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针对流域梯级水电站长期优化调度模型存在高维、非凸、非线性等特点,提出一种改进的变尺度混沌蜂群算法(VCBA),通过引入混沌方程和余弦收缩策略,使其具有更强的全局收敛能力和更快的收敛速度。以丰枯分时电价下金沙江下游梯级水电站群长期优化调度作为工程背景进行实例研究,并将计算结果与基本蜂群算法(BA)和粒子群算法(PSO)进行比较。结果表明,VCBA求解梯级水电站长期优化调度问题收敛速度快且优化结果精度较高,满足实际优化运行需求,具有很高的工程应用价值。
In view of the high dimensional, non-convex and nonlinear characteristics of the long-term optimal scheduling model for cascade hydropower stations, an improved variable scale chaos bee colony algorithm (VCBA) is proposed. By introducing chaotic equations and cosine shrinking strategies, Global convergence and faster convergence. The long-term optimal operation of the cascade hydropower stations in the lower reaches of the Jinsha River at abundant and dry-hour electricity prices is taken as an example to study the results. The results are compared with the basic bee colony algorithm (BA) and particle swarm optimization (PSO). The results show that VCBA has a high engineering application value for solving the problem of long-term optimal operation of cascaded hydropower stations with high convergence rate and high accuracy of the optimization results, satisfying the requirements of actual optimization operation.