Reinforcement Learning for Energy-Storage Systems in Grid-Connected Microgrids: An Investigation of Online vs. Offline Implementation
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- Kapil Deshpande & Philipp Möhl & Alexander Hämmerle & Georg Weichhart & Helmut Zörrer & Andreas Pichler, 2022. "Energy Management Simulation with Multi-Agent Reinforcement Learning: An Approach to Achieve Reliability and Resilience," Energies, MDPI, vol. 15(19), pages 1-35, October.
- Marvin B. Sigalo & Saptarshi Das & Ajit C. Pillai & Mohammad Abusara, 2023. "Real-Time Economic Dispatch of CHP Systems with Battery Energy Storage for Behind-the-Meter Applications," Energies, MDPI, vol. 16(3), pages 1-20, January.
- Khawaja Haider Ali & Mohammad Abusara & Asif Ali Tahir & Saptarshi Das, 2023. "Dual-Layer Q-Learning Strategy for Energy Management of Battery Storage in Grid-Connected Microgrids," Energies, MDPI, vol. 16(3), pages 1-17, January.
- Anis ur Rehman & Muhammad Ali & Sheeraz Iqbal & Aqib Shafiq & Nasim Ullah & Sattam Al Otaibi, 2022. "Artificial Intelligence-Based Control and Coordination of Multiple PV Inverters for Reactive Power/Voltage Control of Power Distribution Networks," Energies, MDPI, vol. 15(17), pages 1-13, August.
- Pinciroli, Luca & Baraldi, Piero & Compare, Michele & Zio, Enrico, 2023. "Optimal operation and maintenance of energy storage systems in grid-connected microgrids by deep reinforcement learning," Applied Energy, Elsevier, vol. 352(C).
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Keywords
reinforcement learning (RL); microgrid; battery management; offline and online RL; optimisation;All these keywords.
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