Abstract
This paper proposes a multi-Agent deep reinforcement learning-based approach for distribution system voltage regulation with high penetration of photovoltaics (PVs). The designed agents can learn the coordinated control strategies from historical data through the counter-Training of local policy networks and centric critic networks. The learned strategies allow us to perform online coordinated control. Comparative results with other methods show the enhanced control capability of the proposed method under various conditions.
Original language | English |
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Article number | 9113746 |
Journal | I E E E Transactions on Power Electronics |
Volume | 35 |
Issue number | 5 |
Pages (from-to) | 4120-4123 |
Number of pages | 4 |
ISSN | 0885-8993 |
DOIs | |
Publication status | Published - Sept 2020 |
Keywords
- voltage regulation
- multi-agent deep reinforcement learning
- coordinated control
- Distributed system