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文章摘要
基于多层模型的智能配电网故障恢复方法研究
Research on Fault Recovery Methods for Intelligent Distribution Networks Based on Multilayer Models
Received:June 07, 2024  Revised:July 01, 2024
DOI:
中文关键词: 含DG配电网  故障恢复方法  多层建模  鲸鱼算法  二进制粒子群算法
英文关键词: Including  distributed generation  distribution network, Fault  recovery methods, Multi  layer modeling, Whale  algorithm, Binary  particle swarm  optimization algorithm
基金项目:国网浙江省电力有限公司省管产业单位科技项目(2022-KJLH--009)
Author NameAffiliationE-mail
Huang Hongsheng* State Grid Zhejiang Jiaxing District Power Supply CO.,LTD,Jiaxing,314033
China 
hongsheng923@163.com 
Liu Qiangqing State Grid Zhejiang Jiaxing District Power Supply CO.,LTD,Jiaxing,314033
China 
hongsheng923@163.com 
Zhong Lijun State Grid Zhejiang Jiaxing District Power Supply CO.,LTD,Jiaxing,314033
China 
7654153900@qq.com 
Shen Hongfeng State Grid Zhejiang Jiaxing District Power Supply CO.,LTD,Jiaxing,314033
China 
shongfeng12120@163.com 
Zhou Xinguo State Grid Zhejiang Jiaxing District Power Supply CO.,LTD,Jiaxing,314033
China 
zhouxgzhoux2006@163.com 
Liu Fengquan State Grid Zhejiang Jiaxing District Power Supply CO.,LTD,Jiaxing,314033
China 
lfqmail940916@163.com 
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中文摘要:
      针对现有含DG配电网故障恢复存在的效率低和可靠性差等问题,提出一种多层建模方法用于含DG配电网故障恢复。上层模型根据负荷水平和可控性建立孤岛划分模型,结合广义优先搜索法和深度优先搜索法求解模型。下层模型以最小网损、失电总功率最小、最少开关动作次数和电压偏移最小为目标建立主网供电恢复模型,结合改进二进制粒子群算法和改进鲸鱼算法求解模型。通过算例验证其优越性。结果表明,所提方法在含DG配电网故障恢复中具有较好的效果,能够更加可靠和高效的恢复故障供电,在完成故障恢复的基础上降低重构后网络损耗和改善电能质量。
英文摘要:
      Aiming at the problems of low efficiency and poor reliability in fault recovery of existing DG containing distribution networks, a multi-layer modeling method is proposed for fault recovery of DG containing distribution networks. The upper level model establishes an island partitioning model based on load level and controllability, and solves the model by combining generalized first search method and depth first search method. The lower level model aims to establish a main grid power recovery model with the minimum network loss, total power loss, minimum switching actions, and voltage offset as the objectives, the model is solved by combining the improved binary particle swarm optimization algorithm and the improved whale algorithm. Verify its superiority through numerical examples. The results indicate that, proposed method has good results in fault recovery of distribution networks containing DG, which can more reliably and efficiently restore faulty power supply, reduce network losses after reconstruction and improve power quality on the basis of completing fault recovery.
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