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Renewable Energy Forecasting

Renewable Energy Forecasting
  • Author : Georges Kariniotakis
  • Publisher :Unknown
  • Release Date :2017-09-29
  • Total pages :386
  • ISBN : 9780081005057
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Summary : 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

Renewable Energy: Forecasting and Risk Management

Renewable Energy: Forecasting and Risk Management
  • Author : Philippe Drobinski,Mathilde Mougeot,Dominique Picard,Riwal Plougonven,Peter Tankov
  • Publisher :Unknown
  • Release Date :2018-12-27
  • Total pages :246
  • ISBN : 9783319990521
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Summary : Gathering selected, revised and extended contributions from the conference ‘Forecasting and Risk Management for Renewable Energy FOREWER’, which took place in Paris in June 2017, this book focuses on the applications of statistics to the risk management and forecasting problems arising in the renewable energy industry. The different contributions explore all aspects of the energy production chain: forecasting and probabilistic modelling of renewable resources, including probabilistic forecasting approaches; modelling and forecasting of wind and solar power production; prediction of electricity demand; optimal operation of microgrids involving renewable production; and finally the effect of renewable production on electricity market prices. Written by experts in statistics, probability, risk management, economics and electrical engineering, this multidisciplinary volume will serve as a reference on renewable energy risk management and at the same time as a source of inspiration for statisticians and probabilists aiming to work on energy-related problems.

Solar Energy Forecasting and Resource Assessment

Solar Energy Forecasting and Resource Assessment
  • Author : Jan Kleissl
  • Publisher :Unknown
  • Release Date :2013-06-25
  • Total pages :462
  • ISBN : 9780123977724
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Summary : Solar Energy Forecasting and Resource Assessment is a vital text for solar energy professionals, addressing a critical gap in the core literature of the field. As major barriers to solar energy implementation, such as materials cost and low conversion efficiency, continue to fall, issues of intermittency and reliability have come to the fore. Scrutiny from solar project developers and their financiers on the accuracy of long-term resource projections and grid operators’ concerns about variable short-term power generation have made the field of solar forecasting and resource assessment pivotally important. This volume provides an authoritative voice on the topic, incorporating contributions from an internationally recognized group of top authors from both industry and academia, focused on providing information from underlying scientific fundamentals to practical applications and emphasizing the latest technological developments driving this discipline forward. The only reference dedicated to forecasting and assessing solar resources enables a complete understanding of the state of the art from the world’s most renowned experts. Demonstrates how to derive reliable data on solar resource availability and variability at specific locations to support accurate prediction of solar plant performance and attendant financial analysis. Provides cutting-edge information on recent advances in solar forecasting through monitoring, satellite and ground remote sensing, and numerical weather prediction.

Time Series Analysis and Applications

Time Series Analysis and Applications
  • Author : Nawaz Mohamudally
  • Publisher :Unknown
  • Release Date :2018-01-24
  • Total pages :180
  • ISBN : 9789535137429
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Summary : Time Series Analysis (TSA) and Applications offers a dense content of current research and development in the field of data science. The book presents time series from a multidisciplinary approach that covers a wide range of sectors ranging from biostatistics to renewable energy forecasting. Contrary to previous literatures on time, serious readers will discover the potential of TSA in areas other than finance or weather forecasting. The choice of the algorithmic transform for different scenarios, which is a key determinant in the application of TSA, can be understood through the diverse domain applications. Readers looking for deep understanding and practicability of TSA will be delighted. Early career researchers too will appreciate the technicalities and refined mathematical complexities surrounding TSA. Our wish is that this book adds to the body of TSA knowledge and opens up avenues for those who are looking forward to applying TSA in their own context.

