Intelligent Data Mining and Analysis in Power and Energy Systems


Book Description

Intelligent Data Mining and Analysis in Power and Energy Systems A hands-on and current review of data mining and analysis and their applications to power and energy systems In Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems, the editors assemble a team of distinguished engineers to deliver a practical and incisive review of cutting-edge information on data mining and intelligent data analysis models as they relate to power and energy systems. You’ll find accessible descriptions of state-of-the-art advances in intelligent data mining and analysis and see how they drive innovation and evolution in the development of new technologies. The book combines perspectives from authors distributed around the world with expertise gained in academia and industry. It facilitates review work and identification of critical points in the research and offers insightful commentary on likely future developments in the field. It also provides: A thorough introduction to data mining and analysis, including the foundations of data preparation and a review of various analysis models and methods In-depth explorations of clustering, classification, and forecasting Intensive discussions of machine learning applications in power and energy systems Perfect for power and energy systems designers, planners, operators, and consultants, Intelligent Data Mining and Analysis in Power and Energy Systems will also earn a place in the libraries of software developers, researchers, and students with an interest in data mining and analysis problems.




Intelligent Data Mining and Analysis in Power and Energy Systems


Book Description

Intelligent Data Mining and Analysis in Power and Energy Systems A hands-on and current review of data mining and analysis and their applications to power and energy systems In Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems, the editors assemble a team of distinguished engineers to deliver a practical and incisive review of cutting-edge information on data mining and intelligent data analysis models as they relate to power and energy systems. You’ll find accessible descriptions of state-of-the-art advances in intelligent data mining and analysis and see how they drive innovation and evolution in the development of new technologies. The book combines perspectives from authors distributed around the world with expertise gained in academia and industry. It facilitates review work and identification of critical points in the research and offers insightful commentary on likely future developments in the field. It also provides: A thorough introduction to data mining and analysis, including the foundations of data preparation and a review of various analysis models and methods In-depth explorations of clustering, classification, and forecasting Intensive discussions of machine learning applications in power and energy systems Perfect for power and energy systems designers, planners, operators, and consultants, Intelligent Data Mining and Analysis in Power and Energy Systems will also earn a place in the libraries of software developers, researchers, and students with an interest in data mining and analysis problems.




Intelligent Data Analytics for Power and Energy Systems


Book Description

This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.




Intelligent Data Analytics for Power and Energy Systems


Book Description

This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.




Big Data Application in Power Systems


Book Description

Big Data Application in Power Systems, Second Edition presents a thorough update of the previous volume, providing readers with step-by-step guidance in big data analytics utilization for power system diagnostics, operation, and control. Bringing back a team of global experts and drawing on fresh, emerging perspectives, this book provides cutting-edge advice for meeting today's challenges in this rapidly accelerating area of power engineering. Divided into three parts, this book begins by breaking down the big picture for electric utilities, before zooming in to examine theoretical problems and solutions in detail. Finally, the third section provides case studies and applications, demonstrating solution troubleshooting and design from a variety of perspectives and for a range of technologies. Readers will develop new strategies and techniques for leveraging data towards real-world outcomes. Including five brand new chapters on emerging technological solutions, Big Data Application in Power Systems, Second Edition remains an essential resource for the reader aiming to utilize the potential of big data in the power systems of the future. - Provides a total refresh to include the most up-to-date research, developments, and challenges - Focuses on practical techniques, including rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches for processing high dimensional, heterogeneous, and spatiotemporal data - Engages with cross-disciplinary lessons, drawing on the impact of intersectional technology including statistics, computer science, and bioinformatics - Includes five brand new chapters on hot topics, ranging from uncertainty decision-making to features, selection methods, and the opportunities provided by social network data




Smart Meter Data Analytics


Book Description

This book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied. The following works try to model complex consumer behavior. Specific works include load profiling, pattern recognition, personalized price design, socio-demographic information identification, and household behavior coding. On this basis, the book extends consumer behavior in spatial and temporal scale. Works such as consumer aggregation, individual load forecasting, and aggregated load forecasting are introduced. We hope this book can inspire readers to define new problems, apply novel methods, and obtain interesting results with massive smart meter data or even other monitoring data in the power systems.




Design of Smart Power Grid Renewable Energy Systems


Book Description

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.




Intelligent Renewable Energy Systems


Book Description

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.




Application of Machine Learning and Deep Learning Methods to Power System Problems


Book Description

This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.




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.