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Machine Learning Applications for Intelligent Energy Management

Author: Haris Doukas

Publisher: Springer

Published: 2024-02-02

Total Pages: 0

ISBN-13: 9783031479083

As carbon dioxide (CO2) emissions and other greenhouse gases constantly rise and constitute the main contributor to climate change, temperature rise and global warming, artificial intelligence, big data, Internet of things, and blockchain technologies are enlisted to help enforce energy transition and transform the entire energy sector. The book at hand presents state-of-the-art developments in artificial intelligence-empowered analytics of energy data and artificial intelligence-empowered application development. Topics covered include a presentation of the various stakeholders in the energy sector and their corresponding required analytic services, such as state-of-the-art machine learning, artificial intelligence, and optimization models and algorithms tailored for a series of demanding energy problems and aiming at providing optimal solutions under specific constraints. Professors, researchers, scientists, engineers, and students in energy sector-related disciplines are expected to be inspired and benefit from this book, along with readers from other disciplines wishing to learn more about this exciting new field of research.

Predictive Modelling for Energy Management and Power Systems Engineering

Author: Ravinesh Deo

Publisher: Elsevier

Published: 2020-09-30

Total Pages: 553

ISBN-13: 012817773X

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Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets. Presents advanced optimization techniques to improve existing energy demand system Provides data-analytic models and their practical relevance in proven case studies Explores novel developments in machine-learning and artificial intelligence applied in energy management Provides modeling theory in an easy-to-read format

Applications of Big Data and Artificial Intelligence in Smart Energy Systems

Author: Neelu Nagpal

Publisher: CRC Press

Published: 2023-09-29

Total Pages: 318

ISBN-13: 1000963829

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In the era of propelling traditional energy systems to evolve towards smart energy systems, including power generation, energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, domestic loads, and industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution, automation, energy regulation & control, and energy trading. This book covers the applications of various big data analytics,artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book delves into the new technologies for modern power systems such as the Internet of Things, Blockchain for smart home and smart city solutions in depth. Technical topics discussed in the book include: • Hybrid smart energy system technologies • Smart meters • Energy demand forecasting • Use of different protocols and communication in smart energy systems • Power quality and allied issues and mitigation using AI • Intelligent transportation • Virtual power plants • AI based smart energy business models • Smart home solutions • Blockchain solutions for smart grids.

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

Smart Energy Management

Author: Kaile Zhou

Publisher: Springer

Published: 2022-03-18

Total Pages: 310

ISBN-13: 9789811693595

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This book provides a relatively whole view of data-driven decision-making methods for energy service innovation and energy system optimization. Through personalized energy services provision and energy efficiency improvement, the book can contribute to the green transformation of energy system and the sustainable development of the society. The book gives a new way to achieve smart energy management, based on various data mining and machine learning methods, including fuzzy clustering, shape-based clustering, ensemble clustering, deep learning, and reinforcement learning. The applications of these data-driven methods in improving energy efficiency and supporting energy service innovation are presented. Moreover, this book also investigates the role of blockchain in supporting peer-to-peer (P2P) electricity trading innovation, thus supporting smart energy management. The general scope of this book mainly includes load clustering, load forecasting, price-based demand response, incentive-based demand response, and energy blockchain-based electricity trading. The intended readership of the book includes researchers and engineers in related areas, graduate and undergraduate students in university, and some other general interested audience. The important features of the book are: (1) it introduces various data-driven methods for achieving different smart energy management tasks; (2) it investigates the role of data-driven methods in supporting various energy service innovation; and (3) it explores energy blockchain in P2P electricity trading, and thus supporting smart energy management.

Machine Learning for Energy Systems

Author: Denis Sidorov

Publisher: MDPI

Published: 2020-12-08

Total Pages: 272

ISBN-13: 3039433822

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This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

Applications of Big Data and Artificial Intelligence in Smart Energy Systems

Author: Neelu Nagpal

Publisher: CRC Press

Published: 2023-11-23

Total Pages: 250

ISBN-13: 1000963977

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In the era of propelling traditional energy systems to evolve towards smart energy systems, including power generation, energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, and domestic & industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution automation, energy regulation and control, and energy trading. This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book delves into the new technologies such as the Internet of Things, blockchain, etc. for smart home solutions, and smart city solutions in depth in the context of the modern power systems. Technical topics discussed in the book include: • Hybrid smart energy system technologies • Energy demand forecasting • Use of different protocols and communication in smart energy systems • Power quality and allied issues and mitigation using AI • Intelligent transportation • Virtual power plants • AI business models.

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.

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.

Artificial Intelligence of Things for Smart Green Energy Management

Author: Sarah El Himer

Publisher: Springer Nature

Published: 2022-06-23

Total Pages: 240

ISBN-13: 3031048512

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This book is intended to assist in the development of smart and efficient green energy solutions. It introduces energy systems, power generation, and power demands which able to minimise generation costs, power loss or environmental effects. It proposes cutting-edge solutions and approaches based on recent technologies such as intelligent renewable energy systems (wind and solar). These solutions, applied to different sectors, can provide a solid basis for meeting the needs of both developed and developing countries. The book provides a collection of contributions including new techniques, methods, algorithms, practical solutions and models based on applying artificial intelligence and the Internet of things into green energy management systems. It provides a comprehensive reference for researchers, scholars and industry in the field of green energy and computational intelligence.