基于SPADE算法的梯级水库群联合防洪优化调度  

Optimal operation of joint flood control for cascade reservoirs based on SPADE algorithm

作　　者：何中政 辛秀钰 魏博文[1,2] 尹恒 徐富刚 邓欢 HE Zhongzheng;XIN Xiuyu;WEI Bowen;YIN Heng;XU Fugang;DENG Huan(School of Infrastructure Engineering,Nanchang University,Nanchang 330031,China;Key Laboratory of Poyang Lake Environment and Resources Utilization of Ministry of Education,Nanchang University,Nanchang 330031,China)

机构地区：[1]南昌大学工程建设学院,南昌330031 [2]南昌大学鄱阳湖环境与资源利用教育部重点实验室,南昌330031

出　　处：《南水北调与水利科技（中英文）》2024年第4期651-660,共10页South-to-North Water Transfers and Water Science & Technology

基　　金：国家自然科学基金项目(52209024);江西省水科院开放基金项目(2022SKSH01);江西省自然科学基金项目(20224BAB204075,20212BAB214065);江西省水利厅科技项目(202324YBKT24);贵州省科技重大专项(黔科合重大专项字[2018]3010)。

摘　　要：针对梯级水库群联合防洪优化调度问题,提出一种基于自适应成功历史策略的改进差分进化算法(strategy and parameter adaptive differential evolution,SPADE)。该算法通过自适应成功历史差分策略来提升随机搜索效率,通过精英种群保守策略提升局部收敛速度及全局探索能力。据此开展包含10个测试函数的数值实验和赣江中游梯级水库群联合防洪优化调度实例,用于检验所提出的算法应用效果。结果表明:在数值实验中,SPADE算法收敛结果的最优值、平均值、标准差和成功次数评价指标整体优于SHADE、自适应差分进化算法(self-adaptive differential evolution,SADE)、遗传算法(genetic algorithm,GA)、粒子群算法(particle swarm optimization,PSO)、人工蜂群算法(artificial bee colony,ABC);在梯级水库群联合防洪优化调度实例应用中,通过对1964单峰和1973多峰型历史洪水过程进行分析,发现SPADE算法结果在削峰率指标上明显优于SADE、GA、PSO算法,且相比SHADE在两次历史洪水条件下的削峰率指标结果分别提升0.9%、3.4%。实验结果充分验证所提SPADE算法的优越性,可作为梯级水库群联合优化调度问题的有效求解工具。optimization problems in the mathematical sense,and transforms these problems into different constraints,and seeks the optimal solution based on these constraints.The combined operation of reservoir groups needs to consider the influence of meteorological,hydrological,hydraulic and other factors,as well as the conflict of interests between upstream and downstream and between multi-functions.Domestic and foreign scholars have used dynamic programming(DP),progressive optimization algorithm(POA),genetic algorithm(GA),and particle swarm algorithm(PSO)and other algorithms to solve the problem.However,the above traditional optimization algorithms still have the problems of poor stability and easy to fall into the local optimal situation,and still need to carry out more in-depth research on the algorithm parameter updating mechanism,search strategy and other aspects.SPADE algorithm is an improved differential evolution algorithm,which uses adaptive success history difference strategy to improve random search efficiency,and adaptive success history parameter update strategy and elite group conservative strategy to improve local convergence speed and global search capability. The algorithm divides all the populations in each generation into elite and base populations in the process of differential variation, the elite population conserves the good genes without adopting the variation strategy, and individuals in the base population randomly select each variation strategy for evolution according to the probability, in which the probability of selecting the differential strategy in each generation is reassigned according to the evolution success rate of each individual produced by the differential strategy, and the flow of the high-quality genes is effectively controlled. A joint flood control optimal scheduling model of a group of terrace reservoirs with the objective function of minimizing the maximum flow rate discharged from the reservoirs is established, combined with the flow constraints and their constraint violation

关 键 词：防洪调度 梯级水库群 差分进化算法 成功历史 差分策略 精英种群 

分 类 号：TV697[水利工程—水利水电工程]