Download or read book Comparative Models for Electrical Load Forecasting written by Derek W. Bunn and published by . This book was released on 1985 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Takes a practical look at how short-term forecasting has actually been undertaken and is being developed in public utility organizations.
Download or read book Comparative Models for Electrical Load Forecasting written by Derek W. Bunn and published by . This book was released on 1985 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Takes a practical look at how short-term forecasting has actually been undertaken and is being developed in public utility organizations.
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
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.
Download or read book A Comparative Study of Electric Load Forecasting Models in the Iowa Environment written by Burton C. English and published by . This book was released on 1984 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Comparative models of short term forecasting of electric loads written by and published by . This book was released on 1904 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Aplicação de duas metodologias baseadas em estatísticas adaptativas, com a finalidade de modelar e prever o comportamento de uma série temporal (série histórica de carga elétrica horária) gerada pela concessionária de energia elétrica Light. Foi aplicada à série de carga elétrica horária a metodologia de amortecimento direto, utilizada para a previsão horária e diária de carga e o modelo de previsão adaptativa de carga elétrica horária de curto prazo (GUPTA, P.C.), utilizado para a previsão diária de carga. É demonstrado o bom desempenho do método de amortecimento direto na previsão horária de carga elétrica. Na previsão diária, o modelo de previsão adaptativa de curto prazo de cargas elétricas horárias (GUPTA, P.C) apresenta resultados superiores aos do método de amortecimento direto.
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.
Download or read book Commercial Industrial and Household Electrical Load Modelling and Short term Load Forecasting written by Hla-U-May Marma and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, a transfer function-based load model is determined for commercial and industrial load. This model is derived from the composite load model which consist of an induction motor and static load. This developed model is compared to composite load model by considering two cases: 1) a small motor composition load or commercial load and 2) higher motor composition load or industrial load. The research is conducted through MATLAB/Simulink simulation. In order to compare the dynamic response of developed model, a comparative study has been done between the two models. In addition, the influence of voltage and frequency dependency terms on the overall model accuracy for developed model has been evaluated through several case studies considering both voltage and frequency dependency disturbances. A short-term load forecast model is developed for an electrically heated house. This research work is based on experimental data collected by installing current sensors in a house in St. Johns, Newfoundland, Canada. The data was collected for three years and only one-year data is used for this model. The model is based on Recurrent Neural Network (RNN) with wavelet transform. The proposed model is verified by comparing other developed models in the literature through MATLAB deep learning toolbox and wavelet toolbox. The proposed model can more accurately forecast the load.
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.
Download or read book Energy Model Comparison an Overview written by Stanford University. Energy Modeling Forum and published by . This book was released on 1980 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introductory Time Series with R written by Paul S.P. Cowpertwait and published by Springer Science & Business Media. This book was released on 2009-05-28 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation. Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence enhances understanding of both the time series model and the R function used to fit the model to data. Finally, the model is used to analyse observed data taken from a practical application. By using R, the whole procedure can be reproduced by the reader. All the data sets used in the book are available on the website http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/. The book is written for undergraduate students of mathematics, economics, business and finance, geography, engineering and related disciplines, and postgraduate students who may need to analyse time series as part of their taught programme or their research.
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.
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.
Download or read book Complex Intelligent and Software Intensive Systems written by Leonard Barolli and published by Springer. This book was released on 2019-06-20 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents scientific interactions between the three interwoven and challenging areas of research and development of future ICT-enabled applications: software, complex systems and intelligent systems. Software intensive systems heavily interact with other systems, sensors, actuators, and devices, as well as other software systems and users. More and more domains involve software intensive systems, e.g. automotive, telecommunication systems, embedded systems in general, industrial automation systems and business applications. Moreover, web services offer a new platform for enabling software intensive systems. Complex systems research focuses on understanding overall systems rather than their components. Such systems are characterized by the changing environments in which they act, and they evolve and adapt through internal and external dynamic interactions. The development of intelligent systems and agents features the use of ontologies, and their logical foundations provide a fruitful impulse for both software intensive systems and complex systems. Research in the field of intelligent systems, robotics, neuroscience, artificial intelligence, and cognitive sciences is a vital factor in the future development and innovation of software intensive and complex systems.
Download or read book Smart Meter Data Analytics written by Yi Wang and published by Springer Nature. This book was released on 2020-02-24 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied. The following works try to model complex consumer behavior. Specific works include load profiling, pattern recognition, personalized price design, socio-demographic information identification, and household behavior coding. On this basis, the book extends consumer behavior in spatial and temporal scale. Works such as consumer aggregation, individual load forecasting, and aggregated load forecasting are introduced. We hope this book can inspire readers to define new problems, apply novel methods, and obtain interesting results with massive smart meter data or even other monitoring data in the power systems.
Download or read book Model Comparison for Energy Policy and Planning written by Stanford University. Energy Modeling Forum and published by . This book was released on 1979 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
