基于改进生物地理优化算法的梯级水电站优化运行研究

Yuechun Jiang, Zhongnan He, A. Liu, Zhong-ying Bai
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引用次数: 0

摘要

梯级水电站能够综合开发流域水电资源,实现清洁能源的充分利用,其优化运行是一个具有复杂约束条件的动态非线性多目标优化问题。基于生物地理的优化算法(BBO)是一种基于生物地理的新型进化算法。本文引入差分进化算法的动态非均匀变异算子和变异策略,对BBO算法的迁移算子和变异算子进行改进,增强了算法的探索能力,加快了算法的收敛速度。采用改进的BBO算法求解梯级水电站多目标优化模型,经过多次迁移和突变运行,得到问题的最优解。以某两级梯级水电站优化运行为例,验证了所提模型及改进BBO算法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on optimal operation of cascade hydropower station based on improved biogeography-based optimization algorithm
Cascade hydropower station can comprehensively develop hydropower resources of river basin and realize the full use of clean energy, its optimal operation is a dynamic nonlinear multi-objective optimization problem with complex constraints. Biogeography-based optimization (BBO) algorithm is a new evolutionary algorithm based on biogeography. In this paper, dynamic non-uniform mutation operator and mutation strategy of differential evolution algorithm are introduced to improve migration operator and mutation operator of BBO algorithm, which enhance exploration ability of the algorithm and accelerate convergence speed of the algorithm. Improved BBO algorithm is used to solve the multi — objective optimization model of cascade hydropower station, and the optimal solution of the problem is obtained after several times of migration and mutation operation. Taking the optimal operation of a two-stage cascade hydropower station as an example, the feasibility and effectiveness of the proposed model and improved BBO algorithm are verified.
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