Energy Management for Microgrid Systems
Algorithms and Applications
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Beschreibung
This book provides an in-depth discussion of the significance of energy management in microgrids, focusing on three key areas: multi-energy cooperative management in single and multi-microgrid systems, and energy management issues related to the Internet of Vehicles (IoV) in microgrids.
In Part 1, the book emphasizes the collaborative management of multiple energy sources, considering electric, gas, hydrogen, and renewable energy for a single microgrid system. In Part 2, it addresses the challenges in multi-microgrid systems and proposes a scheduling scheme for multi-energy cooperative management. Finally, Part 3 investigates the energy management challenges posed by the Internet of Vehicles in microgrids, and proposes a management scheme for electric vehicles (EVs) within microgrids using deep reinforcement learning.
Overall, the algorithms discussed in this book are essential for addressing the energy management challenges in microgrids.
This book provides an in-depth discussion of the significance of energy management in microgrids, focusing on three key areas: multi-energy cooperative management in single and multi-microgrid systems, and energy management issues related to the Internet of Vehicles (IoV) in microgrids.
In Part 1, the book emphasizes the collaborative management of multiple energy sources, considering electric, gas, hydrogen, and renewable energy for a single microgrid system. In Part 2, it addresses the challenges in multi-microgrid systems and proposes a scheduling scheme for multi-energy cooperative management. Finally, Part 3 investigates the energy management challenges posed by the Internet of Vehicles in microgrids, and proposes a management scheme for electric vehicles (EVs) within microgrids using deep reinforcement learning.
Overall, the algorithms discussed in this book are essential for addressing the energy management challenges in microgrids.
Addresses single and multiple microgrid systems, and the energy management of Internet of Vehicles in microgrids systems Provides innovative solutions and algorithms A future-oriented exploration of the field, addressing developments and challenges in microgrid energy management
Autor*in
Guanglin Zhang
Themen in »Energy Management for Microgrid Systems«
Microgrid Energy management Energy scheduling Combined heat and power (CHP) Energy storage Lyapunov optimization Online scheduling Renewable energy Cost minimization Hydrogen Carbon emission Power-to-gas (P2G) Deep reinforcement learning (DRL) Deep deterministic policy gradient (DDPG) Markov decision process (MDP)