Smart cyber-physical power systems : (Record no. 95972)

000 -LEADER
fixed length control field 12483cam a2200625 i 4500
001 - CONTROL NUMBER
control field 14321125
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260724155208.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cnu---unuuu
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250308s2025 njua ob 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394334568
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1394334575
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394334599
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1394334591
Qualifying information electronic book
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394334582
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1394334583
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781394334575
Qualifying information (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 1394334567
Qualifying information hardcover
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9781394334568
Qualifying information hardcover
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1002/9781394334599
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1504823410
035 #9 - SYSTEM CONTROL NUMBER
System control number (OCLCCM-Owned)1504823410
037 ## - SOURCE OF ACQUISITION
Stock number 10922799
Source of stock number/acquisition IEEE
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TJ213
Item number .S485 2025
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 23
Classification number 006.22
245 00 - TITLE STATEMENT
Title Smart cyber-physical power systems :
Remainder of title solutions from emerging technologies.
Number of part/section of a work Volume 2 /
Statement of responsibility, etc edited by Ali Parizad, Hamid Reza Baghaee, Saifur Rahman.
264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Hoboken, New Jersey :
Name of publisher, distributor, etc John Wiley & Sons, Inc. ;
Place of publication, distribution, etc Piscataway, NJ :
Name of publisher, distributor, etc IEEE Press,
Date of publication, distribution, etc [2025]
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xxxix, 576 pages) :
Other physical details color illustrations.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
490 1# - SERIES STATEMENT
Series statement IEEE Press series on power and energy systems ;
Volume number/sequential designation 131
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 0# - CONTENTS
Formatted contents note About the Editors -- List of Contributors -- Foreword (John D. McDonald) -- Foreword (Massoud Amin) -- Preface for Volume 2: Smart Cyber-Physical Power Systems: Solutions from Emerging Technologies -- Acknowledgments -- 1 Information Theory and Gray Level Transformation Techniques in Detecting False Data Injection Attacks on Power System State Estimation 1 Ali Parizad and Constantine Hatziadoniu -- 1.1 Introduction -- 1.2 Cyber-attacks on the State Variables of the Power System -- 1.3 Information Theory -- 1.4 Gray Level Transformation -- 1.5 Linear Transformation -- 1.6 Logarithmic Transformations -- 1.7 Power-Law Transformations -- 1.8 Simulation Results -- 1.9 Conclusion -- References -- 2 Artificial Intelligence and Machine Learning Applications in Modern Power Systems 49 Sohom Datta, Zhangshuan Hou, Milan Jain, and Syed Ahsan Raza Naqvi -- 2.1 The Need for AI/ML in Modern Power Systems -- 2.2 AL/ML Algorithms in Power System Applications -- 2.3 AI/ML-Based Applications in the Electricity Grid -- 2.4 Future of AI/ML in Power Systems -- References -- 3 Physics-Informed Deep Reinforcement Learning-Based Control in Power Systems 67 Ramij Raja Hossain, Qiuhua Huang, Kaveri Mahapatra, and Renke Huang -- 3.1 Introduction -- 3.2 Overview of RL/DRL -- 3.3 Grid Control Perspectives -- 3.4 Importance of Physics-Informed DRL in Grid Control and Different Methods -- 3.5 Grid Control Applications of Physics-Informed DRL -- 3.6 Discussion and Research Directions -- 3.7 Conclusions -- References -- 4 Digital Twin Approach Toward Modern Power Systems 79 Sabrieh Choobkar -- 4.1 Digital Twin Concept -- 4.2 Digital Twin: The Convergence of Recent Technologies -- 4.3 Cyber-Physical System and Digital Twin -- 4.4 Novelties and Suggestions of Digital Twin to Smart Grid Subsystems -- 4.5 Conclusions -- References -- 5 Application of AI and Machine Learning Algorithms in Power System State Estimation 93 Behrouz Azimian, Reetam Sen Biswas, and Anamitra Pal -- 5.1 Introduction -- 5.2 Motivation and Theoretical Background -- 5.3 DNN Architecture for DSSE and TI -- 5.4 SMD Measurement Selection for DSSE and TI -- 5.5 Smart Meter Data Consideration -- 5.6 Implementation of DNN-Based TI and DSSE -- 5.7 Conclusion -- Acknowledgment -- Appendix -- References -- 6 ANN-Based Scenario Generation Approach for Energy Management of Smart Buildings 131 Mahoor Ebrahimi, Mahan Ebrahimi, Miadreza Shafie-khah, Hannu Laaksonen, and Pierluigi Siano -- 6.1 Introduction -- 6.2 Problem Formulation -- 6.3 Application of AI in Energy Management of Smart Homes -- 6.4 Simulation and Results -- 6.5 Conclusion -- References -- 7 Protection Challenges