Name: Deep Learning for Power System Applications. Case Studies Linking Artificial Intelligence and Power Systems
SKU: 64793505
Price: 3681.00 TWD
Availability: InStock
Author: Fangxing Li;Yan Du

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

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

Type

Physical Book

Publisher

Springer International Publishing AG

Author

Fangxing Li;Yan Du

Collection

Power Electronics and Power Systems

Year

2024

Pages

101

Format

Paperback

Dimensions

23.5x15.5 cm

ISBN13

9783031453595

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

Fangxing Li;Yan Du (Author) · Springer International Publishing AG · Paperback

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Synopsis "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.