Online EVs Vehicle-to-Grid Scheduling Coordinated with Multi-Energy Microgrids: A Deep Reinforcement Learning-Based Approach
Author:
Affiliation:
1. School of Electrical Engineering, Southeast University, Nanjing 210096, China
2. State Grid Jiangsu Electric Vehicle Service Co., Ltd., Nanjing 320105, China
Abstract
Funder
Jiangsu Province Key Research and Development Program
Jiangsu Key Laboratory of Smart Grid Technology and Equipment
Publisher
MDPI AG
Link
https://www.mdpi.com/1996-1073/17/11/2491/pdf
Reference34 articles.
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3. Martin, X.A., Escoto, M., Guerrero, A., and Juan, A.A. (2024). Battery Management in Electric Vehicle Routing Problems: A Review. Energies, 17.
4. Armenta-Déu, C., and Demas, L. (2024). Optimization of Grid Energy Balance Using Vehicle-to-Grid Network System. Energies, 17.
5. Belany, P., Hrabovsky, P., and Florkova, Z. (2024). Probability Calculation for Utilization of Photovoltaic Energy in Electric Vehicle Charging Stations. Energies, 17.
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