梯级水库生态调度多目标混合蛙跳差分算法研究

Ecological dispatch of cascade reservoir based on multi-objects shuffled frog leaping-difference algorithm

提出多目标混合蛙跳差分算法求解梯级水库多目标生态调度模型。该算法结合混沌理论生成初始解以提高初始解群体质量,构建基于动态更新机制的外部归档集引导种群进化,提高算法的收敛性与非劣解的多样性,引入自适应差分算法加快子种群个体寻优,提高算法收敛速度。对L河梯级水库多目标生态调度进行实例研究,计算结果表明:本文所提出的算法能够计算得到收敛性与分布性较好的调度方案集,对比典型调度方案下泄径流与物种生态适宜径流,表明生态调度能够较好满足物种的生态需水,生态效益显著。

A multi-objectives shuffled frog leaping-difference algorithm was proposed to solve ecological dispatch model of cascade reservoirs, this algorithm was combined with chaos theory to generate the initial population in order to improve its group quality, the external archive based on dynamic updating mechanism was built to guide population evolution to increase the algorithm convergence and diversity of not-bad solutions , the adaptive differential algorithm was introduced to accelerate optimization of individual group to improve the algorithm convergence speed. Taking the L river cascade reservoirs＇multi-objects ecological dispatch as a study case, the results showed that, the proposed algorithm could get a scheduling scheme set with good convergence and distribution. By comparing the discharge runoff of typical scheduling scheme and ecologically suitable runoff of specie, it showed that the ecological operation could meet the ecological demand of the speicies, and its ecological efficiency was significant.