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.

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

Science.gov (United States)

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

2014-12-23

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

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)

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

International Nuclear Information System (INIS)

Yalcinoz, T.; Eminoglu, U.

2005-01-01

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

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

Alaska Village Electric Load Calculator

Energy Technology Data Exchange (ETDEWEB)

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

2004-10-01

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

Spatial electric load forecasting

CERN Document Server

Willis, H Lee

2002-01-01

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

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

Directory of Open Access Journals (Sweden)

Lintao Yang

2018-01-01

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

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

International Nuclear Information System (INIS)

Kouhi, Sajjad; Keynia, Farshid

2013-01-01

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

Network Theory Integrated Life Cycle Assessment for an Electric Power System

Directory of Open Access Journals (Sweden)

Heetae Kim

2015-08-01

Full Text Available In this study, we allocate Greenhouse gas (GHG emissions of electricity transmission to the consumers. As an allocation basis, we introduce energy distance. Energy distance takes the transmission load on the electricity energy system into account in addition to the amount of electricity consumption. As a case study, we estimate regional GHG emissions of electricity transmission loss in Chile. Life cycle assessment (LCA is used to estimate the total GHG emissions of the Chilean electric power system. The regional GHG emission of transmission loss is calculated from the total GHG emissions. We construct the network model of Chilean electric power grid as an undirected network with 466 nodes and 543 edges holding the topology of the power grid based on the statistical record. We analyze the total annual GHG emissions of the Chilean electricity energy system as 23.07 Mt CO2-eq. and 1.61 Mt CO2-eq. for the transmission loss, respectively. The total energy distance for the electricity transmission accounts for 12,842.10 TWh km based on network analysis. We argue that when the GHG emission of electricity transmission loss is estimated, the electricity transmission load should be separately considered. We propose network theory as a useful complement to LCA analysis for the complex allocation. Energy distance is especially useful on a very large-scale electric power grid such as an intercontinental transmission network.

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.

Integration of electric drive vehicles in the Danish electricity network with high wind power penetration

DEFF Research Database (Denmark)

Chandrashekhara, Divya K; Østergaard, Jacob; Larsen, Esben

2010-01-01

/conventional) which are likely to fuel these cars. The study was carried out considering the Danish electricity network state around 2025, when the EDV penetration levels would be significant enough to have an impact on the power system. Some of the interesting findings of this study are - EDV have the potential......This paper presents the results of a study carried out to examine the feasibility of integrating electric drive vehicles (EDV) in the Danish electricity network which is characterised by high wind power penetration. One of the main aims of this study was to examine the effect of electric drive...... vehicles on the Danish electricity network, wind power penetration and electricity market. In particular the study examined the effect of electric drive vehicles on the generation capacity constraints, load curve, cross border transmission capacity and the type of generating sources (renewable...

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.

Pay for load demand - electricity pricing with load demand component

International Nuclear Information System (INIS)

Pyrko, Jurek; Sernhed, Kerstin; Abaravicius, Juozas

2003-01-01

This publication is part of a project called Direct and Indirect Load Control in Buildings. Peak load problems have attracted considerable attention in Sweden during last three winters, caused by a significant decrease in available reserve power, which is a consequence of political decisions and liberalisation of the electricity market. A possible way to lower peak loads, avoiding electricity shortages and reducing electricity costs both for users and utilities, is to make customers experience the price difference during peak load periods and, in this way, become more aware of their energy consumption pattern and load demand. As of January 1st 2001, one of the Swedish energy utilities - Sollentuna Energi - operating in the Stockholm area, introduced a new electricity tariff with differentiated grid fees based on a mean value of the peak load every month. This tariff was introduced for all residential customers in the service area. The objective of this study is to investigate the extent to which a Load Demand Component, included in electricity pricing, can influence energy use and load demand in residential buildings. What are the benefits and disadvantages for customers and utilities? This paper investigates the impact of the new tariff on the utility and different types of typical residential customers, making comparisons with previous tariff. Keywords Load demand, electricity pricing, tariff, residential customers, energy behaviour

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.

Radial basis function neural network for power system load-flow

International Nuclear Information System (INIS)

Karami, A.; Mohammadi, M.S.

2008-01-01

This paper presents a method for solving the load-flow problem of the electric power systems using radial basis function (RBF) neural network with a fast hybrid training method. The main idea is that some operating conditions (values) are needed to solve the set of non-linear algebraic equations of load-flow by employing an iterative numerical technique. Therefore, we may view the outputs of a load-flow program as functions of the operating conditions. Indeed, we are faced with a function approximation problem and this can be done by an RBF neural network. The proposed approach has been successfully applied to the 10-machine and 39-bus New England test system. In addition, this method has been compared with that of a multi-layer perceptron (MLP) neural network model. The simulation results show that the RBF neural network is a simpler method to implement and requires less training time to converge than the MLP neural network. (author)

Impacts of climate change on electricity network business

International Nuclear Information System (INIS)

Auvinen, O.; Martikainen, A.

2006-01-01

In this project the impact of climate change on electricity network business was study. The results are based on RCAO climate model scenarios. The climate predictions were composed to the period 2016- 2045. The period 1960-1990 was used as a control period. The climate predictions were composed for precipitation, temperature, hoarfrost, thunder, ground frost and wind. Impacts of the change of the climate variables on electricity network business were estimated from technical and economical points of view. It is expected that climate change will cause more damages than benefits on the electricity network business. The increase of the number of network faults will be the most significant and demanding disadvantage caused by climate change in distribution network. If networks are not improved to be more resistant for faults, then thunder, heavy snow and wind cause more damages especially to overhead lines in medium voltage network. Increasing precipitation and decreasing amount of ground frost weaken the strength of soil. The construction work will be more difficult with the present vehicles because wet and unfrozen ground can not carry heavy vehicles. As a consequence of increasing temperature, the demand of heating energy will decrease and the demand of cooling energy will increase. This is significant for the electricity consumption and the peak load of temperature-dependent electricity users. (orig.)

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

Directory of Open Access Journals (Sweden)

Yuancheng Zhao

2018-01-01

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

Network reconfiguration for loss reduction in electrical distribution system using genetic algorithm

International Nuclear Information System (INIS)

Adail, A.S.A.A.

2012-01-01

Distribution system is a critical links between the utility and the nuclear installation. During feeding electricity to that installation there are power losses. The quality of the network depends on the reduction of these losses. Distribution system which feeds the nuclear installation must have a higher quality power. For example, in Inshas site, electrical power is supplied to it from two incoming feeders (one from new abu-zabal substation and the other from old abu-zabal substation). Each feeder is designed to carry the full load, while the operator preferred to connect with a new abu-zabal substation, which has a good power quality. Bad power quality affects directly the nuclear reactor and has a negative impact on the installed sensitive equipment's of the operation. The thesis is Studying the electrical losses in a distribution system (causes and effected factors), feeder reconfiguration methods, and applying of genetic algorithm in an electric distribution power system. In the end, this study proposes an optimization technique based on genetic algorithms for distribution network reconfiguration to reduce the network losses to minimum. The proposed method is applied to IEEE test network; that contain 3 feeders and 16 nodes. The technique is applied through two groups, distribution have general loads, and nuclear loads. In the groups the technique applied to seven cases at normal operation state, system fault condition as well as different loads conditions. Simulated results are drawn to show the accuracy of the technique.

Improving distribution efficiency of electrical network using geo-electrical options. A case study in a rural area of Assam (India)

Energy Technology Data Exchange (ETDEWEB)

Hazarika, S.; Hiloidhari, M.; Baruah, D.C. [Energy Conservation Laboratory, Department of Energy, Tezpur University, Tezpur, Assam (India)

2012-11-15

Reduction of electricity distribution loss is a major area of focus in India. This paper aims to investigate geo-electrical options to improve distribution efficiency of electrical network. Distribution efficiencies corresponding to several possible electrical network options are assessed using Geographical Information System (GIS) integrated electrical theory. An existing electrical distribution network of a rural area in Assam (India) is considered for the present investigation. Information related to characteristics of loads, features of conductors, and transformers of the existing network are used for this investigation. The line losses of the three existing transformers are estimated at about 36, 20, and 3 % of their respective connected loads. Longer distribution lines associated with higher loads are the causes of higher line losses. Using basic electrical theory and GIS tools, it is found that line losses can be reduced in the existing distribution system through management of distribution transformer and reconductoring. Two alternative locations for each of the three transformers are identified for optimal management of distribution transformers. Similarly, five different types of commercially available conductors are identified for possible reconductoring to reduce line loss. The economic viability of reconductoring of distribution lines are also assessed through an economic analysis. Net present values of total expenditure comprising purchase prices of conductor and cost attributed to line losses are estimated considering 30 years of useful life. The existing conductor has the worst economic merit, though it is the cheapest amongst all. A net saving of about USD 24,084 is possible through the best choice of distribution conductor for the village.

Analysis of reflectivity & predictability of electricity network tariff structures for household consumers

NARCIS (Netherlands)

Nijhuis, M.; Gibescu, M.; Cobben, J. F.G.

2017-01-01

Distribution network operators charge household consumers with a network tariff, so they can recover their network investment and operational costs. With the transition; towards a sustainable energy system, the household load is changing, through the introduction of photovoltaics and electric

Impacts of climate change on electricity network business

International Nuclear Information System (INIS)

Martikainen, A.

2006-04-01

Climate has a significant impact on the electricity network business. The electricity network is under the weather pressure all the time and it is planned and constructed to withstand normal climatic stresses. The electricity network that has been planned and constructed now, is expected to be in operation next 40 years. If climatic stresses change in this period, it can cause significant impacts on electricity network business. If the impacts of climate change are figured out in advance, it is possible to mitigate negative points of climate change and exploit the positive points. In this paper the impact of climate change on electricity network business is presented. The results are based on RCAO climate model scenarios. The climate predictions were composed to the period 2016. 2045. The period 1960.1990 was used as a control period. The climate predictions were composed for precipitation, temperature, hoarfrost, thunder, ground frost and wind. The impacts of the change of the climate variables on electricity network business were estimated from technical and economical points of view. The estimation was based on the change predictions of the climate variables. It is expected that climate change will cause more damages than benefits on the electricity network business. The increase of the number of network faults will be the most significant and demanding disadvantage caused by climate change. If networks are not improved to be more resistant for faults, then thunder, heavy snow and wind cause more damages especially to overhead lines in medium voltage network. Increasing precipitation and decreasing amount of ground frost weaken the strength of soil. The construction work will be more difficult with the present vehicles because wet and unfrozen ground can not carry heavy vehicles. As a consequence of increasing temperature, the demand of heating energy will decrease and the demand of cooling energy will increase. This is significant for the electricity

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.

LOAD FORECASTING FOR POWER SYSTEM PLANNING AND OPERATION USING ARTIFICIAL NEURAL NETWORK AT AL BATINAH REGION OMAN

Directory of Open Access Journals (Sweden)

HUSSEIN A. ABDULQADER

2012-08-01

Full Text Available Load forecasting is essential part for the power system planning and operation. In this paper the modeling and design of artificial neural network for load forecasting is carried out in a particular region of Oman. Neural network approach helps to reduce the problem associated with conventional method and has the advantage of learning directly from the historical data. The neural network here uses data such as past load; weather information like humidity and temperatures. Once the neural network is trained for the past set of data it can give a prediction of future load. This reduces the capital investment reducing the equipments to be installed. The actual data are taken from the Mazoon Electrical Company, Oman. The data of load for the year 2007, 2008 and 2009 are collected for a particular region called Al Batinah in Oman and trained using neural networks to forecast the future. The main objective is to forecast the amount of electricity needed for better load distribution in the areas of this region in Oman. The load forecasting is done for the year 2010 and is validated for the accuracy.

Smart PV grid to reinforce the electrical network

Science.gov (United States)

AL-Hamad, Mohamed Y.; Qamber, Isa S.

2017-11-01

Photovoltaic (PV) became the new competitive energy resources of the planet and needs to be engaged in grid to break up the congestion in both Distribution and Transmission systems. The objective of this research is to reduce the load flow through the distribution and transmission equipment by 20%. This reduction will help in relief networks loaded equipment's in all networks. Many projects are starting to develop in the GCC countries and need to be organized to achieve maximum benefits from involving the Renewable Energy Sources (RES) in the network. The GCC countries have a good location for solar energy with high intensity of the solar radiation and clear sky along the year. The opportunities of the solar energy is to utilize and create a sustainable energy resource for this region. Moreover, the target of this research is to engage the PV technology in such a way to lower the over loaded equipment and increases the electricity demand at the consumer's side.

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...

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)

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

Directory of Open Access Journals (Sweden)

Yuqi Dong

2016-12-01

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

A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts

International Nuclear Information System (INIS)

Neaimeh, Myriam; Wardle, Robin; Jenkins, Andrew M.; Yi, Jialiang; Hill, Graeme; Lyons, Padraig F.; Hübner, Yvonne; Blythe, Phil T.; Taylor, Phil C.

2015-01-01

Highlights: • Working with unique datasets of EV charging and smart meter load demand. • Distribution networks are not a homogenous group with more capabilities to accommodate EVs than previously suggested. • Spatial and temporal diversity of EV charging demand alleviate the impacts on networks. • An extensive recharging infrastructure could enable connection of additional EVs on constrained distribution networks. • Electric utilities could increase the network capability to accommodate EVs by investing in recharging infrastructure. - Abstract: This work uses a probabilistic method to combine two unique datasets of real world electric vehicle charging profiles and residential smart meter load demand. The data was used to study the impact of the uptake of Electric Vehicles (EVs) on electricity distribution networks. Two real networks representing an urban and rural area, and a generic network representative of a heavily loaded UK distribution network were used. The findings show that distribution networks are not a homogeneous group with a variation of capabilities to accommodate EVs and there is a greater capability than previous studies have suggested. Consideration of the spatial and temporal diversity of EV charging demand has been demonstrated to reduce the estimated impacts on the distribution networks. It is suggested that distribution network operators could collaborate with new market players, such as charging infrastructure operators, to support the roll out of an extensive charging infrastructure in a way that makes the network more robust; create more opportunities for demand side management; and reduce planning uncertainties associated with the stochastic nature of EV charging demand.

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

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.)

A generative modeling approach to connectivity-Electrical conduction in vascular networks

DEFF Research Database (Denmark)

Hald, Bjørn Olav

2016-01-01

The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel...... to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks...... of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub...

Intelligent electrical outlet for collective load control

Science.gov (United States)

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

2015-10-27

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

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.

Thermal and Arc Flash Analysis of Electric Motor Drives in Distribution Networks

OpenAIRE

Nikolovski, Srete; Mlakić, Dragan; Alibašić, Emir

2017-01-01

The paper presents thermal analysis and arc flash analysis taking care of protection relays coordination settings for electric motor drives connected to the electrical network. Power flow analysis is performed to check if there are any voltage and loading violation conditions in the system. Fault analysis is performed to check the short circuit values and compute arc flash energy dissipated at industrial busbars to eliminate damage to electrical equipment and electrical shocks and hazard to p...

Load profiles analysis for electricity market

Directory of Open Access Journals (Sweden)

Radu Porumb

2014-04-01

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

Multi-Objective Scheduling of Electric Vehicles in Smart Distribution Network

Directory of Open Access Journals (Sweden)

Changhong Deng

2016-11-01

Full Text Available Due to the energy savings and environmental protection they provide, plug-in electric vehicles (PEVs are increasing in number quickly. Rapid development of PEVs brings new opportunities and challenges to the electricity distribution network’s dispatching. A high number of uncoordinated charging PEVs has significant negative impacts on the secure and economic operation of a distribution network. In this paper, a bi-level programming approach that coordinates PEVs’ charging with the network load and electricity price of the open market is presented. The major objective of the upper level model is to minimize the total network costs and the deviation of electric vehicle aggregators’ charging power and the equivalent power. The subsequent objective of the lower level model after the upper level decision is to minimize the dispatching deviation of the sum of PEVs’ charging power and their optimization charging power under the upper level model. An improved particle swarm optimization algorithm is used to solve the bi-level programming. Numerical studies using a modified IEEE 69-bus distribution test system including six electric vehicle aggregators verify the efficiency of the proposed model.

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.

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

Electric network interconnection of Mashreq Arab Countries

International Nuclear Information System (INIS)

El-Amin, I.M.; Al-Shehri, A.M.; Opoku, G.; Al-Baiyat, S.A.; Zedan, F.M.

1994-01-01

Power system interconnection is a well established practice for a variety of technical and economical reasons. Several interconnected networks exist worldwide for a number of factors. Some of these networks cross international boundaries. This presentation discusses the future developments of the power systems of Mashreq Arab Countries (MAC). MAC consists of Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, United Arab Emirates (UAE), and Yemen. Mac power systems are operated by government or semigovernment bodies. Many of these countries have national or regional electric grids but are generally isolated from each other. With the exception of Saudi Arabia power systems, which employ 60 Hz, all other MAC utilities use 50 Hz frequency. Each country is served by one utility, except Saudi Arabia, which is served by four major utilities and some smaller utilities serving remote towns and small load centers. The major utilities are the Saudi Consolidated electric Company in the Eastern Province (SCECO East), SCECO Center, SCECO West, and SCECO South. These are the ones considered in this study. The energy resources in MAC are varied. Countries such as Egypt, Iraq, and Syria have significant hydro resources.The gulf countries and Iraq have abundant fossil fuel, The variation in energy resources as well as the characteristics of the electric load make it essential to look into interconnections beyond the national boundaries. Most of the existing or planned interconnections involve few power systems. A study involving 12 countries and over 20 utilities with different characteristics represents a very large scale undertaking

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)

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.

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....

Protection of electricity distribution networks

CERN Document Server

Gers, Juan M

2004-01-01

Written by two practicing electrical engineers, this second edition of the bestselling Protection of Electricity Distribution Networks offers both practical and theoretical coverage of the technologies, from the classical electromechanical relays to the new numerical types, which protect equipment on networks and in electrical plants. A properly coordinated protection system is vital to ensure that an electricity distribution network can operate within preset requirements for safety for individual items of equipment, staff and public, and the network overall. Suitable and reliable equipment sh

Markets in real electric networks require reactive prices

International Nuclear Information System (INIS)

Hogan, W.W.

1996-01-01

Extending earlier seminal work, the author finds that locational spot price differences in an electric network provide the natural measure of the appropriate internodal transport charge. However, the problem of loop flow requires different economic intuition for interpreting the implications of spot pricing. The Direct Current model, which is the usual approximation for estimating spot prices, ignores reactive power effects; this approximation is best when thermal constraints create network congestion. However, when voltage constraints are problematic, the DC Load model is insufficient; a full AC Model is required to determine both real and reactive spot prices. 16 figs., 3 tabs., 22 refs

Scaling of load in communications networks.

Science.gov (United States)

Narayan, Onuttom; Saniee, Iraj

2010-09-01

We show that the load at each node in a preferential attachment network scales as a power of the degree of the node. For a network whose degree distribution is p(k)∼k{-γ} , we show that the load is l(k)∼k{η} with η=γ-1 , implying that the probability distribution for the load is p(l)∼1/l{2} independent of γ . The results are obtained through scaling arguments supported by finite size scaling studies. They contradict earlier claims, but are in agreement with the exact solution for the special case of tree graphs. Results are also presented for real communications networks at the IP layer, using the latest available data. Our analysis of the data shows relatively poor power-law degree distributions as compared to the scaling of the load versus degree. This emphasizes the importance of the load in network analysis.

