Adaptive Online-Learning Volt-Var Control for Smart Inverters Using Deep Reinforcement Learning
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- Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
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- Ode Bokker & Henning Schlachter & Vanessa Beutel & Stefan Geißendörfer & Karsten von Maydell, 2022. "Reactive Power Control of a Converter in a Hardware-Based Environment Using Deep Reinforcement Learning," Energies, MDPI, vol. 16(1), pages 1-12, December.
- Jing Zhang & Yiqi Li & Zhi Wu & Chunyan Rong & Tao Wang & Zhang Zhang & Suyang Zhou, 2021. "Deep-Reinforcement-Learning-Based Two-Timescale Voltage Control for Distribution Systems," Energies, MDPI, vol. 14(12), pages 1-15, June.
- Yu Fujimoto & Akihisa Kaneko & Yutaka Iino & Hideo Ishii & Yasuhiro Hayashi, 2023. "Challenges in Smartizing Operational Management of Functionally-Smart Inverters for Distributed Energy Resources: A Review on Machine Learning Aspects," Energies, MDPI, vol. 16(3), pages 1-26, January.
- Jarosław Korpikiewicz & Mostefa Mohamed-Seghir, 2022. "Static Analysis and Optimization of Voltage and Reactive Power Regulation Systems in the HV/MV Substation with Electronic Transformer Tap-Changers," Energies, MDPI, vol. 15(13), pages 1-26, June.
- Franz Harke & Philipp Otto, 2023. "Solar Self-Sufficient Households as a Driving Factor for Sustainability Transformation," Sustainability, MDPI, vol. 15(3), pages 1-20, February.
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Keywords
deep reinforcement learning; low-voltage grid; reactive power; smart inverter; voltage control; volt-var-optimization;All these keywords.
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