The advancement of sustainable energy is becoming an important concern for many countries. The traditional electrical grid supports only one-way interaction of power being delivered to the consumers. The emergence of improved sensors, actuators, and automation technologies has consequently improved the control, monitoring and communication techniques within the energy sector, including the Smart Grid system. With the support of the aforementioned modern technologies, the information flows in two-ways between the consumer and supplier. This data communication helps the supplier in overcoming challenges like integration of renewable technologies, management of energy demand, load automation and control. Renewable energy (RE) is intermittent in nature and therefore difficult to predict. The accurate RE forecasting is very essential to improve the power system operations. The forecasting models are based on complex function combinations that include seasonality, fluctuation, and dynamic nonlinearity. The advanced intelligent computing algorithms for forecasting should consider the proper parameter determinations for achieving optimization. For this we need, new generation research areas like Machine learning (ML), and Artificial Intelligence (AI) to enable the efficient integration of distributed and renewable generation at large scale and at all voltage levels. The modern research in the above areas will improve the efficiency, reliability and sustainability in the Smart grid.

Recent Advances in Renewable Energy Technologies is a comprehensive reference covering critical research, laboratory and industry developments on renewable energy technological, production, conversion, storage, and management, including solar energy systems (thermal and photovoltaic), wind energy, hydropower, geothermal energy, bioenergy and hydrogen production, and large-scale development of renewable energy technologies and their impact on the global economy and power capacity. Technological advancements include resources assessment and deployment, materials performance improvement, system optimization and sizing, instrumentation and control, modeling and simulation, regulations, and policies.Each modular chapter examines recent advances in specific renewable energy systems, providing theoretical and applied aspects of system optimization, control and management and supports them with global case studies demonstrating practical applications and economical and environmental aspects through life cycle analysis. The book is of interest to engineering graduates, researchers, professors and industry professionals involved in the renewable energy sector and advanced engineering courses dealing with renewable energy, sources, thermal and electrical energy production and sustainability. - Focuses on the progress and research trends in solar, wind, biomass, and hydropower and geothermal energy production and conversion - Includes advanced techniques for the distribution, management, optimization, and storage of heat and energy using case studies

This edited volume on “Recent Advances in Renewable Energy” presents a selection of refereed papers presented at the 1st International Conference on Electrical Systems and Automation. The book provides rigorous discussions, the state of the art, and recent developments in the field of renewable energy sources supported by examples and case studies, making it an educational tool for relevant undergraduate and graduate courses. The book will be a valuable reference for beginners, researchers, and professionals interested in renewable energy.

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.

This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.

Applications of AI and IOT in Renewable Energy provides a future vision of unexplored areas and applications for Artificial Intelligence and Internet of Things in sustainable energy systems. The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles. In all these areas and more, applications of artificial intelligence methods, including artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above in hybrid systems are included. This book is designed to assist with developing low cost, smart and efficient solutions for renewable energy systems and is intended for researchers, academics and industrial communities engaged in the study and performance prediction of renewable energy systems. - Includes future applications of AI and IOT in renewable energy - Based on case studies to give each chapter real-life context - Provides advances in renewable energy using AI and IOT with technical detail and data

The role of manufacturing in a country’s economy and societal development has long been established through their wealth generating capabilities. To enhance and widen our knowledge of materials and to increase innovation and responsiveness to ever-increasing international needs, more in-depth studies of functionally graded materials/tailor-made materials, recent advancements in manufacturing processes and new design philosophies are needed at present. The objective of this volume is to bring together experts from academic institutions, industries and research organizations and professional engineers for sharing of knowledge, expertise and experience in the emerging trends related to design, advanced materials processing and characterization, and advanced manufacturing processes.

In an era where the planet faces unprecedented environmental challenges, such as climate change, loss of biodiversity, and water scarcity, sustainable development has become paramount. Crafting a Sustainable Future Through Education and Sustainable Development delves into the crucial role of educational institutions in shaping a sustainable future from economic, social, and environmental perspectives. By examining new currents and challenges within this discipline, this book provides a valuable study resource that sheds light on the intricate relationship between education and achieving sustainability goals. The book emphasizes the vital role of educational institutions as spaces for fostering new paradigms of human behavior towards the environment. Crafting a Sustainable Future Through Education and Sustainable Development serves as a comprehensive study guide, offering critical reflections and constructive critiques. It covers an array of relevant topics, ranging from artificial intelligence and big data to gender equality, game-based learning, and socio-technological innovation. It is ideal for academics, academic students, and policymakers, this book provides invaluable support for undergraduate and master’s students in business, as well as professionals seeking to deepen their knowledge of the role of education in achieving sustainable development.

This books provides a comprehensive platform to the scientific, education and research communities working on various fields related to sustainable energy. It covers the exploration, generation and application of this area to meet societal needs as well as addressing global issues related to the environment. The content of this book presents research related to energy and how to tackle climate change as a comprehensive framework based on the success of the Millennium Development Goals (MDGs). The authors use the scientific method to analyze and deliver viable technical solutions, demonstrating how chemistry and engineering can be combined to solve technically challenging problems. While maintaining high scientific rigor, a quantitative approach is offered in select chapters to the study of energy related to our societies increasing need for electrical and chemical energy feedstocks.

The 2016 2nd International Conference on Energy Equipment Science and Engineering (ICEESE 2016) was held on November 12-14, 2016 in Guangzhou, China. ICEESE 2016 brought together innovative academics and industrial experts in the field of energy equipment science and engineering to a common forum. The primary goal of the conference is to promote research and developmental activities in energy equipment science and engineering and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in energy equipment science and engineering and related areas. This second volume of the two-volume set of proceedings covers the field of Structural and Materials Sciences, and Computer Simulation & Computer and Electrical Engineering.