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AI-Enhanced Operation and Management of Renewable Energy-Integrated Power Systems - Couverture rigide
Synopsis
This Reprint addresses the emerging paradigm of AI-enhanced operation and management in power systems with high penetration of renewable energy sources. As renewable-rich power systems become increasingly complex and uncertain, AI is poised to reshape traditional operational practices and decision-making processes. The works collated within this Reprint present recent advances in data-driven wind and photovoltaic forecasting, intelligent state estimation and sensing, adaptive and robust scheduling of integrated energy systems, and AI-enabled decision-making for active distribution networks and coupled infrastructures. These studies demonstrate that AI technologies can complement or extend conventional model-based approaches to better manage variability, uncertainty, and scalability challenges. Beyond individual methods, this Reprint highlights a broader shift from static, centralized operation toward adaptive, distributed, and system-aware management frameworks. Several contributions illustrate that AI can integrate heterogeneous information across generation, grids, loads, and external systems, enabling more responsive and low-carbon operational strategies, while others emphasize uncertainty-aware pricing, robust optimization, and voltage or flexibility support aligned with physical and market constraints. By bringing together these perspectives, this Reprint provides a timely overview of how AI-enhanced methodologies are shaping the next generation of renewable-rich power systems.
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AI-Enhanced Operation and Management of Renewable Energy-Integrated Power Systems
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AI-Enhanced Operation and Management of Renewable Energy-Integrated Power Systems (Hardcover)
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Hardcover. Etat : new. Hardcover. This Reprint addresses the emerging paradigm of AI-enhanced operation and management in power systems with high penetration of renewable energy sources. As renewable-rich power systems become increasingly complex and uncertain, AI is poised to reshape traditional operational practices and decision-making processes. The works collated within this Reprint present recent advances in data-driven wind and photovoltaic forecasting, intelligent state estimation and sensing, adaptive and robust scheduling of integrated energy systems, and AI-enabled decision-making for active distribution networks and coupled infrastructures. These studies demonstrate that AI technologies can complement or extend conventional model-based approaches to better manage variability, uncertainty, and scalability challenges. Beyond individual methods, this Reprint highlights a broader shift from static, centralized operation toward adaptive, distributed, and system-aware management frameworks. Several contributions illustrate that AI can integrate heterogeneous information across generation, grids, loads, and external systems, enabling more responsive and low-carbon operational strategies, while others emphasize uncertainty-aware pricing, robust optimization, and voltage or flexibility support aligned with physical and market constraints. By bringing together these perspectives, this Reprint provides a timely overview of how AI-enhanced methodologies are shaping the next generation of renewable-rich power systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783725870905
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AI-Enhanced Operation and Management of Renewable Energy-Integrated Power Systems
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AI-Enhanced Operation and Management of Renewable Energy-Integrated Power Systems
Edité par
Mdpi AG, 2026
ISBN 10 : 372587090X
ISBN 13 : 9783725870905
Ancien ou d'occasion
Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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AI-Enhanced Operation and Management of Renewable Energy-Integrated Power Systems (Hardcover)
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Hardcover. Etat : new. Hardcover. This Reprint addresses the emerging paradigm of AI-enhanced operation and management in power systems with high penetration of renewable energy sources. As renewable-rich power systems become increasingly complex and uncertain, AI is poised to reshape traditional operational practices and decision-making processes. The works collated within this Reprint present recent advances in data-driven wind and photovoltaic forecasting, intelligent state estimation and sensing, adaptive and robust scheduling of integrated energy systems, and AI-enabled decision-making for active distribution networks and coupled infrastructures. These studies demonstrate that AI technologies can complement or extend conventional model-based approaches to better manage variability, uncertainty, and scalability challenges. Beyond individual methods, this Reprint highlights a broader shift from static, centralized operation toward adaptive, distributed, and system-aware management frameworks. Several contributions illustrate that AI can integrate heterogeneous information across generation, grids, loads, and external systems, enabling more responsive and low-carbon operational strategies, while others emphasize uncertainty-aware pricing, robust optimization, and voltage or flexibility support aligned with physical and market constraints. By bringing together these perspectives, this Reprint provides a timely overview of how AI-enhanced methodologies are shaping the next generation of renewable-rich power systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9783725870905
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Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Reprint addresses the emerging paradigm of AI-enhanced operation and management in power systems with high penetration of renewable energy sources. As renewable-rich power systems become increasingly complex and uncertain, AI is poised to reshape traditional operational practices and decision-making processes. The works collated within this Reprint present recent advances in data-driven wind and photovoltaic forecasting, intelligent state estimation and sensing, adaptive and robust scheduling of integrated energy systems, and AI-enabled decision-making for active distribution networks and coupled infrastructures. These studies demonstrate that AI technologies can complement or extend conventional model-based approaches to better manage variability, uncertainty, and scalability challenges. Beyond individual methods, this Reprint highlights a broader shift from static, centralized operation toward adaptive, distributed, and system-aware management frameworks. Several contributions illustrate that AI can integrate heterogeneous information across generation, grids, loads, and external systems, enabling more responsive and low-carbon operational strategies, while others emphasize uncertainty-aware pricing, robust optimization, and voltage or flexibility support aligned with physical and market constraints. By bringing together these perspectives, this Reprint provides a timely overview of how AI-enhanced methodologies are shaping the next generation of renewable-rich power systems. N° de réf. du vendeur 9783725870905
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