and Solutions in Power Grids by AI/Machine Learning 149 Ali Bidram -- 7.1 Introduction -- 7.2 Zonal Setting-Less Modular Protection Using ml -- 7.3 Traveling Wave Protection of dc Microgrids Using ml -- 7.4 Conclusion -- References -- 8 Deep and Reinforcement Learning for Active Distribution Network Protection 171 Mohammed AlSaba and Mohammad Abido -- 8.1 Introduction and Motivation -- 8.2 Problem Statement -- 8.3 Proposed Methodology for Fault Detection and Classification -- 8.4 Case Study and Implementation -- 8.5 Results and Discussion -- 8.6 Hardware in-the-Loop Testing -- 8.7 Conclusion -- Acknowledgments -- References -- 9 Handling and Application of Big Data in Modern Power Systems for Planning, Operation, and Control Processes 189 Meghana Ramesh, Jing Xie, Monish Mukherjee, Thomas E. McDermott, Anjan Bose, and Michael Diedesch -- 9.1 Introduction -- 9.2 Intelligent Modeling and Its Applications -- 9.3 Case Study -- 9.4 Conclusions -- Acknowledgment -- References -- 10 Handling and Application of Big Data in Modern Power Systems for Situational Awareness and Operation 209 Yingqi Liang, Junbo Zhao, and Dipti Srinivasan -- 10.1 Introduction -- 10.2 Challenges for Using Big Data Techniques in Smart Grids -- 10.3 Solutions Using Big Data Techniques for Smart Grid Situational Awareness -- 10.4 Applications of Big Data Techniques for Smart Grid Operation -- 10.5 Numerical Results -- 10.6 Concluding -- References -- 11 Data-Driven Methods in Modern Power System Stability and Security 255 Jinpeng Guo, Georgia Pierrou, Xiaoting Wang, Mohan Du, and Xiaozhe Wang -- 11.1 Introduction -- 11.2 Data-Driven Wide-Area Damping Control -- 11.3 Data-Driven Wide-Area Voltage Control -- 11.4 Data-Driven Inertia Estimation for Frequency Control -- 11.5 A Data-Driven Polynomial Chaos Expansion Method for Available Transfer Capability Assessment -- 11.6 Using PCE to Assess the Ramping Support Capability of a Microgrid -- References -- 12 Application of Quantum Computing for Power Systems 313 Yan Li, Ganesh K. Venayagamoorthy, and Liang -- 12.1 Quantum Computing in Renewable Energy Systems -- 12.2 Quantum Approximate Optimization Algorithm for Renewable Energy Systems -- 12.3 Typical Applications of Quantum Computing -- Acknowledgment -- References -- 13 High-Resolution Building-Level Load Forecasting Employing Convolutional Neural Networks (CNNs) and Cloud Computing Techniques: Part 1 Principles and Concepts 323 Zejia Jing, Ali Parizad, and Saifur Rahman -- 13.1 Introduction -- 13.2 Principles and Concepts of Building Hourly Energy Consumption Forecasting -- 13.3 Conclusion -- References -- 14 High-Resolution Building-Level Load Forecasting Employing Convolutional Neural Networks (CNNs) and Cloud Computing Techniques: Part 2 Simulation and Experimental Results 363 Zejia Jing, Ali Parizad, and Saifur Rahman -- 14.1 Introduction -- 14.2 Case Study and Result of Building Hourly Energy Consumption Forecasting -- 14.3 Building Occupancy Measurement -- 14.4 Conclusion -- 15 PV Energy Forecasting Applying Machine Learning Methods Targeting Energy Trading Systems 417 Zejia Jing, Ali Parizad, and Saifur Rahman -- 15.1 Introduction -- 15.2 PV Energy Forecasting -- 15.3 Conclusion -- References -- 16 An Intelligent Reinforcement-Learning-Based Load Shedding to Prevent Voltage Instability 449 Pouria Akbarzadeh Aghdam, Hamid Khoshkhoo, and Ahmad Akbari -- 16.1 Introduction -- 16.2 Stability Control Methods -- 16.3 Characteristics of Optimal Stability Controller -- 16.4 Utilizing Reinforcement Learning for Enhancing Voltage Stability -- 16.5 Taxonomy of RL -- 16.6 Proposed Algorithm -- 16.7 Reinforcement Learning Algorithm Components -- 16.8 Algorithm Implementation Process -- 16.9 Simulations and Results -- 16.10 Scenario I -- 16.11 Scenario II -- 16.12 Scenario III -- 16.13 Conclusion -- References -- 17 Deep Learning Techniques for Solving Optimal Power Flow Problems 471 Vassilis Kekatos and Manish K. Singh -- 17.1 Introduction -- 17.2 Sensitivity-Informed Learning for OPF -- 17.3 Deep Learning for Stochastic OPF -- 17.4 Conclusions -- References -- 18 Research on Intelligent Prediction of Spatial-Temporal Dynamic Frequency Response and Performance Evaluation 501 Xieli Sun, Longyu Chen, and Xiaoru Wang -- 18.1 Introduction -- 18.2 Modeling Process and Evaluation Method -- 18.3 Case Study -- 18.4 Conclusion -- References -- 19 Emerging Technologies and Future Trends in Cyber-Physical Power Systems: Toward a New Era of Innovations 525 Ali Parizad, Hamid Reza Baghaee, Vahid Alizadeh, and Saifur Rahman -- 19.1 Introduction -- 19.2 Paradigm Shifts in Power Transmission and Management -- 19.3 Innovations in Electric Mobility and Sustainable Transportation -- 19.4 Digital Transformation and Technological Convergence in Cyber-Physical Power Systems -- 19.5 Cyber-Physical Systems Enhancing Societal Well-Being -- 19.6 Toward a Decentralized and Automated Future -- 19.7 Overcoming Challenges with Advanced Technologies -- 19.8 Revolutionizing Modern Power Systems with Real-Time Simulators -- 19.9 Emerging Trends Shaping the Future Energy Landscape -- 19.10 Conclusion -- References -- Index.
