| 引用本文: | 陈建华,阎帅,张瑶,丁涛.基于IPM-intPSO的两阶段动态无功优化算法[J].电力自动化设备,2020,40(3): |
| CHEN Jianhua,YAN Shuai,ZHANG Yao,DING Tao.Two-stage dynamic reactive power optimization algorithm based on IPM-intPSO[J].Electric Power Automation Equipment,2020,40(3): |
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| 摘要: |
| 提出一种基于内点法(IPM)和整数粒子群(intPSO)算法相结合的启发搜索-变量校正两阶段动态无功优化算法。首先，采用intPSO算法求解离散变量，并利用IPM处理连续变量，通过两者交替迭代得到静态无功优化的求解方法；然后，在保证网损最小的同时，自适应得到最优动态分段数，克服传统依据负荷曲线人为分段方法的缺点；最后，对目标函数在启发搜索的结果上进行变量校正的再优化。IEEE 9、14、30、57、118节点测试系统的仿真结果验证了所提算法的有效性。 |
| 关键词: 动态无功优化 启发搜索-变量校正 离散变量 最优分段 |
| DOI：10.16081/j.epae.202002018 |
| 分类号:TM732 |
| 基金项目: |
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| Two-stage dynamic reactive power optimization algorithm based on IPM-intPSO |
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CHEN Jianhua1, YAN Shuai1, ZHANG Yao2, DING Tao3
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1.State Grid Jibei Electric Power Company Limited, Beijing 100054, China;2.China Nuclear Power Engineering Company Limited, Beijing 100840, China;3.School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
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| Abstract: |
| A heuristic search-variable correction two-stage dynamic reactive power optimization algorithm is proposed based on the combination of IPM(Interior Point Method) and intPSO(integer Particle Swarm Optimization) algorithm. Firstly, intPSO algorithm is adopted to solve the discrete variables, and IPM is used to deal with the continuous variables, by the alternate iteration of which the solution method of static reactive power optimization is obtained. Then, the optimal dynamic segmentation number is self-adaptively obtained with the minimum power loss guaranteed, which overcomes the shortages of the load curve based artificial segmentation method. Finally, the re-optimization of variable correction based on the results of heuristic search is carried out for the objective function. The simulative results of IEEE 9-,14-,30-,57-and 118-bus systems verify the effectiveness of the proposed algorithm. |
| Key words: dynamic reactive power optimization heuristic search-variable correction discrete variable optimal segmentation |
