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Renewable Energy Forecasting

Renewable Energy Forecasting
Author: Georges Kariniotakis
Publisher: Woodhead Publishing
Total Pages: 388
Release: 2017-09-29
Genre: Technology & Engineering
ISBN: 0081005059

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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. Offers comprehensive coverage of wind, solar, wave, and hydropower forecasting in one convenient volume Addresses a topic that is growing in importance, given the increasing penetration of renewable energy in many countries Reviews state-of-the-science techniques for renewable energy forecasting Contains chapters on operational applications


Artificial Intelligence for Renewable Energy Systems

Artificial Intelligence for Renewable Energy Systems
Author: Ajay Kumar Vyas
Publisher: John Wiley & Sons
Total Pages: 276
Release: 2022-03-02
Genre: Computers
ISBN: 1119761697

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ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.


Forecasting in Mathematics

Forecasting in Mathematics
Author: Abdo Abou Jaoude
Publisher: BoD – Books on Demand
Total Pages: 156
Release: 2021-01-27
Genre: Computers
ISBN: 1838808256

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Mathematical probability and statistics are an attractive, thriving, and respectable part of mathematics. Some mathematicians and philosophers of science say they are the gateway to mathematics’ deepest mysteries. Moreover, mathematical statistics denotes an accumulation of mathematical discussions connected with efforts to most efficiently collect and use numerical data subject to random or deterministic variations. Currently, the concept of probability and mathematical statistics has become one of the fundamental notions of modern science and the philosophy of nature. This book is an illustration of the use of mathematics to solve specific problems in engineering, statistics, and science in general.


Development of an Offshore Specific Wind Power Forecasting System

Development of an Offshore Specific Wind Power Forecasting System
Author: Melih Kurt
Publisher: kassel university press GmbH
Total Pages: 200
Release: 2017-01-01
Genre:
ISBN: 3737603464

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This study explains the data preparation processes, plausibility checking of meteorological parameters, correction of met-mast wind speed, and also the determination of the nominal power of a wind farm using met-mast measurements. The wind speed correction of met-mast FINO1 is evaluated from the perspective of power produced by alpha ventus by using uncorrected and corrected measurements from this met-mast. Afterwards this data is used for the determination of nominal power for alpha ventus.


Review of Wind Energy Forecasting Methods for Modeling Ramping Events

Review of Wind Energy Forecasting Methods for Modeling Ramping Events
Author:
Publisher:
Total Pages: 77
Release: 2011
Genre:
ISBN:

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Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF. WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.


Physical Approach to Short-Term Wind Power Prediction

Physical Approach to Short-Term Wind Power Prediction
Author: Matthias Lange
Publisher: Springer
Total Pages: 0
Release: 2010-02-12
Genre: Science
ISBN: 9783642065088

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The effective integration of wind energy into the overall electricity supply is a technical and economical challenge because the availability of wind power is determined by fluctuating meteorological conditions. This book offers an approach to the ultimate goal of the short-term prediction of the power output of winds farms. Starting from basic aspects of atmospheric fluid dynamics, the authors discuss the structure of winds fields, the available forecast systems and the handling of the intrinsic, weather-dependent uncertainties in the regional prediction of the power generated by wind turbines. This book addresses scientists and engineers working in wind energy related R and D and industry, as well as graduate students and nonspecialists researchers in the fields of atmospheric physics and meteorology.


Wind Energy Explained

Wind Energy Explained
Author: James F. Manwell
Publisher: John Wiley & Sons
Total Pages: 704
Release: 2010-09-14
Genre: Technology & Engineering
ISBN: 9780470686287

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Wind energy’s bestselling textbook- fully revised. This must-have second edition includes up-to-date data, diagrams, illustrations and thorough new material on: the fundamentals of wind turbine aerodynamics; wind turbine testing and modelling; wind turbine design standards; offshore wind energy; special purpose applications, such as energy storage and fuel production. Fifty additional homework problems and a new appendix on data processing make this comprehensive edition perfect for engineering students. This book offers a complete examination of one of the most promising sources of renewable energy and is a great introduction to this cross-disciplinary field for practising engineers. “provides a wealth of information and is an excellent reference book for people interested in the subject of wind energy.” (IEEE Power & Energy Magazine, November/December 2003) “deserves a place in the library of every university and college where renewable energy is taught.” (The International Journal of Electrical Engineering Education, Vol.41, No.2 April 2004) “a very comprehensive and well-organized treatment of the current status of wind power.” (Choice, Vol. 40, No. 4, December 2002)


Soft Computing in Green and Renewable Energy Systems

Soft Computing in Green and Renewable Energy Systems
Author: Kasthurirangan Gopalakrishnan
Publisher: Springer Science & Business Media
Total Pages: 315
Release: 2011-08-20
Genre: Computers
ISBN: 3642221750

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Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems. Research is proceeding at jet speed on renewable energy (energy derived from natural resources such as sunlight, wind, tides, rain, geothermal heat, biomass, hydrogen, etc.) as policy makers, researchers, economists, and world agencies have joined forces in finding alternative sustainable energy solutions to current critical environmental, economic, and social issues. The innovative models, environmentally benign processes, data analytics, etc. employed in renewable energy systems are computationally-intensive, non-linear and complex as well as involve a high degree of uncertainty. Soft computing technologies, such as fuzzy sets and systems, neural science and systems, evolutionary algorithms and genetic programming, and machine learning, are ideal in handling the noise, imprecision, and uncertainty in the data, and yet achieve robust, low-cost solutions. As a result, intelligent and soft computing paradigms are finding increasing applications in the study of renewable energy systems. Researchers, practitioners, undergraduate and graduate students engaged in the study of renewable energy systems will find this book very useful.


IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions

IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions
Author: Corinna Möhrlen
Publisher: Academic Press
Total Pages: 390
Release: 2022-11-12
Genre: Technology & Engineering
ISBN: 0443186820

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Published as an Open Access book available on Science Direct, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions translates decades of academic knowledge and standard requirements into applicable procedures and decision support tools for the energy industry. Designed specifically for practitioners in the energy industry, readers will find the tools to maximize the value of renewable energy forecast information in operational decision-making applications and significantly reduce the costs of integrating large amounts of wind and solar generation assets into grid systems through more efficient management of the renewable generation variability. Authored by a group of international experts as part of the IEA Wind Task 36 (Wind Energy Forecasting), the book addresses the issue that many current operational forecast solutions are not properly optimized for their intended applications. It provides detailed guidelines and recommended practices on forecast solution selection processes, designing and executing forecasting benchmarks and trials, forecast solution evaluation, verification, and validation, and meteorological and power data requirements for real-time forecasting applications. In addition, the guidelines integrate probabilistic forecasting, integrate wind and solar forecasting, offer improved IT data exchange and data format standards, and have a dedicated section to dealing with the requirements for SCADA and meteorological measurements. A unique and comprehensive reference, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions is an essential guide for all practitioners involved in wind and solar energy generation forecasting from forecast vendors to end-users of renewable forecasting solutions. Brings together the decades-long expertise of authors from a range of backgrounds, including universities and government laboratories, commercial forecasters, and operational forecast end-users into a single comprehensive set of practices Addresses all areas of wind power forecasting, including forecasting methods, measurement selection, setup and data quality control, and the evaluation of forecasting processes related to renewable energy forecasting Provides purpose-built decision-support tools, process diagrams, and code examples to help readers visualize and navigate the book and support decision-making