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文章摘要
基于“云-群-端”架构分布式光伏群调群控策略研究
Research on group control strategy of distributed photovoltaic based on “cloud-group-end” architecture
Received:October 21, 2022  Revised:November 14, 2022
DOI:j.issn1001-1390.2025.08.017
中文关键词: 分布式光伏  群调群控  群间协调  群内自治  节点电压
英文关键词: distributed photovoltaic, group control, inter-group coordination, intra-group autonomous, node voltage
基金项目:国家自然科学基金资助项目(51307152);国网河南省电力公司科技项目(20220256A)
Author NameAffiliationE-mail
ZHANG Linjuan Economic Research Institute of State Grid Henan Electric Power Company zlinj@163.com 
ZHANG Ping Economic Research Institute of State Grid Henan Electric Power Company 29188392@qq.com 
LU Dan Economic Research Institute of State Grid Henan Electric Power Company ludan555@qq.com 
HAN Junwei Economic Research Institute of State Grid Henan Electric Power Company 405702923@qq.com 
LI Jingli* School of Electrical and Information Engineering, Zhengzhou University lijingli1022@zzu.edu.cn 
YUAN Hao School of Electrical and Information Engineering ,Zhengzhou University yhaore0108@163.com 
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中文摘要:
      针对大规模分布式电源并网引起的电压波动、潮流返送等问题,开展分布式电源的群调群控策略研究是构建新型电力系统保障其安全稳定运行的重要基础工作。文中分析了分布式光伏并网时的可观可控性,提出基于“云-群-端”架构,并以集群为中间层的分布式光伏分层调控策略;其中云层调控中心整合并分析各集群的上传运行数据,选取能灵敏反映集群电压变化的主导节点,以整个区域节点电压不越限、系统的网损最小为目标,构建群间协调优化策略;集群层控制平台分析终端设备层上传的光伏电站运行数据、负荷信息以及无功补偿装置监测数据,以实现集群内部节点电压安全运行、集群网损最小以及分布式光伏的最大就地消纳为目标,构建群内自治优化调控策略。最后采用所提出的分布式电源群调群控优化策略对改进的IEEE 33节点系统节点电压安全运行、越限等多种典型场景进行优化调控,结果表明所提控制策略可有效解决电压越限等问题,并能减小节点电压偏差与系统网损,保障系统安全经济运行。
英文摘要:
      In view of the voltage fluctuations and power flow returns caused by large-scale distributed power grid-connection, the research on the group control strategy of distributed power is an important work for the construction of novel power system to ensure its safe and stable operation. In this paper, the observable controllability of distributed photovoltaic grid-connection is analyzed, and a distributed photovoltaic layer control strategy based on cloud-cluster-end architecture is proposed, with cluster as the middle layer. The cloud control center integrates and analyzes the uploaded operation data of each cluster, selects the dominant node which can sensitively reflect the voltage change of the cluster, and constructs a coordinated optimization strategy among the clusters with the goal of no overrun of the node voltage in the whole region and minimal network loss in the system. Cluster layer control platform analyzes the operation data, load information and reactive power compensation device monitoring data uploaded by the terminal device layer, so as to achieve the safe operation of node voltage within the cluster, the minimum network loss of the cluster and the maximum in-place absorption of distributed photovoltaic cells, and constructs an optimal control strategy within the cluster. Finally, the safe operation of node voltage in IEEE 33-node system, over-limit and other typical scenarios are optimized and controlled by the proposed distributed power group control optimization strategy. The results show that the proposed control strategy can effectively solve the over-limit voltage problem, reduce the node voltage deviation and system network loss, and ensure the safe and economic operation of the system.
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