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This work presents a two-stage model for the data analysis of electricity consumption. The first stage divides the consumption in two parts: weather- and illumination-related, and residual consumption, where weather-related consumption refers to heating, ventilation, and air conditioning (HVAC). Given the hourly total consumption, we obtain the hourly weather-related and illumination-related electricity...
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....
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...
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 researches on a generating scheduling model which is based on the supply function and aims to maximize the social surplus. It's divided into two situations to conduct a study. One studies the electricity transmission scheduling model without the consideration of transmission constraints and presents the model algorithm, and then we can get the unified clearing market prices, the electricity...
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...
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.
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...
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