在建立抽水蓄能电站优化运行方式计算模型的基础上 ,将遗传算法与领域问题的算法相结合 :选择机组运行状态作为编码变量 ,使机组的运行状态与二进制遗传编码具有简洁对应关系 ;采用符合问题本身特点的基因片段式杂交算子和改造的变异算子 ,使遗传操作更适应问题的求解 ;根据领域问题的性质及算法求解承担系统基荷的机组运行方式 ,使问题的规模得到有效压缩 ;应用领域问题求解的等微增率原理计算各个体因子所对应的运行机组间最优负荷分配方案 ,并以此计算个体适应值 .由于在遗传编码设计、遗传操作改造、问题规模压缩以及适应值计算几个方面融合了问题所涉及的领域知识 ,提高了算法的计算效率和全局搜索能力 ,形成一种适合于求解复杂约束条件下抽水蓄能电站优化运行方式的混合遗传算法 Based on the calculation model of optimal operation mode of pumped storage power station, the algorithm of genetic algorithm is combined with the algorithm of field problems: the operation status of the unit is selected as the coding variable, so that the operating status of the unit has a concise correspondence with the binary genetic code; According to the nature of the domain problem and the algorithm, the running mode of the unit with system base load is solved, so that the scale of the problem can be effectively compressed ; The application of the problem of such as the micro-incremental rate of principle to calculate the individual factors corresponding to the operation of the unit load distribution and optimal load sharing program to calculate individual fitness due to the genetic code design, genetic manipulation transformation, the scale of the problem compression and adaptation Several aspects of the value calculation combine the domain knowledge involved in the problem, and improve the computational efficiency and global search ability of the algorithm to form a hybrid genetic algorithm suitable for solving the optimal operation mode of pumped storage plants under complex constraints