鲸鱼优化算法在水库优化调度中的应用

摘要

为验证鲸鱼优化算法在水库优化调度求解中的可行性和有效性,采用4个典型测试函数对鲸鱼优化算法进行仿真验证,并与布谷鸟搜索算法、差分进化算法、混合蛙跳算法、 粒子群优化算法、萤火虫算法和SCE-UA算法共6种算法的仿真结果进行对比分析;将鲸鱼优化算法与6种对比算法应用于某单一水库和某梯级水库中长期优化调度求解.结果表明:鲸鱼优化算法寻优精度高于其他6种算法8个数量级以上,具有收敛速度快、收敛精度高和极值寻优能力强等特点;鲸鱼优化算法单一水库和梯级水库优化调度结果均优于其他6种算法;鲸鱼优化算法应用于水库优化调度求解是可行和有效的.%In order to verify the feasibility and effectiveness of the whale optimization algorithm for reservoir optimal operation, four test functions were used in the whale optimization algorithm, and the simulated results were compared with those obtained from six algorithms, including the cuckoo search algorithm, differential evolution algorithm, shuffled frog leaping algorithm, particle swarm optimization algorithm, firefly algorithm, and SCE-UA algorithm. The whale optimization algorithm and the six comparison algorithms were used to solve the long-term optimal operation of a single reservoir and cascade reservoirs. The results show that the accuracy of the whale optimization algorithm is higher than that of the other six algorithms by eight or more orders of magnitude, and it has the fast convergence speed, high convergence precision, and excellent ability of optimization. The results of the whale optimization algorithm for the optimal operation of a single reservoir and cascade reservoirs are superior to those of the other six algorithms. The whale optimization algorithm is feasible and effective for reservoir optimal operation.