A Basic Study Of Power Behavior In Strategy Bidding

As the global trend of the power market is coming ,the price of the power in the market is becoming more and more important element in the whole market.Market cleaaring price is the uniform price reflecting short-term supply-demand relationship of electric commodities in the electric power market.It contacts customers,market supervisors and individual energy enterprises.It has economic relations with supply side and demand side.Accordingly,forecast of market clearing price is significant for participators in power market.One of the most solution is to forecast the price by means of ANN .In this paper,Back-Propagation Network is used to forecast the price of the electricity .A short-term price forecasting model based on the background of California in America is established by artificial neural network .The model is a network with 3 layers .The data of California electricity market is apply to train and forecast the electricity data .The results illustrate that the model is effective .Based on the analysis of transmission cost and forecast of market clearing price,the well-known genetic algorithm is presented for developing risk-constrained bidding strategies for grid companies participating in an electricity in which step-wise bidding functions and pay-as-bid settlement protocols are utilized.The calculation results of practical examples and the experience of on-site application show that using this method reliable support to the reasonable bidding strategy can be provided for grid companie.