LAPSE:2023.26510
Published Article

LAPSE:2023.26510
A Multi-Stage Coordinated Volt-Var Optimization for Integrated and Unbalanced Radial Distribution Networks
April 3, 2023
Abstract
The growing penetrations of rooftop photovoltaics (PVs) into low-voltage (LV) distribution networks are challenging voltage regulation. Developing an effective volt-var (VV) control has been the focus of many researchers with various approaches proposed so far. However, assuming a single voltage level and balanced network model, widely adopted in existing literatures, tends to cause inaccurate and even infeasible control solutions. Besides, existing distribution VV control studies are usually based on the day-ahead predictions of PV generations and loads, introducing inevitable and non-negligible errors. To address the challenges above, this paper proposes a VV co-optimization across unbalanced medium-voltage (MV) and LV networks, by traditional and emerging techniques, to ensure the network operation with the required power quality. Specifically, the operation of MV delta-connected switched capacitors and LV distributed PV inverters is coordinated, under a three-stage strategy that suits integrated and unbalanced radial distribution networks. The proposal aims to simultaneously improve voltage magnitude and balance profiles while reducing network power loss, at the least controlling cost. To effectively solve the proposed VV optimization problem, a joint solver of the modified particle swarm optimization and the improved direct load flow is employed. Finally, the proposal is evaluated by simulations on real Australian distribution networks over 24 h.
The growing penetrations of rooftop photovoltaics (PVs) into low-voltage (LV) distribution networks are challenging voltage regulation. Developing an effective volt-var (VV) control has been the focus of many researchers with various approaches proposed so far. However, assuming a single voltage level and balanced network model, widely adopted in existing literatures, tends to cause inaccurate and even infeasible control solutions. Besides, existing distribution VV control studies are usually based on the day-ahead predictions of PV generations and loads, introducing inevitable and non-negligible errors. To address the challenges above, this paper proposes a VV co-optimization across unbalanced medium-voltage (MV) and LV networks, by traditional and emerging techniques, to ensure the network operation with the required power quality. Specifically, the operation of MV delta-connected switched capacitors and LV distributed PV inverters is coordinated, under a three-stage strategy that suits integrated and unbalanced radial distribution networks. The proposal aims to simultaneously improve voltage magnitude and balance profiles while reducing network power loss, at the least controlling cost. To effectively solve the proposed VV optimization problem, a joint solver of the modified particle swarm optimization and the improved direct load flow is employed. Finally, the proposal is evaluated by simulations on real Australian distribution networks over 24 h.
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Keywords
coordinated optimization, integrated distribution networks, unbalance, volt-var control
Subject
Suggested Citation
Su X, Liu J, Tian S, Ling P, Fu Y, Wei S, SiMa C. A Multi-Stage Coordinated Volt-Var Optimization for Integrated and Unbalanced Radial Distribution Networks. (2023). LAPSE:2023.26510
Author Affiliations
Su X: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Liu J: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Tian S: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Ling P: Electric Power Research Institute of State Grid Shanghai Municipal Electric Power Company, Shanghai 200437, China
Fu Y: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Wei S: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
SiMa C: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Liu J: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Tian S: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Ling P: Electric Power Research Institute of State Grid Shanghai Municipal Electric Power Company, Shanghai 200437, China
Fu Y: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Wei S: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
SiMa C: School of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Journal Name
Energies
Volume
13
Issue
18
Article Number
E4877
Year
2020
Publication Date
2020-09-17
ISSN
1996-1073
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PII: en13184877, Publication Type: Journal Article
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LAPSE:2023.26510
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https://doi.org/10.3390/en13184877
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