Application of improved multistage optimization method for optimal reservoirs operation of cascade hydropower stations

Stochastic Dynamic Programming (SDP) is a basic method for optimal operation of reservoirs. However, when the SDP is applied to the optimal operation of multi-reservoirs system with multi-annual regulating reservoirs, the problems of 'curse of dimensionality' will be aroused and the characteristic of uncertain regulated cycles can't be showed. Aiming at these problems, a multistage optimization method of SDP with an improved genetic algorithms and simulated annealing algorithms (IGA-SA) is presented in this paper. This method decompounds the optimal reservoirs problems of cascade hydropower stations into the first stage optimization of SDP and the second stage optimization of IGA-SA. The optimal operation results of cascade reservoirs are then obtained. The application of the long-middle term optimal reservoirs operation of cascade hydropower stations on Wujiang River demonstrates that the model operates very well, and is capable of overcoming the 'curse of dimensionality' problem, it provides an effective tool and method for optimal operation problems of multi-reservoirs system.