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portada Deep Learning for Power System Applications. Case Studies Linking Artificial Intelligence and Power Systems
Formato
Libro Físico
Colección
Power Electronics and Power Systems
Año
2024
N° páginas
101
Encuadernación
Tapa Blanda
Dimensiones
23.50 x 15.50 cm
ISBN13
9783031453595

Deep Learning for Power System Applications. Case Studies Linking Artificial Intelligence and Power Systems

Fangxing Li;Yan Du (Autor) · Springer International Publishing AG · Tapa Blanda

Deep Learning for Power System Applications. Case Studies Linking Artificial Intelligence and Power Systems - Fangxing Li;Yan Du

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Reseña del libro "Deep Learning for Power System Applications. Case Studies Linking Artificial Intelligence and Power Systems"

This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control. Deep Learning for Power System Applications: Case Studies Linking Artificial Intelligence and Power Systems is an ideal resource for professors, students, and industrial and government researchers in power systems, as well as practicing engineers and AI researchers. Provides a history of AI in power grid operation and planning;Introduces deep learning algorithms and applications in power systems;Includes several representative case studies.

This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control.
Deep Learning for Power System Applications: Case Studies Linking Artificial Intelligence and Power Systems is an ideal resource for professors, students, and industrial and government researchers in power systems, as well as practicing engineers and AI researchers.
Provides a history of AI in power grid operation and planning;Introduces deep learning algorithms and applications in power systems;
Includes several representative case studies.

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