Analysis of recurrent neural networks for short-term energy load forecasting

Science.gov (United States)

Di Persio, Luca; Honchar, Oleksandr

2017-11-01

Short-term forecasts have recently gained an increasing attention because of the rise of competitive electricity markets. In fact, short-terms forecast of possible future loads turn out to be fundamental to build efficient energy management strategies as well as to avoid energy wastage. Such type of challenges are difficult to tackle both from a theoretical and applied point of view. Latter tasks require sophisticated methods to manage multidimensional time series related to stochastic phenomena which are often highly interconnected. In the present work we first review novel approaches to energy load forecasting based on recurrent neural network, focusing our attention on long/short term memory architectures (LSTMs). Such type of artificial neural networks have been widely applied to problems dealing with sequential data such it happens, e.g., in socio-economics settings, for text recognition purposes, concerning video signals, etc., always showing their effectiveness to model complex temporal data. Moreover, we consider different novel variations of basic LSTMs, such as sequence-to-sequence approach and bidirectional LSTMs, aiming at providing effective models for energy load data. Last but not least, we test all the described algorithms on real energy load data showing not only that deep recurrent networks can be successfully applied to energy load forecasting, but also that this approach can be extended to other problems based on time series prediction.

A sequential Monte Carlo model of the combined GB gas and electricity network

International Nuclear Information System (INIS)

Chaudry, Modassar; Wu, Jianzhong; Jenkins, Nick

2013-01-01

A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties. -- Highlights: •A Monte Carlo model of the combined GB gas and electricity network was developed. •Reliability indices are calculated for the combined GB gas and electricity system. •The efficacy of doubling GB gas storage capacity on reliability of the energy system is assessed. •Integrated reliability indices could be used to assess the impact of investment in energy assets

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

Science.gov (United States)

Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

2010-02-01

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

A control technique for integration of DG units to the electrical networks

DEFF Research Database (Denmark)

Pouresmaeil, Edris; Miguel-Espinar, Carlos; Massot-Campos, Miquel

2013-01-01

This paper deals with a multiobjective control technique for integration of distributed generation (DG) resources to the electrical power network. The proposed strategy provides compensation for active, reactive, and harmonic load current components during connection of DG link to the grid...

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.

Load balancing in integrated optical wireless networks

DEFF Research Database (Denmark)

Yan, Ying; Dittmann, Lars; Wong, S-W.

2010-01-01

In this paper, we tackle the load balancing problem in Integrated Optical Wireless Networks, where cell breathing technique is used to solve congestion by changing the coverage area of a fully loaded cell tower. Our objective is to design a load balancing mechanism which works closely...... with the integrated control scheme so as to maximize overall network throughput in the integrated network architecture. To the best of our knowledge no load balancing mechanisms, especially based on the Multi-Point Control Protocol (MPCP) defined in the IEEE 802.3ah, have been proposed so far. The major research...... issues are outlined and a cost function based optimization model is developed for power management. In particularly, two alternative feedback schemes are proposed to report wireless network status. Simulation results show that our proposed load balancing mechanism improves network performances....

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.

Leveraging Microgrids for Capturing Uncertain Distribution Network Net Load Ramping

OpenAIRE

Majzoobi, Alireza; Khodaei, Amin

2016-01-01

In this paper, a flexibility-oriented microgrid optimal scheduling model is proposed to mitigate distribution network net load variability caused by large penetration distributed solar generation. The distributed solar generation variability, which is caused by increasing adoption of this technology by end-use consumers, is mainly addressed by electric utilities using grid reinforcement. Microgrids, however, provide viable and local solutions to this pressing challenge. The proposed model, wh...

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...

New Operation and Maintenance Contract for Electrical Network

CERN Document Server

Kowalik, G

2001-01-01

The Electrical Exploitation is one of the few remaining operation services at CERN which nearly entirely relies on the CERN staff. Last year CERN policy, in connection with the LHC project needs, have led to the formulation of the strategy of out-sourcing of the Electrical Exploitation activities, market survey and subsequent Invitation to Tender. The following paper presents the approach used in the preparation of the Invitation to Tender and in solving of the out-sourcing issues applied to the operation and maintenance of the CERN electrical network. In particular the problems of the results oriented contract, quality assurance and performance as well requirement of the constantly increasing productivity of the Contractors team are treated. The paper gives also the particularities of the application of the out-sourcing to the electrical operation service as will as techniques used for the estimation of the work load of the activities being outsourced.

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.

Predicting the Response of Electricity Load to Climate Change

Energy Technology Data Exchange (ETDEWEB)

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

2015-07-28

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

Electricity load modelling using computational intelligence

NARCIS (Netherlands)

Ter Borg, R.W.

2005-01-01

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

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

Directory of Open Access Journals (Sweden)

Arlys Michel Lastre Aleaga

2015-09-01

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

Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network

Energy Technology Data Exchange (ETDEWEB)

Liu, Chao; Akintayo, Adedotun; Jiang, Zhanhong; Henze, Gregor P.; Sarkar, Soumik

2018-02-01

Non-intrusive load monitoring (NILM) of electrical demand for the purpose of identifying load components has thus far mostly been studied using univariate data, e.g., using only whole building electricity consumption time series to identify a certain type of end-use such as lighting load. However, using additional variables in the form of multivariate time series data may provide more information in terms of extracting distinguishable features in the context of energy disaggregation. In this work, a novel probabilistic graphical modeling approach, namely the spatiotemporal pattern network (STPN) is proposed for energy disaggregation using multivariate time-series data. The STPN framework is shown to be capable of handling diverse types of multivariate time-series to improve the energy disaggregation performance. The technique outperforms the state of the art factorial hidden Markov models (FHMM) and combinatorial optimization (CO) techniques in multiple real-life test cases. Furthermore, based on two homes' aggregate electric consumption data, a similarity metric is defined for the energy disaggregation of one home using a trained model based on the other home (i.e., out-of-sample case). The proposed similarity metric allows us to enhance scalability via learning supervised models for a few homes and deploying such models to many other similar but unmodeled homes with significantly high disaggregation accuracy.

Failure cascade in interdependent network with traffic loads

International Nuclear Information System (INIS)

Hong, Sheng; Wang, Baoqing; Wang, Jianghui; Zhao, Tingdi; Ma, Xiaomin

2015-01-01

Complex networks have been widely studied recent years, but most researches focus on the single, non-interacting networks. With the development of modern systems, many infrastructure networks are coupled together and therefore should be modeled as interdependent networks. For interdependent networks, failure of nodes in one network may lead to failure of dependent nodes in the other networks. This may happen recursively and lead to a failure cascade. In the real world, different networks carry different traffic loads. Overload and load redistribution may lead to more nodes’ failure. Considering the dependency between the interdependent networks and the traffic load, a small fraction of fault nodes may lead to complete fragmentation of a system. Based on the robust analysis of interdependent networks, we propose a costless defense strategy to suppress the failure cascade. Our findings highlight the need to consider the load and coupling preference when designing robust interdependent networks. And it is necessary to take actions in the early stage of the failure cascade to decrease the losses caused by the large-scale breakdown of infrastructure networks. (paper)

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.

Assessment of the voltage level and losses with photovoltaic and electric vehicle in low voltage network

NARCIS (Netherlands)

Ye, G.; Xiang, Y.; Cobben, J.F.G.

2014-01-01

Livelab from Alliander, a network operator, is a program which started to measure electrical and power quality data in the Dutch distribution network since 2013. A proper probability distribution can be used to model load distribution on feeders. This paper presents a methodology to generate the

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 ...

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.

Load balancing in 5G Networks

Directory of Open Access Journals (Sweden)

Tsirakis Christos

2017-01-01

Full Text Available The expected huge increase of mobile devices and user data demand by 2020 will stress the current mobile network in an unprecedented way. The future mobile networks must meet several strong requirements regarding the data rate, latency, quality of service and experience, mobility, spectrum and energy efficiency. Therefore, efforts for more efficient mobile network solutions have been recently initiated. To this direction, load balancing has attracted much attention as a promising solution for higher resource utilization, improved system performance and decreased operational cost. It is an effective method for balancing the traffic and alleviating the congestion among heterogeneous networks in the upcoming 5G networks. In this paper, we focus on an offloading scenario for load balancing among LTE and Wi-Fi networks. Additionally, network graphs methodology and its abstracted parameters are investigated in order to better manage wireless resource allocation among multiple connections. The COHERENT architectural framework, which consists of two main control components, makes use of such abstracted network graphs for controlling or managing various tasks such as traffic steering, load balancing, spectrum sharing and RAN sharing. As a result, the COHERENT project eventually develops a unified programmable control framework used to efficiently coordinate the underlying heterogeneous mobile networks as a whole.

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.

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.

Neural Network Based Load Frequency Control for Restructuring ...

African Journals Online (AJOL)

Neural Network Based Load Frequency Control for Restructuring Power Industry. ... an artificial neural network (ANN) application of load frequency control (LFC) of a Multi-Area power system by using a neural network controller is presented.

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)

Modelling and designing electric energy networks

International Nuclear Information System (INIS)

Retiere, N.

2003-11-01

The author gives an overview of his research works in the field of electric network modelling. After a brief overview of technological evolutions from the telegraph to the all-electric fly-by-wire aircraft, he reports and describes various works dealing with a simplified modelling of electric systems and with fractal simulation. Then, he outlines the challenges for the design of electric networks, proposes a design process, gives an overview of various design models, methods and tools, and reports an application in the design of electric networks for future jumbo jets

Application of the load flow and random flow models for the analysis of power transmission networks

International Nuclear Information System (INIS)

Zio, Enrico; Piccinelli, Roberta; Delfanti, Maurizio; Olivieri, Valeria; Pozzi, Mauro

2012-01-01

In this paper, the classical load flow model and the random flow model are considered for analyzing the performance of power transmission networks. The analysis concerns both the system performance and the importance of the different system elements; this latter is computed by power flow and random walk betweenness centrality measures. A network system from the literature is analyzed, representing a simple electrical power transmission network. The results obtained highlight the differences between the LF “global approach” to flow dispatch and the RF local approach of randomized node-to-node load transfer. Furthermore, computationally the LF model is less consuming than the RF model but problems of convergence may arise in the LF calculation.

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

Basic Principles of Electrical Network Reliability Optimization in Liberalised Electricity Market

Science.gov (United States)

Oleinikova, I.; Krishans, Z.; Mutule, A.

2008-01-01

The authors propose to select long-term solutions to the reliability problems of electrical networks in the stage of development planning. The guide lines or basic principles of such optimization are: 1) its dynamical nature; 2) development sustainability; 3) integrated solution of the problems of network development and electricity supply reliability; 4) consideration of information uncertainty; 5) concurrent consideration of the network and generation development problems; 6) application of specialized information technologies; 7) definition of requirements for independent electricity producers. In the article, the major aspects of liberalized electricity market, its functions and tasks are reviewed, with emphasis placed on the optimization of electrical network development as a significant component of sustainable management of power systems.

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.

Load Situation Awareness Design for Integration in Multi-Energy System

DEFF Research Database (Denmark)

Cai, Hanmin; You, Shi; Bindner, Henrik W.

2017-01-01

Renewable Energy Sources (RESs) have been penetrating in power system at a staggering pace in recent years. Their intermittent nature is, however, posing great threat to system operation. Recently, active load management has been suggested as a tool to counteract these side effects. In multi......-energy system, thermal load management will benefit not only electric network but also district heating network. Electric heater will be the main focus of this paper as a common thermal load. A situation awareness framework for its integration into electric and district heating network will be proposed...

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.

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

International Nuclear Information System (INIS)

Rostaing, Michel.

1974-01-01

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

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

Short term load forecasting using neuro-fuzzy networks

Energy Technology Data Exchange (ETDEWEB)

Hoffman, M.; Hassan, A. [South Dakota School of Mines and Technology, Rapid City, SD (United States); Martinez, D. [Black Hills Power and Light, Rapid City, SD (United States)

2005-07-01

Details of a neuro-fuzzy network-based short term load forecasting system for power utilities were presented. The fuzzy logic controller was used to fuzzify inputs representing historical temperature and load curves. The fuzzified inputs were then used to develop the fuzzy rules matrix. Output membership function values were determined by evaluating the fuzzified inputs with the fuzzy rules. Output membership function values were used as inputs for the neural network portion of the system. The training process used a back propagation gradient descent algorithm to adjust the weight values of the neural network in order to reduce the error between the neural network output and the desired output. The neural network was then used to predict future load values. Sample data were taken from a local power company's daily load curve to validate the system. A 10 per cent forecast error was introduced in the temperature values to determine the effect on load prediction. Results of the study suggest that the combined use of fuzzy logic and neural networks provide greater accuracy than studies where either approach is used alone. 6 refs., 6 figs.

Energy management of a university campus utilizing short-term load forecasting with an artificial neural network

Science.gov (United States)

Palchak, David

Electrical load forecasting is a tool that has been utilized by distribution designers and operators as a means for resource planning and generation dispatch. The techniques employed in these predictions are proving useful in the growing market of consumer, or end-user, participation in electrical energy consumption. These predictions are based on exogenous variables, such as weather, and time variables, such as day of week and time of day as well as prior energy consumption patterns. The participation of the end-user is a cornerstone of the Smart Grid initiative presented in the Energy Independence and Security Act of 2007, and is being made possible by the emergence of enabling technologies such as advanced metering infrastructure. The optimal application of the data provided by an advanced metering infrastructure is the primary motivation for the work done in this thesis. The methodology for using this data in an energy management scheme that utilizes a short-term load forecast is presented. The objective of this research is to quantify opportunities for a range of energy management and operation cost savings of a university campus through the use of a forecasted daily electrical load profile. The proposed algorithm for short-term load forecasting is optimized for Colorado State University's main campus, and utilizes an artificial neural network that accepts weather and time variables as inputs. The performance of the predicted daily electrical load is evaluated using a number of error measurements that seek to quantify the best application of the forecast. The energy management presented utilizes historical electrical load data from the local service provider to optimize the time of day that electrical loads are being managed. Finally, the utilization of forecasts in the presented energy management scenario is evaluated based on cost and energy savings.

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.

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

African Journals Online (AJOL)

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

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

Science.gov (United States)

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

Global Electricity Trade Network: Structures and Implications

Science.gov (United States)

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S. F.; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions. PMID:27504825

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.

Electricity price forecasting using Enhanced Probability Neural Network

International Nuclear Information System (INIS)

Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang

2010-01-01

This paper proposes a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Probability Neural Network (PNN) and Orthogonal Experimental Design (OED), an Enhanced Probability Neural Network (EPNN) is proposed in the solving process. In this paper, the Locational Marginal Price (LMP), system load and temperature of PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday, and weekend. With the OED to smooth parameters in the EPNN, the forecasting error can be improved during the training process to promote the accuracy and reliability where even the ''spikes'' can be tracked closely. Simulation results show the effectiveness of the proposed EPNN to provide quality information in a price volatile environment. (author)

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

A High Precision Artificial Neural Networks Model for Short-Term Energy Load Forecasting

Directory of Open Access Journals (Sweden)

Ping-Huan Kuo

2018-01-01

Full Text Available One of the most important research topics in smart grid technology is load forecasting, because accuracy of load forecasting highly influences reliability of the smart grid systems. In the past, load forecasting was obtained by traditional analysis techniques such as time series analysis and linear regression. Since the load forecast focuses on aggregated electricity consumption patterns, researchers have recently integrated deep learning approaches with machine learning techniques. In this study, an accurate deep neural network algorithm for short-term load forecasting (STLF is introduced. The forecasting performance of proposed algorithm is compared with performances of five artificial intelligence algorithms that are commonly used in load forecasting. The Mean Absolute Percentage Error (MAPE and Cumulative Variation of Root Mean Square Error (CV-RMSE are used as accuracy evaluation indexes. The experiment results show that MAPE and CV-RMSE of proposed algorithm are 9.77% and 11.66%, respectively, displaying very high forecasting accuracy.

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.

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

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

Directory of Open Access Journals (Sweden)

Yuancheng Li

2016-11-01

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

GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE

Directory of Open Access Journals (Sweden)

Ashish Jain

2012-07-01

Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.

Ad-hoc Network of Smart Sensors for Mechanical Load Measurement

Directory of Open Access Journals (Sweden)

Manuel A. Vieira

2016-07-01

Full Text Available Strain gauges load cells are transducers devices capable of converting changes in applied mechanical load into an electrical analog signal. Those devices have a large spectrum of applications ranging from domestic to industrial or even medical appliances just to name a few. In this work, they are used in the electronic instrumentation of a force platform that will be used to carry out the analysis and characterization of human biomechanical walking. In this platform, four load cells are installed, each one capable of measuring forces along two different axis. A total of eight strain-gauges per load cell are employed. Hence, analog signal transmission, besides requiring a large number of connection wires, is prone to interference and noise. Moreover, with this solution, scalability requires severe changes in the connection topology. In order to circumvent those problems, an alternative in-situ signal conditioning and digital data transmission system was devised. This approach, as far as investigated, presents an innovative solution to signal conditioning and data transmission for load-cells. In particular, the presented solution allows the creation of an ad-hoc network of load cells, using the I²C protocol with a master interface that allows the users to interact and change the parameters of each load cell. This instrumentation structure has been successfully tested and the obtained results are documented in this article.

A morphological investigation of conductive networks in polymers loaded with carbon nanotubes

KAUST Repository

Lubineau, Gilles

2017-01-13

Loading polymers with conductive nanoparticles, such as carbon nanotubes, is a popular approach toward improving their electrical properties. Resultant materials are typically described by the weight or volume fractions of their nanoparticles. Because these conductive particles are only capable of charge transfer over a very short range, most do not interact with the percolated paths nor do they participate to the electrical transfer. Understanding how these particles are arranged is necessary to increase their efficiency. It is of special interest to understand how these particles participate in creating percolated clusters, either in a specific or in all directions, and non-percolated clusters. For this, we present a computational modeling strategy based on a full morphological analysis of a network to systematically analyse conductive networks and show how particles are arranged. This study provides useful information for designing these types of materials and examples suitable for characterizing important features, such as representative volume element, the role of nanotube tortuosity and the role of tunneling cutoff distance.

A morphological investigation of conductive networks in polymers loaded with carbon nanotubes

KAUST Repository

Lubineau, Gilles; Mora Cordova, Angel; Han, Fei; Odeh, I.N.; Yaldiz, R.

2017-01-01

Loading polymers with conductive nanoparticles, such as carbon nanotubes, is a popular approach toward improving their electrical properties. Resultant materials are typically described by the weight or volume fractions of their nanoparticles. Because these conductive particles are only capable of charge transfer over a very short range, most do not interact with the percolated paths nor do they participate to the electrical transfer. Understanding how these particles are arranged is necessary to increase their efficiency. It is of special interest to understand how these particles participate in creating percolated clusters, either in a specific or in all directions, and non-percolated clusters. For this, we present a computational modeling strategy based on a full morphological analysis of a network to systematically analyse conductive networks and show how particles are arranged. This study provides useful information for designing these types of materials and examples suitable for characterizing important features, such as representative volume element, the role of nanotube tortuosity and the role of tunneling cutoff distance.

Electricity networks: how 'natural' is the monopoly?

International Nuclear Information System (INIS)

Kuenneke, Rolf W.

1999-01-01

This article deals with the changing economic characteristics of the electricity network. Traditionally, electricity networks are considered natural monopolies for various kinds of market failures coincide in this essential part of the electricity infrastructure. Technological induced complementarities between nodes and links are causing network externalities, economies of scale, a high degree of mono-functionality, collective good characteristics and an inherent tendency towards concentrated market structures. It is argued that recent technological trends imply a dramatic change of the network economics, leading to possibilities of inter- and intra-network competition, as well as inter fuel competition. The possible implications for the regulatory framework of this sector are addressed. (Author)

Quantum load balancing in ad hoc networks

Science.gov (United States)

Hasanpour, M.; Shariat, S.; Barnaghi, P.; Hoseinitabatabaei, S. A.; Vahid, S.; Tafazolli, R.

