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Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids.Provides expert analysis of the latest developments by global authoritiesContains detailed references for further reading and extended researchProvides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformaticsFocuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data.

Electric power systems. --- Smart power grids.

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Operation of Distributed Energy Resources in Smart Distribution Networks defines the barriers and challenges of smart distribution networks, ultimately proposing optimal solutions for addressing them. The book considers their use as an important part of future electrical power systems and their ability to improve the local flexibility and reliability of electrical systems. It carefully defines the concept as a radial network with a cluster of distributed energy generations, various types of loads, and energy storage systems. In addition, the book details how the huge penetration of distributed energy resources and the intermittent nature of renewable generations may cause system problems. Readers will find this to be an important resource that analyzes and introduces the features and problems of smart distribution networks from different aspects.

Smart power grids. --- Electric power distribution --- Renewable energy sources. --- Energy conservation.

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This book contains peer-reviewed papers from International Conference on Renewable and Clean Energy 2022 (contributions from various authors from all sectors of academia and industries), exploring cutting-edge solutions and best practices for renewable and clean energy technologies for achieving the UN's SDG7 to "ensure access to affordable, reliable, sustainable and modern energy for all." This book presents innovative grid integration technologies for techno-economic operation of renewable and clean energy technologies (e.g., solar photovoltaic, wind energy, hydrogen technologies including electrolyzer and fuel cell, energy storage technologies, etc.). It covers key aspects on energy conversion systems related to renewable energy technologies and their grid integration, techno-economic power dispatching from the distributed environmental-friendly energy sources considering combined heat and power applications, electrical energy network operation with increasing penetration of renewable energy sources, energy efficiency and demand side management, e-mobility, including machine learning applications for intelligent operation of energy systems, etc. The key objective of book is to educate the readers on how sustainable energy technologies can be integrated with energy conversion processes for achieving net zero targets in real-world applications. The book will serve as a useful reference for graduate students, academicians, industry professionals and policy makers interested in exploring the potential of energy technologies in development of sustainable energy system. .

Relation between energy and economics --- hernieuwbare energie --- Smart power grids --- Renewable energy sources --- Electric power systems

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With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch. Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts. (1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch. (2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast. (3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch. The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.

Artificial intelligence. Robotics. Simulation. Graphics --- mineralen (chemie) --- mijnbouw --- KI (kunstmatige intelligentie) --- Artificial intelligence. --- Smart power grids. --- AI (artificiële intelligentie)