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{ "item_title" : "AI Control Strategies for Optimal Power Distribution", "item_author" : [" Balasubramaniam S", "Aravind C. K", "B. Sundaravadivazhagan "], "item_description" : "The global energy landscape is transforming as economies prioritize decarbonization and energy resilience. Microgrids--intelligent, autonomous energy systems integrating renewable sources, energy storage, and advanced controls--are central to this revolution, offering a promising pathway to sustainable and secure energy. Their potential to revolutionize the sector is both promising and inspiring, motivating further exploration of their capabilities. However, microgrid operations present significant challenges because traditional rule-based approaches often struggle to accommodate uncertainties inherent in renewable energy systems and fluctuating load demandsAI Control Strategies for Optimal Power Distribution explores the intersection of artificial intelligence and renewable energy systems, with microgrids as its central focus. These small-scale power systems combine renewable sources like solar and wind with energy storage, offering cleaner, more reliable power for homes, businesses, and communities. The book provides a comprehensive overview of AI-driven control strategies for optimal power distribution in microgrids. It explores AI's theoretical foundations, applications in power systems, and the specific challenges and opportunities within microgrid contexts. The book illustrates distinct advancements in the microgrid space achieved through AI's transformative power. As AI transitions from predictive to generative capabilities, it facilitates multiple aspects of establishing and sustaining highly efficient, versatile microgrids. Explaining how combining AI and microgrids is game-changing, the book covers such AI applications as forecasting, optimization, and trading.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/1/04/108/051/1041080514_b.jpg", "price_data" : { "retail_price" : "180.00", "online_price" : "180.00", "our_price" : "180.00", "club_price" : "180.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
AI Control Strategies for Optimal Power Distribution|Balasubramaniam S

AI Control Strategies for Optimal Power Distribution : Ai-Based Strategies for Power Efficiency

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Overview

The global energy landscape is transforming as economies prioritize decarbonization and energy resilience. Microgrids--intelligent, autonomous energy systems integrating renewable sources, energy storage, and advanced controls--are central to this revolution, offering a promising pathway to sustainable and secure energy. Their potential to revolutionize the sector is both promising and inspiring, motivating further exploration of their capabilities. However, microgrid operations present significant challenges because traditional rule-based approaches often struggle to accommodate uncertainties inherent in renewable energy systems and fluctuating load demands

AI Control Strategies for Optimal Power Distribution explores the intersection of artificial intelligence and renewable energy systems, with microgrids as its central focus. These small-scale power systems combine renewable sources like solar and wind with energy storage, offering cleaner, more reliable power for homes, businesses, and communities. The book provides a comprehensive overview of AI-driven control strategies for optimal power distribution in microgrids. It explores AI's theoretical foundations, applications in power systems, and the specific challenges and opportunities within microgrid contexts. The book illustrates distinct advancements in the microgrid space achieved through AI's transformative power. As AI transitions from predictive to generative capabilities, it facilitates multiple aspects of establishing and sustaining highly efficient, versatile microgrids. Explaining how combining AI and microgrids is game-changing, the book covers such AI applications as forecasting, optimization, and trading.

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Details

  • ISBN-13: 9781041080510
  • ISBN-10: 1041080514
  • Publisher: Auerbach Publications
  • Publish Date: December 2026
  • Page Count: 296

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