Cost-effective coordinated voltage control in active distribution networks with photovoltaics and mobile energy storage systems
Abstract
High penetration of intermittent renewable energy resources (RES) will impose great challenges on the conventional voltage control in distribution networks. This paper proposes a two-stage cost-effective coordinated voltage control strategy to mitigate fast voltage violations while minimizing the total voltage regulation cost. In the first stage, the optimal power flow (OPF) is performed to determine the day-ahead dispatch results of on-load tap changers (OLTC) and capacitor banks (CBs). The hourly charging schedule of mobile energy storage systems (MESS) is also obtained through a spatial-temporal decision model embedded in the optimization problem. In the second stage, the real-time voltage control strategy is implemented to regulate the power output of photovoltaics (PVs) and MESS with one minute resolution. A novel fine-tuning control method is proposed to adjust the power output, which can further reduce voltage regulation cost within a certain voltage dead band. To reserve more fast-response power resources for PVs and MESS, the voltage regulation cost curves are designed as a piecewise linear function with different per unit cost in each range. The proposed approach is tested on the IEEE 33-bus and 123-bus distribution systems and comparative simulation results show the enhanced control effect in mitigating voltage violations and saving costs.
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Voltage-var control (VVC) has become a central task in modern distribution system operation and in the day-to-day operation of grid-connected community microgrids.
“As a result, voltage-var control (VVC) has become a central task in modern distribution system operation and, more specifically, in the day-to-day operation of gridconnected community microgrids [2,3].”
From Physics-Informed AI-Based EV smart inverter control for two-stage Volt/Var coordination in renewable-rich active distribution networks (2026) · cites this paper as [3]
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Zhong, Y., Qiu, J., Yang, Y., Zhang, C., Tao, Y., Sun, X., & Lai, S. (2026) · Energy and AI · doi:10.1016/j.egyai.2026.100869
Self-citation
- Authors
- Sun, X., Qiu, J., Yi, Y., & Tao, Y.
- Affiliations
- The University of Sydney (AU)
- Venue
- IEEE Transactions on Sustainable Energy
- Published
- 2022-01
- Volume
- 13
- Issue
- 1
- Pages
- 501-513
- ISSN
- 1949-3029 (ISSN-L)
- 1949-3037
- OpenAlex
- W3205868375
- Cited by
- 87
- References
- 0
- Citations by year
- 2026: 16 · 2025: 18 · 2024: 33 · 2023: 10 · 2022: 9 · 2021: 1
- FWCI
- 3.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Sustainable Energy (publishedVersion)
- Funders
- ARC Research Hub (IH180100020)
- ARC Training Centre (IC200100023, ,)
- ARC Linkage Project (LP200100056)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Control and Systems Engineering › Microgrid Control and Optimization
- Keywords
- coordinated voltage control, active distribution networks, photovoltaics, mobile energy storage, on-load tap changer, capacitor bank, optimal power flow, day-ahead dispatch, real-time voltage control, piecewise linear cost function
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