2017-06-01

This paper presents a novel approach in targeting load balancing in ad hoc networks utilizing the properties of quantum game theory. This approach benefits from the instantaneous and information-less capability of entangled particles to synchronize the load balancing strategies in ad hoc networks. The quantum load balancing (QLB) algorithm proposed by this work is implemented on top of OLSR as the baseline routing protocol; its performance is analyzed against the baseline OLSR, and considerable gain is reported regarding some of the main QoS metrics such as delay and jitter. Furthermore, it is shown that QLB algorithm supports a solid stability gain in terms of throughput which stands a proof of concept for the load balancing properties of the proposed theory.

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.

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

Electrical network limitations on large-scale deployment of offshore wind energy

Energy Technology Data Exchange (ETDEWEB)

Power, P.B.

2001-07-01

In this report we have summarised the electrical network limitations to the connection of offshore wind energy schemes in the United Kingdom. The offshore wind resource in the United Kingdom could enable energy production in excess of 230 TWh to be realised. The wind resource of the UK coast should enable 4 GW of wind generation (13.4 GWh assuming 30% load factor) to be developed, providing appropriate technical and commercial arrangements can be made. (author)

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-11-15

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

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.

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-23

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.

Operating principle of Soft Open Points for electrical distribution network operation

International Nuclear Information System (INIS)

Cao, Wanyu; Wu, Jianzhong; Jenkins, Nick; Wang, Chengshan; Green, Timothy

2016-01-01

Highlights: • Two control modes were developed for a B2B VSCs based SOP. • The SOP operating principle was investigated under various network conditions. • The performance of the SOP using two control modes was analyzed. - Abstract: Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. Two control modes were developed for the operation of an SOP, using back-to-back voltage-source converters (VSCs). A power flow control mode with current control provides independent control of real and reactive power. A supply restoration mode with a voltage controller enables power supply to isolated loads due to network faults. The operating principle of the back-to-back VSCs based SOP was investigated under both normal and abnormal network operating conditions. Studies on a two-feeder medium-voltage distribution network showed the performance of the SOP under different network-operating conditions: normal, during a fault and post-fault supply restoration. During the change of network operating conditions, a mode switch method based on the phase locked loop controller was used to achieve the transitions between the two control modes. Hard transitions by a direct mode switching were noticed unfavourable, but seamless transitions were obtained by deploying a soft cold load pickup and voltage synchronization process.

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

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.

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.

Modelling renewable energy resource and the electricity network (East Midlands region)

Energy Technology Data Exchange (ETDEWEB)

Newton, P.A.; Ma, T.

2002-07-01

The UK Government's targets for renewable generation and combined heat and power (CHP) are expected to result in a significant growth in embedded generation. This report describes the results of a study of the capability of the electricity distribution network in the East Midlands to accept embedded generation. Detailed network studies were performed for two sample networks: one representing an urban network (Leicester) and one representing a rural network (Boston). The 132 kV networks of the grid groups covering these areas were also studied. This included an examination of the connection points from major 132 kV busbars at grid supply points down to 11 kV primary substations. Power system studies were performed to identify the constraints and capabilities of the existing network, These studies included load flow to examine voltage profile and overloading, fault level analysis and transient studies to examine generator and network stability following faults on the network and voltage step change due to generator tripping. Space network capacity for the region was identified and used to assess the ability to accommodate regional targets for renewables and CHP. The study also examined constraining factors and potential solutions, including four improvement scenarios.

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

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.

Design of digital load torque observer in hybrid electric vehicle

Science.gov (United States)

Sun, Yukun; Zhang, Haoming; Wang, Yinghai

2008-12-01

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

multilevel buck converter for automotive electrical load

African Journals Online (AJOL)

user

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

An aggregated approach to harmonic modelling of loads in power distribution networks

Energy Technology Data Exchange (ETDEWEB)

Moellerstedt, E.

1998-06-01

The use of power electronics have given possibilities for more sophisticated control of power networks. This creates new demands on power network modelling. The models must not only allow for efficient and accurate simulation, but also be suitable for analysis and control design. The Harmonic Norton Equivalent presented in this thesis addresses two problems that are central in control theory, namely model reduction and system identification. It is essential to have simple representations of large systems, and there must be a way to obtain these simple models experimentally, as detailed modelling most often is too complicated. The Harmonic Norton Equivalent has its roots in the method of harmonic balance. It is a frequency domain description of loads in electric networks and describes a linear relation between the current spectrum and the voltage spectrum. The linearization implies that aggregation of loads for model reduction is a straightforward, non-iterative procedure. The models can be obtained through analytical calculations, measurements or time domain simulations. A procedure for experimental estimation of model parameters is presented. The procedure is used to estimate the parameters of a dimmer model from measurements on a real dimmer. The obtained model shows a very good agreement with validation data 24 refs, 24 figs

Neural Network Algorithm for Particle Loading

International Nuclear Information System (INIS)

Lewandowski, J.L.V.

2003-01-01

An artificial neural network algorithm for continuous minimization is developed and applied to the case of numerical particle loading. It is shown that higher-order moments of the probability distribution function can be efficiently renormalized using this technique. A general neural network for the renormalization of an arbitrary number of moments is given

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.

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...

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.

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.

An open data repository for steady state analysis of a 100-node electricity distribution network with moderate connection of renewable energy sources.

Science.gov (United States)

Lazarou, Stavros; Vita, Vasiliki; Ekonomou, Lambros

2018-02-01

The data of this article represent a real electricity distribution network on twenty kilovolts (20 kV) at medium voltage level of the Hellenic electricity distribution system [1]. This network has been chosen as suitable for smart grid analysis. It demonstrates moderate penetration of renewable sources and it has capability in part of time for reverse power flows. It is suitable for studies of load aggregation, storage, demand response. It represents a rural line of fifty-five kilometres (55 km) total length, a typical length for this type. It serves forty-five (45) medium to low voltage transformers and twenty-four (24) connections to photovoltaic plants. The total installed load capacity is twelve mega-volt-ampere (12 MVA), however the maximum observed load is lower. The data are ready to perform load flow simulation on Matpower [2] for the maximum observed load power on the half production for renewables. The simulation results and processed data for creating the source code are also provided on the database available at http://dx.doi.org/10.7910/DVN/1I6MKU.

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...

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.

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.

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 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 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.

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

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

Directory of Open Access Journals (Sweden)

Dragan Tasić

2013-04-01

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

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

Science.gov (United States)

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

2015-01-01

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

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-07-26

In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution system operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.

Combined natural gas and electricity network pricing

Energy Technology Data Exchange (ETDEWEB)

Morais, M.S.; Marangon Lima, J.W. [Universidade Federal de Itajuba, Rua Dr. Daniel de Carvalho, no. 296, Passa Quatro, Minas Gerais, CEP 37460-000 (Brazil)

2007-04-15

The introduction of competition to electricity generation and commercialization has been the main focus of many restructuring experiences around the world. The open access to the transmission network and a fair regulated tariff have been the keystones for the development of the electricity market. Parallel to the electricity industry, the natural gas business has great interaction with the electricity market in terms of fuel consumption and energy conversion. Given that the transmission and distribution monopolistic activities are very similar to the natural gas transportation through pipelines, economic regulation related to the natural gas network should be coherent with the transmission counterpart. This paper shows the application of the main wheeling charge methods, such as MW/gas-mile, invested related asset cost (IRAC) and Aumman-Shapley allocation, to both transmission and gas network. Stead-state equations are developed to adequate the various pricing methods. Some examples clarify the results, in terms of investments for thermal generation plants and end consumers, when combined pricing methods are used for transmission and gas networks. The paper also shows that the synergies between gas and electricity industry should be adequately considered, otherwise wrong economic signals are sent to the market players. (author)

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.

Multidimensional Risk Management for Underground Electricity Networks

Directory of Open Access Journals (Sweden)

Garcez Thalles V.

2014-08-01

Full Text Available In the paper we consider an electricity provider company that makes decision on allocating resources on electric network maintenance. The investments decrease malfunction rate of network nodes. An accidental event (explosion, fire, etc. or a malfunctioning on underground system can have various consequences and in different perspectives, such as deaths and injuries of pedestrians, fires in nearby locations, disturbances in the flow of vehicular traffic, loss to the company image, operating and financial losses, etc. For this reason it is necessary to apply an approach of the risk management that considers the multidimensional view of the consequences. Furthermore an analysis of decision making should consider network dependencies between the nodes of the electricity distribution system. In the paper we propose the use of the simulation to assess the network effects (such as the increase of the probability of other accidental event and the occurrence of blackouts of the dependent nodes in the multidimensional risk assessment in electricity grid. The analyzed effects include node overloading due to malfunction of adjacent nodes and blackouts that take place where there is temporarily no path in the grid between the power plant and a node. The simulation results show that network effects have crucial role for decisions in the network maintenance – outcomes of decisions to repair a particular node in the network can have significant influence on performance of other nodes. However, those dependencies are non-linear. The effects of network connectivity (number of connections between nodes on its multidimensional performance assessment depend heavily on the overloading effect level. The simulation results do not depend on network type structure (random or small world – however simulation outcomes for random networks have shown higher variance compared to small-world networks.

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Wavelet neural network load frequency controller

International Nuclear Information System (INIS)

Hemeida, Ashraf Mohamed

2005-01-01

This paper presents the feasibility of applying a wavelet neural network (WNN) approach for the load frequency controller (LFC) to damp the frequency oscillations of two area power systems due to load disturbances. The present intelligent control system trained the wavelet neural network (WNN) controller on line with adaptive learning rates, which are derived in the sense of a discrete type Lyapunov stability theorem. The present WNN controller is designed individually for each area. The proposed technique is applied successfully for a wide range of operating conditions. The time simulation results indicate its superiority and effectiveness over the conventional approach. The effects of consideration of the governor dead zone on the system performance are studied using the proposed controller and the conventional one

Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation

Directory of Open Access Journals (Sweden)

Jafar Jallad

2018-05-01

Full Text Available In a radial distribution network integrated with distributed generation (DG, frequency and voltage instability could occur due to grid disconnection, which would result in an islanded network. This paper proposes an optimal load shedding scheme to balance the electricity demand and the generated power of DGs. The integration of the Firefly Algorithm and Particle Swarm Optimization (FAPSO is proposed for the application of the planned load shedding and under frequency load shedding (UFLS scheme. In planning mode, the hybrid optimization maximizes the amount of load remaining and improves the voltage profile of load buses within allowable limits. Moreover, the hybrid optimization can be used in UFLS scheme to identify the optimal combination of loads that need to be shed from a network in operation mode. In order to assess the capabilities of the hybrid optimization, the IEEE 33-bus radial distribution system and part of the Malaysian distribution network with different types of DGs were used. The response of the proposed optimization method in planning and operation were compared with other optimization techniques. The simulation results confirmed the effectiveness of the proposed hybrid optimization in planning mode and demonstrated that the proposed UFLS scheme is quick enough to restore the system frequency without overshooting in less execution time.

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.

Software defined network architecture based research on load balancing strategy

Science.gov (United States)

You, Xiaoqian; Wu, Yang

2018-05-01

As a new type network architecture, software defined network has the key idea of separating the control place of the network from the transmission plane, to manage and control the network in a concentrated way; in addition, the network interface is opened on the control layer and the data layer, so as to achieve programmable control of the network. Considering that only the single shortest route is taken into the calculation of traditional network data flow transmission, and congestion and resource consumption caused by excessive load of link circuits are ignored, a link circuit load based flow media business QoS gurantee system is proposed in this article to divide the flow in the network into ordinary data flow and QoS flow. In this way, it supervises the link circuit load with the controller so as to calculate reasonable route rapidly and issue the flow table to the exchanger, to finish rapid data transmission. In addition, it establishes a simulation platform to acquire optimized result through simulation experiment.

Overload cascading failure on complex networks with heterogeneous load redistribution

Science.gov (United States)

Hou, Yueyi; Xing, Xiaoyun; Li, Menghui; Zeng, An; Wang, Yougui

2017-09-01

Many real systems including the Internet, power-grid and financial networks experience rare but large overload cascading failures triggered by small initial shocks. Many models on complex networks have been developed to investigate this phenomenon. Most of these models are based on the load redistribution process and assume that the load on a failed node shifts to nearby nodes in the networks either evenly or according to the load distribution rule before the cascade. Inspired by the fact that real power-grid tends to place the excess load on the nodes with high remaining capacities, we study a heterogeneous load redistribution mechanism in a simplified sandpile model in this paper. We find that weak heterogeneity in load redistribution can effectively mitigate the cascade while strong heterogeneity in load redistribution may even enlarge the size of the final failure. With a parameter θ to control the degree of the redistribution heterogeneity, we identify a rather robust optimal θ∗ = 1. Finally, we find that θ∗ tends to shift to a larger value if the initial sand distribution is homogeneous.

Machine learning based switching model for electricity load forecasting

Energy Technology Data Exchange (ETDEWEB)

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

2008-06-15

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

Machine learning based switching model for electricity load forecasting

Energy Technology Data Exchange (ETDEWEB)

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

2008-06-15

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

Machine learning based switching model for electricity load forecasting

International Nuclear Information System (INIS)

Fan Shu; Chen Luonan; Lee, Weijen

2008-01-01

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

Australia's long-term electricity demand forecasting using deep neural networks

OpenAIRE

Hamedmoghadam, Homayoun; Joorabloo, Nima; Jalili, Mahdi

2018-01-01

Accurate prediction of long-term electricity demand has a significant role in demand side management and electricity network planning and operation. Demand over-estimation results in over-investment in network assets, driving up the electricity prices, while demand under-estimation may lead to under-investment resulting in unreliable and insecure electricity. In this manuscript, we apply deep neural networks to predict Australia's long-term electricity demand. A stacked autoencoder is used in...

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.

Noticing climate change in electricity network design and construction

International Nuclear Information System (INIS)

Syri, S.; Martikeinen, A.; Lehtonen, M.

2007-01-01

The climate change is widely known to cause remarkable effects to electricity network systems on the whole. Some of the changes are good but the most of the changes cause disadvantages to electricity network. Consequence of climate change, blackouts can be long-standing which affect remarkable society and economic life. Most of electricity networks are coming to a renovation phase and the solutions, that are being made nowadays, affect still after decades. Taking account of climate change, now when networks are being developed and planned, it is possible to avoid possible large repair operation and increase reliability of distribution in the future. The aim of this project is to clarify how climate change should be noticed in planning and construction processes. According to the results of this project electricity network companies can be prepared for climate change by developing planning processes and network cost effectively. Also construction processes are being developed but emphasis is on planning process. The results and developed knowledge of VTT research project 'Impacts of climate change on electricity network business' are exploited in this project. In addition, impacts of climate change on cables and transformers are analyzed in collaboration with TKK in the project. (orig.)

Wind integration in self-regulating electric load distributions

Energy Technology Data Exchange (ETDEWEB)

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

2012-12-15

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

Analyzing and Forecasting Electrical Load Consumption in Healthcare Buildings

Directory of Open Access Journals (Sweden)

Rodolfo Gordillo-Orquera

2018-02-01

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

Artificial Neural Networks for SCADA Data based Load Reconstruction (poster)

NARCIS (Netherlands)

Hofemann, C.; Van Bussel, G.J.W.; Veldkamp, H.

2011-01-01

If at least one reference wind turbine is available, which provides sufficient information about the wind turbine loads, the loads acting on the neighbouring wind turbines can be predicted via an artificial neural network (ANN). This research explores the possibilities to apply such a network not

An enhanced radial basis function network for short-term electricity price forecasting

International Nuclear Information System (INIS)

Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang

2010-01-01

This paper proposed a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Radial Basis Function Network (RBFN) and Orthogonal Experimental Design (OED), an Enhanced Radial Basis Function Network (ERBFN) has been proposed for the solving process. The Locational Marginal Price (LMP), system load, transmission flow and temperature of the PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday and weekend. With the OED applied to learning rates in the ERBFN, the forecasting error can be reduced during the training process to improve both accuracy and reliability. This would mean that even the ''spikes'' could be tracked closely. The Back-propagation Neural Network (BPN), Probability Neural Network (PNN), other algorithms, and the proposed ERBFN were all developed and compared to check the performance. Simulation results demonstrated the effectiveness of the proposed ERBFN to provide quality information in a price volatile environment. (author)

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.

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.

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 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.

REDISTRIBUTION OF BASE STATIONS LOAD IN MOBILE COMMUNICATION NETWORKS

Directory of Open Access Journals (Sweden)

Igor Ruban

2017-09-01

Full Text Available The subject matter of the article is the processes of load distribution in mobile communication networks. The object of research is the handover. The goal is to develop a method for redistributing the load between neighboring areas for mobile nodes. The considered base stations are supposed to have the signal-to-noise ratios that are equal or close. The methods that are used: methods of system analysis, methods of digital signal processing. The following results are obtained. The method that allows mobile nodes, whose signal-to-noise ratios are equal or close, to switch to a less loaded base station. This method allows the base station to launch the handover process enabling more even distribution of the load from mobile nodes among neighboring base stations in wireless and mobile networks. In the suggested modification of the method, the function assessing the bandwidth of the uplink channel is added to the base stations, as well a threshold value for using its bandwidth. Thus, when the current value of bandwidth reaches the threshold, the base station starts sending out a message to all mobile nodes and verifies free neighboring areas for switching over mobile nodes. If there are adjacent areas with a lower load, the base station notifies all potential candidates about the necessity of their switching over. The handover process is launched when the available bandwidth of the base station decreases below a certain threshold. Therefore, it is possible to optimize the operation of the WiMAX network with respect to the criterion of the total bandwidth capacity of the base stations. Besides, the results of the comparative analysis of the handover process in networks based on the WiMAX technology that are obtained using the OpNet simulation environment are presented. Conclusions.The suggested approach can be used to improve the basic software of mobile communication networks. When moving a node from one area to another one in access servers, the

Design and Analysis of Electrical Distribution Networks and Balancing Markets in the UK: A New Framework with Applications

Directory of Open Access Journals (Sweden)

Vijayanarasimha Hindupur Pakka

2016-02-01

Full Text Available We present a framework for the design and simulation of electrical distribution systems and short term electricity markets specific to the UK. The modelling comprises packages relating to the technical and economic features of the electrical grid. The first package models the medium/low distribution networks with elements such as transformers, voltage regulators, distributed generators, composite loads, distribution lines and cables. This model forms the basis for elementary analysis such as load flow and short circuit calculations and also enables the investigation of effects of integrating distributed resources, voltage regulation, resource scheduling and the like. The second part of the modelling exercise relates to the UK short term electricity market with specific features such as balancing mechanism and bid-offer strategies. The framework is used for investigating methods of voltage regulation using multiple control technologies, to demonstrate the effects of high penetration of wind power on balancing prices and finally use these prices towards achieving demand response through aggregated prosumers.

Optimized green operation of LTE networks in the presence of multiple electricity providers

KAUST Repository

Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim; Abu-Dayya, Adnan A.

2012-01-01

Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.

Optimized green operation of LTE networks in the presence of multiple electricity providers

KAUST Repository

Ghazzai, Hakim

2012-12-01

Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.

Load forecasting using different architectures of neural networks with the assistance of the MATLAB toolboxes; Previsao de cargas eletricas utilizando diferentes arquiteturas de redes neurais artificiais com o auxilio das toolboxes do MATLAB

Energy Technology Data Exchange (ETDEWEB)

Nose Filho, Kenji; Araujo, Klayton A.M.; Maeda, Jorge L.Y.; Lotufo, Anna Diva P. [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Ilha Solteira, SP (Brazil)], Emails: kenjinose@yahoo.com.br, klayton_ama@hotmail.com, jorge-maeda@hotmail.com, annadiva@dee.feis.unesp.br

2009-07-01

This paper presents a development and implementation of a program to electrical load forecasting with data from a Brazilian electrical company, using four different architectures of neural networks of the MATLAB toolboxes: multilayer backpropagation gradient descendent with momentum, multilayer backpropagation Levenberg-Marquardt, adaptive network based fuzzy inference system and general regression neural network. The program presented a satisfactory performance, guaranteeing very good results. (author)

EMMNet: Sensor Networking for Electricity Meter Monitoring

Directory of Open Access Journals (Sweden)

Zhi-Ting Lin

2010-06-01

Full Text Available Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters.

