文章摘要
张倩,丁津津,张道农,等.基于集群划分的高渗透率分布式系统无功优化[J].电力系统自动化,2019,43(3):130-137. DOI: 10.7500/AEPS20180110002.
ZHANG Qian,DING Jinjin,ZHANG Daonong, et al.Reactive Power Optimization of High-penetration Distributed Generation System Based on Clusters Partition[J].Automation of Electric Power Systems,2019,43(3):130-137. DOI: 10.7500/AEPS20180110002.
基于集群划分的高渗透率分布式系统无功优化
Reactive Power Optimization of High-penetration Distributed Generation System Based on Clusters Partition
DOI:10.7500/AEPS20180110002
关键词: 分布式能源系统  集群划分  电气距离  功优化  粒子群优化算法
KeyWords: distributed energy network  cluster partition  electrical distance  reactive power optimization  particle swarm optimization algorithm
上网日期:2018-12-14
基金项目:国家重点研发计划资助项目(2016YFB0900400);国家自然科学基金资助项目(51507001)
作者单位E-mail
张倩 安徽大学电气工程与自动化学院, 安徽省合肥市 230601
合肥恒大江海泵业股份有限公司, 安徽省合肥市 231131 
qianzh@ahu.edu.cn 
丁津津 安徽大学电气工程与自动化学院, 安徽省合肥市 230601
国网安徽省电力有限公司电力科学研究院, 安徽省合肥市230022 
 
张道农 中国电力工程顾问集团华北电力设计院有限公司, 北京市100120  
王群京 安徽大学电气工程与自动化学院, 安徽省合肥市 230601
安徽大学工业节电与电能质量控制协同创新中心, 安徽省合肥市230601 
 
马金辉 国网安徽省电力有限公司, 安徽省合肥市 230061  
摘要:
      可再生能源在电力系统的渗透率不断增长,大规模分布式电源的接入对电力系统的优化调度带来新的挑战。在考虑分布式电源大规模接入的基础上,对电力系统进行集群划分和功优化研究。首先引入改进的电气距离的概念,以此作为聚类算法的距离量度,应用谱聚类方法,将含高渗透率分布式可再生能源系统划分为若干亚群落,并确定各集群内关键节点。再以网损和电压波动最小为优化目标,调节关键节点处光伏逆变器的功功率,达到减小网损和稳定电压输出的目的。为求解所建立的双目标功优化问题,提出基于改进粒子群优化算法的智能调压策略,对多个亚群落进行功优化。将集群划分方法和功优化策略应用于IEEE 33节点标准系统,提高了节点电压稳定性,降低了网损。针对大规模分布式能源系统,进一步提出快速智能调压策略,应用于安徽省金寨县某台区实际系统,得到良好控制效果,且在调节时间、运行成本、投入成本方面均有大幅削减。
Abstract:
      With the increase of distributed generator (DG) penetration in the power system, new challenges have been taken to the optimal operation of distributed system in large scale. The reactive power optimization is analyzed on the basis of cluster division with the consideration of DG integration. The modified electrical distance is introduced as the distance measurement in clustering algorithm. The spectral clustering method is applied to divide the high-denetration distributed renewable energy system into several sub-communities and determine the key nodes in each cluster. With the minimum network loss and voltage fluctuation as the optimization goal, the reactive power of the photovoltaic inverter at the key node is adjusted to reduce the network loss and stabilize the voltage output. In order to solve the problem of dual-objective reactive power optimization, an intelligent voltage regulation strategy based on improved particle swarm optimization algorithm is proposed to optimize reactive power for multiple sub-communities. The cluster division method and the reactive power optimization strategy are applied to the IEEE 33-bus standard system, which improves the node voltage stability and reduces the network loss. Aiming at the large-scale distributed energy system, a fast intelligent voltage regulation strategy is further proposed, which is applied to the actual system of a certain district in Jinzhai County, Anhui Province, and has good control effect, and has been greatly reduced in terms of adjustment time, operation cost and input cost.
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