A Multi-Agent Framework for Voltage Regulation Control in Distribution Systems

被引:0
|
作者
Sreechithra, Sumith Madampath [1 ]
Jirutitijaroen, Panida [1 ]
机构
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 119077, Singapore
关键词
Distribution system voltage control; Multi-agent framework; Photovoltaic agents;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As the penetration of distributed generation (DG) increases in distribution power systems, it causes voltage rises and voltage fluctuations in the systems. The DG units can be properly controlled to mitigate these power quality issues. There are several methods of controlling the DG units for achieving acceptable voltage profile. This paper investigates a decentralized control approach to handle voltage regulation problems in the distribution systems. The objective of this paper is to discuss the design of a multi-agent framework for a decentralized voltage control in the distribution systems. We discuss the selection, coordination and interaction of agents required to achieve the desired voltage profile.
引用
收藏
页码:106 / 111
页数:6
相关论文
共 50 条
  • [21] Distributed Formation Control: A Generalized Framework for Multi-Agent and Network Systems
    Ahn, Hyo-Sung
    [J]. IEEE 13TH INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI 2019), 2019, : 13 - 13
  • [22] Decentralized Multi-Agent Algorithm for Voltage Control
    Panasetsky, Daniil
    Tomin, Nikita
    Sidorov, Denis
    Kurbatsky, Viktor
    Osak, Alexey
    [J]. 2016 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2016, : 852 - 856
  • [23] A Multi-agent Cooperative Voltage Control Method
    Nagata, T.
    Nakachi, Y.
    Hatano, R.
    [J]. 2008 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, VOLS 1-11, 2008, : 3685 - +
  • [24] Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks
    Wang, Jianhong
    Xu, Wangkun
    Gu, Yunjie
    Song, Wenbin
    Green, Tim C.
    [J]. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 34 (NEURIPS 2021), 2021, 34
  • [25] Containment Control for the Cooperative Output Regulation of Linear Multi-Agent Systems
    Shen Yanchao
    Yan Huaicheng
    Zhang Hao
    Shi Hongbo
    [J]. 2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 7296 - 7301
  • [26] An Improved Distributed Control on Output Regulation for Heterogeneous Multi-Agent Systems
    Zhang, Ji-Lie
    Feng, Tao
    Yan, Fei
    Zhou, Yiduo
    [J]. 2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 6579 - 6583
  • [27] Design of a Multi-Agent System for Distributed Voltage Regulation
    Chen, Minjiang
    Athanasiadis, Dimitrios
    Al Faiya, Badr
    McArthur, Stephen
    Kockar, Ivana
    Lu, Haowei
    de Leon, Francisco
    [J]. 2017 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM APPLICATION TO POWER SYSTEMS (ISAP), 2017,
  • [28] A novel formation control for multi-agent systems by nonlinear output regulation
    Li Weixun
    Chen Zengqiang
    Liu Zhongxin
    [J]. 2013 32ND CHINESE CONTROL CONFERENCE (CCC), 2013, : 7066 - 7071
  • [29] Output regulation distributed formation control for nonlinear multi-agent systems
    Li, Weixun
    Chen, Zengqiang
    Liu, Zhongxin
    [J]. NONLINEAR DYNAMICS, 2014, 78 (02) : 1339 - 1348
  • [30] Output regulation distributed formation control for nonlinear multi-agent systems
    Weixun Li
    Zengqiang Chen
    Zhongxin Liu
    [J]. Nonlinear Dynamics, 2014, 78 : 1339 - 1348