机组组合是电力系统日发电计划中主要的优化任务,在满足各种约束条件下求得全局最优解是一个比较困难的问题。传统遗传算法的二进制编码和随机遗传操作不适合于求解大规模机组组合问题。针对电力系统日发电计划的特点,提出了一种混合智能messy遗传算法(HIMGA),该算法实现简单,大大减小了求解问题的规模,保证了群体的多样性,提高了算法的搜索效率,改善了算法的收敛性。仿真计算结果表明了该算法的有效性和实用性。 Unit commitment is the main optimization task in daily power generation plan of power system. It is a difficult problem to find the global optimal solution under various constraints. Traditional genetic algorithm binary coding and random genetic operations are not suitable for solving large-scale unit commitment problems. A hybrid intelligent messy genetic algorithm (HIMGA) is proposed based on the characteristics of daily power generation plan in power system. The algorithm is simple, reduces the size of solving problems greatly, ensures the diversity of groups and improves the searching efficiency of the algorithm. Improve the convergence of the algorithm. Simulation results show that the algorithm is effective and practical.