Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies


Book Description

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. - Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment - Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum - Addresses the advanced field of renewable generation, from research, impact and idea development of new applications




Renewable Energy and AI for Sustainable Development


Book Description

Electronic device usage has increased considerably in the past two decades. System configurations are continuously requiring upgrades; existing systems often become obsolete in a matter of 2–3 years. Green computing is the complete effective management of design, manufacture, use, and disposal, involving as little environmental impact as possible. This book intends to explore new and innovative ways of conserving energy, effective e-waste management, and renewable energy sources to harness and nurture a sustainable eco-friendly environment. This book: • Highlights innovative principles and practices using effective e-waste management and disposal • Explores artificial intelligence based sustainable models • Discovers alternative sources and mechanisms for minimizing environmental hazards • Highlights successful case studies in alternative sources of energy • Presents solid illustrations, mathematical equations, as well as practical in-the-field applications • Serves as a one-stop reference guide to stakeholders in the domain of green computing, e-waste management, renewable energy alternatives, green transformational leadership including theory concepts, practice and case studies • Explores cutting-edge technologies like internet of energy and artificial intelligence, especially the role of machine learning and deep learning in renewable energy and creating a sustainable ecosystem • Explores futuristic trends in renewable energy This book aims to address the increasing interest in reducing the environmental impact of energy as well as its further development and will act as a useful reference for engineers, architects, and technicians interested in and working with energy systems; scientists and engineers in developing countries; industries, manufacturers, inventors, universities, researchers, and interested consultants to explain the foundation to advanced concepts and research trends in the domain of renewable energy and sustainable computing. The content coverage of the book is organized in the form of 11 clear and thorough chapters providing a comprehensive view of the global renewable energy scenario, as well as how science and technology can play a vital role in renewable energy.




Clean Energy for Sustainable Development


Book Description

Clean Energy for Sustainable Development: Comparisons and Contrasts of New Approaches presents information on the fundamental challenge that the energy sector faces with regard to meeting the ever growing demand for sustainable, efficient, and cleaner energy. The book compares recent developments in the field of energy technology, clean and low emission energy, and energy efficiency and environmental sustainability for industry and academia. Rasul, Azad and Sharma, along with their team of expert contributors, provide high-end research findings on relevant industry themes, including clean and sustainable energy sources and technologies, renewable energy technologies and their applications, biomass and biofuels for sustainable environment, energy system and efficiency improvement, solar thermal applications, and the environmental impacts of sustainable energy systems. This book uses global institutes and case studies to explore and analyze technological advancements alongside practical applications. This approach helps readers to develop and affirm a better understanding of the relevant concepts and solutions necessary to achieve clean energy and sustainable development in both medium and large-scale industries. - Compares in-depth research on a wide range of clean technologies, from global institutes in Australia, Europe, and India - Evaluates the recent developments in clean technologies against the efficiency of tried and tested applications - Considers case studies on the advancements of sustainable energy into industry from around the world




Renewable-Energy-Driven Future


Book Description

In order to promote the sustainable development of renewable energy and renewable-energy-driven technologies, Renewable-Energy-Driven Future: Technologies, Modelling, Applications, Sustainability and Policies provides a comprehensive view of the advanced renewable technologies and the benefits of utilizing renewable energy sources.Discussing the ways for promoting the sustainable development of renewable energy from the perspectives of technology, modelling, application, sustainability and policy, this book includes the advanced renewable-energy-driven technologies, the models for renewable energy planning and integration, the innovative applications of renewable energy sources, decision-support tools for sustainability assessment and ranking of renewable energy systems, and the regulations and policies of renewable energy.This book can benefit the researchers and experts of renewable energy by helping them to have a holistic view of renewable energy. It can also benefit the policymakers and decision-makers by helping them to make informed decisions. - Presents the advanced renewable-energy-driven technologies and the innovative applications of renewable energy sources - Develops the models for the efficient use of renewable energy, decision-making and the investigation of its climate and economic benefits - Investigates the sustainability of renewable energy systems - Features the regulations and policies of renewable energy




Artificial Intelligence for Smart and Sustainable Energy Systems and Applications


Book Description

Energy has been a crucial element for human beings and sustainable development. The issues of global warming and non-green energy have yet to be resolved. This book is a collection of twelve articles that provide strong evidence for the success of artificial intelligence deployment in energy research, particularly research devoted to non-intrusive load monitoring, network, and grid, as well as other emerging topics. The presented artificial intelligence algorithms may provide insight into how to apply similar approaches, subject to fine-tuning and customization, to other unexplored energy research. The ultimate goal is to fully apply artificial intelligence to the energy sector. This book may serve as a guide for professionals, researchers, and data scientists—namely, how to share opinions and exchange ideas so as to facilitate a better fusion of energy, academic, and industry research, and improve in the quality of people's daily life activities.




Energy for Sustainable Development


Book Description

Energy for Sustainable Development: Demand, Supply, Conversion and Management presents a comprehensive look at recent developments and provides guidance on energy demand, supply, analysis and forecasting of modern energy technologies for sustainable energy conversion. The book analyzes energy management techniques and the economic and environmental impact of energy usage and storage. Including modern theories and the latest technologies used in the conversion of energy for traditional fossil fuels and renewable energy sources, this book provides a valuable reference on recent innovations. Researchers, engineers and policymakers will find this book to be a comprehensive guide on modern theories and technologies for sustainable development.




Renewable Energy for Smart and Sustainable Cities


Book Description

This book features cutting-edge research presented at the second international conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES2018, held on 24–26 November 2018, at the High School of Commerce, ESC-Koléa in Tipaza, Algeria. Today, the fundamental challenge of integrating renewable energies into the design of smart cities is more relevant than ever. While based on the advent of big data and the use of information and communication technologies, smart cities must now respond to cross-cutting issues involving urban development, energy and environmental constraints; further, these cities must also explore how they can integrate more sustainable energies. Sustainable energies are a major determinant of smart cities’ longevity. From an environmental and technological standpoint, these energies offer an optimal power supply to the electric network while creating significantly less pollution. This requires flexibility, i.e., the availability of supply and demand. The end goal of any smart city is to improve the quality of life for all citizens (both in the city and in the countryside) in a way that is sustainable and respectful of the environment. This book encourages the reader to engage in the preservation of our environment, every moment, every day, so as to help build a clean and healthy future, and to think of the future generations who will one day inherit our planet. Further, it equips those whose work involves energy systems and those engaged in modelling artificial intelligence to combine their expertise for the benefit of the scientific community and humanity as a whole.




Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications


Book Description

This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications. Discussing theory, applications and research, it covers all aspects of artificial intelligence in the context of sustainable development.




Introduction to AI Techniques for Renewable Energy System


Book Description

Introduction to AI techniques for Renewable Energy System Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems. Features Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.




Explainable AI (XAI) for Sustainable Development


Book Description

This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. • Focuses on virtual machine placement and migration techniques for cloud data centres • Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services • Includes application of placement techniques for quality of service, performance, and reliability improvement • Explores data centre resource management, load balancing and orchestration using machine learning techniques • Analyses dynamic and scalable resource scheduling with a focus on resource management The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.