| 引用本文: | 王瑞峰,王庆荣.基于改进双层聚类多目标优化的配电网动态重构[J].电力系统保护与控制,2019,47(21):92-99.[点击复制] |
| WANG Ruifeng,WANG Qingrong.Multi-objective optimization of dynamic reconfiguration of distribution network based on improved Bilayer clustering[J].Power System Protection and Control,2019,47(21):92-99[点击复制] |
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| 摘要: |
| 随着配电网的高速发展，电力用户对供电可靠性的要求越来越高。针对现有配电网动态重构中开关次数难以约束，系统节点功率变化对配电网潮流分布的影响以及单一聚类算法负荷识别不足的问题，提出基于形态与幅值的双层聚类。外层以皮尔逊为相似度量进行形态相似聚类，内层以欧氏距离为相似度量进行幅值相近聚类。建立减小网损、提高电压稳定性、均衡馈线负荷、减少开关操作次数的多目标优化数学模型，采用改进粒子群算法完成配电网多目标动态重构。仿真结果表明，较静态重构开关操作次数降低了54.76%，减小电能15 575.4 kW.h，降低了39.28%，较重构前电压偏移指数降低49.1%，负荷均衡度改善41.9%。该研究所提改进的双层负荷聚类相比FCM聚类，准确度提高了11%，聚类效果更加接近原始数据。该动态重构方案可提高配电网运行的可靠性。 |
| 关键词: 配电网动态重构 改进双层聚类 改进粒子群算法 皮尔逊系数 |
| DOI：10.19783/j.cnki.pspc.181502 |
| 投稿时间：2018-12-03修订日期：2019-04-01 |
| 基金项目:国家自然科学基金项目资助(51667013) |
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| Multi-objective optimization of dynamic reconfiguration of distribution network based on improved Bilayer clustering |
| WANG Ruifeng,WANG Qingrong |
| (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China) |
| Abstract: |
| With the rapid development of distribution networks, power users are demanding more and more from power supply reliability.Aiming at the constraint of switch operation times in existing dynamic reconfiguration of distribution network and the distribution network power flow distribution impact of each node of the system and considering the shortage of load identification in a single clustering algorithm, a two-layer clustering algorithm is proposed based on morphology and amplitude. On outer layer, the sample data is clustered with Pearson correlation coefficient as the performance evaluation index. On inner layer, each cluster obtained from the outer clustering is clustered with Euclidean distance function as evaluation index. Multi-objective optimization mathematical model is established, which can reduce power loss of network, increase voltage stability, balance load of feeder, and minimize operation times of all switches. Multi-objective dynamic reconfiguration of distribution network is finished by improved particle swarm optimization. Simulation results show that the times of switching operation is decreased by 54.76% compared to static reconstruction, the power reduction is 15575.4 kW.h, decreased by 39.28%, the voltage deviation index is decreased by 49.1% before reconstruction, and the load imbalance is improved by 41.9%. The accuracy of the improved double-layer load clustering is improved by 11% compared with FCM clustering, and the clustering effect is closer to the original data. It is verified that the dynamic reconfiguration can effectively improve the reliability of distribution network running. This work is supported by National Natural Science Foundation of China (No. 51667013). |
| Key words: dynamic reconfiguration of distribution network improved bilayer clustering improved particle swarm algorithm Pearson correlation coefficient |
