基于模拟退火粒子群算法的五强溪水电站厂内经济运行模型与应用

Economic Operation Model of Wuqiangxi Hydropower Station Based on Simulated Annealing Particle Swarm Optimization Algorithm and Its Application

围绕水电站厂内经济运行问题,建立了以发电耗水量最小为目标的机组组合优化模型,针对传统粒子群算法(PSO)寻优能力不足及易陷入局部最优的缺点,引入收缩因子并结合模拟退火算法,提出了一种模拟退火粒子群算法(SAPSO),同时采用动态规划修补策略处理约束条件。以五强溪水电站为例,将SAPSO算法应用于厂内经济运行模型求解,获得电站机组组合及机组间最优负荷分配策略,并与SA算法、PSO算法及实际运行数据进行对比。结果表明,SAPSO拥有更强的寻优能力和寻优速度,实现了机组间负荷的最优分配,工程实用性强。

Aiming at the problem of economic operation of hydropower station,an optimization model with the objective of minimizing water consumption for power generation was established.In view of the shortcomings of traditional particle swarm optimization(PSO),such as insufficient optimization ability and easy to fall into local optimum,a simulated annealing particle swarm optimization algorithm(SAPSO)was proposed by introducing shrinkage factor and combining with simulated annealing algorithm.Taking Wuqiangxi Hydropower Station as an example,the SAPSO algorithm was used to solve the economic operation model.The dynamic programming repair strategy is used to deal with the constraint conditions to determine unit commitment and the optimal load distribution among units.Compared with the SA algorithm,PSO algorithm and the actual operation data,the results show that the SAPSO has stronger optimization ability and achieves optimal load distribution of units,and it has strong engineering practicability.