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Deep Learning for Power System Applications : Case Studies Linking Artificial Intelligence and Power Systems / by Fangxing Li, Yan Du.

Springer eBooks EBA - Energy Collection 2024 Available online

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Format:
Book
Author/Creator:
Li, Fangxing.
Contributor:
Du, Yan.
Series:
Power Electronics and Power Systems, 2196-3193
Language:
English
Subjects (All):
Electric power production.
Electric power distribution.
Energy policy.
Artificial intelligence.
Machine learning.
Electrical Power Engineering.
Energy Grids and Networks.
Energy Policy, Economics and Management.
Artificial Intelligence.
Machine Learning.
Local Subjects:
Electrical Power Engineering.
Energy Grids and Networks.
Energy Policy, Economics and Management.
Artificial Intelligence.
Machine Learning.
Physical Description:
1 online resource (111 pages)
Edition:
1st ed. 2024.
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2024.
Summary:
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.
Contents:
Introduction-A Brief History of Deep Learning and Its Applications in Power Systems
Deep Neural Network for Microgrid Management
Deep Convolutional Neural Network for Power System N-1 Contingency Screening and Cascading Outage Screening
Intelligent Multi-zone Residential HVAC Control Strategy Based on Deep Reinforcement Learning
Summary and Future Works.
ISBN:
9783031453571
3031453573

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