EMMNet: sensor networking for electricity meter monitoring.

Science.gov (United States)

Lin, Zhi-Ting; Zheng, Jie; Ji, Yu-Sheng; Zhao, Bao-Hua; Qu, Yu-Gui; Huang, Xu-Dong; Jiang, Xiu-Fang

2010-01-01

Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters.

Methods for calculation of undelivered electricity in medium voltage network that is not integrated into the remote control system

Directory of Open Access Journals (Sweden)

Vrcelj Nada

2013-01-01

Full Text Available The method is based on data obtained from the so-called. hand-held measuring current at 10 kV voltage level and from reports of outages at reclosers that are installed in a part of network that is observed. At first, is calculates the electrical load of the main distribution power lines, and then simulates the corresponding power flow and calculates the undelivered electricity. The method was applied to parts of the network PD ED Belgrade that are not in the remote control system and is developed for the purpose of considering the effects of automation in the 10 kV PD ED Belgrade.

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.

Technique applied in electrical power distribution for Satellite Launch Vehicle

Directory of Open Access Journals (Sweden)

João Maurício Rosário

2010-09-01

Full Text Available The Satellite Launch Vehicle electrical network, which is currently being developed in Brazil, is sub-divided for analysis in the following parts: Service Electrical Network, Controlling Electrical Network, Safety Electrical Network and Telemetry Electrical Network. During the pre-launching and launching phases, these electrical networks are associated electrically and mechanically to the structure of the vehicle. In order to succeed in the integration of these electrical networks it is necessary to employ techniques of electrical power distribution, which are proper to Launch Vehicle systems. This work presents the most important techniques to be considered in the characterization of the electrical power supply applied to Launch Vehicle systems. Such techniques are primarily designed to allow the electrical networks, when submitted to the single-phase fault to ground, to be able of keeping the power supply to the loads.

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.

A study of electrical power network of renewable energies and water desalination research center using power quality phenomena and indices

International Nuclear Information System (INIS)

Segayer, Ali Mehemmed

2008-08-01

Renewable energies and water distillation research center (REWDRC) is a very strategic research facility and contains many important and critical industrial and electrical loads that must to be operated as a group to fulfill the requirements and the needs of the center in the operation of the main research facility of the center which a 10 MW reactor. Faults on the electrical or the industrial system can occur on many ways such as a malfunction in the questioned system, power quality related problem, or a failure of any of the loads (such as central ventilation or water circulation system or one of the substations) have a great diverse effect on the operation of the main research facility (reactor). In this research common problems due to power quality phenomena were studied, assessed through a assigning some power quality indices to the electrical network of the center so that the operational condition of the REWDRC electrical and industrial network could be evaluated. power quality indices (PQI) were assigned based on results of real time measurements at the points of common coupling of the network (PCC) and the initial power quality survey report. indices analysis was done using three methods which were the normalization method, method of comparing to the limit value and analysis of measurement data time function profile. As a result of this research a recommendation for safe operation against power quality disturbances was pointed out through a continuous monitoring of assigned power quality indices. (Author)

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)

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

Directory of Open Access Journals (Sweden)

Yang Shuai

2016-01-01

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

LOW-POWER AC LOADS AND ELECTRICAL POWER QUALITY

Directory of Open Access Journals (Sweden)

EPURE S.

2016-12-01

Full Text Available This paper deals with experimental study and numerical simulation of single phase AC low power loads: artificial light sources, personal computers, refrigeration units, air conditioning units and TV receivers. These loads are in such large numbers that represents the main source of disturbances (harmonic current, reactive power and unbalanced three-phase network. The obtained simulation models, verified by comparison with experimental results may be used in larger simulation models for testing and sizing the optimum parameters of active power filters. Models can also be used to study the interactions between grid elements and various loads or situations.

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...

Residential Load Manageability Factor Analyses by Load Sensitivity Affected by Temperature

Directory of Open Access Journals (Sweden)

N. Eskandari

2016-12-01

Full Text Available Load side management is the basic and significant principle to keeping the balance between generation side and consumption side of electrical power energy. Load side management on typical medium voltage feeder is the power energy consumption control of connected loads with variation of essential parameters that loads do reaction to their variation. Knowing amount of load's reaction to each parameters variation in typical medium voltage feeder during the day, leads to gain Load Manageability Factor (LMF for that specific feeder that helps power utilities to manage their connected loads. Calculating this LMF needs to find out each types of load with unique inherent features behavior to each parameters variation. This paper results and future work results will help us to catch mentioned LMF. In this paper analysis of residential load behavior due to temperature variation with training artificial neural network will be done. Load behavior due to other essential parameters variations like energy pricing variation, major event happening, and power utility announcing to the customers, and etc will study in future works. Collecting all related works results in a unit mathematical equation or an artificial neural network will gain LMF.

Improving electrical power systems reliability through locally controlled distributed curtailable load

Science.gov (United States)

Dehbozorgi, Mohammad Reza

2000-10-01

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

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

International Nuclear Information System (INIS)

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

2013-01-01

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

artificial neural network (ann) approach to electrical load

African Journals Online (AJOL)

2004-08-18

Aug 18, 2004 ... self organizing feature map; which is back-propagating in nature. ... distribution scheduling. ... electricity demand with lead times that range from ... become increasingly vital since the rise of the ... implemented for advanced control, data and sensor ... inspired methods of computing are thought to be the.

Load-induced modulation of signal transduction networks.

Science.gov (United States)

Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla

2011-10-11

Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.

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)

LAMAN: Load Adaptable MAC for Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Realp Marc

2005-01-01

Full Text Available In mobile ad hoc radio networks, mechanisms on how to access the radio channel are extremely important in order to improve network efficiency. In this paper, the load adaptable medium access control for ad hoc networks (LAMAN protocol is described. LAMAN is a novel decentralized multipacket MAC protocol designed following a cross-layer approach. Basically, this protocol is a hybrid CDMA-TDMA-based protocol that aims at throughput maximization in multipacket communication environments by efficiently combining contention and conflict-free protocol components. Such combination of components is used to adapt the nodes' access priority to changes on the traffic load while, at the same time, accounting for the multipacket reception (MPR capability of the receivers. A theoretical analysis of the system is developed presenting closed expressions of network throughput and packet delay. By simulations the validity of our analysis is shown and the performances of a LAMAN-based system and an Aloha-CDMA-based one are compared.

Base-Load and Peak Electricity from a Combined Nuclear Heat and Fossil Combined-Cycle Plant

International Nuclear Information System (INIS)

Conklin, Jim; Forsberg, Charles W.

2007-01-01

A combined-cycle power plant is proposed that uses heat from a high-temperature reactor and fossil fuel to meet base-load and peak electrical demands. The high-temperature gas turbine produces shaft power to turn an electric generator. The hot exhaust is then fed to a heat recovery steam generator (HRSG) that provides steam to a steam turbine for added electrical power production. A simplified computational model of the thermal power conversion system was developed in order to parametrically investigate two different steady-state operation conditions: base load nuclear heat only from an Advanced High Temperature Reactor (AHTR), and combined nuclear heat with fossil heat to increase the turbine inlet temperature. These two cases bracket the expected range of power levels, where any intermediate power level can result during electrical load following. The computed results indicate that combined nuclear-fossil systems have the potential to offer both low-cost base-load electricity and lower-cost peak power relative to the existing combination of base-load nuclear plants and separate fossil-fired peak-electricity production units. In addition, electric grid stability, reduced greenhouse gases, and operational flexibility can also result with using the conventional technology presented here for the thermal power conversion system coupled with the AHTR

STRATEGIC RESEARCH AGENDA FOR EUROPE’S ELECTRICITY NETWORKS OF THE FUTURE

DEFF Research Database (Denmark)

Bamberger, Yves; Baptista, João; Botting, Duncan

The first milestone towards the establishment of a common strategy for the development of Europe’s electricity networks was set in April 2006 when the paper ‘Vision and Strategy for Europe’s Electricity Networks of the Future’1 was published. In this Vision, future electricity markets and networks...

Incorporating network effects in a competitive electricity industry. An Australian perspective

International Nuclear Information System (INIS)

Outhred, H.; Kaye, J.

1996-01-01

The role of an electricity network in a competitive electricity industry is reviewed, the nation's experience with transmission pricing is discussed, and a 'Nodal Auction Model' for incorporating network effects in a competitive electricity industry is proposed. The model uses a computer-based auction procedure to address both the spatial issues associated with an electricity network and the temporal issues associated with operation scheduling. The objective is to provide a market framework that addresses both network effects and operation scheduling in a coordinated implementation of spot pricing theory. 12 refs

Network governance in electricity distribution: Public utility or commodity

International Nuclear Information System (INIS)

Kuenneke, Rolf; Fens, Theo

2005-01-01

This paper addresses the question whether the operation and management of electricity distribution networks in a liberalized market environment evolves into a market driven commodity business or might be perceived as a genuine public utility task. A framework is developed to classify and compare different institutional arrangements according to the public utility model and the commodity model. These models are exemplified for the case of the Dutch electricity sector. It appears that the institutional organization of electricity distribution networks is at the crossroads of two very different institutional development paths. They develop towards commercial business if the system characteristics of the electricity sector remain basically unchanged to the traditional situation. If however innovative technological developments allow for a decentralization and decomposition of the electricity system, distribution networks might be operated as public utilities while other energy services are exploited commercially. (Author)

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...

A Morphology Study of Nanofiller Networks in Polymer Nanocomposites: Improving Their Electrical Conductivity through Better Doping Strategies

KAUST Repository

Mora, Angel

2018-02-01

Over the past years, research efforts have focused on adding highly conductive nanoparticles, such as carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs), into polymers to improve their electrical conductivity or to tailor their piezoresistive behavior. Resultant materials are typically described by the weight or volume fractions of their nanoparticles. The weight/volume fraction alone is a very global quantity, making it a poor evaluator of a doping configuration. Knowing which particles actually participate in improving electrical conductivity can optimize the doping strategy. Additionally, conductive particles are only capable of charge transfer over a very short range, thus most of them do not form part of the conduction path. Thus, understanding how these particles are arranged is necessary to increase their efficiency. First, this work focuses on polymers loaded with CNTs. A computational modeling strategy based on a full morphological analysis of the CNT network is presented to systematically analyze conductive networks and show how particles are arranged. A definition of loading efficiency is provided based on the results obtained from this morphology analysis. This study provides useful guidelines for designing these types of materials based on important features, such as representative volume element, nanotube tortuosity and length, tunneling cutoff distance, and efficiency. Second, a computational approach is followed to study the conductive network formed by hybrid particles in polymer nanocomposites. These hybrid particles are synthesized by growing CNTs on the surfaces of GNPs. The objective of this study is to show that the higher electrical conductivity of these composites is due to the hybrids forming a segregated structure. Polymers loaded with hybrid particles have shown a higher electrical conductivity compared with classical carbon fillers: only CNTs, only GNPs or mixed CNTs and GNPs. This is done to understand and compare the doping

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)

Impact evaluation of conducted UWB transients on loads in power-line networks

Science.gov (United States)

Li, Bing; Månsson, Daniel

2017-09-01

Nowadays, faced with the ever-increasing dependence on diverse electronic devices and systems, the proliferation of potential electromagnetic interference (EMI) becomes a critical threat for reliable operation. A typical issue is the electronics working reliably in power-line networks when exposed to electromagnetic environment. In this paper, we consider a conducted ultra-wideband (UWB) disturbance, as an example of intentional electromagnetic interference (IEMI) source, and perform the impact evaluation at the loads in a network. With the aid of fast Fourier transform (FFT), the UWB transient is characterized in the frequency domain. Based on a modified Baum-Liu-Tesche (BLT) method, the EMI received at the loads, with complex impedance, is computed. Through inverse FFT (IFFT), we obtain time-domain responses of the loads. To evaluate the impact on loads, we employ five common, but important quantifiers, i.e., time-domain peak, total signal energy, peak signal power, peak time rate of change and peak time integral of the pulse. Moreover, to perform a comprehensive analysis, we also investigate the effects of the attributes (capacitive, resistive, or inductive) of other loads connected to the network, the rise time and pulse width of the UWB transient, and the lengths of power lines. It is seen that, for the loads distributed in a network, the impact evaluation of IEMI should be based on the characteristics of the IEMI source, and the network features, such as load impedances, layout, and characteristics of cables.

Three-Phase Unbalanced Load Flow Tool for Distribution Networks

DEFF Research Database (Denmark)

Demirok, Erhan; Kjær, Søren Bækhøj; Sera, Dezso

2012-01-01

This work develops a three-phase unbalanced load flow tool tailored for radial distribution networks based on Matlab®. The tool can be used to assess steady-state voltage variations, thermal limits of grid components and power losses in radial MV-LV networks with photovoltaic (PV) generators where...... most of the systems are single phase. New ancillary service such as static reactive power support by PV inverters can be also merged together with the load flow solution tool and thus, the impact of the various reactive power control strategies on the steady-state grid operation can be simply...... investigated. Performance of the load flow solution tool in the sense of resulting bus voltage magnitudes is compared and validated with IEEE 13-bus test feeder....

A COMPARATIVE ANALYSIS OF ENERGY MANAGEMENT STRATEGIES FOR ELECTRIC VEHICLES

OpenAIRE

ÇAKAR, Fahri; YILMAZ, Musa; ASKER, Mehmet Emin

2016-01-01

In next two decade duration the electric car will participate a significant role in auto marketing. The electrical car use electric that is supported by current electrical network. Indeed the current electrical network cannot support the hole system in specific time in the case of loading electric car to it that will increase the demand in that specific time duration. To support the electric car energy requirement you have to manage both energy generation and energy consumption. The solution ...

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.

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.

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...

Dynamic preventive control of electric power systems through load shedding; Controle preventivo dinamico de sistemas de energia eletrica: formulacao atraves do corte de carga

Energy Technology Data Exchange (ETDEWEB)

Righeto, Luzia F.P.; Minussi, Carlos R. [UNESP, Ilha Solteira, SP (Brazil). Dept. de Engenharia Eletrica

1997-12-31

This work presents a model to be used in Electric Power System preventive control, taking into account the dynamic network aspects, the effects caused by great oscillations in the synchronous machines angles (transient stability), electric equipment outages, short-circuit, etc. The energy function will be used as a form of measure the system stability degree using a criterion defined as security margin. The used control action will be the load shedding. (author) 16 refs.; e-mail: minussi at dee.feis.unesp.br

Market tools: the immaterial part of the electricity transmission network

International Nuclear Information System (INIS)

Maillard, Dominique

2014-01-01

The author first evokes the activities of RTE (Reseau de transport d'electricite - the French power transmission network) to improve the performance of its technical and industrial equipment (notably equipment evolution, maintenance policies) with, for example, the installation of a fibre optic network for network control automation, the development of software for a better exploitation and steering of electricity fluxes, notably the electricity produced by wind and photovoltaic power. He more particularly addresses the role of RTE in the construction of the electricity market. He outlines the role of the European electricity market in the economic optimization, the new approaches and tools for a higher flexibility of the electric system, the expertise of RTE, and the perspective of always more smart grids

Will electrical cyber-physical interdependent networks undergo first-order transition under random attacks?

Science.gov (United States)

Ji, Xingpei; Wang, Bo; Liu, Dichen; Dong, Zhaoyang; Chen, Guo; Zhu, Zhenshan; Zhu, Xuedong; Wang, Xunting

2016-10-01

Whether the realistic electrical cyber-physical interdependent networks will undergo first-order transition under random failures still remains a question. To reflect the reality of Chinese electrical cyber-physical system, the "partial one-to-one correspondence" interdependent networks model is proposed and the connectivity vulnerabilities of three realistic electrical cyber-physical interdependent networks are analyzed. The simulation results show that due to the service demands of power system the topologies of power grid and its cyber network are highly inter-similar which can effectively avoid the first-order transition. By comparing the vulnerability curves between electrical cyber-physical interdependent networks and its single-layer network, we find that complex network theory is still useful in the vulnerability analysis of electrical cyber-physical interdependent networks.

Developing electricity distribution networks and their regulation to support sustainable energy

International Nuclear Information System (INIS)

Shaw, Rita; Attree, Mike; Jackson, Tim

2010-01-01

A more sustainable energy system will alter the current patterns of electricity demand and generation. This means technical, commercial and regulatory change for electricity network systems such as distribution networks. This paper traces the links in Great Britain between changes in energy policy since privatisation, changes in the objectives of the electricity regulator and changes in the objectives of the distribution networks and their owners, the distribution network operators (DNOs). The paper identifies tensions in regulatory policy and suggests reforms to the regulatory framework to support a lower-carbon future. DNOs are licensed regional infrastructure providers. In addition to their network services, the network companies can potentially deliver public policy objectives to facilitate heat infrastructure, energy-efficiency and distributed renewables. The paper identifies the potential benefits of a novel approach to facilitating renewable energy feed-in tariffs for electricity and heat, using DNOs.

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

Immune networks: multi-tasking capabilities at medium load

International Nuclear Information System (INIS)

Agliari, E; Annibale, A; Barra, A; Coolen, A C C; Tantari, D

2013-01-01

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ∼ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ∼ N δ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ < 1 the existence of large regions in the phase diagram where the network can retrieve all stored patterns simultaneously. Finally, in the high-load regime δ = 1 we find that the system behaves as a spin-glass, suggesting that finite-connectivity frameworks are required to achieve effective retrieval. (paper)

Impact evaluation of conducted UWB transients on loads in power-line networks

Directory of Open Access Journals (Sweden)

B. Li

2017-09-01

Full Text Available Nowadays, faced with the ever-increasing dependence on diverse electronic devices and systems, the proliferation of potential electromagnetic interference (EMI becomes a critical threat for reliable operation. A typical issue is the electronics working reliably in power-line networks when exposed to electromagnetic environment. In this paper, we consider a conducted ultra-wideband (UWB disturbance, as an example of intentional electromagnetic interference (IEMI source, and perform the impact evaluation at the loads in a network. With the aid of fast Fourier transform (FFT, the UWB transient is characterized in the frequency domain. Based on a modified Baum–Liu–Tesche (BLT method, the EMI received at the loads, with complex impedance, is computed. Through inverse FFT (IFFT, we obtain time-domain responses of the loads. To evaluate the impact on loads, we employ five common, but important quantifiers, i.e., time-domain peak, total signal energy, peak signal power, peak time rate of change and peak time integral of the pulse. Moreover, to perform a comprehensive analysis, we also investigate the effects of the attributes (capacitive, resistive, or inductive of other loads connected to the network, the rise time and pulse width of the UWB transient, and the lengths of power lines. It is seen that, for the loads distributed in a network, the impact evaluation of IEMI should be based on the characteristics of the IEMI source, and the network features, such as load impedances, layout, and characteristics of cables.

Distributed control of deregulated electrical power networks

NARCIS (Netherlands)

Hermans, R.M.

2012-01-01

A prerequisite for reliable operation of electrical power networks is that supply and demand are balanced at all time, as efficient ways for storing large amounts of electrical energy are scarce. Balancing is challenging, however, due to the power system's dimensions and complexity, the low

Failure mitigation in software defined networking employing load type prediction

KAUST Repository

Bouacida, Nader

2017-07-31

The controller is a critical piece of the SDN architecture, where it is considered as the mastermind of SDN networks. Thus, its failure will cause a significant portion of the network to fail. Overload is one of the common causes of failure since the controller is frequently invoked by new flows. Even through SDN controllers are often replicated, the significant recovery time can be an overkill for the availability of the entire network. In order to overcome the problem of the overloaded controller failure in SDN, this paper proposes a novel controller offload solution for failure mitigation based on a prediction module that anticipates the presence of a harmful long-term load. In fact, the long-standing load would eventually overwhelm the controller leading to a possible failure. To predict whether the load in the controller is short-term or long-term load, we used three different classification algorithms: Support Vector Machine, k-Nearest Neighbors, and Naive Bayes. Our evaluation results demonstrate that Support Vector Machine algorithm is applicable for detecting the type of load with an accuracy of 97.93% in a real-time scenario. Besides, our scheme succeeded to offload the controller by switching between the reactive and proactive mode in response to the prediction module output.

