{"title":"Distributed Diffusion-Oriented Cooperation for Power Sharing in Self-Expanding Microgrids","authors":"Jingang Lai, Xiaoqing Lu, Fei Wang","doi":"10.1109/ICPS51807.2021.9416592","DOIUrl":null,"url":null,"abstract":"This paper proposes a multiagent-based distributed self-organizing control scheme that will enable the power sharing of massive renewable distributed generators (DG) in a low-voltage microgird. The proposed fully distributed self-organizing control strategy can achieve effective power sharing challenge among massive DGs by adopts a peer-to-peer diffusion protocol, in which DGs from the same neighborhood are allowed to communicate with each other at every iteration. Furthermore, learning adaptability via automatic agent discovery is proposed to alter topologies as a result of incoming or outgoing DGs in the microgird network. The resulting algorithm is distributed, cooperative and able to respond in real time to changes in the environment. Eventually, the proposed algorithm is superior over consensus algorithms in terms of convergence speed and utilizes reduced communication infrastructure compared to centralized controllers. The proposed approach can handle networks of different size and topology using the information about the number of nodes which is also evaluated in a distributed fashion. The effectiveness of the proposed control strategy is verified under various scenarios by a modified IEEE 34-bus test network.","PeriodicalId":350508,"journal":{"name":"2021 IEEE/IAS 57th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/IAS 57th Industrial and Commercial Power Systems Technical Conference (I&CPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPS51807.2021.9416592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a multiagent-based distributed self-organizing control scheme that will enable the power sharing of massive renewable distributed generators (DG) in a low-voltage microgird. The proposed fully distributed self-organizing control strategy can achieve effective power sharing challenge among massive DGs by adopts a peer-to-peer diffusion protocol, in which DGs from the same neighborhood are allowed to communicate with each other at every iteration. Furthermore, learning adaptability via automatic agent discovery is proposed to alter topologies as a result of incoming or outgoing DGs in the microgird network. The resulting algorithm is distributed, cooperative and able to respond in real time to changes in the environment. Eventually, the proposed algorithm is superior over consensus algorithms in terms of convergence speed and utilizes reduced communication infrastructure compared to centralized controllers. The proposed approach can handle networks of different size and topology using the information about the number of nodes which is also evaluated in a distributed fashion. The effectiveness of the proposed control strategy is verified under various scenarios by a modified IEEE 34-bus test network.