<p class="MsoNormal" style="margin-top: 12.0pt; text-align: justify; line-height: 115%;"><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; color: black; mso-color-alt: windowtext; background: white;">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.</span></p><p class="MsoNormal" style="margin-bottom: 0cm; text-align: justify; line-height: 115%; mso-layout-grid-align: none; text-autospace: none;"><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif;">This book aims to provide insights into various <span style="color: black; mso-color-alt: windowtext; background: white;">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. </span></span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-language: KO;">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. </span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif;">The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), </span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman';">IoT, </span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: EN-GB;">Cybersecurity</span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman';">, and their applications in modern p</span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif;">ower and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc.</span></p>

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Artificial Intelligence for Integrated Smart Energy Systems in Electric Vehicles

摘要

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.