Artificial Neural Network Maximum Power Point Tracker for Solar Electric Vehicle

Institute of Scientific and Technical Information of China (English)

Theodore Amissah OCRAN; CAO Junyi; CAO Binggang; SUN Xinghua

2005-01-01

This paper proposes an artificial neural network maximum power point tracker (MPPT) for solar electric vehicles. The MPPT is based on a highly efficient boost converter with insulated gate bipolar transistor (IGBT) power switch. The reference voltage for MPPT is obtained by artificial neural network (ANN) with gradient descent momentum algorithm. The tracking algorithm changes the duty-cycle of the converter so that the PV-module voltage equals the voltage corresponding to the MPPT at any given insolation, temperature, and load conditions. For fast response, the system is implemented using digital signal processor (DSP). The overall system stability is improved by including a proportional-integral-derivative (PID) controller, which is also used to match the reference and battery voltage levels. The controller, based on the information supplied by the ANN, generates the boost converter duty-cycle. The energy obtained is used to charge the lithium ion battery stack for the solar vehicle. The experimental and simulation results show that the proposed scheme is highly efficient.

On electric vehicle battery charger modeling

OpenAIRE

Sainz Sapera, Luis; Mesas García, Juan José; Balcells Sendra, Josep

2011-01-01

The increase of electric vehicle (EV) battery chargers connected to electric networks could lead to future harmonic problems in power systems. These loads are nonlinear devices that inject harmonic currents and pollute network voltages. Thus, battery charger modeling must be studied in detail to determine their harmonic emissions and prevent future problems. This paper investigates EV battery charger behavior, analyzes its equivalent circuit and reports a model for each ...

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

Directory of Open Access Journals (Sweden)

Nenad Floranović

2013-02-01

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

Neural network based photovoltaic electrical forecasting in south Algeria

International Nuclear Information System (INIS)

Hamid Oudjana, S.; Hellal, A.; Hadj Mahammed, I

2014-01-01

Photovoltaic electrical forecasting is significance for the optimal operation and power predication of grid-connected photovoltaic (PV) plants, and it is important task in renewable energy electrical system planning and operating. This paper explores the application of neural networks (NN) to study the design of photovoltaic electrical forecasting systems for one week ahead using weather databases include the global irradiance, and temperature of Ghardaia city (south of Algeria) for one year of 2013 using a data acquisition system. Simulations were run and the results are discussed showing that neural networks Technique is capable to decrease the photovoltaic electrical forecasting error. (author)

Adaptive short-term electricity price forecasting using artificial neural networks in the restructured power markets

International Nuclear Information System (INIS)

Yamin, H.Y.; Shahidehpour, S.M.; Li, Z.

2004-01-01

This paper proposes a comprehensive model for the adaptive short-term electricity price forecasting using Artificial Neural Networks (ANN) in the restructured power markets. The model consists: price simulation, price forecasting, and performance analysis. The factors impacting the electricity price forecasting, including time factors, load factors, reserve factors, and historical price factor are discussed. We adopted ANN and proposed a new definition for the MAPE using the median to study the relationship between these factors and market price as well as the performance of the electricity price forecasting. The reserve factors are included to enhance the performance of the forecasting process. The proposed model handles the price spikes more efficiently due to considering the median instead of the average. The IEEE 118-bus system and California practical system are used to demonstrate the superiority of the proposed model. (author)

Developing electricity distribution networks and their regulation to support sustainable energy

Energy Technology Data Exchange (ETDEWEB)

Shaw, Rita; Attree, Mike [Electricity North West Ltd., 304 Bridgewater Place, Birchwood, Warrington, Cheshire WA3 6XG (United Kingdom); Jackson, Tim [RESOLVE, Centre for Environmental Strategy D3, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

2010-10-15

A more sustainable energy system will alter the current patterns of electricity demand and generation. This means technical, commercial and regulatory change for electricity network systems such as distribution networks. This paper traces the links in Great Britain between changes in energy policy since privatisation, changes in the objectives of the electricity regulator and changes in the objectives of the distribution networks and their owners, the distribution network operators (DNOs). The paper identifies tensions in regulatory policy and suggests reforms to the regulatory framework to support a lower-carbon future. DNOs are licensed regional infrastructure providers. In addition to their network services, the network companies can potentially deliver public policy objectives to facilitate heat infrastructure, energy-efficiency and distributed renewables. The paper identifies the potential benefits of a novel approach to facilitating renewable energy feed-in tariffs for electricity and heat, using DNOs. (author)

Introduction to neural networks with electric power applications

International Nuclear Information System (INIS)

Wildberger, A.M.; Hickok, K.A.

1990-01-01

This is an introduction to the general field of neural networks with emphasis on prospects for their application in the power industry. It is intended to provide enough background information for its audience to begin to follow technical developments in neural networks and to recognize those which might impact on electric power engineering. Beginning with a brief discussion of natural and artificial neurons, the characteristics of neural networks in general and how they learn, neural networks are compared with other modeling tools such as simulation and expert systems in order to provide guidance in selecting appropriate applications. In the power industry, possible applications include plant control, dispatching, and maintenance scheduling. In particular, neural networks are currently being investigated for enhancements to the Thermal Performance Advisor (TPA) which General Physics Corporation (GP) has developed to improve the efficiency of electric power generation

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

Directory of Open Access Journals (Sweden)

Danladi Ali

2018-03-01

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

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.

CDMA coverage under mobile heterogeneous network load

NARCIS (Netherlands)

Saban, D.; van den Berg, Hans Leo; Boucherie, Richardus J.; Endrayanto, A.I.

2002-01-01

We analytically investigate coverage (determined by the uplink) under non-homogeneous and moving traffic load of third generation UMTS mobile networks. In particular, for different call assignment policies, we investigate cell breathing and the movement of the coverage gap occurring between cells

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.

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%.

Recurrent Neural Network For Forecasting Time Series With Long Memory Pattern

Science.gov (United States)

Walid; Alamsyah

2017-04-01

Recurrent Neural Network as one of the hybrid models are often used to predict and estimate the issues related to electricity, can be used to describe the cause of the swelling of electrical load which experienced by PLN. In this research will be developed RNN forecasting procedures at the time series with long memory patterns. Considering the application is the national electrical load which of course has a different trend with the condition of the electrical load in any country. This research produces the algorithm of time series forecasting which has long memory pattern using E-RNN after this referred to the algorithm of integrated fractional recurrent neural networks (FIRNN).The prediction results of long memory time series using models Fractional Integrated Recurrent Neural Network (FIRNN) showed that the model with the selection of data difference in the range of [-1,1] and the model of Fractional Integrated Recurrent Neural Network (FIRNN) (24,6,1) provides the smallest MSE value, which is 0.00149684.

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.

Fibre optical measuring network based on quasi-distributed amplitude sensors for detecting deformation loads

International Nuclear Information System (INIS)

Kul'chin, Yurii N; Kolchinskiy, V A; Kamenev, O T; Petrov, Yu S

2013-01-01

A new design of a sensitive element for a fibre optical sensor of deformation loads is proposed. A distributed fibre optical measuring network, aimed at determining both the load application point and the load mass, has been developed based on these elements. It is shown that neural network methods of data processing make it possible to combine quasi-distributed amplitude sensors of different types into a unified network. The results of the experimental study of a breadboard of a fibre optical measuring network are reported, which demonstrate successful reconstruction of the trajectory of a moving object (load) with a spatial resolution of 8 cm, as well as the load mass in the range of 1 – 10 kg with a sensitivity of 0.043 kg -1 . (laser optics 2012)

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.

Modeling and prediction of Turkey's electricity consumption using Artificial Neural Networks

International Nuclear Information System (INIS)

Kavaklioglu, Kadir; Ozturk, Harun Kemal; Canyurt, Olcay Ersel; Ceylan, Halim

2009-01-01

Artificial Neural Networks are proposed to model and predict electricity consumption of Turkey. Multi layer perceptron with backpropagation training algorithm is used as the neural network topology. Tangent-sigmoid and pure-linear transfer functions are selected in the hidden and output layer processing elements, respectively. These input-output network models are a result of relationships that exist among electricity consumption and several other socioeconomic variables. Electricity consumption is modeled as a function of economic indicators such as population, gross national product, imports and exports. It is also modeled using export-import ratio and time input only. Performance comparison among different models is made based on absolute and percentage mean square error. Electricity consumption of Turkey is predicted until 2027 using data from 1975 to 2006 along with other economic indicators. The results show that electricity consumption can be modeled using Artificial Neural Networks, and the models can be used to predict future electricity consumption. (author)

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

Directory of Open Access Journals (Sweden)

Hong-Juan Li

2013-04-01

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

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 ...

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...

Cascading failures with local load redistribution in interdependent Watts-Strogatz networks

Science.gov (United States)

Hong, Chen; Zhang, Jun; Du, Wen-Bo; Sallan, Jose Maria; Lordan, Oriol

2016-05-01

Cascading failures of loads in isolated networks have been studied extensively over the last decade. Since 2010, such research has extended to interdependent networks. In this paper, we study cascading failures with local load redistribution in interdependent Watts-Strogatz (WS) networks. The effects of rewiring probability and coupling strength on the resilience of interdependent WS networks have been extensively investigated. It has been found that, for small values of the tolerance parameter, interdependent networks are more vulnerable as rewiring probability increases. For larger values of the tolerance parameter, the robustness of interdependent networks firstly decreases and then increases as rewiring probability increases. Coupling strength has a different impact on robustness. For low values of coupling strength, the resilience of interdependent networks decreases with the increment of the coupling strength until it reaches a certain threshold value. For values of coupling strength above this threshold, the opposite effect is observed. Our results are helpful to understand and design resilient interdependent networks.

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).

Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization

Directory of Open Access Journals (Sweden)

Da Xie

2016-06-01

Full Text Available Network-connected combined heat and powers (CHPs, owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs’ overall efficiency and heat to electricity ratio (HTER are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.

Design of pressure-driven microfluidic networks using electric circuit analogy.

Science.gov (United States)

Oh, Kwang W; Lee, Kangsun; Ahn, Byungwook; Furlani, Edward P

2012-02-07

This article reviews the application of electric circuit methods for the analysis of pressure-driven microfluidic networks with an emphasis on concentration- and flow-dependent systems. The application of circuit methods to microfluidics is based on the analogous behaviour of hydraulic and electric circuits with correlations of pressure to voltage, volumetric flow rate to current, and hydraulic to electric resistance. Circuit analysis enables rapid predictions of pressure-driven laminar flow in microchannels and is very useful for designing complex microfluidic networks in advance of fabrication. This article provides a comprehensive overview of the physics of pressure-driven laminar flow, the formal analogy between electric and hydraulic circuits, applications of circuit theory to microfluidic network-based devices, recent development and applications of concentration- and flow-dependent microfluidic networks, and promising future applications. The lab-on-a-chip (LOC) and microfluidics community will gain insightful ideas and practical design strategies for developing unique microfluidic network-based devices to address a broad range of biological, chemical, pharmaceutical, and other scientific and technical challenges.

Modeling and optimization of an electric power distribution network ...

African Journals Online (AJOL)

Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...

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.

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.

An optimization planning technique for Suez Canal Network in Egypt

Energy Technology Data Exchange (ETDEWEB)

Abou El-Ela, A.A.; El-Zeftawy, A.A.; Allam, S.M.; Atta, Gasir M. [Electrical Engineering Dept., Faculty of Eng., Shebin El-Kom (Egypt)

2010-02-15

This paper introduces a proposed optimization technique POT for predicting the peak load demand and planning of transmission line systems. Many of traditional methods have been presented for long-term load forecasting of electrical power systems. But, the results of these methods are approximated. Therefore, the artificial neural network (ANN) technique for long-term peak load forecasting is modified and discussed as a modern technique in long-term load forecasting. The modified technique is applied on the Egyptian electrical network dependent on its historical data to predict the electrical peak load demand forecasting up to year 2017. This technique is compared with extrapolation of trend curves as a traditional method. The POT is applied also to obtain the optimal planning of transmission lines for the 220 kV of Suez Canal Network (SCN) using the ANN technique. The minimization of the transmission network costs are considered as an objective function, while the transmission lines (TL) planning constraints are satisfied. Zafarana site on the Red Sea coast is considered as an optimal site for installing big wind farm (WF) units in Egypt. So, the POT is applied to plan both the peak load and the electrical transmission of SCN with and without considering WF to develop the impact of WF units on the electrical transmission system of Egypt, considering the reliability constraints which were taken as a separate model in the previous techniques. The application on SCN shows the capability and the efficiently of the proposed techniques to obtain the predicting peak load demand and the optimal planning of transmission lines of SCN up to year 2017. (author)

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...

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.

FEATURES OF SELECTION OF CAPACITOR BANKS IN ELECTRIC NETWORKS WITH INTERHARMONIC SOURCES

Directory of Open Access Journals (Sweden)

Yu. L. Sayenko

2017-10-01

Full Text Available Purpose. Development of a methodology for selecting capacitor bank parameters designed to compensate for reactive power, if there are sources of interharmonics in the electrical network. Development of a methodology for selecting the parameters of capacitor banks that are part of resonant filters of higher harmonics and interharmonics. Methodology. For the research, we used the decomposition of the non-sinusoidal voltage (current curve into the sum of the harmonic components with frequencies as multiple of the fundamental frequency - higher harmonics, and not multiple fundamental frequencies - interharmonics. Results. Expressions are obtained for checking the absence of inadmissible overloads of capacitor banks by voltage and current in the presence of voltage (current in the curve, along with higher harmonics, of the discrete spectrum of interharmonics. When selecting capacitor banks, both for reactive power compensation and for filter-compensating devices, the necessity of constructing the frequency characteristics of the input and mutual resistances of the electrical network for analyzing possible resonant phenomena is confirmed. Originality. The expediency of simplified calculation of the voltage variation at the terminals of the banks of the capacitors of the higher harmonics filters and interharmonics due to the presence of the reactor in the filters is substantiated. Practical value. The use of the proposed approaches will make it possible to resolve a number of issues related to the choice of parameters of capacitor banks in networks with nonlinear loads, including: ensuring reliable operation of capacitor banks when their parameters deviate from their nominal values, as well as deviations in the parameters of the supply network and sources of harmonic distortion; ensuring the absence of resonant phenomena at frequencies of both higher harmonics and interharmonics.

Development of Fast-Running Simulation Methodology Using Neural Networks for Load Follow Operation

International Nuclear Information System (INIS)

Seong, Seung-Hwan; Park, Heui-Youn; Kim, Dong-Hoon; Suh, Yong-Suk; Hur, Seop; Koo, In-Soo; Lee, Un-Chul; Jang, Jin-Wook; Shin, Yong-Chul

2002-01-01

A new fast-running analytic model has been developed for analyzing the load follow operation. The new model was based on the neural network theory, which has the capability of modeling the input/output relationships of a nonlinear system. The new model is made up of two error back-propagation neural networks and procedures to calculate core parameters, such as the distributions and density of xenon in a quasi-steady-state core like load follow operation. One neural network is designed to retrieve the axial offset of power distribution, and the other is for reactivity corresponding to a given core condition. The training data sets for learning the neural networks in the new model are generated with a three-dimensional nodal code and, also, the measured data of the first-day test of load follow operation. Using the new model, the simulation results of the 5-day load follow test in a pressurized water reactor show a good agreement between the simulation data and the actual measured data. Required computing time for simulating a load follow operation is comparable to that of a fast-running lumped model. Moreover, the new model does not require additional engineering factors to compensate for the difference between the actual measurements and analysis results because the neural network has the inherent learning capability of neural networks to new situations

Electric Vehicle Integration into Modern Power Networks

DEFF Research Database (Denmark)

software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models......Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

Electric Vehicle Integration into Modern Power Networks

DEFF Research Database (Denmark)

Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

Electrical Properties of an m × n Hammock Network

Science.gov (United States)

Tan, Zhen; Tan, Zhi-Zhong; Zhou, Ling

2018-05-01

Electrical property is an important problem in the field of natural science and physics, which usually involves potential, current and resistance in the electric circuit. We investigate the electrical properties of an arbitrary hammock network, which has not been resolved before, and propose the exact potential formula of an arbitrary m × n hammock network by means of the Recursion-Transform method with current parameters (RT-I) pioneered by one of us [Z. Z. Tan, Phys. Rev. E 91 (2015) 052122], and the branch currents and equivalent resistance of the network are derived naturally. Our key technique is to setting up matrix equations and making matrix transformation, the potential formula derived is a meaningful discovery, which deduces many novel applications. The discovery of potential formula of the hammock network provides new theoretical tools and techniques for related scientific research. Supported by the Natural Science Foundation of Jiangsu Province under Grant No. BK20161278

An Improved Method for Reconfiguring and Optimizing Electrical Active Distribution Network Using Evolutionary Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Nur Faziera Napis

2018-05-01

Full Text Available The presence of optimized distributed generation (DG with suitable distribution network reconfiguration (DNR in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a DG unit at non-optimal size with non-optimal DNR may lead to higher power losses, power quality problem, voltage instability and incremental of operational cost. Thus, an appropriate DG and DNR planning are essential and are considered as an objective of this research. An effective heuristic optimization technique named as improved evolutionary particle swarm optimization (IEPSO is proposed in this research. The objective function is formulated to minimize the total power losses (TPL and to improve the voltage stability index (VSI. The voltage stability index is determined for three load demand levels namely light load, nominal load, and heavy load with proper optimal DNR and DG sizing. The performance of the proposed technique is compared with other optimization techniques, namely particle swarm optimization (PSO and iteration particle swarm optimization (IPSO. Four case studies on IEEE 33-bus and IEEE 69-bus distribution systems have been conducted to validate the effectiveness of the proposed IEPSO. The optimization results show that, the best achievement is done by IEPSO technique with power losses reduction up to 79.26%, and 58.41% improvement in the voltage stability index. Moreover, IEPSO has the fastest computational time for all load conditions as compared to other algorithms.

Insensitivity of proportional fairness in critically loaded bandwidth sharing networks

NARCIS (Netherlands)

Vlasiou, M.; Zhang, J.; Zwart, B.

2014-01-01

Proportional fairness is a popular service allocation mechanism to describe and analyze the performance of data networks at flow level. Recently, several authors have shown that the invariant distribution of such networks admits a product form distribution under critical loading. Assuming

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....

Software defined networks reactive flow programming and load balance switching

OpenAIRE

Καλλιανιώτης, Νικόλαος; Kallianiotis, Nikolaos

2017-01-01

This project serves as a Master Thesis as the requirements of the master’s programme Master of Digital Communications and Networks. It proposes load balancing algorithms applied to Software-Defined Networks to achieve the best possible resource utilisation of each of the links present in a network. The open-sources Opendaylight project and Floodlight project are used as SDN controllers, and the network is emulated using Mininet software

Investigation of Load Sharing in Hybrid (2G/3G) Mobile Networks

OpenAIRE

Martynas Stirbys; Karolis Žvinys

2015-01-01

The main purpose of this work is to investigate load sharing methods for 2G/3G cellular networks in order to determine their impact on the network and users. One of the study aims is to analyze the performance of the methods. Moreover the paper provides an overview of the methods circumstances, limitations. Directed Retry and Load Based Handover methods were chosen. Data was obtained from real Lithuanian mobile operator’s network. The paper also discusses the changes in Key Performance Indica...

