论文信息 - Mid-Term Load Forecasting Based on Grey Neural Network Corrector Model

Mid-Term Load Forecasting Based on Grey Neural Network Corrector Model

A novel grey neural network corrector model is presented in this paper, because mid-term load forecasting is affected by many factors and has large research space. This method combines BP neural network with 3 kinds of grey models, and selects influential factors by grey related analysis method, and then adds the equal dimension and new information technology. The validity of the novel model can be tested by utilizing actual data of a certain area. Comparing with 3 kinds of grey models, the novel model can improve the accuracy of load forecasting results. Experimental results prove that this method is feasible and effective to mid-term load forecasting.

Chao Yang | Yunliang Wang

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