Machine Learning For Solar Array Monitoring Optimization And Control
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Machine Learning For Solar Array Monitoring Optimization And Control
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Author : Sunil Rao
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Machine Learning For Solar Array Monitoring Optimization And Control written by Sunil Rao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Technology & Engineering categories.
The efficiency of solar energy farms requires detailed analytics and information on each panel regarding voltage, current, temperature, and irradiance. Monitoring utility-scale solar arrays was shown to minimize the cost of maintenance and help optimize the performance of the photo-voltaic arrays under various conditions. We describe a project that includes development of machine learning and signal processing algorithms along with a solar array testbed for the purpose of PV monitoring and control. The 18kW PV array testbed consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. We develop machine learning and neural network algorithms for fault classification. In addition, we use weather camera data for cloud movement prediction using kernel regression techniques which serves as the input that guides topology reconfiguration. Camera and satellite sensing of skyline features as well as parameter sensing at each panel provides information for fault detection and power output optimization using topology reconfiguration achieved using programmable actuators (relays) in the SMDs. More specifically, a custom neural network algorithm guides the selection among four standardized topologies. Accuracy in fault detection is demonstrate at the level of 90+% and topology optimization provides increase in power by as much as 16% under shading.
Machine Learning And The Internet Of Things In Solar Power Generation
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Author : Prabha Umapathy
language : en
Publisher: CRC Press
Release Date : 2023-07-14
Machine Learning And The Internet Of Things In Solar Power Generation written by Prabha Umapathy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-14 with Computers categories.
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.
Signal Processing For Solar Array Monitoring Fault Detection And Optimization
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Author : Henry Braun
language : en
Publisher: Springer
Release Date : 2011-09-28
Signal Processing For Solar Array Monitoring Fault Detection And Optimization written by Henry Braun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-28 with Technology & Engineering categories.
Although the solar energy industry has experienced rapid growth recently, high-level management of photovoltaic (PV) arrays has remained an open problem. As sensing and monitoring technology continues to improve, there is an opportunity to deploy sensors in PV arrays in order to improve their management. In this book, we examine the potential role of sensing and monitoring technology in a PV context, focusing on the areas of fault detection, topology optimization, and performance evaluation/data visualization. First, several types of commonly occurring PV array faults are considered and detection algorithms are described. Next, the potential for dynamic optimization of an array's topology is discussed, with a focus on mitigation of fault conditions and optimization of power output under non-fault conditions. Finally, monitoring system design considerations such as type and accuracy of measurements, sampling rate, and communication protocols are considered. It is our hope that the benefits of monitoring presented here will be sufficient to offset the small additional cost of a sensing system, and that such systems will become common in the near future. Table of Contents: Introduction / Overview of Photovoltaics / Causes Performance Degradation and Outage / Fault Detection Methods / Array Topology Optimization / Monitoring of PV Systems / Summary
Machine And Deep Learning Algorithms And Applications
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Author : Uday Shankar
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Machine And Deep Learning Algorithms And Applications written by Uday Shankar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Technology & Engineering categories.
This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of machine learning that involves extensive use of layers of artificial neural networks typically trained on massive amounts of data. Machine and deep learning methods are often used in contemporary data science tasks to address the growing data sets and detect, cluster, and classify data patterns. Although machine learning commercial interest has grown relatively recently, the roots of machine learning go back to decades ago. We note that nearly all organizations, including industry, government, defense, and health, are using machine learning to address a variety of needs and applications. The machine learning paradigms presented can be broadly divided into the following three categories: supervised learning, unsupervised learning, and semi-supervised learning. Supervised learning algorithms focus on learning a mapping function, and they are trained with supervision on labeled data. Supervised learning is further sub-divided into classification and regression algorithms. Unsupervised learning typically does not have access to ground truth, and often the goal is to learn or uncover the hidden pattern in the data. Through semi-supervised learning, one can effectively utilize a large volume of unlabeled data and a limited amount of labeled data to improve machine learning model performances. Deep learning and neural networks are also covered in this book. Deep neural networks have attracted a lot of interest during the last ten years due to the availability of graphics processing units (GPU) computational power, big data, and new software platforms. They have strong capabilities in terms of learning complex mapping functions for different types of data. We organize the book as follows. The book starts by introducing concepts in supervised, unsupervised, and semi-supervised learning. Several algorithms and their inner workings are presented within these three categories. We then continue with a brief introduction to artificial neural network algorithms and their properties. In addition, we cover an array of applications and provide extensive bibliography. The book ends with a summary of the key machine learning concepts.
Proceedings Of The First International Conference On Aeronautical Sciences Engineering And Technology
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Author : Abid Ali Khan
language : en
Publisher: Springer Nature
Release Date : 2024-01-26
Proceedings Of The First International Conference On Aeronautical Sciences Engineering And Technology written by Abid Ali Khan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-26 with Technology & Engineering categories.
This volume contains forty-one revised and extended research articles, written by prominent researchers participating in the International Conference on Aeronautical Sciences, Engineering and Technology 2023, held in Muscat, October 3-5 2023. It focuses on the latest research developments in aeronautical applications, avionics systems, advanced aerodynamics, atmospheric chemistry, emerging technologies, safety management, unmanned aerial vehicles, and industrial applications. This book offers the state of the art of notable advances in engineering technologies and aviation applications and serves as an excellent source of reference for researchers and graduate students.
