Introduction To Ai Techniques For Renewable Energy System
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Introduction To Ai Techniques For Renewable Energy System
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Author : Suman Lata Tripathi
language : en
Publisher: CRC Press
Release Date : 2021-11-25
Introduction To Ai Techniques For Renewable Energy System written by Suman Lata Tripathi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-25 with Technology & Engineering categories.
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.
Intelligent Renewable Energy Systems
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Author : Neeraj Priyadarshi
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-29
Intelligent Renewable Energy Systems written by Neeraj Priyadarshi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-29 with Computers categories.
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.
Optimization In Renewable Energy Systems
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Author : Ozan Erdinc
language : en
Publisher: Butterworth-Heinemann
Release Date : 2017-02-25
Optimization In Renewable Energy Systems written by Ozan Erdinc and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-25 with Technology & Engineering categories.
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
Intelligent Solar Energy Systems Optimizing Efficiency Through Artificial Intelligence Machine Learning
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Author : Dr. Mude Sreenivasulu
language : en
Publisher: Xoffencer International Book Publication house
Release Date : 2024-08-01
Intelligent Solar Energy Systems Optimizing Efficiency Through Artificial Intelligence Machine Learning written by Dr. Mude Sreenivasulu and has been published by Xoffencer International Book Publication house this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-01 with Computers categories.
Artificial intellect (AI) is a subfield of computer science that focuses on the development of computer systems that are capable of carrying out activities that would typically need the intellect of a human being. Reasoning, learning, problem-solving, perception, and language comprehension are some of the activities that fall under this category. basic algorithms have grown into sophisticated systems that enable advancements like as self-driving vehicles, virtual assistants like Siri and Alexa, and enhanced diagnostic tools in the healthcare industry. Artificial intelligence (AI) has evolved from basic algorithms. AI is based on the concept of building computers that are capable of simulating human cognitive processes. This would allow the machines to learn from their experiences, adapt to new inputs, and carry out jobs that are similar to those performed by humans. Artificial intelligence (AI) may be roughly classified into two categories: narrow AI and general AI. Narrow artificial intelligence, commonly referred to as weak AI, is a kind of artificial intelligence that is meant to do a single activity, such as face recognition or internet searches, exceeding the capabilities of humans in that area. On the other hand, general artificial intelligence, also known as strong AI, is a more sophisticated kind of artificial intelligence that is capable of understanding, learning, and applying intelligence to a broad variety of issues, in a manner that is comparable to the cognitive capacities of humans. Narrow artificial intelligence is widely used in today's world, while universal artificial intelligence is still primarily theoretical and is the topic of substantial study and controversy. Across a wide range of industries, the development and use of artificial intelligence technologies have important ramifications. Artificial intelligence (AI) technologies are used in the medical field to forecast the outcomes of patients, provide therapy recommendations, and provide assistance during surgical procedures. AI algorithms are used in the financial sector to manage investments and monitor market movements. A number of sectors, including transportation, education, and manufacturing, are being revolutionized by artificial intelligence, which is leading to higher efficiency and creativity. The advent of artificial intelligence, on the other hand, has brought up a number of ethical and social challenges, including the loss of jobs, worries over privacy, and the want for rigorous governance to guarantee that AI technologies are produced and used in a responsible manner.
Ai Techniques For Renewable Source Integration And Battery Charging Methods In Electric Vehicle Applications
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Author : Angalaeswari, S.
language : en
Publisher: IGI Global
Release Date : 2023-02-03
Ai Techniques For Renewable Source Integration And Battery Charging Methods In Electric Vehicle Applications written by Angalaeswari, S. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-03 with Technology & Engineering categories.
Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
Artificial Intelligence Techniques In Power Systems
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Author : Kevin Warwick
language : en
Publisher: IET
Release Date : 1997
Artificial Intelligence Techniques In Power Systems written by Kevin Warwick and has been published by IET this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
The intention of this book is to give an introduction to, and an overview of, the field of artificial intelligence techniques in power systems, with a look at various application studies.
