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《Proceedings of the CSU-EPSA》 2014-10
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Characteristic Analysis and Forecasting Method for Daily Peak Load

MA Li-xin;LI Yuan;School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology;  
Dispatch and marketing departments of electric power put great emphasis on trend and forecasting method of power load data. In practical applications,the electricity market raises new requirement for forecasting the daily peak load in continuous multi-days ahead of time. In this paper,according to the history data of daily peak load,the characteristics of holiday and non-holiday daily peak load are investigated respectively. For the forecasting of holiday daily peak load,a holiday factor is added;for the non-holidays,the period characteristic of daily peak load is obtained through the wavelet decomposition. And then,the forecasting is respectively carried out by establishing BP neural network model. Simulation results show that this method is feasible and effective,which can meet the industry requirement for prediction accuracy and has a strong theoretical significance and wide application prospects.
【Fund】: 国家科技部政府间科技合作项目(2009014);; 上海市创新基金项目(jwcxsl1302)
【CateGory Index】: TM73
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