Prediction Techniques For Renewable Energy Generation And Load Demand Forecasting
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Prediction Techniques For Renewable Energy Generation And Load Demand Forecasting
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Author : Anuradha Tomar
language : en
Publisher: Springer Nature
Release Date : 2023-01-20
Prediction Techniques For Renewable Energy Generation And Load Demand Forecasting written by Anuradha Tomar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Technology & Engineering categories.
This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.
Renewable Energy Forecasting
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Author : Georges Kariniotakis
language : en
Publisher: Woodhead Publishing
Release Date : 2017-06-14
Renewable Energy Forecasting written by Georges Kariniotakis and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-14 with Technology & Engineering categories.
Renewable Energy Forecasting: From Models to Applications provides an overview of the state-of-the-art of renewable energy forecasting technology and its applications. After an introduction to the principles of meteorology and renewable energy generation, groups of chapters address forecasting models, very short-term forecasting, forecasting of extremes, and longer term forecasting. The final part of the book focuses on important applications of forecasting for power system management and in energy markets. Due to shrinking fossil fuel reserves and concerns about climate change, renewable energy holds an increasing share of the energy mix. Solar, wind, wave, and hydro energy are dependent on highly variable weather conditions, so their increased penetration will lead to strong fluctuations in the power injected into the electricity grid, which needs to be managed. Reliable, high quality forecasts of renewable power generation are therefore essential for the smooth integration of large amounts of solar, wind, wave, and hydropower into the grid as well as for the profitability and effectiveness of such renewable energy projects.
Electrical Load Forecasting
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Author : S.A. Soliman
language : en
Publisher: Elsevier
Release Date : 2010-05-26
Electrical Load Forecasting written by S.A. Soliman and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-26 with Business & Economics categories.
Succinct and understandable, this book is a step-by-step guide to the mathematics and construction of electrical load forecasting models. Written by one of the world’s foremost experts on the subject, Electrical Load Forecasting provides a brief discussion of algorithms, their advantages and disadvantages and when they are best utilized. The book begins with a good description of the basic theory and models needed to truly understand how the models are prepared so that they are not just blindly plugging and chugging numbers. This is followed by a clear and rigorous exposition of the statistical techniques and algorithms such as regression, neural networks, fuzzy logic, and expert systems. The book is also supported by an online computer program that allows readers to construct, validate, and run short and long term models. Step-by-step guide to model construction Construct, verify, and run short and long term models Accurately evaluate load shape and pricing Creat regional specific electrical load models
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.
Emerging Technologies For The Construction Of Renewable Energy Dominated Power System
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Author : Liansong Xiong
language : en
Publisher: Frontiers Media SA
Release Date : 2024-12-02
Emerging Technologies For The Construction Of Renewable Energy Dominated Power System written by Liansong Xiong and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-02 with Technology & Engineering categories.
Over the past decade, significant breakthroughs have been achieved in renewable energy generation, operation, and control technology, greatly enhancing the safe operation and efficient utilization of renewable energy. However, as the penetration ratio of the renewable energy continues to grow, the characteristics of randomness, variability, weak inertia and damping have posed great challenges to the power generation, operation and control. There is an urgent need to provide efficient, safe and diverse technological choices for the construction of the renewable energy-dominated power system: 1) Improving the efficiency of renewable energy generation and transmission; 2) Increasing the capability of renewable energy to support and regulate the system voltage, frequency, and inertia, thus guaranteeing the security and stability operation of power systems; 3) Scaling up development of offshore wind power and distributed renewable energy in remote regions like Gobi Desert requires technological innovation for further development
Data Driven Approaches For Efficient Smart Grid Systems
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Author : Jinran Wu
language : en
Publisher: Frontiers Media SA
Release Date : 2025-03-26
Data Driven Approaches For Efficient Smart Grid Systems written by Jinran Wu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-26 with Technology & Engineering categories.
This Research Topic aims to highlight the exciting potential of innovative forecasting methods and their practical applications using machine learning in smart grid systems (SGSs). Machine learning techniques, which encompass traditional neural networks and advanced deep learning methods, have gained significant attention for their ability to address the complex challenges within SGSs and simultaneously improve cost-effectiveness. It's important to note that when machine learning models are employed in SGSs, they primarily focus on forecasting. This emphasis is grounded in the models' impressive capability to accurately replicate the intricate dynamics that characterize smart grid systems. By harnessing these forecasting models, researchers and practitioners are equipped with a valuable tool to better understand and predict the behavior of SGSs. This not only contributes to academic advancements but also enhances the practical implementation of smart grid technologies.
Advances In Integrated Energy Systems Design Control And Optimization
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Author : Josep M. Guerrero
language : en
Publisher: MDPI
Release Date : 2018-03-23
Advances In Integrated Energy Systems Design Control And Optimization written by Josep M. Guerrero and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-23 with Mathematics categories.
This book is a printed edition of the Special Issue "Advances in Integrated Energy Systems Design, Control and Optimization" that was published in Applied Sciences
Big Data Application In Power Systems
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Author : Reza Arghandeh
language : en
Publisher: Elsevier
Release Date : 2017-11-27
Big Data Application In Power Systems written by Reza Arghandeh and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-27 with Science categories.
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 authorities - Contains detailed references for further reading and extended research - Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics - Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data
Low Carbon Oriented Improvement Strategy For Flexibility And Resiliency Of Multi Energy Systems
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Author : Yumin Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2024-09-18
Low Carbon Oriented Improvement Strategy For Flexibility And Resiliency Of Multi Energy Systems written by Yumin Zhang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-18 with Technology & Engineering categories.
Due to the inherent volatility and randomness, the increasing share of energy from renewable resources presents a challenge to the operation of multi-energy systems with heterogeneous energy carriers such as electricity, heat, hydrogen, etc. These factors will make the systems hard to adjust their supply and demand flexibly to maintain energy balance to ensure reliability. Further, this hinders the development of a low-carbon and economically viable energy system. By making full use of the synergistic interaction of generation, transmission, load demand, and energy storage, a three-fold approach focused on quantifying demand flexibility, evaluating supply capabilities, and enhancing resilience can unlock the flexibility potential across various sectors of new energy systems. This approach provides an effective means of facilitating the transition from conventional energy systems to low-carbon, clean-energy-oriented paradigms. However, huge challenges arising from renewable energy pose great obstacles to the aforementioned solution pathway. The main objectives of this Research Topic are： 1. Develop advanced carbon emission accounting and measurement techniques for emerging multi-energy systems 2. Design effective methods for predicting renewable electricity generation 3. Proposed efficient methods for quantitative assessment of uncertainty from renewables and loads 4. Put forward advanced evaluation, optimization, and planning strategies incorporating diverse flexibility resources 5. Design multifaceted market mechanisms and collaborative frameworks balancing economics and low carbon footprint 6. Develop operational control and resilience-enhancement techniques for distribution networks under large-scale distributed energy integration
Intelligent Learning Approaches For Renewable And Sustainable Energy
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Author : Josep M. Guerrero
language : en
Publisher: Elsevier
Release Date : 2024-02-21
Intelligent Learning Approaches For Renewable And Sustainable Energy written by Josep M. Guerrero and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-21 with Computers categories.
Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy.The book begins by introducing the intelligent learning approaches, and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. The second section of the book provides detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, and optimization, supported by case studies, figures, schematics, and references.This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence. - Explores cutting-edge intelligent techniques and their implications for future energy systems development - Opens the door to a range of applications across forecasting, supply and demand, energy management, optimization, and more - Includes a range of case studies that provide insights into the challenges and solutions in real-world applications