基于改进遗传算法的梯级水电系统短期发电优化调度  

Optimal Scheduling of Short-term Generation of Cascade Hydropower System Based on Improved Genetic Algorithm

作　　者：郝少飞 张新源 葛浩然 夏宇 邹文进 马刚[1] Hao Shaofei;Zhang Xinyuan;Ge Haoran;Xia Yu;Zou Wenjin;Ma Gang(School of Electrical and Automation Engineering,Nanjing Normal University,Nanjing Jiangsu 210046,China)

机构地区：[1]南京师范大学电气与自动化工程学院,江苏南京210046

出　　处：《电气自动化》2022年第6期53-56,共4页Electrical Automation

基　　金：2021年研究生科研与创新计划-有源配电网网元自治-协同控制技术研究(1812000024582)。

摘　　要：为解决梯级水电系统在发电优化调度中存在的非线性、决策变量多以及求解困难等问题,构建了梯级水电系统最小缺电量模型。在基本遗传算法中,采用改进的轮盘赌选择策略改善算法的收敛性,引入非线性的自适应遗传算子提高算法的搜索能力,针对不同的约束条件进行相应的约束处理。最后,利用改进的遗传算法来求解优化模型。仿真结果验证了改进遗传算法和约束处理方法的有效性与可行性。In order to solve the problems of non-linearity,multiple decision variables,and difficulty in solving problems in the optimal dispatching of cascade hydropower systems,a minimum power shortage model for cascade hydropower systems was constructed.In the basic genetic algorithm,an improved roulette selection strategy was used to improve the convergence of the algorithm,a nonlinear adaptive genetic operator was introduced to improve the search ability of the algorithm,and the corresponding constraint processing was performed for different constraints.Finally,an improved genetic algorithm was used to solve the optimization model.The simulation results verify the effectiveness and feasibility of the improved genetic algorithm and the constraint handling method.

关 键 词：梯级水电系统 发电优化调度 改进遗传算法 非线性遗传算子 约束处理 

分 类 号：TM715[电气工程—电力系统及自动化]