Iot And Analytics In Renewable Energy Systems Volume 2
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Author : O.V. Gnana Swathika
language : en
Publisher: CRC Press
Release Date : 2023-08-11
Iot And Analytics In Renewable Energy Systems Volume 2 written by O.V. Gnana Swathika and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-11 with Computers categories.
Smart cities emanate from a smart renewable-energy-aided power grid. The smart grid technologies offer an array of benefits like reliability, availability, and resiliency. Smart grids phenomenally contribute to facilitating cities reaching those sustainability goals over time. Digital technologies, such as the Internet of Things (IoT), automation, artificial intelligence (AI) and machine learning (ML) significantly contribute to the two-way communication between utilities and customers in smart cities. Five salient features of this book are as follows: Smart grid to the smart customer Intelligent computing for smart grid applications Novel designs of IoT systems such as smart healthcare, smart transportation, smart home, smart agriculture, smart manufacturing, smart grid, smart education, smart government, smart traffic management systems Innovations in using IoT and AI in improving resilience of smart energy infrastructure Challenges and future research directions of smart city applications
Applied Soft Computing And Embedded System Applications In Solar Energy
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Author : Rupendra Kumar Pachauri
language : en
Publisher: CRC Press
Release Date : 2021-05-26
Applied Soft Computing And Embedded System Applications In Solar Energy written by Rupendra Kumar Pachauri and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-26 with Computers categories.
Applied Soft Computing and Embedded System Applications in Solar Energy deals with energy systems and soft computing methods from a wide range of approaches and application perspectives. The authors examine how embedded system applications can deal with the smart monitoring and controlling of stand-alone and grid-connected solar photovoltaic (PV) systems for increased efficiency. Growth in the area of artificial intelligence with embedded system applications has led to a new era in computing, impacting almost all fields of science and engineering. Soft computing methods implemented to energy-related problems regularly face data-driven issues such as problems of optimization, classification, clustering, or prediction. The authors offer real-time implementation of soft computing and embedded system in the area of solar energy to address the issues with microgrid and smart grid projects (both renewable and non-renewable generations), energy management, and power regulation. They also discuss and examine alternative solutions for energy capacity assessment, energy efficiency systems design, as well as other specific smart grid energy system applications. The book is intended for students, professionals, and researchers in electrical and computer engineering fields, working on renewable energy resources, microgrids, and smart grid projects. Examines the integration of hardware with stand-alone PV panels and real-time monitoring of factors affecting the efficiency of the PV panels Offers real-time implementation of soft computing and embedded system in the area of solar energy Discusses how soft computing plays a huge role in the prediction of efficiency of stand-alone and grid-connected solar PV systems Discusses how embedded system applications with smart monitoring can control and enhance the efficiency of stand-alone and grid-connected solar PV systems Explores swarm intelligence techniques for solar PV parameter estimation Dr. Rupendra Kumar Pachauri is Assistant Professor – Selection Grade in the Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies (UPES), Dehradun, India. Dr. Jitendra Kumar Pandey is Professor & Head of R&D in the University of Petroleum and Energy Studies (UPES), Dehradun, India. Mr. Abhishek Sharma is working as a research scientist in the research and development department (UPES, India). Dr. Om Prakash Nautiyal is working as a scientist in Uttarakhand Science Education & Research Centre (USERC), Department of Information and Science Technology, Govt. of Uttarakhand, Dehradun, India. Prof. Mangey Ram is working as a Research Professor at Graphic Era Deemed to be University, Dehradun, India.
Iot And Analytics In Renewable Energy Systems Volume 1
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Author : O.V. Gnana Swathika
language : en
Publisher: CRC Press
Release Date : 2023-08-11
Iot And Analytics In Renewable Energy Systems Volume 1 written by O.V. Gnana Swathika and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-11 with Computers categories.
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
Ai Powered Iot In The Energy Industry
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Author : S. Vijayalakshmi
language : en
Publisher: Springer Nature
Release Date : 2023-04-05
Ai Powered Iot In The Energy Industry written by S. Vijayalakshmi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-05 with Technology & Engineering categories.
AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties. Covers renewable energy sector fundamentals; Explains the application of big data in distributed energy domains; Discusses AI and IoT prediction methods and models.