| 引用本文: | 徐小琴,郑 旭,王思聪,等.基于改进遗传退火算法的输配电网协调规划方法[J].电力系统保护与控制,2021,49(15):124-131.[点击复制] |
| XU Xiaoqin,ZHENG Xu,WANG Sicong,et al.Coordinated planning method of transmission and distribution network based on an improved genetic annealing algorithm[J].Power System Protection and Control,2021,49(15):124-131[点击复制] |
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| 基于改进遗传退火算法的输配电网协调规划方法 |
| 徐小琴1,郑旭1,王思聪1,刘巨1,蔡杰1,廖爽1,赵佳伟2,张天东2,郭露方2 |
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| (1.国网湖北省电力有限公司经济技术研究院，湖北 武汉 430077;2.武汉大学电气与自动化学院，湖北 武汉 430072) |
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| 摘要: |
| 针对目前对输配电网协调性考虑不足的问题，考虑机组间负荷优化分配因素，引入耗量成本，构建了包含输配电网协调性指标的电网评价指标体系。结合电网经济性指标和可靠性指标，通过优化算法选出综合性能最优的输配电网规划方案。在解决遗传算法“早熟”、易陷于局部最优等问题的基础上，提出了一种优化算法并将其应用于考虑输配网协调性的电网规划问题中。仿真计算结果表明，所提出的方法是可行、高效的。 |
| 关键词: 输配电网协调 负荷优化配置 遗传算法 模拟退火算法 输配电网规划 |
| DOI：DOI: 10.19783/j.cnki.pspc.201236 |
| 投稿时间：2020-10-14修订日期：2021-02-05 |
| 基金项目:国家自然科学基金项目资助(51777142， 51477121)；国家重点研发计划项目资助(2018YFB0904200) |
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| Coordinated planning method of transmission and distribution network based on an improved genetic annealing algorithm |
| XU Xiaoqin1,ZHENG Xu1,WANG Sicong1,LIU Ju1,CAI Jie1,LIAO Shuang1,ZHAO Jiawei2,ZHANG Tiandong2,GUO Lufang2 |
| (1. Economy & Technology Research Institute, State Grid Hubei Electric Power Company, Wuhan 430077, China;
2. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China) |
| Abstract: |
| There is currently insufficient consideration of the coordination of the power transmission and distribution network. In considering the optimization of load distribution among units and introducing consumption costs, a grid evaluation index system including the coordination index of the power transmission and distribution network is constructed. Combining the economic and reliability indicators of the power grid, the power transmission and distribution network planning scheme with the best comprehensive performance is selected through optimization algorithms. To solve the problems of a genetic algorithm being "premature" and easily falling into a local optimum, an optimization algorithm is proposed and applied to the grid planning problem considering the coordination of transmission and distribution network. The simulation results show that the proposed method is feasible and efficient.
This work is supported by the National Natural Science Foundation of China (No. 51777142 and No. 51477121) and the National Key Research and Development Program of China (No. 2018YFB0904200). |
| Key words: transmission and distribution network coordination load optimization configuration genetic algorithm simulated annealing algorithm power transmission and distribution network planning |
