Introduction to AI Techniques for Renewable Energy System
Introduction to AI Techniques for Renewable Energy System

Author: Suman Lata Tripathi

Publisher: CRC Press

Published: 2021-11-25

Total Pages: 423

ISBN-13: 1000392457

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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.

Optimization in Renewable Energy Systems
Optimization in Renewable Energy Systems

Author: Ozan Erdinc

Publisher: Butterworth-Heinemann

Published: 2017-02-25

Total Pages: 327

ISBN-13: 0081012098

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Optimization in Renewable Energy Systems: Recent Perspectives covers all major areas where optimization techniques have been applied to reduce uncertainty or improve results in renewable energy systems (RES). Production of power with RES is highly variable and unpredictable, leading to the need for optimization-based planning and operation in order to maximize economies while sustaining performance. This self-contained book begins with an introduction to optimization, then covers a wide range of applications in both large and small scale operations, including optimum operation of electric power systems with large penetration of RES, power forecasting, transmission system planning, and DG sizing and siting for distribution and end-user premises. This book is an excellent choice for energy engineers, researchers, system operators, system regulators, and graduate students. - Provides chapters written by experts in the field - Goes beyond forecasting to apply optimization techniques to a wide variety of renewable energy system issues, from large scale to relatively small scale systems - Provides accompanying computer code for related chapters

Applications of AI and IOT in Renewable Energy
Applications of AI and IOT in Renewable Energy

Author: Rabindra Nath Shaw

Publisher: Academic Press

Published: 2022-02-09

Total Pages: 248

ISBN-13: 0323984010

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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

Intelligent Renewable Energy Systems
Intelligent Renewable Energy Systems

Author: Neeraj Priyadarshi

Publisher: John Wiley & Sons

Published: 2022-01-19

Total Pages: 484

ISBN-13: 1119786274

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INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.

IoT and Analytics in Renewable Energy Systems (Volume 1)
IoT and Analytics in Renewable Energy Systems (Volume 1)

Author: O.V. Gnana Swathika

Publisher: CRC Press

Published: 2023-08-11

Total Pages: 471

ISBN-13: 1000909794

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Smart grid technologies include sensing and measurement technologies, advanced components aided with communications and control methods along with improved interfaces and decision support systems. Smart grid techniques support the extensive inclusion of clean renewable generation in power systems. Smart grid use also promotes energy saving in power systems. Cyber security objectives for the smart grid are availability, integrity and confidentiality. Five salient features of this book are as follows: AI and IoT in improving resilience of smart energy infrastructure IoT, smart grids and renewable energy: an economic approach AI and ML towards sustainable solar energy Electrical vehicles and smart grid Intelligent condition monitoring for solar and wind energy systems

Machine Learning and Computer Vision for Renewable Energy
Machine Learning and Computer Vision for Renewable Energy

Author: Acharjya, Pinaki Pratim

Publisher: IGI Global

Published: 2024-05-01

Total Pages: 351

ISBN-13:

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As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial Intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine Learning and Computer Vision for Renewable Energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems. Transitioning from the complexities of energy prediction to the promise of advanced technology, the book sets its sights on the game-changing potential of computer vision (CV) in the realm of renewable energy. Amidst the struggle to enhance sustainability across industries, CV technology emerges as a powerful ally, collecting invaluable data from digital photos and videos. This data proves instrumental in achieving better energy management, predicting factors affecting renewable energy, and optimizing overall sustainability. Readers, including researchers, academicians, and students, will find themselves immersed in a comprehensive understanding of the AI approaches and CV methodologies that hold the key to resolving the challenges faced by renewable energy systems.

