UID:
almahu_9949568575302882
Format:
1 online resource (235 p.).
ISBN:
9781000921786
,
1000921786
,
9781003301820
,
1003301827
,
9781000921793
,
1000921794
Series Statement:
Advances in Computational Collective Intelligence
Content:
An electrical power system consists of a large number of generation, transmission, and distribution subsystems. It is a very large and complex system; hence, its installation and management are very difficult tasks. An electrical system is essentially a very large network with very large data sets. Handling these data sets can require much time to analyze and subsequently implement. An electrical system is necessary but also potentially very dangerous if not operated and controlled properly. The demand for electricity is ever increasing, so maintaining load demand without overloading the system poses challenges and difficulties. Thus, planning, installing, operating, and controlling such a large system requires new technology. Artificial intelligence (AI) applications have many key features that can support a power system and handle overall power system operations. AI-based applications can manage the large data sets related to a power system. They can also help design power plants, model installation layouts, optimize load dispatch, and quickly respond to control apparatus. These applications and their techniques have been successful in many areas of power system engineering. Artificial Intelligence Techniques in Power Systems Operations and Analysis focuses on the various challenges arising in power systems and how AI techniques help to overcome these challenges. It examines important areas of power system analysis and the implementation of AI-driven analysis techniques. The book helps academicians and researchers understand how AI can be used for more efficient operation. Multiple AI techniques and their application are explained. Also featured are relevant data sets and case studies. Highlights include: Power quality enhancement by PV-UPQC for non-linear load Energy management of a nanogrid through flair of deep learning from IoT environments Role of artificial intelligence and machine learning in power systems with fault detection and diagnosis AC power optimization techniques Artificial intelligence and machine learning techniques in power systems automation
Note:
Description based upon print version of record.
,
Cover -- Half Title -- Series -- Title -- Copyright -- Contents -- List of Contributors -- 1 Faults Diagnosis Using AI and ML -- 2 Load Frequency Control for Multi-Area Power System Using PSO-Based Technique -- 3 Power Quality Enhancement by PV-UPQC for Non-Linear Load -- 4 A Hybrid Energy Management for Stand-Alone Microgrids Using Grey Wolf Optimization System -- 5 Energy Management of Nanogrid through Flair of Deep Learning from IoT Environments -- 6 An Elitism-Based SAMP-JAYA Algorithm for Optimal VA Loading of Unified Power Quality Conditioner -- 7 Applications of Artificial Intelligence
,
8 Role of Artificial Intelligence and Machine Learning in Power Systems with Fault Detection and Diagnosis -- 9 AC Power Optimization Technique -- 10 Data Transformation: A Preprocessing Stage in Machine Learning Regression Problems -- 11 Predicting Native Language with Machine Learning: An Automated Approach -- 12 Artificial Intelligence and Machine Learning Techniques in Power Systems Automation -- Index
Additional Edition:
Print version: Singh, Nagendra Artificial Intelligence Techniques in Power Systems Operations and Analysis Milton : Auerbach Publishers, Incorporated,c2023 ISBN 9781032294865
Language:
English
DOI:
10.1201/9781003301820
URL:
https://www.taylorfrancis.com/books/9781003301820
