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Long Term Electric Load Demand Forecasting And Modeling
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Book Synopsis Electrical Load Forecasting by : S.A. Soliman
Download or read book Electrical Load Forecasting written by S.A. Soliman and published by Elsevier. This book was released on 2010-05-26 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Applied Mathematics for Restructured Electric Power Systems by : Joe H. Chow
Download or read book Applied Mathematics for Restructured Electric Power Systems written by Joe H. Chow and published by Springer. This book was released on 2010-12-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Mathematics for Restructured Electric Power Systems: Optimization, Control, and Computational Intelligence consists of chapters based on work presented at a National Science Foundation workshop organized in November 2003. The theme of the workshop was the use of applied mathematics to solve challenging power system problems. The areas included control, optimization, and computational intelligence. In addition to the introductory chapter, this book includes 12 chapters written by renowned experts in their respected fields. Each chapter follows a three-part format: (1) a description of an important power system problem or problems, (2) the current practice and/or particular research approaches, and (3) future research directions. Collectively, the technical areas discussed are voltage and oscillatory stability, power system security margins, hierarchical and decentralized control, stability monitoring, embedded optimization, neural network control with adaptive critic architecture, control tuning using genetic algorithms, and load forecasting and component prediction. This volume is intended for power systems researchers and professionals charged with solving electric and power system problems.
Book Synopsis Short-Term Load Forecasting 2019 by : Antonio Gabaldón
Download or read book Short-Term Load Forecasting 2019 written by Antonio Gabaldón and published by MDPI. This book was released on 2021-02-26 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Short-term load forecasting (STLF) plays a key role in the formulation of economic, reliable, and secure operating strategies (planning, scheduling, maintenance, and control processes, among others) for a power system and will be significant in the future. However, there is still much to do in these research areas. The deployment of enabling technologies (e.g., smart meters) has made high-granularity data available for many customer segments and to approach many issues, for instance, to make forecasting tasks feasible at several demand aggregation levels. The first challenge is the improvement of STLF models and their performance at new aggregation levels. Moreover, the mix of renewables in the power system, and the necessity to include more flexibility through demand response initiatives have introduced greater uncertainties, which means new challenges for STLF in a more dynamic power system in the 2030–50 horizon. Many techniques have been proposed and applied for STLF, including traditional statistical models and AI techniques. Besides, distribution planning needs, as well as grid modernization, have initiated the development of hierarchical load forecasting. Analogously, the need to face new sources of uncertainty in the power system is giving more importance to probabilistic load forecasting. This Special Issue deals with both fundamental research and practical application research on STLF methodologies to face the challenges of a more distributed and customer-centered power system.
Book Synopsis Forecasting and Assessing Risk of Individual Electricity Peaks by : Maria Jacob
Download or read book Forecasting and Assessing Risk of Individual Electricity Peaks written by Maria Jacob and published by Springer Nature. This book was released on 2019-09-25 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks. A cross-section of popular demand forecasting algorithms from statistics, machine learning and mathematics is presented, followed by extreme value theory techniques with examples. In order to achieve carbon targets, good forecasts of peaks are essential. For instance, shifting demand or charging battery depends on correct demand predictions in time. Majority of forecasting algorithms historically were focused on average load prediction. In order to model the peaks, methods from extreme value theory are applied. This allows us to study extremes without making any assumption on the central parts of demand distribution and to predict beyond the range of available data. While applied on individual loads, the techniques described in this book can be extended naturally to substations, or to commercial settings. Extreme value theory techniques presented can be also used across other disciplines, for example for predicting heavy rainfalls, wind speed, solar radiation and extreme weather events. The book is intended for students, academics, engineers and professionals that are interested in short term load prediction, energy data analytics, battery control, demand side response and data science in general.
Book Synopsis Spatial Electric Load Forecasting by : H. Lee Willis
Download or read book Spatial Electric Load Forecasting written by H. Lee Willis and published by CRC Press. This book was released on 2002-08-09 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: Containing 12 new chapters, this second edition offers increased coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.