Time Series and Renewable Energy Forecasting

Time Series and Renewable Energy Forecasting
  • Author : Mahmoud Ghofrani
  • Publisher :Unknown
  • Release Date :2018
  • Total pages :229
  • ISBN : OCLC:1154228126
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Summary : Reliability is a key important criterion in every single system in the world, and it is not different in engineering. Reliability in power systems or electric grids can be generally defined as the availability time (capable of fully supplying the demand) of the system compared to the amount of time it is unavailable (incapable of supplying the demand). For systems with high uncertainties, such as renewable energy based power systems, achieving a high level of reliability is a formidable challenge due to the increased penetrations of the intermittent renewable sources such as wind and solar. A careful and accurate planning is at the utmost importance to achieve high reliability in renewable energy based systems. This chapter will assess wind-based power system's reliability issues, and provide a case study that proposes a solution to enhance the reliability of the system.

Renewable Energy Forecasting

Renewable Energy Forecasting
  • Author : Pierre Pinson,Henrik Madsen,Peder Bacher
  • Publisher :Unknown
  • Release Date :2020-07-10
  • Total pages :350
  • ISBN : 1118932625
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Summary :

Renewable Energy Resource Assessment and Forecasting

Renewable Energy Resource Assessment and Forecasting
  • Author : George Galanis
  • Publisher :Unknown
  • Release Date :2020-11-27
  • Total pages :306
  • ISBN : 9783039430864
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Summary : In recent years, several projects and studies have been launched towards the development and use of new methodologies, in order to assess, monitor, and support clean forms of energy. Accurate estimation of the available energy potential is of primary importance, but is not always easy to achieve. The present Special Issue on ‘Renewable Energy Resource Assessment and Forecasting’ aims to provide a holistic approach to the above issues, by presenting multidisciplinary methodologies and tools that are able to support research projects and meet today’s technical, socio-economic, and decision-making needs. In particular, research papers, reviews, and case studies on the following subjects are presented: wind, wave and solar energy; biofuels; resource assessment of combined renewable energy forms; numerical models for renewable energy forecasting; integrated forecasted systems; energy for buildings; sustainable development; resource analysis tools and statistical models; extreme value analysis and forecasting for renewable energy resources.

Time Series and Renewable Energy Forecasting, Chapter 12

Time Series and Renewable Energy Forecasting, Chapter 12
  • Author : Mahmoud Ghofrani
  • Publisher :Unknown
  • Release Date :2018
  • Total pages :1
  • ISBN : OCLC:1163857014
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Summary : Reliability is a key important criterion in every single system in the world, and it is not different in engineering. Reliability in power systems or electric grids can be generally defined as the availability time (capable of fully supplying the demand) of the system compared to the amount of time it is unavailable (incapable of supplying the demand). For systems with high uncertainties, such as renewable energy based power systems, achieving a high level of reliability is a formidable challenge due to the increased penetrations of the intermittent renewable sources such as wind and solar. A careful and accurate planning is at the utmost importance to achieve high reliability in renewable energy based systems. This chapter will assess wind-based power system's reliability issues, and provide a case study that proposes a solution to enhance the reliability of the system.

Time Series and Renewable Energy Forecasting, Chapter 6

Time Series and Renewable Energy Forecasting, Chapter 6
  • Author : Mahmoud Ghofrani
  • Publisher :Unknown
  • Release Date :2018
  • Total pages :1
  • ISBN : OCLC:1163856071
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Summary : Renewable energy generation has been constantly increasing during recent years. Wind and solar have had the most significant growths among all renewable resources. Wind and solar resources are highly intermittent and dependent on meteorological parameters and climatic conditions. The power output of wind turbines is subject to various meteorological parameters, such as wind speed, wind direction, air temperature, relative humidity, etc., among which the wind speed is the most direct and influential factor in wind power generation. Solar photovoltaic (PV) power is a function of solar radiation. Wind speed and solar radiation time series data exhibit unique features which complicate their prediction. This makes wind and solar power forecasting challenging. Accurate wind and solar forecasting enhances the value of renewable energy by improving the reliability and economic feasibility of these resources. It also supports integrating solar and wind power into electric grids by reducing the integration and operation costs associated with these intermittent generation sources. This chapter provides an overview of the time series methods that can be used for more accurate wind and solar forecasting.

