基于改进差分进化鲸鱼算法的经济负荷分配

Economic Load Distribution Based on Improved Differential Evolution Whale Algorithm

针对电力系统经济负荷分配这一典型的非凸、非线性、组合优化问题,提出一种将改进差分进化算法和鲸鱼算法相结合的优化算法。该算法首先在鲸鱼优化算法中引入了非线性的收敛变化策略,加速寻优算法的迭代;再利用差分进化算法的交叉和选择,丰富算法种群个体信息,增强优化算法的全局收敛性;同时引入一种淘汰机制,将适应度较好的个体信息更快地保留用于下一次鲸鱼优化算法的迭代,提高了求最优解的速度和精度;最后,对多个经济负荷分配问题进行了测试,将该算法与标准鲸鱼算法、标准差分进化算法进行对比,验证了差分进化鲸鱼算法可以更合理地配置电力系统的经济负荷,能够有效找到可行解,避免陷入局部最优,能实现经济负荷的合理分配。

For the typical nonconvex,nonlinear,combinatorial optimization problem of economic load distribution in power system,an optimization algorithm combining improved differential evolutionary algorithm and whale algorithm is proposed.The algorithm first introduces a nonlinear convergence change strategy in the whale optimization algorithm to accelerate the iteration of the optimization algorithm,and then uses the crossover and selection of the differential evolution algorithm to enrich the individual information of the algorithm population and enhance the global convergence of the optimization algorithm.At the same time,it introduces an elimination mechanism to retain the information of individuals with better adaptability faster for the next iteration of the whale optimization algorithm,which improves the speed and accuracy of solving the optimal solution.Finally,the improved algorithm was tested on several economic load allocation problems,and the results were compared with the standard whale algorithm and the standard differential evolutionary algorithm to verify that the differential evolutionary whale algorithm can allocate the economic load of the power system more rationally and can effectively find feasible solutions to avoid falling into the local optimum,and can realize the reasonable distribution of economic load.