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Cited by 23Optimal Power Flow DistributionMicrogrid Control and OptimizationSmart Grid Energy Management

Voltage Regulation Strategies in Photovoltaic-Energy Storage System Distribution Network: A Review

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Dong, Qianwen, Song, Xingyuan, Gong, Chunyang, Hu, Chenchen, Rui, Junfeng, Wang, Tingting, Xia, Ziyang, Wang, Zhixin·2025·Energies
DOI 10.3390/en18112740
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Abstract

With the increasing penetration of distributed photovoltaic-energy storage system (PV-ESS) access distribution networks, the safe and stable operation of the system has brought a huge impact, in which the voltage regulation of PV-ESS distribution networks is more prominent. This paper comprehensively reviews the voltage over-run mechanism in the PV-ESS distribution network and combs through the current mainstream voltage regulation strategies, of which two strategies of direct voltage regulation and current optimization are summarized. At the same time, this paper discusses the advantages and limitations of centralized, distributed, multi-timescale, voltage-reactive joint optimization and other regulation methods and focuses on the analysis of heuristic algorithms and algorithms based on deep reinforcement learning in the voltage regulation of the relevant research progress. Finally, this paper points out the main challenges currently facing voltage regulation in PV-ESS distribution networks, including cluster dynamic partitioning technologies, multi-timescale control of hybrid voltage regulation devices, and synergistic problems of demand-side resources, such as electric vehicle participation in voltage regulation, etc., and gives an outlook on future research directions. The aim of this paper is to provide a theoretical basis and practical guidance for voltage regulation of PV-ESS distribution networks and to promote the intelligent construction and sustainable development of power grids.

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  • Distributed multi-agent voltage control approaches for LV feeders have been developed where smart inverters share reactive power support based on local measurements and limited information exchange.

    “Other studies have developed distributed multi-agent voltage control approaches for LV feeders, where smart inverters share reactive power support based on local measurements and limited information exchange [93,94].”

    From Voltage Regulation in Rooftop PV-Rich Distribution Networks: A Review and Detailed Case Study (2026) · cites this paper as [93]

    Section 4.2 (page unavailable) describes distributed agents using local information and partial exchanges with neighboring nodes; it also reports neighboring controllers requesting reactive-power support. Section 3 describes multi-agent coordination of photovoltaic inverters. The passages do not establish that this combined approach was developed specifically for LV feeders, or that the inverters themselves share reactive-power support in that setting. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

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References 96 · Cited by 23

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Authors
Dong, Q., Song, X., Gong, C., Hu, C., Rui, J., Wang, T., Xia, Z., & Wang, Z.
Affiliations
  • Shanghai University of Electric Power (CN)
  • Shanghai Jiao Tong University (CN)
  • Lithos New Energy Group Company Limited, Shanghai 201615, China
  • Shanghai Institute of Quality Inspection and Technical Research (CN)
  • Nantong Legend Energy Co., Ltd., Nantong 226000, China
Corresponding author
  • Gong, Chunyang
  • Wang, Zhixin
ORCID
Venue
Energies
Publisher
MDPI AG
Published
2025-05-25
Volume
18
Issue
11
Pages
2740
ISSN
1996-1073 (ISSN-L)
DOI
10.3390/en18112740
OpenAlex
W4410721889
Cited by
23
References
96
Citations by year
2026: 19 · 2025: 4
FWCI
5.11
Type
journal article
Language
en
Open access
Licence
Locations
  • Energies (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Key R&D Program of China (2018YFB1503001, 24DZ3001500)
  • Science and Technology Commission of Shanghai Municipality (2018YFB1503001, 24DZ3001500)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
  • Physical Sciences › Engineering › Control and Systems Engineering › Microgrid Control and Optimization
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
Keywords
voltage regulation, photovoltaic energy storage system, distribution networks, current optimization, multi-timescale control, deep reinforcement learning, heuristic algorithms, demand-side resources

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