抽水蓄能电站优化运行方式的混合遗传算法

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面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，并以此计算了个体适应值，由于在遗传编码设计，遗传操作改造，问题规律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。

The mixed genetic algorithm for optimal operation pattern of pumped storage plant

Genetic algorithm is combined with traditional algorithm in the field based on algorithm model of optimal operation mode in pumped storage power station. Selecting unit operation states as coding variable, the states are compactly homologous with binary system genetic coding. Using gene segment crossover operator and reconstructive variation operator, genetic operation is much more seasoned with the solution of the problem. Working out the operation mode of units taking on basic load, the scale of the problem is effectively compressed. Using the theory of equal slight increasing efficiency, the optimal load distribution scheme among units with which genes of each chromosome correspond is shaped and the function value of each chromosome is calculated. A mixed genetic algorithm for solving the optimal operation mode in pumped storage power station is formed.