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A preliminary Investigation on Short-term Load Prediction of Extra-large Power Grid using Artifical Neural Network Method

Meng Xiansheng Yu Mingzheng (Shanghai Institute of Electric Power Shanghai 200090) Wu han Guo Jiatian (East China Electric Power Dispatching Bureau Shanghai 200002)  
Factors influencing the extra large power network are very complicated,and variation of load is of a non steady stochastic process.The paper presents the study and application of Artifical Neural Network (ANN) in the filed of short term load forecasting of extralarge power network.The BP(Back Propagation)based on the ANN with methods of variable step,momentum parameter,non uniform weights and semi stochastic initial solutions,which cause a rapid converge of iteration,minimization of predicating error and enhancemant of studying precision.The target error is used as the ending condition of network iteration,The load of different seasons and periods are forecasted with the matrix of models of forecasting points. A satisfactory results of short term load predication has been obtained.
【CateGory Index】: TP18
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