Research On Optimum Regulation Of Hydropower Station Based On Price Forecast Under The Condition Of Power Market

The marketization of power industry is a development trend of the current power industry in the world and a focus of the international electric scientific research and project practice. Electricity price is not only a signal of the electric market supply-demand relationship, but also an economic lever of controlling electric marketing, therefore, the theory of electricity price is a key subject for the current electric market research. So exactly forecast the price is not only related to the benefit of the every Market corpus, but also is the base to the macro view adjusts and control for the government, to conform the stabilization of the power system and to keep the development of power industry. As the progress of the electric power market in our country quickly, carry out power plant optimum regulation in the market environment not only relate to the power plant performance in the future but also an important problem to its existences. This paper has done more thorough research in view of this question.Firstly, the main methods of more mature price forecasting and present status are presented. Then the price data of power market in California are applied to neural network to forecast the price of the next day, which gives a favorable result.Secondly, the characteristics of gray system are analyzed. The price data in Sichuan Province and California are calculated in GM(1,1) model to forecast the future price. Moreover, the improved GM(1,1) model combined with the GM(1,1) residual model is implemented to the above system. The result indicates the forecast precision is high.At the end, reservoir optimum regulation model under condition of electric power market are established. Based on it, the paper founds mathematical model of pinnacle-valley price. Using Yaoheba reservoirs, the paper gained the solution to the most generate-electricity income of one day by Genetic Algorithms. Getting across calculation of the examples, the correctness and validity of models are validated. By the using of the models, we may succeed to resolve the running game under condition of electric power market, it is the most concerned to operate of reservoir.