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This paper reports findings from a study of electrical load profiles obtained from a survey of a representative cross section of approximately 4,000 Irish dwellings. Electricity demand was recorded at half-hourly intervals for each dwelling over a six month period from 1st July 2009 to 31st December 2009. Descriptive statistics are shown for each electrical parameter such as mean, maximum demand,...
Time-of-use (TOU) tariff is an important means toad just the residential electricity consumption behavior and reduce the difference between the peak and valley load. This paper sets up a residential electricity consumption inclination model by extracting data from the Huainan Electricity Sales & Marketing Database including three typical users electricity consumption. The mathematic model contains...
This paper focus on two types of the industry class high-voltage consumer, to investigate various kind of electricity fees which includes demand charge, energy charge, power factor charge and penalty charge, and correlation among them according to the monthly electricity fee calculation structure in the past. Using the simulation of Fuzzy theory analysis and the Optimal Learning of Genetic Algorithm...
This paper describes a novel methodology for regulating electricity demand peaks for home appliances. To achieve this objective, we will make use of the reversible fair scheduling algorithm originally developed for telecommunication networks. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power consumption threshold...
The network model bases upon the energy hub concept, which was developed by the Vision of Future Energy Networks” (VoFEN) research group at ETH Zurich in the last years. Keynote of the concept is a combined optimization of different energy carrier. Synergetic effects are expected to give unusual optimization results, when allowing any possible energy conversion inside a specific area that constitute...
An essential element of electric utility resource planning is the long term forecast of the electricity consumption. This paper presents an approach to forecast annual electricity consumption by using artificial neural network based on historical data for Malaysia. It involves developing several ANN designs and selecting the best network that can produce the best results in terms of its accuracy....
Jiangsu province, the eastern coastal province with rapid economic development and high demand for electricity, power prediction seems very important. In this paper, we start from the current situation of electric power needs in Jiangsu province, a large number of historical data in Jiangsu province are taken as analytical basis, and gray model is used to forecast electricity consumption in Jiangsu...
Nowadays, many researches are made to estimate some of socio-economic variables in which methods such as regression, time series (ARIMA, AR and etc.), Artificial Neural Networks (ANN) and so on are used. In this paper integrated System Approach and ANN are applied for estimating affects of subsidy on electricity consumption and social welfare. Actual electricity price is estimated by ANN, which has...
Cloud providers, like Amazon, offer their data centers' computational and storage capacities for lease to paying customers. High electricity consumption, associated with running a data center, not only reflects on its carbon footprint, but also increases the costs of running the data center itself. This paper addresses the problem of maximizing the revenues of Cloud providers by trimming down their...
Electricity industry is one of the main foundations of each country. Electricity demand growth in developing countries is at its peak so that these countries play an important role in electricity consumption. Since this energy can't be stored in large quantity, forecasting consuming load is a major concern in using electricity energy. This paper has formulated electrify consumption for residential...
Accurate electricity demand forecasting is the foundation of power system operation and planning, the basic of placing development plans, business strategy and tactics of the power companies. Electricity consumption is a gray system which is impacted by economic development, industrial structure, income levels and national policies. The paper counted Inner Mongolia electricity data from four factors,...
This paper studies the impact of climate change on the electricity consumption by means of a fuzzy regression approach. The climate factors which have been considered in this paper are humidity and temperature, whereas the simultaneous effect of these two climate factors is considered. The impacts of other climate variables, like the wind, with a minor effect on energy consumption are ignored. The...
This paper attempts to investigate the relationship between power plant investment, electricity production and economic growth in China, and forecasts at least 5 years, using modern econometrics techniques and software for the period 1980-2009. The paper applies unit root test, Johansen cointegration test and vector error correction model for the past 30 years data, which include GDP, power industry...
This paper presents a residential energy and power conservation system that utilizes an optimization model and user side controller. The aim of this paper is to enforce a reduction in the users' current level of consumption and yet minimize any discomfort as the result. An energy usage optimization model is the foundation of this work. It computes a set of directives for a specific user based on the...
This document presents the new model of distributed consumers of electricity powering - named power modes. There is presented a conceptual model of an IT hierarchical distributed system for data acquisition and evidence the state of the controlled distributed object - the electric energy consumption. The authors will try to show that the proposed model of the IT system is accurate to solve the problem...
In the paper, we investigate the vector error correction model considering co-feature. The identification procedure and algorithms are overviewed briefly in line with (Hecq. A., 2004). Then a simple case study for electricity consumption and economic growth in China is given for model comparison. It is found that model considering co-feature can potentially improve the model estimation efficiency.
With the development of power markets, forecasting is becoming more and more important in such new competitive markets since the electricity demand forecasting is the basis of decision making for participants in electricity market. The aim of this project is to develop an electricity demand predictor. In this paper, we present an Grey-based prediction algorithm to forecast a long-term electric power...
Indices factors decomposition method is used to decompose the factors affecting electricity consumption into four effects: structure effect, quantity effect, intensity effect, structure effect of power consumption. It is considered that the structure effect and the quantity effect are the critical factors to affect the total indices of electricity consumption. Further more, total indices of electricity...
To improve the forecasting precision of electricity consumption, and content the demand of marketing, we establish the model by combining particle swarm optimization (PSO) with the improved grey theory. The method is simple, easy to do practice and its convergence rate is quick. It can find the overall optimal solution of problems in great probability, and can effectively overcome the shortage of...
This paper analyzes the main factors impacting electricity intensity (namely power consumption per unit GDP) in China first, which include power price, gross domestic product and the proportion of industry in whole economy. Then the relationships between power price and electricity intensity was studied based on Granger-causality and cointegration tests. The result indicates that there exists Granger...
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