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《Power System Technology》 2001-12
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SHI De\|ming, LI Lin\|chuan, SONG Jian\|wen (Tianjin University, Tianjin 300072, China)  
Load is the foundation of power system operation and planning. Accurate load forecasting is advantageous to improving the reliability and economic effect of power system. Based on the combination of grey forecast and artificial neural network a new method for power system load forecasting is put forward. In the grey forecasting, after differently accepting or rejecting historical data and through accumulation and generation, different models are established, then the different results of grey forecasting are combined by artificial neural network. For artificial neural network, its inputs are the forecasting results of different Grey Models and its output is the result of combination forecasting. The learning samples select n known values which are most close to the forecasted values and the learning method is modified BP algorithm. The presented method synthesizes the advantages of GM forecasting method, which is simple and needs less original data, and neural network which possesses the characteristics of nonlinear fitting, therefore the forecasting accuracy is improved. Calculation examples show that the presented method is feasible and effective.
【CateGory Index】: TM714;TP183
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