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鉴于流域梯级水电站联合运行是一类多目标、高维数、多约束的复杂优化问题,以流域梯级总发电量最大和最小下泄流量最大为目标,建立梯级水电站多目标兴利调度模型。同时,结合Pareto优化理论的数学描述方法,提出了适用于多目标优化问题求解的双种群多目标粒子群算法(DPPSO),通过构建外部精英种群及其更新维护模式,为原始种群进化提供了精英向导。在金沙江下游梯级水电站多目标兴利调度中的应用表明,所提方法可均衡优化发电、通航两个目标,且求解精度高、非劣解集分布性好,为求解复杂梯级水电站多目标优化调度问题提供了一种新思路。
In view of the multi-objective, high-dimensional and multi-constrained complex optimization problem, the joint operation of cascade hydropower stations in the basin is aiming at the maximum and minimum discharge of cascade hydropower stations. At the same time, combined with the mathematical description of Pareto optimization theory, a two-species multi-objective particle swarm optimization algorithm (DPPSO) is proposed to solve the multi-objective optimization problem. By building an external elite population and its updated maintenance mode, Wizard. The application of the multi-objective scheduling in the cascade hydropower stations in the lower reaches of the Jinsha River shows that the proposed method can balance the two objectives of power generation and navigation with high precision and good distribution of non-inferior solutions. In order to solve the multi-objective optimization of complex cascaded hydropower stations, Scheduling problem provides a new idea.