Advances In Ai For Simulation And Optimization Of Energy Systems
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Advances in AI for Simulation and Optimization of Energy Systems
Advances in AI for Simulation and Optimization of Energy Systems explores AI’s groundbreaking role in the future of energy. As the demand for cleaner, more efficient energy systems grows, AI‐driven methodologies are leading the way in simulating and optimizing critical processes across the power generation, transmission, and storage sectors. Whether applied to traditional power grids, renewable energy systems, or energy markets, AI techniques such as neural networks, reinforcement learning, fuzzy logic, and metaheuristic optimization are revolutionizing how energy systems are modeled and managed. This comprehensive volume offers: In‐depth chapters on AI‐driven simulation and optimization strategies Case studies that demonstrate real‐world applications of AI in energy systems An examination of the ethical concerns and legal frameworks surrounding AI Cutting‐edge methodologies for improving energy technologies’ accuracy, efficiency, and performance Bringing together leading researchers and practitioners in AI and energy systems, this book is an invaluable resource for academics, engineers, and professionals who want to stay ahead of the curve in this rapidly evolving field.
Advances in Artificial Intelligence, Software and Systems Engineering
This book addresses emerging issues concerning the integration of artificial intelligence systems in our daily lives. It focuses on the cognitive, visual, social and analytical aspects of computing and intelligent technologies, and highlights ways to improve the acceptance, effectiveness, and efficiency of said technologies. Topics such as responsibility, integration and training are discussed throughout. The book also reports on the latest advances in systems engineering, with a focus on societal challenges and next-generation systems and applications for meeting them. Further, it covers some cutting-edge issues in energy, including intelligent control systems for power plant, and technology acceptance models. Based on the AHFE 2021 Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, held virtually on 25–29 July, 2021, from USA, this book provides readers with extensive information on current research and future challenges in these fields, together with practical insights into the development of innovative services for various purposes.
Artificial Intelligence for Integrated Smart Energy Systems in Electric Vehicles
Author: Surender Reddy Salkuti
language: en
Publisher: Springer Nature
Release Date: 2025-07-02
This book provides a comprehensive exploration of cutting-edge research in electric vehicles (EVs) integrated smart energy systems with a main focus on the application of artificial intelligence (AI). This book offers a wide and comprehensive practical approach with the applications of AI to address the challenges and opportunities of modern hybrid energy systems for developing advanced hybrid intelligent methodologies for forecasting and scheduling variable power output from renewable energy sources (RESs) and EVs. This will enhance system flexibility and facilitate the integration of RESs and EVs efficiently, which is a step towards a sustainable future. The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Cybersecurity, and their applications in modern power and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc. This book aims to provide insights into various suitable solutions to increase the security, reliability, and interoperability of the grid under high penetration of renewable energy, storage systems, and electric transport in the context of the modern smart grid. The multi-objective optimization problems such as economic and emission dispatch problems; flexibility and reliability problems; and economic and reliability problems are solved to determine the trade-off solutions using efficient evolutionary algorithms. The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), IoT, Cybersecurity, and their applications in modern power and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc.