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Research in residential electricity characteristics and short-term load forecasting
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第一作者: Feng HX(冯海霞);Wang ZF(王忠锋);Ge WC(葛维春);Wang YN(王英男)
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发表年度: 2013
期: 12
卷: 11
页: 7021-7026
摘要: In this paper we make research in Residential short-term load forecasting. Different application scenes have different affecting factors of short-term load, so we should specifically analysis of factors that affect the load of the residential electricity. We use SPSS (Statistic Package for Social Science) to figure out the relationship between the daily load and temperature, weather conditions and other factors, finding the main factors among the impacting factors, and analyzing residential electricity consumption habits and load characteristics. Then, the paper introduces the common prediction methods. Combining with the above analysis to choose short-term load forecasting methods for residential users, we create automatic linear regression model and artificial neural network model to predict the future electricity load, calculating the residual between the predicted values and the actual values and mean square deviation of the values, and evaluating the accuracy of the load forecasting. The results prove that automatic linear regression model is effective in residential short-term electricity load forecasting.
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刊物名称: Telkomnika
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