程春田

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:水利工程系

学科:水文学及水资源. 水利水电工程. 电力系统及其自动化. 计算机应用技术

联系方式:ctcheng@dlut.edu.cn

电子邮箱:ctcheng@dlut.edu.cn

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A Multi-Core Parallel Genetic Algorithm for the Long-Term Optimal Operation of Large-Scale Hydropower Systems

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论文类型:会议论文

发表时间:2016-01-01

收录刊物:CPCI-S

页面范围:220-230

关键字:Cascade hydropower system; Long-term optimal operation; Genetic algorithm; Multi-core parallel

摘要:The hydropower has undertaken a rapid development in the past several decades in China. At present, China has become the largest hydropower country and has built several huge hydropower bases. A favorable long-term optimal scheduling scheme of large-scale hydropower systems (LHS) is very important for improving the efficiency of hydropower plants. As hydropower optimal operation is nonlinear and nonconvex, and the problem scale increased significantly with the expanding scale of hydropower stations, the necessity of improving the solving efficiency for optimal operation has been amplified by the growing of hydropower stations and the increasing frequent of extreme climate events. This article presented a multi-core parallel genetic algorithm (MPGA) to solve long-term optimal operation of LHS. This algorithm based on genetic algorithm (GA), it distributes individuals to several isolate subpopulations to maintain the diversity, use single circle migration model to exchange individuals between subpopulations to assure the astringency of the algorithm. At the same time, multi-core parallel computing is adopted to make better use of multi-core CPU and improve the computing efficiency. Case study of in the Hongshui River cascaded hydropower system in the south China shown that MPGA is effective and can make a significant reduction in computing time and get reasonable hydropower operation results, which is an effective algorithm in long-term optimal operation for hydropower system.