| 改进量子粒子群算法在水电站群优化调度中的应用 |
| |
| 引用本文： | 冯仲恺,廖胜利,牛文静,申建建,程春田,李泽宏.改进量子粒子群算法在水电站群优化调度中的应用[J].水科学进展,2015,26(3):413-422. |
| |
| 作者姓名： | 冯仲恺 廖胜利 牛文静 申建建 程春田 李泽宏 |
| |
| 作者单位： | 1.大连理工大学水电与水信息研究所, 辽宁大连 116024; |
| |
| 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)资助项目(2013CB035906) |
| |
| 摘 要： | 针对量子粒子群算法求解水电站群优化调度问题存在的早熟收敛、寻优能力欠佳等缺陷,从种群初始化、进化和变异等方面提出了改进量子粒子群算法。该方法引入混沌搜索增强初始种群质量;通过加权更新种群最优位置中心改善种群进化模式并提升收敛速度;利用邻域变异搜索增加种群多样性避免早熟收敛。同时依据问题特点设计了矩阵实数编码方式与复杂约束处理方法。乌江梯级综合对比分析表明所提方法能切实保证快速获得高质量优化调度结果,有效提高梯级水能利用率,如长序列模拟调度较逐步优化算法分别减少8.9%的弃水和72.3%的耗时,是一种适用于大规模水电站群优化调度的高效实用方法。
|
| 关 键 词： | 量子粒子群 水电站群 优化调度 混沌 进化模式 变异 |
| 收稿时间： | 2014-12-22 |
Improved quantum-behaved particle swarm optimization and its application in optimal operation of hydropower stations |
| |
| FENG Zhongkai,LIAO Shengli,NIU Wenjing,SHEN Jianjian,CHENG Chuntian,LI Zehong.Improved quantum-behaved particle swarm optimization and its application in optimal operation of hydropower stations[J].Advances in Water Science,2015,26(3):413-422. |
| |
| Authors: | FENG Zhongkai LIAO Shengli NIU Wenjing SHEN Jianjian CHENG Chuntian LI Zehong |
| |
| Institution: | 1.Institute of Hydropower & Hydroinformation, Dalian University of Technology, Dalian 116024, China;2.Guizhou Wujiang Hydropower Development Limited Liability Company, Guiyang 550000, China |
| |
| Abstract: | This paper develops an improved quantum-behaved particle swarm optimization (IQPSO) to alleviate the existing defects of the quantum-behaved particle swarm optimization, such as premature convergence and poor search ability. Firstly, the chaotic search is employed to promote the quality of initial population. Secondly, the evolution pattern of the population is improved by using the weighted updating the population mean best position. Thirdly, the mutation operator is introduced to ensure the global searching ability. Moreover, according to the peculiarities of the optimization problem, the matrix real-coded particle and the complex constraints handling method are designed to further enhance the search efficiency. The proposed method is applied to the optimal operation in Wujiang River cascade hydropower stations. The results demonstrate the effectiveness and practicality of the proposed method in engineering applications. Compared to the progressive optimality algorithm, the spilling discharge and computation time of IQPSO in long-term simulation are reduced by 8.9％ and 72.3％, respectively. IQPSO is an efficient and practical approach for the optimal operation of large-scale hydropower system. |
| |
| Keywords: | quantum-behaved particle swarm optimization hydroelectric stations optimal operation chaos evolution pattern mutation |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《水科学进展》浏览原始摘要信息 |
| 点击此处可从《水科学进展》下载免费的PDF全文 |
|