Unleashing Flexibility from Electric Boilers and Heat Pumps in Danish Residential Distribution Network

DEFF Research Database (Denmark)

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

2018-01-01

and thereby improving its techno-economic efficiency. The data used for the evaluation are also from the real household sites in Denmark provided by the district heating utility. Focus is on the low-voltage grid, and that’s very relevant since many doesn’t expect any flexibility from that voltage level. Study...... this model is compared to responses from an average model of the hot water storage tank to evaluate the benefit of the more detailed model. Finally, analysis on consumption patterns of electrical and thermal loads in residential buildings in Northern Jutland, Denmark, are used for analysis of the system...... and use of thermal units as flexible consumer loads in the low voltage (LV) distribution network grid. The models of EB and HP with storage tank are briefly discussed in relation to the actual control and flexibility based on grid condition and status of storage tank temperature or position...

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.

Facing a Problem of Electrical Energy Quality in Ship Networks-measurements, Estimation, Control

Institute of Scientific and Technical Information of China (English)

Tomasz Tarasiuk; Janusz Mindykowski; Xiaoyan Xu

2003-01-01

In this paper, electrical energy quality and its indices in ship electric networks are introduced, especially the meaning of electrical energy quality terms in voltage and active and reactive power distribution indices. Then methods of measurement of marine electrical energy indices are introduced in details and a microprocessor measurement-diagnosis system with the function of measurement and control is designed. Afterwards, estimation and control of electrical power quality of marine electrical power networks are introduced. And finally, according to the existing method of measurement and control of electrical power quality in ship power networks, the improvement of relative method is proposed.

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.

NOTICE OF ELECTRICAL CUT - TEST OF THE SECURED NETWORK

CERN Multimedia

Electrical Service ST/EL

2001-01-01

The electrical service ST/EL will test the switching sequence between the secured network and the diesel generators on January 8, 2002. The normal network, general services of the sites Meyrin, Prevessin, SPS, Zone Nord, LHC1 and LHC18 will be cut between 6:00am and 6:10am. The secured network will be resupplied by the diesel generators after approximately 1 minute. The UPS network will not be affected. To facilitate the restart of the electrical network and to minimize the impact of the tests on critical equipment, we would like to ask you to stop any equipment that might suffer major inconveniences during the tests (e.g. computers). For any further information, please do not hesitate to contact the Technical Control Room TCR (72201) or G. Cumer (160592).

Investigation of Load Sharing in Hybrid (2G/3G Mobile Networks

Directory of Open Access Journals (Sweden)

Martynas Stirbys

2015-07-01

Full Text Available The main purpose of this work is to investigate load sharing methods for 2G/3G cellular networks in order to determine their impact on the network and users. One of the study aims is to analyze the performance of the methods. Moreover the paper provides an overview of the methods circumstances, limitations. Directed Retry and Load Based Handover methods were chosen. Data was obtained from real Lithuanian mobile operator’s network. The paper also discusses the changes in Key Performance Indicators.

An optimal power-dispatching system using neural networks for the electrochemical process of zinc depending on varying prices of electricity.

Science.gov (United States)

Yang, Chunhua; Deconinck, G; Gui, Weihua; Li, Yonggang

2002-01-01

Depending on varying prices of electricity, an optimal power-dispatching system (OPDS) is developed to minimize the cost of power consumption in the electrochemical process of zinc (EPZ). Due to the complexity of the EPZ, the main factors influencing the power consumption are determined by qualitative analysis, and a series of conditional experiments is conducted to acquire sufficient data, then two backpropagation neural networks are used to describe these relationships quantitatively. An equivalent Hopfield neural network is constructed to solve the optimization problem where a penalty function is introduced into the network energy function so as to meet the equality constraints, and inequality constraints are removed by alteration of the Sigmoid function. This OPDS was put into service in a smeltery in 1998. The cost of power consumption has decreased significantly, the total electrical energy consumption is reduced, and it is also beneficial to balancing the load of the power grid. The actual results show the effectiveness of the OPDS. This paper introduces a successful industrial application and mainly presents how to utilize neural networks to solve particular problems for the real world.

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....

Day-ahead residential load forecasting with artificial neural network using smart meter data

NARCIS (Netherlands)

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

2013-01-01

Load forecasting is an important operational procedure for the electric industry particularly in a liberalized, deregulated environment. It enables the prediction of utilization of assets, provides input for load/supply balancing and supports optimal energy utilization. Current residential load

Node Load Balance Multi-flow Opportunistic Routing in Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Wang Tao

2014-04-01

Full Text Available Opportunistic routing (OR has been proposed to improve the performance of wireless networks by exploiting the multi-user diversity and broadcast nature of the wireless medium. It involves multiple candidate forwarders to relay packets every hop. The existing OR doesn’t take account of the traffic load and load balance, therefore some nodes may be overloaded while the others may not, leading to network performance decline. In this paper, we focus on opportunities routing selection with node load balance which is described as a convex optimization problem. To solve the problem, by combining primal-dual and sub-gradient methods, a fully distributed Node load balance Multi-flow Opportunistic Routing algorithm (NMOR is proposed. With node load balance constraint, NMOR allocates the flow rate iteratively and the rate allocation decides the candidate forwarder selection of opportunities routing. The simulation results show that NMOR algorithm improves 100 %, 62 % of the aggregative throughput than ETX and EAX, respectively.

Harmonics: Generation and Suppression in AC System Networks ...

African Journals Online (AJOL)

However, reactive power flow in electrical networks has adverse effects depending on their magnitude and the nature of the supply network. How these harmonics are generated by nonlinear loads and the means by which they can be kept low are the focus of this paper. Keywords: non-linear loads, harmonics, reactive ...

Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled Mission Command

Science.gov (United States)

2017-11-22

ARL-TN-0859 ● NOV 2017 US Army Research Laboratory Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled...Applied Knowledge Management to Mitigate Cognitive Load in Network-Enabled Mission Command by John K Hawley Human Research and Engineering...REPORT TYPE Technical Note 3. DATES COVERED (From - To) 1 May 2016–20 April 2017 4. TITLE AND SUBTITLE Applied Knowledge Management to Mitigate

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...

Structural behaviour of concrete poles used in electric's power distribution network

Directory of Open Access Journals (Sweden)

Mehran Zeynalian

2017-12-01

Full Text Available Based on a preliminary study on regional electric companies, it is shown that there is no precise structural design on the concrete poles. This leads to uneconomical and overestimated networks’ components. Therefore, this study was aimed to investigate the lateral performance of the concrete poles which are employed in electric’s power distribution network. This paper presents a numerical study on structural performance of 12 m concrete poles used in electric’s power distribution network using Abaqus software. A sensitivity study for mesh size is carried out and concrete damaged plasticity has been employed. The results show that relatively coarse mesh (average in damaged concrete method gives more reliable result. Some experimental tests based on the Iranian standards were performed in order to make a bench mark for numerical output. Comparison between numerical and experimental results indicates a good agreement between the results. The outcomes also suggest that while the applied lateral load is less than around 400 kg which is assumed as the nominal resistance of the pole, no transverse crack occurs. Based on both experimental and numerical results, one or two transverse cracks are reported when the applied force reaches up to 600 kg. The rate of cracks is amplified by increasing the applied force; and finally, the pole would lose its capacity when the load rises much more than 1200 kg. The study also shows that the poles are very weak when the load direction changes. Also, it can be concluded that the final strength of the pole is higher than what the standards recommend. Finally, seismic behavior factor of the poles around both main axes are evaluated. The estimated seismic resistance factor for the concrete poles indicates that the prescribed R factor for such structure is relatively low; and can be improved at least 20%.

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

International Nuclear Information System (INIS)

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

2004-01-01

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

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

International Nuclear Information System (INIS)

Feuerriegel, Stefan; Neumann, Dirk

2016-01-01

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

Electrical load modeling

Energy Technology Data Exchange (ETDEWEB)

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

1994-12-31

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-05-02

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

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.

Using active power filter to compensate the current component of asymmetrical non-linear load in the four wire network

Directory of Open Access Journals (Sweden)

Руслан Володимирович Власенко

2016-07-01

Full Text Available Electricity quality improving is extremely relevant nowadays. With such industrial loads as induction motors, induction furnaces, welding machines, controlled or uncontrolled rectifiers, frequency converters and others reactive power, harmonics and unbalance are generated in power grid. Reactive power, higher harmonic currents and asymmetry loads influence the functioning of electric devices and electrical mains. An effective technical solution is the use of new compensating devices, that is active power filters. The emergence of consumers with a unit capacity of four wire networks requires a new approach to building system control active power filter. When designing the active power filter control system the current flowing in the neutral wire must be taken into account. To assess the power balance in the four wire active power filter, scientists have proposed to apply pqr theory of power based on the Clarke transformation. There are different topologies of three-phase four wire active power filters. A visual simulation of Matlab / Simulink model with an active power filter based on pqr theory of power has been created. A method of pulse width modulation with four control channels was used as pulses forming systems with transistor keys. Operating conditions of three-phase four wire active power filter with asymmetry, non-sinosoidal voltage source and asymmetric load have been studied. The correction taking into account the means improving the active power filter has been offered as pqr theory of power does not take into account non-sinosoidal voltage

A study on the evolution of crack networks under thermal fatigue loading

International Nuclear Information System (INIS)

Kamaya, Masayuki; Taheri, Said

2008-01-01

The crack network is a typical cracking morphology caused by thermal fatigue loading. It was pointed out that the crack network appeared under relatively small temperature fluctuations and did not grow deeply. In this study, the mechanism of evolution of crack network and its influence on crack growth was examined by numerical calculation. First, the stress field near two interacting cracks was investigated. It was shown that there are stress-concentration and stress-shielding zones around interacting cracks, and that cracks can form a network under the bi-axial stress condition. Secondly, a Monte Carlo simulation was developed in order to simulate the initiation and growth of cracks under thermal fatigue loading and the evolution of the crack network. The local stress field formed by pre-existing cracks was evaluated by the body force method and its role in the initiation and growth of cracks was considered. The simulation could simulate the evolution of the crack network and change in number of cracks observed in the experiments. It was revealed that reduction in the stress intensity factor due to stress feature in the depth direction under high cycle thermal fatigue loading plays an important role in the evolution of the crack network and that mechanical interaction between cracks in the network affects initiation rather than growth of cracks. The crack network appears only when the crack growth in the depth direction is interrupted. It was concluded that the emergence of the crack network is preferable for the structural integrity of cracked components

Human networks in the European electric power industry

International Nuclear Information System (INIS)

Barjot, Dominique; Kurgan-van Hentenryk, Ginette

2004-01-01

Behind electrical systems, we should not forget the human networks. The European case is interesting for that matter. There were major players involved, from the pioneers up to the conceivers of national and international systems. More particularly, the engineers should be considered for their technical as well as organizational performance. Attitudes must also be stressed: in Europe, electricity has constantly been developed with both nationalist and internationalist considerations, as shown by the passage from Unternehmergeschaeft to Bankgeschaeft after 1918. Neither should we forget the role played by institutions in the formation of networks: schools, holdings, cartels, and also those frontier zones formed by small countries like Belgium and Switzerland. The human networks, finally, left long term results such as: interconnection, inter-firm cooperation, technocracy, and the growing intervention of the State

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.

The impact of high PV penetration levels on electrical distribution networks

Energy Technology Data Exchange (ETDEWEB)

Collinson, A; Beddoes, A; Thornycroft, J [Halcrow (United Kingdom); Strbac, G; Jenkins, N [UMIST, Manchester (United Kingdom); Verhoeven, B [KEMA (Netherlands)

2002-07-01

This report describes the results of a collaborative study by EA Technology, UMIST and Halcrow into the effects of large-scale connection of dispersed photovoltaic (PV) power systems on the national electricity supply network. The report is intended to help manufacturers and installers of PV systems and electricity companies to understand the issues associated with grid connection of PV power systems. The increased use of PV systems is expected to have a significant impact on the design, operation and management of electricity supply networks. The study examined three main areas: probability and risk analysis of islanding; PV and network voltage control (including analysis of voltage control in a commercial, domestic retrofit and domestic new build scenarios); and future low voltage network design and operational policies.

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

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)

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.

Short-Term Load Forecasting Model Based on Quantum Elman Neural Networks

Directory of Open Access Journals (Sweden)

Zhisheng Zhang

2016-01-01

Full Text Available Short-term load forecasting model based on quantum Elman neural networks was constructed in this paper. The quantum computation and Elman feedback mechanism were integrated into quantum Elman neural networks. Quantum computation can effectively improve the approximation capability and the information processing ability of the neural networks. Quantum Elman neural networks have not only the feedforward connection but also the feedback connection. The feedback connection between the hidden nodes and the context nodes belongs to the state feedback in the internal system, which has formed specific dynamic memory performance. Phase space reconstruction theory is the theoretical basis of constructing the forecasting model. The training samples are formed by means of K-nearest neighbor approach. Through the example simulation, the testing results show that the model based on quantum Elman neural networks is better than the model based on the quantum feedforward neural network, the model based on the conventional Elman neural network, and the model based on the conventional feedforward neural network. So the proposed model can effectively improve the prediction accuracy. The research in the paper makes a theoretical foundation for the practical engineering application of the short-term load forecasting model based on quantum Elman neural networks.

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.

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.

Virtual CO2 Emission Flows in the Global Electricity Trade Network.

Science.gov (United States)

Qu, Shen; Li, Yun; Liang, Sai; Yuan, Jiahai; Xu, Ming

2018-05-14

Quantifying greenhouse gas emissions due to electricity consumption is crucial for climate mitigation in the electric power sector. Current practices primarily use production-based emission factors to quantify emissions for electricity consumption, assuming production and consumption of electricity take place within the same region. The increasingly intensified cross-border electricity trade complicates the accounting for emissions of electricity consumption. This study employs a network approach to account for the flows in the whole electricity trade network to estimate CO 2 emissions of electricity consumption for 137 major countries/regions in 2014. Results show that in some countries, especially those in Europe and Southern Africa, the impacts of electricity trade on the estimation of emission factors and embodied emissions are significant. The changes made to emission factors by considering intergrid electricity trade can have significant implications for emission accounting and climate mitigation when multiplied by total electricity consumption of the corresponding countries/regions.

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 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.

Information and management system for the secondary electricity distribution network

Energy Technology Data Exchange (ETDEWEB)

Knezevic, M. (Rudnik i Termoelectrana Gacko u Osnivanju (Yugoslavia))

1988-07-01

Emphasizes the importance of a reliable and continuous secondary electrical distribution network for surface coal mine productivity. Interruptions in equipment operation caused by mechanical and electrical failures should be eliminated without delay. Effective communication systems should lead to reliable management and high productivity in mines. It is suggested that mines be divided into four groups according to their sensitivity to supply interruptions, and provided with remotely controlled signalling devices linked to main and auxiliary dispatching stations equipped with micro-computers. Productivity may be increased by some 50-70% and supply costs decreased by some 35% if appropriate electrical distribution systems are used. A sketch of a secondary electrical supply network is attached. 11 refs.

Intelligent harmonic load model based on neural networks

Science.gov (United States)

Ji, Pyeong-Shik; Lee, Dae-Jong; Lee, Jong-Pil; Park, Jae-Won; Lim, Jae-Yoon

2007-12-01

In this study, we developed a RBFNs(Radial Basis Function Networks) based load modeling method with harmonic components. The developed method implemented by using harmonic information as well as fundamental frequency and voltage which are essential input factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. The RBFNs have certain advantage such as simple structure and rapid computation ability compared with multilayer perceptron which is extensively applied for load modeling. To show the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with conventional methods such as polynominal 2nd equation method, MLP and RBF without considering harmonic components.

Immune networks: multi-tasking capabilities at medium load

Science.gov (United States)

Agliari, E.; Annibale, A.; Barra, A.; Coolen, A. C. C.; Tantari, D.

2013-08-01

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ˜ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ˜ Nδ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ frameworks are required to achieve effective retrieval.

Forecasting electricity infeed for distribution system networks : an analysis of the Dutch case

NARCIS (Netherlands)

Tanrisever, F.; Derinkuyu, K.; Heeren, M.

2013-01-01

Estimating and managing electricity distribution losses are the core business competencies of distribution system operators (DSOs). Since electricity demand is a major driver of network losses, it is essential for DSOs to have an accurate estimate of the electricity infeed in their network. In this

THE EVALUATION OF THE EFFECT OF REACTIVE POWER COMPENSATION IN ELECTRIC POWER LOSSES IN ELECTRIC NETWORK OF RAILWAY JUNCTION

OpenAIRE

O. I. Bondar; I. L. Bondar

2009-01-01

In this work the generalized mathematical model of an electrical network of the electrified railway junction is proposed. An estimation of influence of static var compensators installation on electric power losses in a network is executed on the basis of given model.

AC Electric Field Communication for Human-Area Networking

Science.gov (United States)

Kado, Yuichi; Shinagawa, Mitsuru

We have proposed a human-area networking technology that uses the surface of the human body as a data transmission path and uses an AC electric field signal below the resonant frequency of the human body. This technology aims to achieve a “touch and connect” intuitive form of communication by using the electric field signal that propagates along the surface of the human body, while suppressing both the electric field radiating from the human body and mutual interference. To suppress the radiation field, the frequency of the AC signal that excites the transmitter electrode must be lowered, and the sensitivity of the receiver must be raised while reducing transmission power to its minimally required level. We describe how we are developing AC electric field communication technologies to promote the further evolution of a human-area network in support of ubiquitous services, focusing on three main characteristics, enabling-transceiver technique, application-scenario modeling, and communications quality evaluation. Special attention is paid to the relationship between electro-magnetic compatibility evaluation and regulations for extremely low-power radio stations based on Japan's Radio Law.

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.

Deep Constrained Siamese Hash Coding Network and Load-Balanced Locality-Sensitive Hashing for Near Duplicate Image Detection.

Science.gov (United States)

Hu, Weiming; Fan, Yabo; Xing, Junliang; Sun, Liang; Cai, Zhaoquan; Maybank, Stephen

2018-09-01

We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced locality-sensitive hashing (LSH) indexing. We propose a deep constrained siamese hash coding neural network combined with deep feature learning. Our neural network is able to extract effective features for near duplicate image detection. The extracted features are used to construct a LSH-based index. We propose a load-balanced LSH method to produce load-balanced buckets in the hashing process. The load-balanced LSH significantly reduces the query time. Based on the proposed load-balanced LSH, we design an effective and feasible algorithm for near duplicate image detection. Extensive experiments on three benchmark data sets demonstrate the effectiveness of our deep siamese hash encoding network and load-balanced LSH.

Room air conditioner load control under summer comfort constraint

OpenAIRE

Da Silva , David; Brancaccio , M; Duplessis , Bruno; Adnot , J

2010-01-01

International audience; Load control options interest is growing because it can represent a response to future network investments and to congestion problems. In this frame, the present paper gives a methodology to quantify the value of load control for heat pumps (room air conditioners), in small tertiary and residential buildings, considering the occupant's comfort and the electrical grid needs for load shift. This methodology was applied to a small office building where simulations were ma...

Dynamic Load Balanced Clustering using Elitism based Random Immigrant Genetic Approach for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

K. Mohaideen Pitchai

2017-07-01

Full Text Available Wireless Sensor Network (WSN consists of a large number of small sensors with restricted energy. Prolonged network lifespan, scalability, node mobility and load balancing are important needs for several WSN applications. Clustering the sensor nodes is an efficient technique to reach these goals. WSN have the characteristics of topology dynamics because of factors like energy conservation and node movement that leads to Dynamic Load Balanced Clustering Problem (DLBCP. In this paper, Elitism based Random Immigrant Genetic Approach (ERIGA is proposed to solve DLBCP which adapts to topology dynamics. ERIGA uses the dynamic Genetic Algorithm (GA components for solving the DLBCP. The performance of load balanced clustering process is enhanced with the help of this dynamic GA. As a result, the ERIGA achieves to elect suitable cluster heads which balances the network load and increases the lifespan of the network.

