Fair Reinforcement Learning Algorithm for PV Active Control in LV Distribution Networks
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Abstract (arXiv)
The increasing adoption of distributed energy resources, particularly photovoltaic (PV) panels, has presented new and complex challenges for power network control. With the significant energy production from PV panels, voltage issues in the network have become a problem. Currently, PV smart inverters (SIs) are used to mitigate the voltage problems by controlling their active power generation and reactive power injection or absorption. However, reducing the active power output of PV panels can be perceived as unfair to some customers, discouraging future installations. To solve this issue, in this paper, a reinforcement learning technique is proposed to address voltage issues in a distribution network, while considering fairness in active power curtailment among customers. The feasibility of the proposed approach is explored through experiments, demonstrating its ability to effectively control voltage in a fair and efficient manner.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 26 references that are in the map. First posted on arXiv 9 Sep 2024.
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6 of 26 references.
References · 6
- 2015Continuous control with deep reinforcement learningcited by 3,407
- 2017Deep Reinforcement Learning: An Overviewcited by 333
- 2021Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networkscited by 54
- 2019Distributed Optimal Voltage Control with Asynchronous and Delayed Communicationcited by 4
- 2022Model-Free Approach to Fair Solar PV Curtailment Using Reinforcement Learningcited by 2
- 2019Resilient Decentralized Control of Inverter-interfaced Distributed Energy Sources in Low-voltage Distribution Gridscited by 1
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- 2026Two-Stage Active Distribution Network Voltage Control via LLM-RL Collaboration: A Hybrid Knowledge-Data-Driven Approach
- 2025Partially Observable Residual Reinforcement Learning for PV-Inverter-Based Voltage Control in Distribution Grids
- 2025Leveraging Predictions in Power System Voltage Control: An Adaptive Approach ↗
- 2025Distributed Reinforcement Learning using Local Smart Meter Data for Voltage Regulation in Distribution Networks
- 2025Offline Reinforcement Learning for Microgrid Voltage Regulation
- 2025Optimizing Power Grid Topologies with Reinforcement Learning: A Survey of Methods and Challenges
- 2024Safety Constrained Multi-Agent Reinforcement Learning for Active Voltage Control