Positive Unlabeled Learning
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Author : Kristen Jaskie
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2022-04-20
Positive Unlabeled Learning written by Kristen Jaskie and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-20 with Computers categories.
Machine learning and artificial intelligence (AI) are powerful tools that create predictive models, extract information, and help make complex decisions. They do this by examining an enormous quantity of labeled training data to find patterns too complex for human observation. However, in many real-world applications, well-labeled data can be difficult, expensive, or even impossible to obtain. In some cases, such as when identifying rare objects like new archeological sites or secret enemy military facilities in satellite images, acquiring labels could require months of trained human observers at incredible expense. Other times, as when attempting to predict disease infection during a pandemic such as COVID-19, reliable true labels may be nearly impossible to obtain early on due to lack of testing equipment or other factors. In that scenario, identifying even a small amount of truly negative data may be impossible due to the high false negative rate of available tests. In such problems, it is possible to label a small subset of data as belonging to the class of interest though it is impractical to manually label all data not of interest. We are left with a small set of positive labeled data and a large set of unknown and unlabeled data. Readers will explore this Positive and Unlabeled learning (PU learning) problem in depth. The book rigorously defines the PU learning problem, discusses several common assumptions that are frequently made about the problem and their implications, and considers how to evaluate solutions for this problem before describing several of the most popular algorithms to solve this problem. It explores several uses for PU learning including applications in biological/medical, business, security, and signal processing. This book also provides high-level summaries of several related learning problems such as one-class classification, anomaly detection, and noisy learning and their relation to PU learning.
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
Photovoltaic Systems
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Author : K.Mohana Sundaram
language : en
Publisher: CRC Press
Release Date : 2022-03-07
Photovoltaic Systems written by K.Mohana Sundaram and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-07 with Science categories.
This book provides comprehensive insight into the fault detection techniques implemented for photovoltaic (PV) panels. It includes studies related to predictive maintenance needed to improve the performance of the solar PV systems using Artificial Intelligence (AI) techniques. The readers gain knowledge on the fault identification algorithm and the significance of all such algorithms in real-time power system applications. Gives detailed overview of fundamental concepts of fault diagnosis algorithm for solar PV system Explains AC and DC side of the solar PV system-based electricity generation with real-time examples Covers effective extraction of the energy from solar radiation Illustrates artificial intelligence techniques for detecting the faults occurring in the solar PV system Includes MATLAB® based simulations and results on fault diagnosis including case studies This book is aimed at researchers, professionals and graduate students in electrical engineering, artificial intelligence, control algorithms, energy engineering, photovoltaic systems, industrial electronics.
Handbook Of Artificial Intelligence Techniques In Photovoltaic Systems
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Author : Adel Mellit
language : en
Publisher: Academic Press
Release Date : 2022-06-23
Handbook Of Artificial Intelligence Techniques In Photovoltaic Systems written by Adel Mellit and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-23 with Technology & Engineering categories.
Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modelling, Control, Optimization, Forecasting and Fault Diagnosis provides readers with a comprehensive and detailed overview of the role of artificial intelligence in PV systems. Covering up-to-date research and methods on how, when and why to use and apply AI techniques in solving most photovoltaic problems, this book will serve as a complete reference in applying intelligent techniques and algorithms to increase PV system efficiency. Sections cover problem-solving data for challenges, including optimization, advanced control, output power forecasting, fault detection identification and localization, and more. Supported by the use of MATLAB and Simulink examples, this comprehensive illustration of AI-techniques and their applications in photovoltaic systems will provide valuable guidance for scientists and researchers working in this area. Includes intelligent methods in real-time using reconfigurable circuits FPGAs, DSPs and MCs Discusses the newest trends in AI forecasting, optimization and control applications Features MATLAB and Simulink examples highlighted throughout
Social And Ethical Implications Of Ai In Finance For Sustainability
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Author : Derbali, Abdelkader Mohamed Sghaier
language : en
Publisher: IGI Global
Release Date : 2024-04-22
Social And Ethical Implications Of Ai In Finance For Sustainability written by Derbali, Abdelkader Mohamed Sghaier and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-22 with Business & Economics categories.
The crucial challenge of integrating sustainability into business and investment decisions is compounded by the complexity of analyzing vast and intricate datasets to make informed choices. Traditional approaches often fail to provide timely and accurate insights into environmental, social, and governance (ESG) factors, hindering progress toward a greener future. Additionally, the rapid evolution of AI and machine learning in finance has left many professionals needing help to grasp their full potential in advancing sustainability goals. With a comprehensive understanding and practical guidance, organizations can stay caught up in adopting sustainable practices and leveraging AI for financial and environmental benefits. Social and Ethical Implications of AI in Finance for Sustainability offers a timely and comprehensive solution to these challenges by thoroughly examining how AI can safely enhance sustainability in finance. The book bridges the gap between theory and practice, offering practical insights and real-world applications to empower academics, practitioners, policymakers, and students. Through a series of expertly curated chapters, readers will gain a deep understanding of the role AI plays in reshaping finance for a sustainable future. The book's instructional elements, including case studies and expert analysis, provide a roadmap for incorporating AI into sustainability strategies, enabling organizations to make informed decisions and drive positive change.