水利学报2017，Vol.48Issue(1)：104-112,9.DOI:10.13243/j.cnki.slxb.20160096
梯级水电站群并行多目标优化调度方法
Parallel multi-objective optimal operation of cascaded hydropower system
摘要
Abstract
To ensure the computational efficiency and solution quality of multi-objective optimal dispatch of cascaded hydropower system,we proposed a novel method,called parallel multi-objective genetic algorithm (PMOGA),based on the Fork/Join parallel computation framework.PMOGA makes full use of the features of multi-objective genetic algorithm (MOGA).Moreover,in order to maintain the diversity and astringency,the whole individuals are distributed into a number of sub-populations,and the migration model is used to exchange information between neighboring populations.In addition,three different strategies are introduced to enhance the convergence and diversity of solutions,which are the real number encoding technique,chaos initialization strategy and Pareto dominance by constraints.The proposed method is applied to the optimal operation of the Lancang river cascade hydropower stations.The results indicate that the method can improve the accuracy of the solutions with good convergence and diversity,which is feasible to address the multi-objective optimal dispatch problem of cascaded hydropower system.关键词
梯级水电站群/优化调度/多目标优化/遗传算法/并行计算/Fork/Join框架Key words
cascaded hydropower system/optimal operation/multi-objective optimization/genetic algorithm/parallel computing/Fork/Join framework分类
建筑与水利引用本文复制引用
牛文静,冯仲恺,程春田,武新宇,申建建..梯级水电站群并行多目标优化调度方法[J].水利学报,2017,48(1):104-112,9.基金项目
国家自然科学基金重大国际合作项目(51210014) （51210014）
国家重点基础研究发展计划(973计划)项目(2013CB035906) （973计划）