Green IGP Link Weights for Energy-efficiency and Load-balancing in IP Backbone Networks

OpenAIRE

Francois, Frederic; Wang, Ning; Moessner, Klaus; Georgoulas, Stylianos; Xu, Ke

2013-01-01

The energy consumption of backbone networks has become a primary concern for network operators and regulators due to the pervasive deployment of wired backbone networks to meet the requirements of bandwidth-hungry applications. While traditional optimization of IGP link weights has been used in IP based load-balancing operations, in this paper we introduce a novel link weight setting algorithm, the Green Load-balancing Algorithm (GLA), which is able to jointly optimize both energy efficiency ...

Electrical localization of weakly electric fish using neural networks

International Nuclear Information System (INIS)

Kiar, Greg; Mamatjan, Yasin; Adler, Andy; Jun, James; Maler, Len

2013-01-01

Weakly Electric Fish (WEF) emit an Electric Organ Discharge (EOD), which travels through the surrounding water and enables WEF to locate nearby objects or to communicate between individuals. Previous tracking of WEF has been conducted using infrared (IR) cameras and subsequent image processing. The limitation of visual tracking is its relatively low frame-rate and lack of reliability when visually obstructed. Thus, there is a need for reliable monitoring of WEF location and behaviour. The objective of this study is to provide an alternative and non-invasive means of tracking WEF in real-time using neural networks (NN). This study was carried out in three stages. First stage was to recreate voltage distributions by simulating the WEF using EIDORS and finite element method (FEM) modelling. Second stage was to validate the model using phantom data acquired from an Electrical Impedance Tomography (EIT) based system, including a phantom fish and tank. In the third stage, the measurement data was acquired using a restrained WEF within a tank. We trained the NN based on the voltage distributions for different locations of the WEF. With networks trained on the acquired data, we tracked new locations of the WEF and observed the movement patterns. The results showed a strong correlation between expected and calculated values of WEF position in one dimension, yielding a high spatial resolution within 1 cm and 10 times higher temporal resolution than IR cameras. Thus, the developed approach could be used as a practical method to non-invasively monitor the WEF in real-time.

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.

A comprehensive approach for computation and implementation of efficient electricity transmission network charges

Energy Technology Data Exchange (ETDEWEB)

Olmos, Luis; Perez-Arriaga, Ignacio J. [Instituto de Investigacion Tecnologica, Universidad Pontificia Comillas, Alberto Aguilera, 23, 28015 Madrid (Spain)

2009-12-15

This paper presents a comprehensive design of electricity transmission charges that are meant to recover regulated network costs. In addition, these charges must be able to meet a set of inter-related objectives. Most importantly, they should encourage potential network users to internalize transmission costs in their location decisions, while interfering as least as possible with the short-term behaviour of the agents in the power system, since this should be left to regulatory instruments in the operation time range. The paper also addresses all those implementation issues that are essential for the sound design of a system of transmission network charges: stability and predictability of the charges; fair and efficient split between generation and demand charges; temporary measures to account for the low loading of most new lines; number and definition of the scenarios to be employed for the calculation and format of the final charges to be adopted: capacity, energy or per customer charges. The application of the proposed method is illustrated with a realistic numerical example that is based on a single scenario of the 2006 winter peak in the Spanish power system. (author)

Private electricity consumption on the rise -- the impact of networking

International Nuclear Information System (INIS)

Aebischer, B.; Huser, A.

2001-01-01

This article discusses the effect of the networking of the various devices to be found in the average home and the trend towards increased electricity consumption that will be brought about by 'intelligent' houses. Different scenarios for the increase in electricity consumption due to the increased use of multimedia systems - from the personal computer and mobile phones to hi-fi systems and the Internet are discussed. The contrasting tendencies noted in this area - such as, for example, the use of electricity to operate systems that are used to optimise and thus reduce electricity consumption in general are also discussed. Also, indirect energy-reduction effects in other areas - such as traffic reduction as a result of tele-working - are examined. Results of simulations and prognoses made concerning future trends for the electricity consumption of the various devices in homes are presented and recommendations are made on how to keep electricity consumption low when networking domestic apparatus

CRISP. Intelligent load shedding. Deliverable 1.5

International Nuclear Information System (INIS)

Gajic, Z.; Karlsson, D.; Ullah, N.R.; Okuboye, S.; Andrieu, C.; Carlsson, P.

2005-08-01

Load shedding has been used to mitigate the consequences of large disturbances in electric power systems, since the beginning of the electrification era. The way to execute the load shedding, i.e. open a circuit breaker, has hardly developed at all for a 100-year period. The modern society dependence on reliable electricity supply is continuously increasing. This means that the consequences of traditional load shedding are not acceptable. In the meantime computer and communication technology has developed tremendously. There is also a trend to use more and more intelligent control and less hardware, such as lines and generators, to provide the required level of reliability for the electric supply. Especially in power systems, and parts of power systems, comprising distributed generation, there seems to be a great potential to improve the overall cost/benefit-ratio for the desired level of reliability, by the use of intelligent load shedding. Intelligent load shedding is a means to improve power system stability, by providing an adapted load control along the distribution network, in situations where the power system otherwise would go unstable. The work with intelligent load shedding in this work package results in various technical principles of dedicated algorithms. These algorithms intend to bring a support tool for the operating system during critical situations. The main aspects are evaluating the right amount and location of power response for a given disturbance, and evaluating the right time response expected in order to comply with an acceptable stability recover. This time response is a main object in order to define appropriate ICT network enabling such a reliable implementation. A main problem of the intelligent load shedding is how to choose load to shed conveniently and quickly. There is a technical problem of finding the right level and location of the load to shed, and also an economical problem of giving incentives in order to have enough remote

Development scheme for the public electricity transport network - 2006-2020

International Nuclear Information System (INIS)

2006-01-01

After having discussed the role of the development scheme and its mains requirements, presented its important components (energy needs, energy transport needs), and described its elaboration mode, this report gives an overview of the present status of the electricity transport network in France: 400.000 volts transport and interconnection networks, 225.000 volts and high voltage networks, development objectives, development context, transport network characteristics in 2006 (country gridding, development dynamics and consumption growth). Then, it presents a set of hypotheses about consumption, production and European exchanges. It identifies different types of constraints (customer connection, supply safety, electric and economic performance, robustness against extreme climate phenomena) and presents a method to assess these constraints (simulation of situations at risk, supply quality analysis, works expertise). The last part present the middle- and long-term constraints for the network

Supply curve bidding of electricity in constrained power networks

Energy Technology Data Exchange (ETDEWEB)

Al-Agtash, Salem Y. [Hijjawi Faculty of Engineering; Yarmouk University; Irbid 21163 (Jordan)

2010-07-15

This paper presents a Supply Curve Bidding (SCB) approach that complies with the notion of the Standard Market Design (SMD) in electricity markets. The approach considers the demand-side option and Locational Marginal Pricing (LMP) clearing. It iteratively alters Supply Function Equilibria (SFE) model solutions, then choosing the best bid based on market-clearing LMP and network conditions. It has been argued that SCB better benefits suppliers compared to fixed quantity-price bids. It provides more flexibility and better opportunity to achieving profitable outcomes over a range of demands. In addition, SCB fits two important criteria: simplifies evaluating electricity derivatives and captures smooth marginal cost characteristics that reflect actual production costs. The simultaneous inclusion of physical unit constraints and transmission security constraints will assure a feasible solution. An IEEE 24-bus system is used to illustrate perturbations of SCB in constrained power networks within the framework of SDM. By searching in the neighborhood of SFE model solutions, suppliers can obtain their best bid offers based on market-clearing LMP and network conditions. In this case, electricity producers can derive their best offering strategy both in the power exchange and the long-term contractual markets within a profitable, yet secure, electricity market. (author)

Supply curve bidding of electricity in constrained power networks

International Nuclear Information System (INIS)

Al-Agtash, Salem Y.

2010-01-01

This paper presents a Supply Curve Bidding (SCB) approach that complies with the notion of the Standard Market Design (SMD) in electricity markets. The approach considers the demand-side option and Locational Marginal Pricing (LMP) clearing. It iteratively alters Supply Function Equilibria (SFE) model solutions, then choosing the best bid based on market-clearing LMP and network conditions. It has been argued that SCB better benefits suppliers compared to fixed quantity-price bids. It provides more flexibility and better opportunity to achieving profitable outcomes over a range of demands. In addition, SCB fits two important criteria: simplifies evaluating electricity derivatives and captures smooth marginal cost characteristics that reflect actual production costs. The simultaneous inclusion of physical unit constraints and transmission security constraints will assure a feasible solution. An IEEE 24-bus system is used to illustrate perturbations of SCB in constrained power networks within the framework of SDM. By searching in the neighborhood of SFE model solutions, suppliers can obtain their best bid offers based on market-clearing LMP and network conditions. In this case, electricity producers can derive their best offering strategy both in the power exchange and the long-term contractual markets within a profitable, yet secure, electricity market. (author)

Load sharing with a local thermal network fed by a microcogenerator: Thermo-economic optimization by means of dynamic simulations

International Nuclear Information System (INIS)

Angrisani, Giovanni; Canelli, Michele; Rosato, Antonio; Roselli, Carlo; Sasso, Maurizio; Sibilio, Sergio

2014-01-01

The cogeneration is the combined production of electric and/or mechanical and thermal energy starting by a single energy source; in particular in this paper the analysis will be focused on a cogeneration system with electric power lower than 15 kW (micro-cogeneration). The paper analyzes a system consisting of a natural gas-fired micro-cogeneration unit (MCHP), a heat storage and a peak boiler. The system provides thermal and electric energy to two end-users, the former is a tertiary building (office), where the generation system is located, and the latter is a residential building connected to the former through a district heating micro-grid. In order to analyze the influence of climatic conditions, two different geographical locations in Italy (Benevento and Milano) are considered, that are also characterized by different natural gas and electricity tariffs. Particular attention is paid to the choice of the users, in order to obtain more stable and continuous electric and thermal loads (load sharing approach) and to increase the operating hours per year of the MCHP unit. The operation of the MCHP is governed by a control system, aimed to optimize a thermo-economic objective function. The models representing the components, the thermo-economic objective function and the buildings have been implemented in a widely used commercial software for building simulations. The models are calibrated and validated through data obtained from experimental tests carried out in the laboratory of the University of Sannio (Benevento). The results of the simulations highlight the potential benefits of the thermal load sharing approach. In particular, this study shows that an MCHP unit connected by means of a thermal micro-grid to different users in “load sharing mode” can obtain a high number of operating hours as well as significant energy (Primary Energy Saving) and environmental (avoided CO 2 equivalent emissions) benefits with respect to an appropriate reference system

ON THE MANAGEMENT OF URBAN ELECTRIC NETWORKS IN THE CONDITIONS OF THE SMART GRID

Directory of Open Access Journals (Sweden)

M. А. Fursanov

2018-01-01

Full Text Available The issues of prospective operation of the city electric networks in the conditions of the MART GRID, which will be quite different as compared to the traditional understanding and approaches, are under consideration. This requires the selection and application of appropriate analytical criteria and approaches to assessment, analysis and control of the networks. With this regard the following criteria are recommended: in a particular case – the optimal (minimal technological electric power consumption (losses, while in general – economically reasonable (minimal cost value of electric power transmission. It should be also borne in mind that contemporary urban networks are actively saturated with distributed sources of small generation that have radically changed the structure of electrical networks; therefore, account for such sources is an absolutely necessary objective of management regimes of urban electric networks, both traditional and in associated with the SMART GRID. A case of the analysis and control of urban electric 10 kV networks with distributed small sources of generation has been developed and presented according to the theoretical criterion of minimum relative active power losses in the circuit as a control case. The conducted research makes it possible to determine the magnitude of the tolerance network mode from the point of the theoretical minimum. 

Pristine transfinite graphs and permissive electrical networks

CERN Document Server

Zemanian, Armen H

2001-01-01

A transfinite graph or electrical network of the first rank is obtained conceptually by connecting conventionally infinite graphs and networks together at their infinite extremities. This process can be repeated to obtain a hierarchy of transfiniteness whose ranks increase through the countable ordinals. This idea, which is of recent origin, has enriched the theories of graphs and networks with radically new constructs and research problems. The book provides a more accessible introduction to the subject that, though sacrificing some generality, captures the essential ideas of transfiniteness for graphs and networks. Thus, for example, some results concerning discrete potentials and random walks on transfinite networks can now be presented more concisely. Conversely, the simplifications enable the development of many new results that were previously unavailable. Topics and features: *A simplified exposition provides an introduction to transfiniteness for graphs and networks.*Various results for conventional g...

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.

Outsourcing services in electricity distribution network industry; Ostopalveluiden kaeyttoe verkkoliiketoiminnassa

Energy Technology Data Exchange (ETDEWEB)

Aminoff, A.; Lappetelaeinen, I. (VTT Technical Research Centre of Finland, Espoo (Finland)); Partanen, J.; Viljainen, S.; Tahvanainen, K. (Lappeenranta Univ. of Technology (Finland)); Jaerventausta, P.; Trygg, P. (Tampere Univ. of Technology (Finland))

2009-02-15

This report examines purchased services in the electricity distribution industry. The report is specially directed to readers working in the industry or otherwise interested in it. This report is a result of a research study that was done in 2008 by VTT, Lappeenranta University of Technology and Tampere University of Technology. The authors are thankful for funders and companies that made this research possible and provided lot of information and knowledge. We appreciate the participants in the steering group as well as the companies and people who answered to questionnaires, gave interviews and took part in GDSSinnovation session. In the business of electricity distribution the usage of purchased services has been increasing during the past years and network companies have focused more on their core business processes. There are a couple of peaks in the number of new purchasing decisions in the middle of the 90s and in the beginning of 2000. The most popular purchased services are network construction and maintenance services. On the other hand, many network planning related activities are still done in-house by the network companies, and are considered their core business. There are some industry specific factors that affect to the decision on whether or not to buy the service outside the company and how to cooperate with the suppliers. For instance, many network companies are owned by municipalities and many service providers are owned by the network companies. The former issue may sometimes bring local politics into the decision-making of the network companies. The latter issue, in turn, has an impact on the relationship between the customer and the supplier, and the infra-organizational issues may sometimes complicate the service purchasing process. Electricity network companies also have natural monopoly positions in their operating areas. To prevent the abuse of monopoly positions, the network companies are subjected to economic regulation. This affects

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.

Electrifying Europe. The power of Europe in the construction of electricity networks

International Nuclear Information System (INIS)

Lagendijk, V.C.

2008-01-01

This book sets out to uncover the origins of the idea of a European electricity network. It explores historically the roots of a transnational European system, showing how engineers came to think in terms of 'Europe' already in the 1920s, and how these ideas continued to influence network-building in later decades. This thinking not only corresponded to economic and technical attributes of the system. This thesis claims that a European system was also legitimised by ideological motives. Covering the period between 1918 and 2001 the book provides a detailed analysis of ideas on, and the building of, a European electricity system. A substantial contribution is made to the much-neglected history of international collaboration in Europe. Prevailing histories of electricity infrastructures the focus is on national developments. Also, the history is placed in the broader historical context of the twentieth century, paying ample attention to the influence of both hot and cold wars, and interwar developments. By combining the specific history of this international collaboration with a more general political and economic history of the twentieth century, the author explains why a European solution emerged. The thesis primarily focuses on Western European developments and explains how this network took its specific shape through the building of different regional powerpools among national systems. In addition, the thesis presents a contribution to the emerging field of transnational history by focusing on the work and activities of international organisations, without neglecting the power and influence of nation-states. The book starts by revealing how an international community of electricity entrepreneurs and electrical engineers had existed since the turn of the century. Yet at the same time, national legislations came to limit the extent of international network development and operation. Whereas the first objections to these limitations were general, they became

Alternative approach to automated management of load flow in engineering networks considering functional reliability

Directory of Open Access Journals (Sweden)

Ирина Александровна Гавриленко

2016-02-01

Full Text Available The approach to automated management of load flow in engineering networks considering functional reliability was proposed in the article. The improvement of the concept of operational and strategic management of load flow in engineering networks was considered. The verbal statement of the problem for thesis research is defined, namely, the problem of development of information technology for exact calculation of the functional reliability of the network, or the risk of short delivery of purpose-oriented product for consumers

Intelligent Electric Power Systems with Active-Adaptive Electric Networks: Challenges for Simulation Tools

Directory of Open Access Journals (Sweden)

Ufa Ruslan A.

2015-01-01

Full Text Available The motivation of the presented research is based on the needs for development of new methods and tools for adequate simulation of intelligent electric power systems with active-adaptive electric networks (IES including Flexible Alternating Current Transmission System (FACTS devices. The key requirements for the simulation were formed. The presented analysis of simulation results of IES confirms the need to use a hybrid modelling approach.

Developing equivalent circuits for radial distribution networks

Energy Technology Data Exchange (ETDEWEB)

Prada, Ricardo; Coelho, Agnelo; Rodrigues, Anselmo [Catholic University of Rio de Janeiro (PUC-Rio), RJ (Brazil). Dept. of Electrical Engineering], Emails: prada@ele.puc-rio.br, agnelo@ele.puc-rio.br, nebulok_99@yahoo.com; Silva, Maria da Guia da [Federal University of Maranhao, Sao Luiz, MA (Brazil). Dept. of Electrical Engineering

2009-07-01

This paper presents a method for evaluating External Equivalent in Electric Distribution Networks (EDN).The proposed method has as its main objectives the reduction of the computational costs in distribution network reconfiguration, investigation of the optimal allocation of banks of capacitors, investigation of the allocation of distributed generation, etc. In these sorts of problems a large number of alternative projects must be assessed in order to identify the optimal solution. The optimal solution comes up with the voltage level in the load points within specified limits. Consequently, the EDN must retain the external network load points but without major increasing in the dimension of the equivalent circuit. The proposed method has been tested and validated in a substation of the Electricity Utility of Maranhao - CEMAR, in Brazil. (author)

Smart control for minimizing distribution network reinforcement cost due to electrification

International Nuclear Information System (INIS)

Pudjianto, Danny; Djapic, Predrag; Aunedi, Marko; Gan, Chin Kim; Strbac, Goran; Huang, Sikai; Infield, David

2013-01-01

Electrification of transport fleets and heating sectors is seen as one of the key strategies to further reduce the use of fossil fuels and the resulting greenhouse gas emissions. However, it will potentially cause a significant increase of electricity peak demand and have adverse consequences on the electricity system, in particular on distribution networks. This paper will address the benefits of various applications of smart network control and demand response technologies for enhancing the integration of these future load categories, and for improvements in operation management and efficient use of distribution network assets. A range of numerical simulations have been carried out on different distribution network topologies (rural and urban networks) to identify the need and the cost of network reinforcement required to accommodate future load under various operating strategies such as Business as Usual (passive demand and passive network) against the smart grid approach. Applications of smart Plug-in vehicle (PiV) charging, smart heat pumps, and optimised control of network voltage regulators to reduce network investment have been studied, and selected key results of our studies on evaluating the benefits of implementing these technologies for Great Britain's distribution networks are presented and discussed in this paper. - Highlights: ► Growth of electricity loads driven by electrification of transport and heat will be significant. ► It will increase the electricity peak demand up to 2–3 times and cost tens of billion pounds if we maintain Business as Usual approach. ► A coordinated application of smart demand technologies can significantly reduce this cost. ► It requires sets of policies and regulations to facilitate timely deployment of such technologies.

