Research On The Decision Support System Of The Hydropower Plant Optimization Dispatching

Optimal dispatching system of hydropower plant is a complex project. Now there is not a systemic, perfect and ripe scheme to solve it.It must take the market mechanism's infection into account so as to embody the price influence. The system have the important significance to research it that can improve the reliability and stability index of electric network. Furthermore, it can optimize the use of energy resources, exploit the electric power market in all sides and improve the benefits. The paper proposes the whole structure and the relation among the modules of the decision support system of the hydropower plant optimization dispatching. The important modules are analyzed in separate, which are the forecasting system, the optimum dispatching operation of hydropower plant system and the maintenance scheduling system under the electricity market environment . The paper researches the questions of GeZhouBa hydroelectric plant from the two sides of economy and reliability . The integrated practical resolvent is putted forward as analytic results of economical dispatching operation and maintenance scheduling of plant. According to the mathematical models and calculation methods by this paper proposed ,which are based on dynamic programming algorithm and genetic algorithm, the software of optimum operation of GeZhouBa hydropower plant and the maintenance scheduling are complied. The economic operation of the plants are calculated and the results are compared that indicate the method is efficient for economic operation of GeZhouBa hydropower plant, and moreover, the results are the basis of practical economical operation in the future. The real-time balancing bidding transaction is an indispensable transaction form in electricity market and it has distinguishing features . The bidding strategy of power generation companies in the bidding process becomes the hot spot in the research of electricity market. Forecasting the market clearing price is the basis of decision making for each participant in electricity market. Under the electricity market environment ,the order of generation companies is the largest profit and profits of generation companies depend, to a large extent, on bidding strategies employed. The paper researches the decision support system for price bidding of joint-stock unit in the hydropower plant and introduces its modules characteristics in different points in detail, such as the thought of design and the arithmetic and its functional characteristics. The system is used for reference of the bidding strategy of unit in the hydropower plant. Furthermore, this paper presents the price prediction model based on radial basic function neural networks and wavelet transform. The model is not only better than the tradition technical analysis method but also is avoiding the defects which relapse into the partial smallest point and convergence rate is little of back-propagation algorithm. The simulation results of the experiment show that model efficient to forecast the trend of market clearing price.