Dependability Engineering

Dependability Engineering
  • Author : Fausto Pedro García Márquez,Mayorkinos Papaelias
  • Publisher :Unknown
  • Release Date :2018-06-06
  • Total pages :234
  • ISBN : 9781789232585
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Summary : The new technology and system communication advances are being employed in any system, being more complex. The system dependability considers the technical complexity, size, and interdependency of the system. The stochastic characteristic together with the complexity of the systems as dependability requires to be under control the Reliability, Availability, Maintainability, and Safety (RAMS). The dependability contemplates, therefore, the faults/failures, downtimes, stoppages, worker errors, etc. Dependability also refers to emergent properties, i.e., properties generated indirectly from other systems by the system analyzed. Dependability, understood as general description of system performance, requires advanced analytics that are considered in this book. Dependability management and engineering are covered with case studies and best practices. The diversity of the issues will be covered from algorithms, mathematical models, and software engineering, by design methodologies and technical or practical solutions. This book intends to provide the reader with a comprehensive overview of the current state of the art, case studies, hardware and software solutions, analytics, and data science in dependability engineering.

Energy Time Series Forecasting

Energy Time Series Forecasting
  • Author : Lars Dannecker
  • Publisher :Unknown
  • Release Date :2015-08-06
  • Total pages :231
  • ISBN : 9783658110390
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Summary : Lars Dannecker developed a novel online forecasting process that significantly improves how forecasts are calculated. It increases forecasting efficiency and accuracy, as well as allowing the process to adapt to different situations and applications. Improving the forecasting efficiency is a key pre-requisite for ensuring stable electricity grids in the face of an increasing amount of renewable energy sources. It is also important to facilitate the move from static day ahead electricity trading towards more dynamic real-time marketplaces. The online forecasting process is realized by a number of approaches on the logical as well as on the physical layer that we introduce in the course of this book. Nominated for the Georg-Helm-Preis 2015 awarded by the Technische Universität Dresden.

Probabilistic Renewable Energy Forecasting by Considering Spatial-temporal Correlation

Probabilistic Renewable Energy Forecasting by Considering Spatial-temporal Correlation
  • Author : Mucun Sun
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :229
  • ISBN : OCLC:1199385443
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Summary : Renewable energy forecasts can help reduce the amount of operating reserves needed for the system, reducing costs of balancing the system, and improving the reliability of the system. Conventional deterministic forecasts might not be sufficient to characterize the inherent uncertainty of renewable energy. Probabilistic forecasts that provide quantitative uncertainty information associated with renewable energy are therefore expected to better assist power system operations. Meanwhile, studies have shown that the integration of geographically dispersed and correlated wind/solar farms could reduce extreme power output, which is referred to as smoothing effect. In addition, power produced from one wind/solar farm at different times is typically temporally correlated. The impacts of spatial-temporal correlation between wind/solar farms on renewable energy forecasting are not well studied in the literature. This dissertation aims at mitigating power system uncertainty by improving probabilistic renewable energy forecasting accuracy utilizing spatial-temporal correlation modeling. In this dissertation, a variety of methods, such as predictive distribution optimization, ensemble learning, deep learning, and scenario generation-based methods, are developed to assist spatial-temporal correlation modeling, and improve probabilistic forecasting accuracy. Computational experiments indicate that the presented study can provide scholars and engineers with critical insights to the usage of spatial-temporal modeling in probabilistic renewable energy forecasting and anomaly detection, and also serve as a valuable reference for practical industry forecasting systems.

