchronous generator supplying three-phase four-wire loads

Energy Technology Data Exchange (ETDEWEB)

Singh, Bhim; Kasal, Gaurav Kumar [Department of Electrical Engineering, Indian Institute of Technology, Delhi, Hauz-Khas, New Delhi 110016 (India)

2008-06-15

This paper deals with a neural network-based solid state voltage controller for an isolated asynchronous generator (IAG) driven by constant speed prime mover like diesel engine, bio-gas or gasoline engine and supplying three-phase four-wire loads. The proposed control scheme uses an indirect current control and a fast adaptive linear element (adaline) based neural network reference current extractor, which extracts the real positive sequence current component without any phase shift. The neutral current of the source is also compensated by using three single-phase bridge configuration of IGBT (insulated gate bipolar junction transistor) based voltage source converter (VSC) along-with single-phase transformer having self-supported dc bus. The proposed controller provides the functions as a voltage regulator, a harmonic eliminator, a neutral current compensator, and a load balancer. The proposed isolated electrical system with its controller is modeled and simulated in MATLAB along with Simulink and PSB (Power System Block set) toolboxes. The simulated results are presented to demonstrate the capability of an isolated asynchronous generating system driven by a constant speed prime mover for feeding three-phase four-wire loads. (author)

Hierarchical Load Tracking Control of a Grid-Connected Solid Oxide Fuel Cell for Maximum Electrical Efficiency Operation

Directory of Open Access Journals (Sweden)

Yonghui Li

2015-03-01

Full Text Available Based on the benchmark solid oxide fuel cell (SOFC dynamic model for power system studies and the analysis of the SOFC operating conditions, the nonlinear programming (NLP optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject to the constraints of fuel utilization factor, stack temperature and output active power. The optimal operating conditions of the grid-connected SOFC were obtained by solving the NLP problem considering the power consumed by the air compressor. With the optimal operating conditions of the SOFC for the maximum efficiency operation obtained at different active power output levels, a hierarchical load tracking control scheme for the grid-connected SOFC was proposed to realize the maximum electrical efficiency operation with the stack temperature bounded. The hierarchical control scheme consists of a fast active power control and a slower stack temperature control. The active power control was developed by using a decentralized control method. The efficiency of the proposed hierarchical control scheme was demonstrated by case studies using the benchmark SOFC dynamic model.

Peak loads and network investments in sustainable energy transitions

Energy Technology Data Exchange (ETDEWEB)

Blokhuis, Erik, E-mail: e.g.j.blokhuis@tue.nl [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands); Brouwers, Bart [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands); Putten, Eric van der [Endinet, Gas and Electricity Network Operations, P.O. Box 2005, 5600CA Eindhoven (Netherlands); Schaefer, Wim [Eindhoven University of Technology, Department of Architecture, Building and Planning, Vertigo 8.11, P.O. Box 513, 5600MB Eindhoven (Netherlands)

2011-10-15

Current energy distribution networks are often not equipped for facilitating expected sustainable transitions. Major concerns for future electricity networks are the possibility of peak load increases and the expected growth of decentralized energy generation. In this article, we focus on peak load increases; the effects of possible future developments on peak loads are studied, together with the consequences for the network. The city of Eindhoven (the Netherlands) is used as reference city, for which a scenario is developed in which the assumed future developments adversely influence the maximum peak loads on the network. In this scenario, the total electricity peak load in Eindhoven is expected to increase from 198 MVA in 2009 to 591-633 MVA in 2040. The necessary investments for facilitating the expected increased peak loads are estimated at 305-375 million Euros. Based upon these projections, it is advocated that - contrary to current Dutch policy - choices regarding sustainable transitions should be made from the viewpoint of integral energy systems, evaluating economic implications of changes to generation, grid development, and consumption. Recently applied and finished policies on energy demand reduction showed to be effective; however, additional and connecting policies on energy generation and distribution should be considered on short term. - Highlights: > Sustainable energy transitions can result in major electricity peak load increases. > Introduction of heat pumps and electrical vehicles requires network expansion. > Under worst case assumptions, peak loads in Eindhoven increase with 200% until 2040. > The necessary investment for facilitating this 2040 peak demand is Euro 305-375 million. > Future policy choices should be made from the viewpoint of the integral energy system.