Book Synopsis Learning and Soft Computing by : Vojislav Kecman
Download or read book Learning and Soft Computing written by Vojislav Kecman and published by MIT Press. This book was released on 2001 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.
Book Synopsis Modeling and Forecasting Electricity Loads and Prices by : Rafal Weron
Download or read book Modeling and Forecasting Electricity Loads and Prices written by Rafal Weron and published by John Wiley & Sons. This book was released on 2007-01-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an in-depth and up-to-date review of different statistical tools that can be used to analyze and forecast the dynamics of two crucial for every energy company processes—electricity prices and loads. It provides coverage of seasonal decomposition, mean reversion, heavy-tailed distributions, exponential smoothing, spike preprocessing, autoregressive time series including models with exogenous variables and heteroskedastic (GARCH) components, regime-switching models, interval forecasts, jump-diffusion models, derivatives pricing and the market price of risk. Modeling and Forecasting Electricity Loads and Prices is packaged with a CD containing both the data and detailed examples of implementation of different techniques in Matlab, with additional examples in SAS. A reader can retrace all the intermediate steps of a practical implementation of a model and test his understanding of the method and correctness of the computer code using the same input data. The book will be of particular interest to the quants employed by the utilities, independent power generators and marketers, energy trading desks of the hedge funds and financial institutions, and the executives attending courses designed to help them to brush up on their technical skills. The text will be also of use to graduate students in electrical engineering, econometrics and finance wanting to get a grip on advanced statistical tools applied in this hot area. In fact, there are sixteen Case Studies in the book making it a self-contained tutorial to electricity load and price modeling and forecasting.
Book Synopsis Optimization of Power System Problems by : Mahmoud Pesaran Hajiabbas
Download or read book Optimization of Power System Problems written by Mahmoud Pesaran Hajiabbas and published by Springer Nature. This book was released on 2020-01-06 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents integrated optimization methods and algorithms for power system problems along with their codes in MATLAB. Providing a reliable and secure power and energy system is one of the main challenges of the new era. Due to the nonlinear multi-objective nature of these problems, the traditional methods are not suitable approaches for solving large-scale power system operation dilemmas. The integration of optimization algorithms into power systems has been discussed in several textbooks, but this is the first to include the integration methods and the developed codes. As such, it is a useful resource for undergraduate and graduate students, researchers and engineers trying to solve power and energy optimization problems using modern technical and intelligent systems based on theory and application case studies. It is expected that readers have a basic mathematical background.
Book Synopsis Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2021 by : Aboul Ella Hassanien
Download or read book Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2021 written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2021-11-08 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceeding book constitutes the refereed proceedings of the 7th International Conference on Advanced Intelligent Systems and Informatics (AISI 2021), which took place in Cairo, Egypt, during December 11-13, 2021, and is an international interdisciplinary conference that presents a spectrum of scientific research on all aspects of informatics and intelligent systems, technologies, and applications.
Download or read book International Energy Outlook written by and published by . This book was released on 1986 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forecasting in Mathematics by : Abdo Abou Jaoude
Download or read book Forecasting in Mathematics written by Abdo Abou Jaoude and published by BoD – Books on Demand. This book was released on 2021-01-27 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Forecasting: principles and practice by : Rob J Hyndman
Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Book Synopsis Power System Planning Technologies and Applications: Concepts, Solutions and Management by : Elkarmi, Fawwaz
Download or read book Power System Planning Technologies and Applications: Concepts, Solutions and Management written by Elkarmi, Fawwaz and published by IGI Global. This book was released on 2012-02-29 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the technical planning of power systems, taking into account technological evolutions in equipment as well as the economic, financial, and societal factors that drive supply and demand and have implications for technical planning at the micro level"--Provided by publisher.
