Artificial Intelligence Techniques for a Scalable Energy Transition: Advanced Methods, Digital Technologies, Decision Support Tools, and Applications

✍ Scribed by Moamar Sayed-Mouchaweh

• Publisher: Springer International Publishing;Springer
• Year: 2020
• Tongue: English
• Leaves: 383
• Edition: 1st ed.
• Category: Library

✦ Synopsis

This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc. The book goes beyond standard application by placing a specific focus on the use of AI techniques to address the challenges related to the different applications and topics of energy transition. The contributions are classified according to the market and actor interactions (service providers, manufacturers, customers, integrators, utilities etc.), to the SG architecture model (physical layer, infrastructure layer, and business layer), to the digital twin of SG (business model, operational model, fault/transient model, and asset model), and to the application domain (demand side management, load monitoring, micro grids, energy consulting (residents, utilities), energy saving, dynamic pricing revenue management and smart meters, etc.).

✦ Table of Contents

Front Matter ....Pages i-ix
Prologue: Artificial Intelligence for Energy Transition (Moamar Sayed-Mouchaweh)....Pages 1-12
Front Matter ....Pages 13-13
Large-Scale Building Thermal Modeling Based on Artificial Neural Networks: Application to Smart Energy Management (Lala Rajaoarisoa)....Pages 15-44
Automated Demand Side Management in Buildings (Hussain Kazmi, Johan Driesen)....Pages 45-76
A Multi-Agent Approach to Energy Optimisation for Demand-Response Ready Buildings (Oudom Kem, Feirouz Ksontini)....Pages 77-107
A Review on Non-intrusive Load Monitoring Approaches Based on Machine Learning (Hajer Salem, Moamar Sayed-Mouchaweh, Moncef Tagina)....Pages 109-131
Front Matter ....Pages 133-133
Neural Networks and Statistical Decision Making for Fault Diagnosis in Energy Conversion Systems (Gerasimos Rigatos, Dimitrios Serpanos, Vasilios Siadimas, Pierluigi Siano, Masoud Abbaszadeh)....Pages 135-156
Support Vector Machine Classification of Current Data for Fault Diagnosis and Similarity-Based Approach for Failure Prognosis in Wind Turbine Systems (Samir Benmoussa, Mohand Arab Djeziri, Roberto Sanchez)....Pages 157-182
Review on Health Indices Extraction and Trend Modeling for Remaining Useful Life Estimation (Mohand Arab Djeziri, Samir Benmoussa, Enrico Zio)....Pages 183-223
How Machine Learning Can Support Cyberattack Detection in Smart Grids (Bruno Bogaz Zarpelão, Sylvio Barbon Jr., Dilara Acarali, Muttukrishnan Rajarajan)....Pages 225-258
Front Matter ....Pages 259-259
Neurofuzzy Approach for Control of Smart Appliances for Implementing Demand Response in Price Directed Electricity Utilization (Miltiadis Alamaniotis, Iosif Papadakis Ktistakis)....Pages 261-278
Using Model-Based Reasoning for Self-Adaptive Control of Smart Battery Systems (Franz Wotawa)....Pages 279-310
Data-Driven Predictive Flexibility Modeling of Distributed Energy Resources (Indrasis Chakraborty, Sai Pushpak Nandanoori, Soumya Kundu, Karanjit Kalsi)....Pages 311-343
Applications of Artificial Neural Networks in the Context of Power Systems (Jan-Hendrik Menke, Marcel Dipp, Zheng Liu, Chenjie Ma, Florian Schäfer, Martin Braun)....Pages 345-373
Back Matter ....Pages 375-382

✦ Subjects

Engineering; Communications Engineering, Networks; Computational Intelligence; Data Mining and Knowledge Discovery; Big Data/Analytics