基于改进电子搜索算法的梯级水库联合发电优化调度
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(华北电力大学可再生能源学院,北京102206)

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E-mail: lpwang@ncepu.edu.cn.

中图分类号:

TP301.6

基金项目:

“十三五”国家重点研发计划课题(2016YFC0402208);国家自然科学基金项目(51709105);中央高校基本科研业务费专项资金项目(2019QN056).


Cascade reservoirs' joint optimal operation of power generation based on improved electro-search algorithm
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(College of Renewable Energy,North China Electric Power University,Beijing102206,China)

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    摘要:

    为解决梯级水库联合优化调度求解时间较长的问题,提出一种改进的电子搜索算法(IESA).改进算法在原算法的基础上,首先采用新的参数自适应方法,同时保证运算前期向优秀个体的迁移速度以及运算后期较强的局部搜索能力;然后,针对梯级水库联合优化调度强约束性的特点,提出可行域内搜索策略,使核周围产生的电子和迁移后的原子核均满足水库调度的各项约束,避免可行域外的无效搜索,提高搜索效率.运用改进后的电子搜索算法求解李仙江流域两座水库联合发电优化调度问题,结果表明,所提出的方法较传统的动态规划和遗传算法,能同时保证算法的收敛速度和所得结果的质量,具有推广价值.

    Abstract:

    An improved electro-search algorithm(IESA) is proposed to solve the problem of long computing time in the process of joint optimal operation of reservoirs. Based on the electro-search algorithm, the proposed algorithm adopts a new parameter adaptive method to accelerate the migration speed to the global optimal solution in the early stage of operation and has strong local search ability in the later stage of operation. At the same time, according to the characteristics of strong constraints of joint optimal operation of cascade reservoirs, two search strategies of searching in feasible region are proposed to make the electrons generated around the core and the migrated nuclei satisfy the feasible region constraints, avoiding the invalid optimization caused by random optimization exceeding the feasible region, and improving the search efficiency. The improved electro-search algorithm is used to solve the optimal operation problem of joint power generation of two reservoirs in Lixianjiang River Basin. The results show that the calculation results of this method are similar to those of the dynamic programming method and are superior to the genetic algorithm, especially in the speed of calculation, which is worth popularizing.

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王丽萍,李宁宁,阎晓冉,等.基于改进电子搜索算法的梯级水库联合发电优化调度[J].控制与决策,2020,35(8):1916-1922

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  • 在线发布日期: 2020-06-08
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