Bosch automotive electrics and automotive electronics systems and components, networking and hybrid drive

CERN Document Server

2014-01-01

The significance of electrical and electronic systems has increased considerably in the last few years and this trend is set to continue. The characteristics feature of innovative systems is the fact that they can work together in a network. This requires powerful bus systems that the electronic control units can use to exchange information. Networking and the various bus systems used in motor vehicles are the prominent new topic in the 5th edition of the "Automotive Electric, Automotive Electronics" technical manual. The existing chapters have also been updated, so that this new edition brings the reader up to date on the subjects of electrical and electronic systems in the motor vehicle. Content Electrical and electronical systems – Basic principles of networking - Examples of networked vehicles – Bus systems – Architecture of electronic systems – Mechatronics – Elektronics – Electronic control Units – Software – Sensors – Actuators – Hybrid drives – Vehicle electrical system – Start...

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.

A network flow model for load balancing in circuit-switched multicomputers

Science.gov (United States)

Bokhari, Shahid H.

1990-01-01

In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.

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

Directory of Open Access Journals (Sweden)

Tae Hyun Yoo

2014-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-02-01

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

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

Directory of Open Access Journals (Sweden)

A. M. Afanasov

2014-12-01

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

Integration of available regenerative energy sources in community networks for both electricity and heating

Energy Technology Data Exchange (ETDEWEB)

Alcalde Melo, Henrique

2013-03-06

. Water can be heated up to 70 C at least once a week preventing the bacterium Legionella to grow. The community is able to supply 99% of the uncontrollable load group demand and 97% of the controllable load group demand. There is enough energy available to heat space during the cold months, if heat pumps with a coefficient of performance greater than two are used. The electric vehicles can be charged using the energy generated in the community via grid or extra battery banks. If energy prices continue to increase, German households will try to find solutions to reduce their energy bills. The integration of several households forming a community network is a solution that optimizes the energy use and space (especially taking wind turbines in consideration), and reduces investments. However, the implementation of such a community still depends on the availability of space, improvement and price reduction of energy storage systems, regulations for energy exchange as well as willingness of the people living in such a community to adapt their daily routine according to the availability of energy.

Integration of available regenerative energy sources in community networks for both electricity and heating

Energy Technology Data Exchange (ETDEWEB)

Alcalde Melo, Henrique

2013-03-06

heated up to 70 C at least once a week preventing the bacterium Legionella to grow. The community is able to supply 99% of the uncontrollable load group demand and 97% of the controllable load group demand. There is enough energy available to heat space during the cold months, if heat pumps with a coefficient of performance greater than two are used. The electric vehicles can be charged using the energy generated in the community via grid or extra battery banks. If energy prices continue to increase, German households will try to find solutions to reduce their energy bills. The integration of several households forming a community network is a solution that optimizes the energy use and space (especially taking wind turbines in consideration), and reduces investments. However, the implementation of such a community still depends on the availability of space, improvement and price reduction of energy storage systems, regulations for energy exchange as well as willingness of the people living in such a community to adapt their daily routine according to the availability of energy.

Information report on electricity distribution network security and financing

International Nuclear Information System (INIS)

2011-01-01

This report first outlines the degradation of electricity quality, and identifies the lack of investment as the main reason of the network weakness. It notices that the French network is much extended, and that the medium and low voltage networks need to be secured, and outlines that some legal measures have already been implemented to correct these problems. In its second part, the report comments the network manager's point of view, and denies his critics of the conceding authorities. It also discusses the network manager's investments, and finally formulates six propositions for a better future of the distribution network

Regulatory Improvements for Effective Integration of Distributed Generation into Electricity Distribution Networks

International Nuclear Information System (INIS)

Scheepers, M.J.J.; Jansen, J.C.; De Joode, J.; Bauknecht, D.; Gomez, T.; Pudjianto, D.; Strbac, G.; Ropenus, S.

2007-11-01

The growth of distributed electricity supply of renewable energy sources (RES-E) and combined heat and power (CHP) - so called distributed generation (DG) - can cause technical problems for electricity distribution networks. These integration problems can be overcome by reinforcing the network. Many European Member States apply network regulation that does not account for the impact of DG growth on the network costs. Passing on network integration costs to the DG-operator who is responsible for these extra costs may result in discrimination between different DG plants and between DG and large power generation. Therefore, in many regulatory systems distribution system operators (DSOs) are not being compensated for the DG integration costs. The DG-GRID project analysed technical and economical barriers for integration of distributed generation into electricity distribution networks. The project looked into the impact of a high DG deployment on the electricity distribution system costs and the impact on the financial position of the DSO. Several ways for improving network regulation in order to compensate DSOs for the increasing DG penetration were identified and tested. The DG-GRID project looked also into stimulating network innovations through economic regulation. The project was co-financed by the European Commission and carried out by nine European universities and research institutes. This report summarises the project results and is based on a number of DG-GRID reports that describe the conducted analyses and their results

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.

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.

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)

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

Directory of Open Access Journals (Sweden)

Mohamed Saad

2015-08-01

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

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.

Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

OpenAIRE

Chassin, David P.; Posse, Christian

2004-01-01

The reliability of electric transmission systems is examined using a scale-free model of network structure and failure propagation. The topologies of the North American eastern and western electric networks are analyzed to estimate their reliability based on the Barabasi-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using s...

A methodology for extracting knowledge rules from artificial neural networks applied to forecast demand for electric power; Uma metodologia para extracao de regras de conhecimento a partir de redes neurais artificiais aplicadas para previsao de demanda por energia eletrica

Energy Technology Data Exchange (ETDEWEB)

Steinmetz, Tarcisio; Souza, Glauber; Ferreira, Sandro; Santos, Jose V. Canto dos; Valiati, Joao [Universidade do Vale do Rio dos Sinos (PIPCA/UNISINOS), Sao Leopoldo, RS (Brazil). Programa de Pos-Graduacao em Computacao Aplicada], Emails: trsteinmetz@unisinos.br, gsouza@unisinos.br, sferreira, jvcanto@unisinos.br, jfvaliati@unisinos.br

2009-07-01

We present a methodology for the extraction of rules from Artificial Neural Networks (ANN) trained to forecast the electric load demand. The rules have the ability to express the knowledge regarding the behavior of load demand acquired by the ANN during the training process. The rules are presented to the user in an easy to read format, such as IF premise THEN consequence. Where premise relates to the input data submitted to the ANN (mapped as fuzzy sets), and consequence appears as a linear equation describing the output to be presented by the ANN, should the premise part holds true. Experimentation demonstrates the method's capacity for acquiring and presenting high quality rules from neural networks trained to forecast electric load demand for several amounts of time in the future. (author)

From electric networks to 'Smart grids'

International Nuclear Information System (INIS)

Hadjsaid, Nourredine; Sabonnadiere, Jean-Claude

2015-12-01

After decades of slow evolutions, and because of the emergence of renewable energies and of a multiplication of actors due to the liberalisation of energy markets, electric networks are entering a phase of large and complex development which will lead to a massive introduction of intelligence and to the building up of the 'smart grid' concept. The authors first identify the characteristics of the new energetic paradigm. The present operation of electric grids is based on four components: production by means of high power units installed in strategic locations, transport to consumption centres by means of a highly instrumented transport network which has highly centralised and hierarchical management, and consumers who are passive actors. They comment the implications of recent development for these three components. They describe how information and communication technologies (ICT) are used at the service of the grid, and how new technologies are integrated in different instruments (smart counter, actuators, fast cut devices, sensors, advanced supervision and control functions). Then they discuss the definition of a smart network or smart grid, the objectives it allows to be reached for energy transport as well as energy distribution. They discuss the desirable evolution of distribution networks and their technical objectives. Then, they give an overview of the various involved actors (consumers, network managers, electric equipment manufacturers, energy producers, and so on), evokes bodies and institutions involved in research on smart grids (notably in Grenoble within the INPG), give some examples of innovative concepts which are now being developed (intelligence distribution, virtual central station, grid monitoring, re-configurable grid, smart building). They also identify scientific and technological deadlocks, and outline the challenge of preparing the needed abilities for the development of smart grids

Comparison and Evaluation of the Performance of Various Types of Neural Networks for Planning Issues Related to Optimal Management of Charging and Discharging Electric Cars in Intelligent Power Grids

Directory of Open Access Journals (Sweden)

Arash Moradzaeh

2018-01-01

Full Text Available The use of electric vehicles in addition to reducing environmental concerns can play a significant role in reducing the peak and filling the characteristic valleys of the daily network load. In other words, in the context of smart grids, it is possible to improve the battery of electric vehicles by scheduling charging and discharging processes. In this research, the issue of controlling the charge and discharge of electric vehicles was evaluated using a variety of neural models, until the by examining the effect of the growth rate of the penetration level of electric vehicles of the hybrid type that can be connected to the distribution network, the results of the charge management and discharge model of the proposed response are examined. The results indicate that due to increased penetration of these cars is increased the amount of responses to charge and discharge management. In this research, a variety of neural network methods, a neural network method using Multilayer Perceptron Training (MLP, b neural network method using Jordan Education (RNN, c neural network method using training (RBF Was evaluated based on parameters such as reduction of training error, reduction of network testing error, duration of run and number of replications for each one. The final results indicate that electric vehicles can be used as scattered power plants, and can be useful for regulating the frequency and regulation of network voltages and the supply of peak traffic. This also reduces peak charges and incidental costs, which ultimately helps to further network stability. Finally, the charge and discharge management response reflects the fact that intelligent network-based models have the ability to manage the charge and discharge of electric vehicles, and among the models the amount of error reduction training and testing is very favourable for both RNN, MLP.

Control strategies for power distribution networks with electric vehicles integration

DEFF Research Database (Denmark)

Hu, Junjie

of electrical energy. A smart grid can also be dened as an electricity network that can intelligently integrate the actions of all users connected to it - generators, consumers and those that do both - in order to eciently deliver sustainable, economic and secure electricity supplies. This thesis focuses...... of the ii market. To build a complete solution for integration of EVs into the distribution network, a price coordinated hierarchical scheduling system is proposed which can well characterize the involved actors in the smart grid. With this system, we demonstrate that it is possible to schedule the charging......Demand side resources, like electric vehicles (EVs), can become integral parts of a smart grids because instead of just consuming power they are capable of providing valuable services to power systems. EVs can be used to balance the intermittent renewable energy resources such as wind and solar...

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

Identifying options for regulating the coordination of network investments with investments in distributed electricity generation

International Nuclear Information System (INIS)

Nisten, E.

2010-02-01

The increase in the distributed generation of electricity, with wind turbines and solar panels, necessitates investments in the distribution network. The current tariff regulation in the Dutch electricity industry, with its ex post evaluation of the efficiency of investments and the frontier shift in the x-factor, delays these investments. In the unbundled electricity industry, the investments in the network need to be coordinated with those in the distributed generation of electricity to enable the DSOs to build enough network capacity. The current Dutch regulations do not provide for a sufficient information exchange between the generators and the system operators to coordinate the investments. This paper analyses these two effects of the Dutch regulation, and suggests improvements to the regulation of the network connection and transportation tariffs to allow for sufficient network capacity and coordination between the investments in the network and in the generation of electricity. These improvements include locally differentiated tariffs that increase with an increasing concentration of distributed generators.

Network investments and the integration of distributed generation: Regulatory recommendations for the Dutch electricity industry

International Nuclear Information System (INIS)

Niesten, Eva

2010-01-01

An increase in the distributed generation of electricity necessitates investments in the distribution network. The current tariff regulation in the Dutch electricity industry, with its ex post evaluation of the efficiency of investments, average benchmarking and a frontier shift in the x-factor, delays these investments. In the unbundled electricity industry, the investments in the network need to be coordinated with those in the distributed generation of electricity to enable the system operators to build enough network capacity. The current Dutch regulations do not provide for a sufficient information exchange between the generators and the system operators to coordinate the investments. This paper analyses these two effects of the Dutch regulations, and suggests improvements to the regulation of the network connection and transportation tariffs to allow for sufficient network capacity and coordination between the investments in the network and in the generation of electricity. These improvements include locally differentiated tariffs that increase with an increasing concentration of distributed generation.

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...

Application of Artificial Neural Networks in the Heart Electrical Axis Position Conclusion Modeling

Science.gov (United States)

Bakanovskaya, L. N.

2016-08-01

The article touches upon building of a heart electrical axis position conclusion model using an artificial neural network. The input signals of the neural network are the values of deflections Q, R and S; and the output signal is the value of the heart electrical axis position. Training of the network is carried out by the error propagation method. The test results allow concluding that the created neural network makes a conclusion with a high degree of accuracy.

PLATON: Peer-to-Peer load adjusting tree overlay networks

NARCIS (Netherlands)

Lymberopoulos, L.; Pittaras, C.; Grammatikou, M.; Papavassiliou, S.; Maglaris, V.

2011-01-01

Peer-to-Peer systems supporting multi attribute and range queries use a number of techniques to partition the multi dimensional data space among participating peers. Load-balancing of data accross peer partitions is necessary in order to avoid the presence of network hotspots which may cause

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

Visible technologies, invisible organisations: An empirical study of public beliefs about electricity supply networks

International Nuclear Information System (INIS)

Devine-Wright, Patrick; Devine-Wright, Hannah; Sherry-Brennan, Fionnguala

2010-01-01

Reducing carbon emissions in the energy system poses significant challenges to electricity transmission and distribution networks. Whilst these challenges are as much social as economic or technical, to date few research studies have investigated public beliefs about electricity supply networks. This research aimed to address this gap by means of a nationally representative study of UK adults (n=1041), probing beliefs about how electricity reaches the home, responsibility for electricity supply, associations with the words 'National Grid', as well as beliefs about the planning of new infrastructure. Findings suggest that electricity networks are represented predominantly in terms of technologies rather than organisations, specifically in terms of familiar, visible components such as cables or wires, rather than more systemic concepts such as networks. Transmission and distribution network operators were largely invisible to members of the public. In terms of planning new lines, most respondents assumed that government ministers were involved in decision-making, while local residents were widely perceived to have little influence; moreover, there was strong public support for placing new power lines underground, regardless of the cost. In conclusion, organisational invisibility, coupled with low expectations of participatory involvement, could provoke public opposition and delay siting new network infrastructure.

Towards building a neural network model for predicting pile static load test curves

Directory of Open Access Journals (Sweden)

Alzo’ubi A. K.

2018-01-01

Full Text Available In the United Arab Emirates, Continuous Flight Auger piles are the most widely used type of deep foundation. To test the pile behaviour, the Static Load Test is routinely conducted in the field by increasing the dead load while monitoring the displacement. Although the test is reliable, it is expensive to conduct. This test is usually conducted in the UAE to verify the pile capacity and displacement as the load increase and decreases in two cycles. In this paper we will utilize the Artificial Neural Network approach to build a model that can predict a complete Static Load Pile test. We will show that by integrating the pile configuration, soil properties, and ground water table in one artificial neural network model, the Static Load Test can be predicted with confidence. We believe that based on this approach, the model is able to predict the entire pile load test from start to end. The suggested approach is an excellent tool to reduce the cost associated with such expensive tests or to predict pile’s performance ahead of the actual test.

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

SYNCHRONIZATION OF NATIONAL GRID NETWORK WITH THE ELECTRICITY SHIPS NETWORK IN THE "SHORE TO SHIP" SYSTEM

Directory of Open Access Journals (Sweden)

Dariusz TARNAPOWICZ

2013-07-01

Full Text Available ‘Shore to ship’ system – ships’ power supply from the local electrical substations – is one of the effective ways to limit the negative impact of the ships lying in ports on the environment. Energy infrastructure of the port installation necessary to provide ships with power supply has to be designed so that different types of ships can use it. The important issue concerning ‘shore to ship’ system is the quality of power supply. This can be achieved via sustaining continuity of power supply while switching from the ships’ electrical network over to the national grid. In this article the author presents the way of synchronizing the national grid with the ships’ electrical network during ship’s lying in port. Such synchronization would allow for uninterruptible work of the ship’s electrical devices.

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.

Simulation platform for direct load control of household appliances. Literature survey and G2 implementation

Energy Technology Data Exchange (ETDEWEB)

Kolm, J; Vlaheli, A

1996-10-01

There is an incentive for the power utilities to look for other ways than building new power stations to satisfy increasing customer power needs. One way to fulfill this demand is by redistributing the available electric power between the different power consumers. This method can successfully be used during high peak hours. The utility is also able to make financial profits selling the redistributed electric power at a higher price to customers with temporary high power demands. Direct Load Control - DLC, a Demand Side Management - DSM tool, is one way to achieve a redistribution of electric power. This masters thesis project consisted in developing a user-friendly simulation platform for domestic appliances combined with an electric power control system to be employed for Direct Load Control. The platform contains the necessary facilities for designing an electrical distribution network model and is implemented in G2, an object-oriented real-time environment. The final application provides an on-line instrument for the utility to control the power consumption over the entire system in terms of dispensing power in an electrical network. The report consists of two main parts. The first part describes a literature survey we systematically compiled to gather literature sources. The second part outlines our design and implementation of the G2 simulation platform for a water-heater model with a Direct Load Control system. The entire simulation platform is designed to allow a flexible change and improvement of the different models. Consequently, our software is a powerful tool for studying a wide range of problems related to a Load Management program involving electrical household loads. 9 refs, 32 figs

Load flow analysis for variable speed offshore wind farms

DEFF Research Database (Denmark)

Chen, Zhe; Zhao, Menghua; Blaabjerg, Frede

2009-01-01

factors such as the different wind farm configurations, the control of wind turbines and the power losses of pulse width modulation converters are considered. The DC/DC converter model is proposed and integrated into load flow algorithm by modifying the Jacobian matrix. Two iterative methods are proposed...... and integrated into the load flow algorithm: one takes into account the control strategy of converters and the other considers the power losses of converters. In addition, different types of variable speed wind turbine systems with different control methods are investigated. Finally, the method is demonstrated......A serial AC-DC integrated load flow algorithm for variable speed offshore wind farms is proposed. It divides the electrical system of a wind farm into several local networks, and different load flow methods are used for these local networks sequentially. This method is fast, more accurate, and many...

Traffic Load on Interconnection Lines of Generalized Double Ring Network Structures

DEFF Research Database (Denmark)

Pedersen, Jens Myrup; Riaz, Muhammad Tahir; Madsen, Ole Brun

2004-01-01

Generalized Double Ring (N2R) network structures possess a number of good properties, but being not planar they are hard to physically embed in communication networks. However, if some of the lines, the interconnection lines, are implemented by wireless technologies, the remaining structure...... consists of two planar rings, which are easily embedded by fiber or other wired solutions. It is shown that for large N2R structures, the interconnection lines carry notably lower loads than the other lines if shortest-path routing is used, and the effects of two other routing schemes are explored, leading...... to lower load on interconnection lines at the price of larger efficient average distance and diameter....

Short-term electricity prices forecasting in a competitive market: A neural network approach

International Nuclear Information System (INIS)

Catalao, J.P.S.; Mariano, S.J.P.S.; Mendes, V.M.F.; Ferreira, L.A.F.M.

2007-01-01

This paper proposes a neural network approach for forecasting short-term electricity prices. Almost until the end of last century, electricity supply was considered a public service and any price forecasting which was undertaken tended to be over the longer term, concerning future fuel prices and technical improvements. Nowadays, short-term forecasts have become increasingly important since the rise of the competitive electricity markets. In this new competitive framework, short-term price forecasting is required by producers and consumers to derive their bidding strategies to the electricity market. Accurate forecasting tools are essential for producers to maximize their profits, avowing profit losses over the misjudgement of future price movements, and for consumers to maximize their utilities. A three-layered feedforward neural network, trained by the Levenberg-Marquardt algorithm, is used for forecasting next-week electricity prices. We evaluate the accuracy of the price forecasting attained with the proposed neural network approach, reporting the results from the electricity markets of mainland Spain and California. (author)