| 高叶军,连志刚,曹宇.基于改进布谷鸟算法的火电厂机组组合优化[J].电气自动化,2015,(4):64~66 |
| 基于改进布谷鸟算法的火电厂机组组合优化 |
| Optimization of Unit Commitment of Thermal Power Plant Based on Improved Cuckoo Algorithm |
| 修订日期：2014-09-30 |
| DOI： |
| 中文关键词: 布谷鸟算法 粒子群算法 机组组合 电力调度 火电厂 |
| 英文关键词:cuckoo algorithm particle swarm algorithm unit commitment electric power dispatching thermal power plant |
| 基金项目: |
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| 摘要点击次数: 3201 |
| 全文下载次数: 3544 |
| 中文摘要: |
| 电力系统机组组合是一个多维,复杂的整数规划问题,利用传统方法较难求解。在通过研究布谷鸟搜索(cuckoo search)算法的基本原理,分析布谷鸟算法的优缺点基础上,结合粒子群算法,提出一种改进的布谷鸟搜索算法。通过在10机组系统中进行验证,结果表明,算法比粒子群算法、标准布谷鸟算法更好。改进的布谷鸟搜索算法同样也在收敛速度等更具有优势。 |
| 英文摘要: |
| Unit commitment in the electronic power system, as a complex multi-dimensional integer programming problem, is difficult to solve in traditional approaches. On the basis of a research on the basic principle of cuckoo search and an analysis on its advantages and disadvantages, under consideration of the particle swarm algorithm, this paper presents an improved cuckoo search algorithm. The result of verification of the Unit System 10 shows that this algorithm is better than the particle swarm algorithm and the standard cuckoo algorithm. Furthermore, the improved cuckoo search algorithm also has its advantages in the respect of convergence speed. |
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