基于改进花粉算法的梯级水电站多目标优化

摘要

Because the power generation,flood control,safe operation of power grid and other targets need to be considered into the optimal scheduling of cascaded hydropower stations,the optimal scheduling of cascaded hydropower stations will be a high-dimensional,dynamic and nonlinear issue and is difficult to solve.In order to solve this problem,the search strategy of flower pollination algorithm is improved and the differential mutation operation is introduced to accelerate the convergence and increase the diversity of population.The improved flower pollination algorithm is used to solve the multi-objective optimization scheduling problem of cascade hydropower stations.The results show that the improved algorithm has fast convergence rate and high solution accuracy,and has certain advantages for solving multi-objective optimization problems of cascaded hydropower stations.%梯级水电站优化调度要考虑发电、防洪、电网安全运行等多个目标,具有高维、动态、非线性等特征,求解复杂.为解决这一问题,通过改进花粉算法搜索策略和引入差分变异操作,加快算法收敛速度,增加种群多样性,并将该算法用于求解梯级水电站多目标优化调度问题.结果表明,该算法收敛速度快,求解精度高,对求解梯级水电站多目标优化问题具有一定的优越性.