基于动态廊道遗传算法的流域梯级水电站厂间负荷分配研究

Study on Load Allocation of Cascade Hydropower Stations Based on Genetic Algorithm Using Dynamic Constraint of Grid

针对流域梯级水电站间负荷分配问题,建立以龙头水库日发电耗水量最小及梯级弃水量最小为目标的流域梯级水电站厂间经济运行模型,提出动态廊道遗传算法的求解思路与步骤,并进行实例分析。结果表明动态廊道遗传算法有效克服了传统遗传算法出力分配结果频繁波动的缺陷,计算结果合理且优于传统遗传算法,对梯级电站日内发电计划的编制具有更强的指导意义。

Aiming at the problem of load allocation between cascade hydropower stations,the optimal model for economic operation of cascade hydropower stations is established,in which the optimization objectives is to minimize the daily water consumption of head reservoir and the total abandoned water volume of cascade hydropower stations,and then the dynamic grid-based genetic algorithm is proposed to solve the model.The calculation results of case study show that the dynamic grid-based genetic algorithm can effectively overcome the defect of frequent output allocation fluctuation of traditional genetic algorithm.The calculation results of dynamic grid-based genetic algorithm are reasonable and superior to that of traditional genetic algorithm,which has stronger guiding significance for the preparation of daily generation plan of cascade hydropower stations.