摘要
Dynamic programming(DP) is an effective and powerful mathematical tool to solve reservoir operation optimization(ROO) problems because it can yield global optimal solutions. But with the increase of the reservoirs’ number, DP will face problems like long computation time, large calculation scale, which is called ‘curse of dimensionality’. Heuristic random search algorithms and improved DP algorithms can decrease the computation time but they can only get near-optimal solutions. By analyzing the principle of DP in ROO, this paper finds that DP involves complex iterative computation and repeated procedures, which is very time-consuming. Aiming at solving these problems, this paper proposes a new notion called Hydropower Station Output Function (HSOF) and uses it to optimize and improve traditional DP, which can reduce the iterative computation and repeated procedures then improve computational efficiency. This paper takes Yayangshan hydroelectric power station in Li Xianjiang River Basin and the cascade hydropower station consisting of Yayangshan and Shimenkan hydropower stations as examples for single reservoir optimal operation (SROO) and cascade reservoir operation optimization (CROO). By comparing with the operation result of traditional DP and the progressive optimality algorithm (POA), case presents that the improved DP based on HSOF can reduce the programming complexity of DP, thus effectively alleviates the time-consuming problem and in the meantime, keeps the global convergence feature of DP.