| 引用本文: | 吉鹏,周建中,张睿,刘志武,卢鹏.改进量子进化混合优化算法在溪洛渡电站机组组合中的应用研究[J].电力系统保护与控制,2014,42(4):84-91.[点击复制] |
| JI Peng,ZHOU Jian-zhong,ZHANG Rui,LIU Zhi-wu,LU Peng.Study of unit commitment in Xiluodu based on a hybrid optimization algorithm of improved quantum evolution algorithm[J].Power System Protection and Control,2014,42(4):84-91[点击复制] |
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| 摘要: |
| 传统方法求解水电站机组组合问题时存在易陷入局部最优、易出现“维数灾”、收敛性差等缺陷，因此提出了一种改进量子进化混合优化算法用以解决这一问题。通过将量子进化算法与基于经济运行总表的动态规划法嵌套，分别对外层机组组合和内层负荷分配问题进行迭代优化；同时，引入最短开、停机时间修补策略和备用容量修补策略，有效处理多重复杂约束，在保证计算精度的前提下，显著提高收敛速度。以溪洛渡电站经济运行中的机组组合问题为工程背景进行了实例研究，并与已有DP和IBPSO方法进行对比分析，结果显示所提算法简单高效，优化效果好，具有较强的工程实用性。 |
| 关键词: 量子进化 动态规划 机组组合 修补策略 负荷分配 |
| DOI：10.7667/j.issn.1674-3415.2014.04.014 |
| 投稿时间：2013-05-16修订日期：2013-09-10 |
| 基金项目:国家自然科学基金重点项目（51239004）；高等学校博士学科点专项科研基金（20100142110012）；水利部公益性行业科研专项(201001080)；国家自然科学基金青年科学基金(51109086) |
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| Study of unit commitment in Xiluodu based on a hybrid optimization algorithm of improved quantum evolution algorithm |
| JI Peng,ZHOU Jian-zhong,ZHANG Rui,LIU Zhi-wu,LU Peng |
| (School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;China Changjiang Electric Power Co., Ltd, Chengdu 610042, China) |
| Abstract: |
| An improved quantum evolution algorithm is presented, which has better global optimization ability and faster convergence speed, because traditional methods have some problems, such as "disaster of dimension" problem, poor convergence performance and so on. The proposed method takes the improved QEA for the outer unit combination and the DP for inner economic load dispatch, the economic operation is solved by the two sub-problems alternating iterative optimization. Meanwhile, the minimum up/down time repair strategy and system reserve capacity repair technique are also used to deal with multiple complex constraints, which effectively improve the convergence speed on the premise of ensuring calculation precision. The proposed method is applied in solving unit commitment problem in Xiluodu Station. Compared with DP and IBPSO methods, the results show that this method is easier and faster, and has better global optimization ability with a strong practical engineering value. |
| Key words: quantum evolution algorithm(QEA) dynamic programming(DP) unit commitment repair strategy load dispatch |
