Advanced Analytics for Reliability and Resilience of Energy System
- 1st Edition - December 1, 2025
- Imprint: Elsevier
- Editors: Fausto Pedro Garcia Marquez, René Vinicio Sánchez Loja, Mayorkinos Papaelias
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 4 7 2 2 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 4 7 2 3 - 1
Advanced Analytics for Reliability and Resilience of Energy Systems prepares students, researchers, and industry engineers to design and maintain reliable, sustainable energy… Read more
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Advanced Analytics for Reliability and Resilience of Energy Systems prepares students, researchers, and industry engineers to design and maintain reliable, sustainable energy systems using state-of-the-art AI techniques. The book provides a clear foundation in the fundaments of power systems statistics and reliability, including resilience principles and strategies, practical applications, and real-world solutions. It covers a wide range of renewable sources, including biomass and biomethane, solar, and hybrid-renewable systems. The AI tools presented cover forecasting, the internet-of-Things, machine learning, digital twin technology, and big data analysis, with a variety of applications to avoid power outrages, minimize disruption, and accurately assess system resilience.
- Provides a foundation of the fundamental principles and strategies for reliability and resilience
- Introduces the readers to a toolbox of AI methodologies with a variety of applications
- Leverages clear chapter objectives, worked problems, and detailed case studies to support real-world solution-building
Researchers, industry professionals, and higher-level undergraduate/graduate students in energy grids and artificial intelligence integration
1. Enhancing Resilience of Power Transmission Systems Against Typhoon Disasters: A Hybrid Data-Model Driven Approach
2.Reliability of Power Electronics in Smart Grids
3. Electricity distribution grids resilience enhancement by network reconfiguration
4. Network-Based Data-Driven Real-Time Analytics for Designing Resilient Next-Generation Power Grids: Challenges, Necessity and Explanations
5.Teaching learning-based optimized artificial neural network for predicting the maximum power point of a large-scale grid-connected solar PV system
6.A reliable PV system based on FPPT implementation incorporating forecasted load demand using Neural Network
7.Robust Stabilization Ellipsoidal Design for Normal and Contingency Operated Power Systems Using Markov Jump
8.From Review to Revolution: Innovative Under-Frequency Load Shedding for Enhanced Power System Resilience
9.Fault Detection and Classification in Hybrid AC/DC Systems Using Artificial Neural Networks
10. A Reliability Constrained Load Balancing Procedure for Neutral Current Reduction in Distribution Systems
11. The impact of cyber network configuration on the dynamic-thermal failure of transformers considering distributed generator controller
12. Operation of Energy Hub to Enhance Power System Resilience
13. Resilient Operation of Power and Gas Networks to Service Restoration
14. Challenges and Solutions in Power Sharing Control of Microgrids with Integrated Renewable Energy Sources
15. Statistical Analysis of Supervisory Control and Data Acquisition System for Maintenance Management of Photovoltaic Solar Power Plant
16. Small-Signal Stability Analysis and Compensation Control for DC Networked-Microgrid under Multiple Time Delays
17. Reliability Improvement by Fault-Tolerant Operation of NPC Inverter for Motor Driving
18. Multiplexing Power Supply Networks with DC Sub-Grid: Control Strategy and Economic Impact Assessment
2.Reliability of Power Electronics in Smart Grids
3. Electricity distribution grids resilience enhancement by network reconfiguration
4. Network-Based Data-Driven Real-Time Analytics for Designing Resilient Next-Generation Power Grids: Challenges, Necessity and Explanations
5.Teaching learning-based optimized artificial neural network for predicting the maximum power point of a large-scale grid-connected solar PV system
6.A reliable PV system based on FPPT implementation incorporating forecasted load demand using Neural Network
7.Robust Stabilization Ellipsoidal Design for Normal and Contingency Operated Power Systems Using Markov Jump
8.From Review to Revolution: Innovative Under-Frequency Load Shedding for Enhanced Power System Resilience
9.Fault Detection and Classification in Hybrid AC/DC Systems Using Artificial Neural Networks
10. A Reliability Constrained Load Balancing Procedure for Neutral Current Reduction in Distribution Systems
11. The impact of cyber network configuration on the dynamic-thermal failure of transformers considering distributed generator controller
12. Operation of Energy Hub to Enhance Power System Resilience
13. Resilient Operation of Power and Gas Networks to Service Restoration
14. Challenges and Solutions in Power Sharing Control of Microgrids with Integrated Renewable Energy Sources
15. Statistical Analysis of Supervisory Control and Data Acquisition System for Maintenance Management of Photovoltaic Solar Power Plant
16. Small-Signal Stability Analysis and Compensation Control for DC Networked-Microgrid under Multiple Time Delays
17. Reliability Improvement by Fault-Tolerant Operation of NPC Inverter for Motor Driving
18. Multiplexing Power Supply Networks with DC Sub-Grid: Control Strategy and Economic Impact Assessment
- Edition: 1
- Published: December 1, 2025
- Imprint: Elsevier
- Language: English
FG
Fausto Pedro Garcia Marquez
Fausto Pedro García Márquez works as a Professor and as Director of the Ingenium Research Group at the Universidad De Castilla-La Mancha, Spain. He is an Honorary Senior Research Fellow at Birmingham University, UK, and a Lecturer at the Postgraduate European Institute. He has published more than 150 papers and 31 books (Elsevier, Springer, Pearson, McGraw-Hill, Intech, IGI, Marcombo, AlfaOmega). He has been Principal Investigator in 4 European projects, 6 national projects, and more than 150 projects for universities, companies, and other institutions. His main interests are: Artificial Intelligence, Maintenance, Management, Renewable Energy, Transport, Advanced Analytics, and Data Science.
Affiliations and expertise
Professor, Universidad De Castilla-La Mancha, SpainRL
René Vinicio Sánchez Loja
René Vinicio Sánchez Loja is a Professor at the Universidad Politécnica Salesiana, Ecuador, working mainly in areas related to the automation of sequential processes. In 2014, he founded the Research and Development Group in Industrial Technologies, and Overseas invited Ph.D. at Chongqing Technology and Business University, China. He is a senior member of IEEE. He has extensive experience in the organization of conferences, implementation of technological projects, management and execution of research projects; currently he has more than 60 publications in Web of Science. His current focus is in the areas of project management, condition-based maintenance, engineering education and industry 4.0 especially for SMEs.
Affiliations and expertise
Professor, Universidad Politécnica Salesiana, EcuadorMP
Mayorkinos Papaelias
Mayorkinos Papaelias is a Reader in NDT and Condition Monitoring in the School of Metallogy and Materials at the University of Birmingham, UK. Dr Papaelias leads the research activity in Non-Destructive Testing and Structural Health Condition Monitoring at the Birmingham Railway Centre for Research and Education and conducts research in structural health condition monitoring of wind turbine towers, and advanced condition monitoring of wind turbine gearboxes and rotating machinery. He served as a technical consultant to TWI, ENGITEC, Innovative Technology and Science Ltd, and Instituto de Soldadura e Qualidade. He is editor of two books on fault detection and condition monitoring, and has contributed chapters to books in fault detection and rail inspection. Mayorkinos is chairman of the Education Committee of the International Society for Condition Monitoring of the British Institute of Non-Destructive Testing.
Affiliations and expertise
Reader in NDT and Condition Monitoring, School of Metallogy and Materials, University of Birmingham, UK