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{ "item_title" : "Energy Management for Microgrid Systems", "item_author" : [" Guanglin Zhang", "Lin Wang", "Ming Chen "], "item_description" : "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. ", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/03/178/563/3031785630_b.jpg", "price_data" : { "retail_price" : "159.99", "online_price" : "159.99", "our_price" : "159.99", "club_price" : "159.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Energy Management for Microgrid Systems|Guanglin Zhang

Energy Management for Microgrid Systems : Algorithms and Applications

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Overview

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 item is Non-Returnable

Details

  • ISBN-13: 9783031785634
  • ISBN-10: 3031785630
  • Publisher: Springer
  • Publish Date: June 2025

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