DAILY OPTIMAL OPERATION OF CASCADE HYDROELECTRIC POWER STATIONSBASED ON ARTIFICIAL NEURAL NETWORK
Zhu Min. Wang Dingyi (Huazhong University of Science and Technology, 430074, Wuhan, China)
This paper presents a new approach based on artificial neural network (ANN) to solve daily optimal operationproblems of cascade hydroelectric power stations in power systems. The new approach can be used not only for the dailyoptimal generation scheduling, but also for the real--time control of cascade hydroelectric power stations. In order to speed upthe convergence of ANN. an analytical technique is used in which the complicated networks are divided into several simpleones. Simulation results show that the presented method is effective.
【CateGory Index】： TV737