| 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 |
| 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 |
| 投稿时间：2016-01-21 |
| DOI：10.13243/j.cnki.slxb.20160096 |
| 中文关键词: 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 |
| 英文关键词: cascaded hydropower system optimal operation multi-objective optimization genetic algorithm parallel computing Fork/Join framework |
| 基金项目:国家自然科学基金重大国际合作项目（51210014）；国家重点基础研究发展计划（973计划）项目（2013CB035906） |
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| 中文摘要: |
| 为保障梯级水电站群多目标优化调度问题的计算效率和求解精度，提出了基于Fork/Join多核并行框架的并行多目标遗传算法。该方法以多目标遗传算法为基础，引入多种群异步进化策略保证种群间个体多样性；采用迁移机制保障子种群的信息有机互馈，提升算法收敛性和解集多样性；利用并行技术实现子种群在各内核的同步求解，提高计算效率。针对问题特点，耦合个体实数串联编码方法、混沌初始化种群策略和约束Pareto占优机制等，进一步提升方法寻优性能。澜沧江流域梯级水电站群多目标优化调度结果表明，所提方法可充分利用多核资源，提升模型计算效率与求解精度，并能获得分布均匀、合理可行的调度方案集，为水电系统多目标高效决策提供科学依据。 |
| 英文摘要: |
| 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. |
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