Model of price forecasting based on blind number and artificial neural networks

The paper utilizes blind number theory with classical price forecasting ways to forecast electrical price accurately which is based on limited historical electrical prices, loads and other related data. It proposes model of market clearing price forecasting which is based on blind number and artificial neural networks. This model uses BP neural networks to train and learn from historical data. After getting weights of networks, networks use blind number instead of real number to forecast price. The results of examples show that the model can eliminate the influence of uncertain factors to forecasting result, as well as historical prices are all in the believable inter zone which has the biggest belief of forecasting results. The model completes the forecasting mission well which proves the feasibility of design and reliability of model.