Analytics and Optimization for Renewable Energy Integration

Analytics and Optimization for Renewable Energy Integration
  • Author : Ning Zhang,Chongqing Kang,Ershun Du,Yi Wang
  • Publisher :Unknown
  • Release Date :2019-02-21
  • Total pages :372
  • ISBN : 9780429847691
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Summary : The scope of this book covers the modeling and forecast of renewable energy and operation and planning of power system with renewable energy integration.The first part presents mathematical theories of stochastic mathematics; the second presents modeling and analytic techniques for renewable energy generation; the third provides solutions on how to handle the uncertainty of renewable energy in power system operation. It includes advanced stochastic unit commitment models to acquire the optimal generation schedule under uncertainty, efficient algorithms to calculate the probabilistic power, and an efficient operation strategy for renewable power plants participating in electricity markets.

Real-time Forecasting for Renewable Energy Development

Real-time Forecasting for Renewable Energy Development
  • Author : United States. Congress. House. Committee on Science and Technology (2007). Subcommittee on Energy and Environment
  • Publisher :Unknown
  • Release Date :2010
  • Total pages :96
  • ISBN : UCSD:31822037817574
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Summary : "A significant barrier to the widespread adoption of many forms of renewable energy, including wind, solar, and marine and hydrokinetic power, is that these sources are intermittent. Electric grid managers address this intermittency by adjusting the delivery of other sources of power based on expected changes in renewable power output. These expected changes are called power production forecasts. Such forecasts must take into account changing weather conditions in conjunction with the land's topography near a renewable energy device, along with the device's expected technical performance ... Several recent reports have determined that improving the accuracy and frequency of these forecasts can have a major impact on the economic viability of renewable energy resources" ... This hearing provides "testimony on the roles that various Federal agencies as well as the private sector play in providing forecasting data and services relevant to expanding the availability of reliable, renewable power, and the extent to which these efforts are coordinated. The hearing will also explore any research, development, demonstration, and monitoring needs that are not currently being adequately addressed."--P. 3-4.

Renewable Energy Integration

Renewable Energy Integration
  • Author : Lawrence E. Jones
  • Publisher :Unknown
  • Release Date :2014-06-12
  • Total pages :474
  • ISBN : 9780124081222
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Summary : Renewable Energy Integration is a ground-breaking new resource - the first to offer a distilled examination of the intricacies of integrating renewables into the power grid and electricity markets. It offers informed perspectives from internationally renowned experts on the challenges to be met and solutions based on demonstrated best practices developed by operators around the world. The book's focus on practical implementation of strategies provides real-world context for theoretical underpinnings and the development of supporting policy frameworks. The book considers a myriad of wind, solar, wave and tidal integration issues, thus ensuring that grid operators with low or high penetration of renewable generation can leverage the victories achieved by their peers. Renewable Energy Integration highlights, carefully explains, and illustrates the benefits of advanced technologies and systems for coping with variability, uncertainty, and flexibility. Lays out the key issues around the integration of renewables into power grids and markets, from the intricacies of operational and planning considerations, to supporting regulatory and policy frameworks Provides global case studies that highlight the challenges of renewables integration and present field-tested solutions Illustrates enabling and disruptive technologies to support the management of variability, uncertainty and flexibility

Intelligent Distributed Computing VIII

Intelligent Distributed Computing VIII
  • Author : David Camacho,Lars Braubach,Salvatore Venticinque,Costin Badica
  • Publisher :Unknown
  • Release Date :2014-09-02
  • Total pages :476
  • ISBN : 9783319104225
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Summary : This book represents the combined peer-reviewed proceedings of the Eight International Symposium on Intelligent Distributed Computing - IDC'2014, of the Workshop on Cyber Security and Resilience of Large-Scale Systems - WSRL-2014, and of the Sixth International Workshop on Multi-Agent Systems Technology and Semantics- MASTS-2014. All the events were held in Madrid, Spain, during September 3-5, 2014. The 47 contributions published in this book address several topics related to theory and applications of the intelligent distributed computing and multi-agent systems, including: agent-based data processing, ambient intelligence, collaborative systems, cryptography and security, distributed algorithms, grid and cloud computing, information extraction, knowledge management, big data and ontologies, social networks, swarm intelligence or videogames amongst others.

