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基于鸟群算法的梯级水库群长期优化调度研究
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Abstract:
针对大规模梯级水电站群调度复杂、优化困难、求解耗时长等问题，研究提出了一种基于鸟群算法(bird swarm algorithm, BSA)的梯级库群长期优化调度求解方法。该方法利用BSA平衡全局搜索和局部搜索的特点，充分发挥其收敛速度快，求解效率高的优势，易于获得满足复杂约束的最优结果。在西南某流域梯级水电站不同典型年调度问题上的应用结果，验证了该方法在梯级库群长期调度问题方面的求解精确性和高效性，是一种实用性较强的有效算法。
In order to solve the problems of complex operation difficulty in optimization and time-consuming solution of large-scale cascade hydropower station group, a method for long-term optimal operation of cascade reservoir group based on bird swarm algorithm (BSA) was put forward. This method utilizes BSA’s characteristics of balancing global search and local search, and makes full use of its advantages of fast convergence, high efficiency of solution and easy to obtain optimal results satisfying complex constraints. The application results on different typical annual dispatching problems of cascade hydropower stations in a watershed in southwest China prove that the method is an effective and practical algorithm for solving long-term dispatching problems of cascade reservoirs.
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