梯级水库群长期优化调度的逐次优化-遗传算法

Long-time Reservoir Optimal Operation Based on Progressive Optimality Algorithm-Genetic Algorithm

梯级水库群长期优化调度问题是一个典型的高度非线性、多维、多时段的优化问题。针对问题特点,提出了一种逐次优化和遗传算法相结合的方法。首先将多阶段优化问题转化为多个两阶段优化问题,然后采用遗传算法求解每个两阶段优化问题。将该方法应用于大渡河4个梯级水库水电站长期优化调度,结果表明,该方法占用计算机内存少,效率高,收敛速度快,是一种有效的求解水库群优化调度模型的方法。

A progressive optimality-genetic algorithm（POA--GA） is proposed to optimize the long-time operation of cascade reser- voirs, which is a typical highly nonlinear, multi-dimensional, multi-period optimization problem. The long-time optimal operation of cascade reservoirs is partitioned into many two-stage problems, each can be optimized by using genetic algorithm（GA） respectively. The optimal results of the Daduhe River＇s four cascade hydropower stations show that POA--GA is effective in the long-term optimal operation of cascade reservoirs, which occupies little of computer＇s memory and has a high rate of convergence.