Transition to Renewable Energy Systems
Transition to Renewable Energy Systems

Author: Detlef Stolten

Publisher: John Wiley & Sons

Published: 2013-05-13

Total Pages: 882

ISBN-13: 352767389X

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In this ready reference, top academic researchers, industry players and government officers join forces to develop commercial concepts for the transition from current nuclear or fossil fuel-based energy to renewable energy systems within a limited time span. They take into account the latest science and technology, including an analysis of the feasibility and impact on the environment, economy and society. In so doing, they discuss such complex topics as electrical and gas grids, fossil power plants and energy storage technologies. The contributions also include robust, conceivable and breakthrough technologies that will be viable and implementable by 2020.

Machine Learning and the Internet of Things in Solar Power Generation
Machine Learning and the Internet of Things in Solar Power Generation

Author: Prabha Umapathy

Publisher: CRC Press

Published: 2023-07-14

Total Pages: 190

ISBN-13: 1000894231

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The book investigates various MPPT algorithms, and the optimization of solar energy using machine learning and deep learning. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse engineering domains including electrical, electronics and communication, computer, and environmental. This book: Discusses data acquisition by the internet of things for real-time monitoring of solar cells. Covers artificial neural network techniques, solar collector optimization, and artificial neural network applications in solar heaters, and solar stills. Details solar analytics, smart centralized control centers, integration of microgrids, and data mining on solar data. Highlights the concept of asset performance improvement, effective forecasting for energy production, and Low-power wide-area network applications. Elaborates solar cell design principles, the equivalent circuits of single and two diode models, measuring idealist factors, and importance of series and shunt resistances. The text elaborates solar cell design principles, the equivalent circuit of single diode model, the equivalent circuit of two diode model, measuring idealist factor, and importance of series and shunt resistances. It further discusses perturb and observe technique, modified P&O method, incremental conductance method, sliding control method, genetic algorithms, and neuro-fuzzy methodologies. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse engineering domains including electrical, electronics and communication, computer, and environmental.

Artificial Intelligence in Energy and Renewable Energy Systems
Artificial Intelligence in Energy and Renewable Energy Systems

Author: Soteris Kalogirou

Publisher: Nova Publishers

Published: 2007

Total Pages: 488

ISBN-13: 9781600212611

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This book presents state of the art applications of artificial intelligence in energy and renewable energy systems design and modelling. It covers such topics as solar energy, wind energy, biomass and hydrogen as well as building services systems, power generation systems, combustion processes and refrigeration. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities dealing with modelling and performance prediction of energy and renewable energy systems.

Design of Smart Power Grid Renewable Energy Systems
Design of Smart Power Grid Renewable Energy Systems

Author: Ali Keyhani

Publisher: John Wiley & Sons

Published: 2019-06-12

Total Pages: 778

ISBN-13: 1119573343

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The Updated Third Edition Provides a Systems Approach to Sustainable Green Energy Production and Contains Analytical Tools for the Design of Renewable Microgrids The revised third edition of Design of Smart Power Grid Renewable Energy Systems integrates three areas of electrical engineering: power systems, power electronics, and electric energy conversion systems. The book also addresses the fundamental design of wind and photovoltaic (PV) energy microgrids as part of smart-bulk power-grid systems. In order to demystify the complexity of the integrated approach, the author first presents the basic concepts, and then explores a simulation test bed in MATLAB® in order to use these concepts to solve a basic problem in the development of smart grid energy system. Each chapter offers a problem of integration and describes why it is important. Then the mathematical model of the problem is formulated, and the solution steps are outlined. This step is followed by developing a MATLAB® simulation test bed. This important book: Reviews the basic principles underlying power systems Explores topics including: AC/DC rectifiers, DC/AC inverters, DC/DC converters, and pulse width modulation (PWM) methods Describes the fundamental concepts in the design and operation of smart grid power grids Supplementary material includes a solutions manual and PowerPoint presentations for instructors Written for undergraduate and graduate students in electric power systems engineering, researchers, and industry professionals, the revised third edition of Design of Smart Power Grid Renewable Energy Systems is a guide to the fundamental concepts of power grid integration on microgrids of green energy sources.