In the era of propelling traditional energy systems to evolve towards smart energy systems, including power generation, energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, and domestic & industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution automation, energy regulation and control, and energy trading.

This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book delves into the new technologies such as the Internet of Things, blockchain, etc. for smart home solutions, and smart city solutions in depth in the context of the modern power systems.

Technical topics discussed in the book include:

• Hybrid smart energy system technologies

• Energy demand forecasting

• Use of different protocols and communication in smart energy systems

• Power quality and allied issues and mitigation using AI

• Intelligent transportation

• Virtual power plants

• AI business models.

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Yes, you can access Applications of Big Data and Artificial Intelligence in Smart Energy Systems by Neelu Nagpal,Hassan Haes Alhelou,Pierluigi Siano,Sanjeevikumar Padmanaban,D. Lakshmi in PDF and/or ePUB format, as well as other popular books in Computer Science & Energy. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Year

Print ISBN

eBook ISBN

Edition

Topic

Computer Science

Subtopic

Energy

Index

Computer Science

Cover Page
Half Title page
Series page
Title Page
Copyright Page
Contents
Preface
List of Figures
List of Tables
List of Contributors
Abbreviations
1 Innovation, Opportunities, and Ongoing Challenges of AI and IOE in the Power and Energy Sector
2 Applications of Artificial Intelligence in Intelligent Combustion and Energy Storage Technologies
3 Sustainable Smart Energy Systems and Energy Preservation Strategies in Intelligent Transportation Sectors
4 Application of ANN Techniques to Mitigation of Power Quality Problems
5 Application of LMS Algorithm for Mitigation of Voltage Sag as Power Quality Problem
6 Blockchain based Solution for Electricity Supply Chain in Smart Grids
7 Virtual Power Plant
8 AI Business Model is Emerging Energy Market and Smart Grid
9 Artificial Neural Network and Forecasting Major Electricity Markets
Index
About the Editors

About this book

Frequently asked questions

Information

Table of contents