基于均匀自组织映射遗传算法的梯级水库优化调度

发布时间：2019-03-08 21:04

【摘要】：针对遗传算法中初始解分布不均以及易早熟等问题,采用均匀设计方法来生成均匀分布的初始解以及自组织映射算法通过高低维空间映射来改变个体基因从而增强局部搜索能力,提出了均匀自组织映射遗传算法,弥补了传统遗传算法中初始解的生成过于随机以及进化过程中易陷入局部解的不足,并将此改进算法在梯级水库的长期优化调度中进行了应用.通过实例计算表明,与遗传算法以及标准粒子群算法相比,此方法拥有更好的全局寻优能力,与动态规划算法结果相近,并且有着较快的计算速度,从而验证了此方法用于处理梯级水库的长期优化调度问题的可行性与合理性.
[Abstract]:Aiming at the problem of uneven distribution of initial solution and precocity in genetic algorithm (GA), The uniform design method is used to generate the initial solution of uniform distribution and the self-organizing mapping algorithm changes individual genes through high and low dimensional spatial mapping to enhance the ability of local search. A uniform self-organizing mapping genetic algorithm is proposed. The original solution is generated too randomly in the traditional genetic algorithm and the local solution is easily trapped in the evolution process. The improved algorithm is applied to the long-term optimal operation of the cascade reservoir. Compared with genetic algorithm and standard particle swarm optimization algorithm, the proposed method has better global optimization ability, similar results with dynamic programming algorithm, and faster computing speed, compared with genetic algorithm and standard particle swarm optimization algorithm, an example shows that the proposed method has better global optimization ability than genetic algorithm and standard particle swarm optimization algorithm. The feasibility and rationality of this method for long-term optimal operation of cascade reservoirs are verified.
【作者单位】：华北电力大学可再生能源学院;
【基金】：国家自然科学基金(51279062) 雅砻江流域水电开发有限公司资助项目(JKZX-201416-01) 中央高校基本科研业务专项基金资助项目(2015XS53,2014ZD12)~~
【分类号】：TP18;TV697.1

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