Book Synopsis Electric Power System Planning by : Hossein Seifi
Download or read book Electric Power System Planning written by Hossein Seifi and published by Springer Science & Business Media. This book was released on 2011-06-24 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present book addresses various power system planning issues for professionals as well as senior level and postgraduate students. Its emphasis is on long-term issues, although much of the ideas may be used for short and mid-term cases, with some modifications. Back-up materials are provided in twelve appendices of the book. The readers can use the numerous examples presented within the chapters and problems at the end of the chapters, to make sure that the materials are adequately followed up. Based on what Matlab provides as a powerful package for students and professional, some of the examples and the problems are solved in using M-files especially developed and attached for this purpose. This adds a unique feature to the book for in-depth understanding of the materials, sometimes, difficult to apprehend mathematically. Chapter 1 provides an introduction to Power System Planning (PSP) issues and basic principles. As most of PSP problems are modeled as optimization problems, optimization techniques are covered in some details in Chapter 2. Moreover, PSP decision makings are based on both technical and economic considerations, so economic principles are briefly reviewed in Chapter 3. As a basic requirement of PSP studies, the load has to be known. Therefore, load forecasting is presented in Chapter 4. Single bus Generation Expansion Planning (GEP) problem is described in Chapter 5. This study is performed using WASP-IV, developed by International Atomic Energy Agency. The study ignores the grid structure. A Multi-bus GEP problem is discussed in Chapter 6 in which the transmission effects are, somehow, accounted for. The results of single bus GEP is used as an input to this problem. SEP problem is fully presented in Chapter 7. Chapter 8 devotes to Network Expansion Planning (NEP) problem, in which the network is planned. The results of NEP, somehow, fixes the network structure. Some practical considerations and improvements such as multi-voltage cases are discussed in Chapter 9. As NEP study is typically based on some simplifying assumptions and Direct Current Load Flow (DCLF) analysis, detailed Reactive Power Planning (RPP) study is finally presented in Chapter 10, to guarantee acceptable ACLF performance during normal as well as contingency conditions. This, somehow, concludes the basic PSP problem. The changing environments due to power system restructuring dictate some uncertainties on PSP issues. It is shown in Chapter 11 that how these uncertainties can be accounted for. Although is intended to be a text book, PSP is a research oriented topic, too. That is why Chapter 12 is devoted to research trends in PSP. The chapters conclude with a comprehensive example in Chapter 13, showing the step-by-step solution of a practical case.
Book Synopsis Artificial Intelligence for Renewable Energy Systems by : Ajay Kumar Vyas
Download or read book Artificial Intelligence for Renewable Energy Systems written by Ajay Kumar Vyas and published by John Wiley & Sons. This book was released on 2022-03-02 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Recurrent Neural Networks for Short-Term Load Forecasting by : Filippo Maria Bianchi
Download or read book Recurrent Neural Networks for Short-Term Load Forecasting written by Filippo Maria Bianchi and published by Springer. This book was released on 2017-11-09 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series. Indeed, both service interruptions and resource waste can be reduced with the implementation of an effective forecasting system. Significant research has thus been devoted to the design and development of methodologies for short term load forecasting over the past decades. A class of mathematical models, called Recurrent Neural Networks, are nowadays gaining renewed interest among researchers and they are replacing many practical implementations of the forecasting systems, previously based on static methods. Despite the undeniable expressive power of these architectures, their recurrent nature complicates their understanding and poses challenges in the training procedures. Recently, new important families of recurrent architectures have emerged and their applicability in the context of load forecasting has not been investigated completely yet. This work performs a comparative study on the problem of Short-Term Load Forecast, by using different classes of state-of-the-art Recurrent Neural Networks. The authors test the reviewed models first on controlled synthetic tasks and then on different real datasets, covering important practical cases of study. The text also provides a general overview of the most important architectures and defines guidelines for configuring the recurrent networks to predict real-valued time series.
Book Synopsis Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting by : Anuradha Tomar
Download or read book Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting written by Anuradha Tomar and published by Springer Nature. This book was released on 2023-01-20 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