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction
  • Author : Harsh S. Dhiman,Valentina Emilia Balas
  • Publisher :Unknown
  • Release Date :2020-01-20
  • Total pages :216
  • ISBN : 9780128213537
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Summary : Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation. Features various supervised machine learning based regression models Offers global case studies for turbine wind farm layouts Includes state-of-the-art models and methodologies in wind forecasting

Renewable Energy Integration

Renewable Energy Integration
  • Author : Lawrence E. Jones
  • Publisher :Unknown
  • Release Date :2014-06-12
  • Total pages :474
  • ISBN : 9780124081222
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Summary : Renewable Energy Integration is a ground-breaking new resource - the first to offer a distilled examination of the intricacies of integrating renewables into the power grid and electricity markets. It offers informed perspectives from internationally renowned experts on the challenges to be met and solutions based on demonstrated best practices developed by operators around the world. The book's focus on practical implementation of strategies provides real-world context for theoretical underpinnings and the development of supporting policy frameworks. The book considers a myriad of wind, solar, wave and tidal integration issues, thus ensuring that grid operators with low or high penetration of renewable generation can leverage the victories achieved by their peers. Renewable Energy Integration highlights, carefully explains, and illustrates the benefits of advanced technologies and systems for coping with variability, uncertainty, and flexibility. Lays out the key issues around the integration of renewables into power grids and markets, from the intricacies of operational and planning considerations, to supporting regulatory and policy frameworks Provides global case studies that highlight the challenges of renewables integration and present field-tested solutions Illustrates enabling and disruptive technologies to support the management of variability, uncertainty and flexibility

Energy Forecasting Tools and Services

Energy Forecasting Tools and Services
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :2017
  • Total pages :229
  • ISBN : OCLC:1032100982
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Summary : Abstract : The increasing complexity of the power grid and the continuous integration of volatile renewable energy systems on all aspects of it have made more precise forecasts of both energy supply and demand necessary for the future Smart Grid. Yet, the ever increasing volume of tools and services makes it difficult for users (e.g., energy utility companies) and researchers to obtain even a general sense of what each tool or service offers. The present contribution provides an overview and categorization of several energy‐related forecasting tools and services (specifically for load and volatile renewable power), as well as general information regarding principles of time series, load, and volatile renewable power forecasting. WIREs Data Mining Knowl Discov 2018, 8:e1235. doi: 10.1002/widm.1235 This article is categorized under: Application Areas > Business and Industry Application Areas > Data Mining Software Tools Technologies > Prediction Abstract : Forecasts provide the only option for the correct planning and scheduling of the power grid. The ever increasing volume of forecasting tools and services makes it difficult to obtain even a general sense of what each tool or service offers. The present contribution provides an overview and categorization of several energy‐related forecasting tools and services.

Weather & Climate Services for the Energy Industry

Weather & Climate Services for the Energy Industry
  • Author : Alberto Troccoli
  • Publisher :Unknown
  • Release Date :2018-01-03
  • Total pages :197
  • ISBN : 9783319684185
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Summary : This open access book showcases the burgeoning area of applied research at the intersection between weather and climate science and the energy industry. It illustrates how better communication between science and industry can help both sides. By opening a dialogue, scientists can understand the broader context for their work and the energy industry is able to keep track of and implement the latest scientific advances for more efficient and sustainable energy systems. Weather & Climate Services for the Energy Industry considers the lessons learned in establishing an ongoing discussion between the energy industry and the meteorological community and how its principles and practises can be applied elsewhere. This book will be a useful guiding resource for research and early career practitioners concerned with the energy industry and the new field of research known as energy meteorology.

Soft Computing in Green and Renewable Energy Systems

Soft Computing in Green and Renewable Energy Systems
  • Author : Kasthurirangan Gopalakrishnan,Siddhartha Kumar Khaitan,Soteris Kalogirou
  • Publisher :Unknown
  • Release Date :2011-08-20
  • Total pages :306
  • ISBN : 9783642221750
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Summary : 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.