520 ## - SUMMARY, ETC.
Summary, etc "A practical roadmap to the application of artificial intelligence and machine learning to power systems. In an era where digital technologies are revolutionizing every aspect of power systems, Smart Cyber-Physical Power Systems, Volume 2: Solutions from Emerging Technologies shifts focus to cutting-edge solutions for overcoming the challenges faced by cyber-physical power systems (CPSs). By leveraging emerging technologies, this volume explores how innovations like artificial intelligence, machine learning, blockchain, quantum computing, digital twins, and data analytics are reshaping the energy sector. This volume delves into the application of AI and machine learning in power system optimization, protection, and forecasting. It also highlights the transformative role of blockchain in secure energy trading and digital twins in simulating real-time power system operations. Advanced big data techniques are presented for enhancing system planning, situational awareness, and stability, while quantum computing offers groundbreaking approaches to solving complex energy problems. For professionals and researchers eager to harness cutting-edge technologies within smart power systems, Volume 2 proves indispensable. Filled with numerous illustrations, case studies, and technical insights, it offers forward-thinking solutions that foster a more efficient, secure, and resilient future for global energy systems, heralding a new era of innovation and transformation in cyber-physical power networks. Welcome to the exploration of Smart Cyber-Physical Power Systems (CPPSs), where challenges are met with innovative solutions, and the future of energy is shaped by the paradigms of AI/ML, Big Data, Blockchain, IoT, Quantum Computing, Information Theory, Edge Computing, Metaverse, DevOps, and more." --
Assigning source Provided by publisher.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Description based on online resource; title from digital title page (viewed on March 20, 2025).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Cooperating objects (Computer systems)
Authority record control number http://id.loc.gov/authorities/subjects/sh2012002854
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Electric power systems
General subdivision Automation.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
Authority record control number http://id.loc.gov/authorities/subjects/sh85008180
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Objets coopérants (Systèmes informatiques)
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Réseaux électriques (Énergie)
General subdivision Automatisation.
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Intelligence artificielle.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element artificial intelligence.
Source of heading or term aat
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Parizad, Ali,
Relator term editor.
Authority record control number http://id.loc.gov/authorities/names/no2024120272
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Baghaee, Hamid Reza,
Relator term editor.
Authority record control number http://id.loc.gov/authorities/names/n2022053172
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Rahman, Saifur,
Relator term editor.
Real World Object URI https://id.oclc.org/worldcat/entity/E39PCjy4kjTwfXM8wvWDvxjmYd
Authority record control number http://id.loc.gov/authorities/names/no2002086591
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Print version:
International Standard Book Number 1394334567
-- 9781394334568
Record control number (OCoLC)1464950457
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title IEEE Press series on power and energy systems ;
Volume number/sequential designation 131.
Authority record control number http://id.loc.gov/authorities/names/no2023117201
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://onlinelibrary.wiley.com/doi/book/10.1002/9781394334599
Link text Full text is available at Wiley Online Library. Click here to view.
942 ## - ADDED ENTRY ELEMENTS
Source of classification or shelving scheme
Item type EBOOK
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Use restrictions Not for loan Permanent Location Current Location Date acquired Full call number Date last seen Price effective from Item type
        In Process   COLLEGE LIBRARY COLLEGE LIBRARY 2026-07-08 006.22 Sm27 2025 2026-07-08 2026-07-08 EBOOK

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