Download or read book A Peak Load Forecasting Model Case Study written by K. Morgan Macrae and published by Calgary : Canadian Energy Research Institute. This book was released on 1987 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Description of a computer model developed to account for electrical systemfactors, such as demand, time of use, customer profile and planning horizon, and their effects on system peak demand. The model tests the impact ofelectricity price changes on energy consumption and the demand forpower, by sector. Assuming no change in customer class load curves, themodel is thenused to derive a peak load forecast consistent with a long-term forecast ofcustomer class energy sales. The effects of potential load managementprograms and customer-owned electric power generation in specific sectors areassessed by modifying existing customer class load curves and electricitysales predictions.

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 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 767 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 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 Long Term Probabilistic Load Forecasting and Normalization with Hourly Information written by Jason R. Wilson and published by . This book was released on 2013 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: The classical approach to long term load forecasting is often limited to the use of peak load and weather information occurring with monthly or annual frequency. The method of using monthly and annual data in forecasting load for time series regression can sometimes lead to inaccurate forecasts, because data of this frequency lacks the requisite number of observations necessary. Load forecasters often have a hard time explaining the errors based on the limited information available through the low resolution data. The increasing usage of Smart Grid and Advanced Metering Infrastructure (AMI) technologies provides the utility load forecasters with high resolution, layered information to improve the load forecasting process. This paper examines the results of a more modern approach, which makes use of high resolution, hourly information to create more accurate and defensible forecasts. The approach has been deployed across many US utilities, including a recent implementation at North Carolina Electric Membership Corporation (NCEMC), which is used as the basis of the case study in this paper. Three key elements of long term load forecasting are being modernized: predictive modeling, scenario analysis and weather normalization.

Download or read book Modeling and Forecasting Electricity Loads and Prices written by Rafal Weron and published by Wiley. 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.

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 Energy Research Abstracts written by and published by . This book was released on 1988 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Travel Demand Forecasting Parameters and Techniques written by and published by Transportation Research Board. This book was released on 2012 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: TRB’s National Cooperative Highway Research Program (NCHRP) Report 716: Travel Demand Forecasting: Parameters and Techniques provides guidelines on travel demand forecasting procedures and their application for helping to solve common transportation problems.

Download or read book Electric Load Forecasting written by Stanford University. Energy Modeling Forum and published by . This book was released on 1980 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Electric Load Forecasting Scenario Design written by Stanford University. Energy Modeling Forum and published by . This book was released on 1978 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Learning Algorithms and Applications written by Witold Pedrycz and published by Springer Nature. This book was released on 2019-10-23 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.

Download or read book A Cost benefit Analysis of Accuracy in Peak Load Forecasting written by Barbara A. Waldman and published by . This book was released on 1978 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Statistical Learning Tools for Electricity Load Forecasting written by Anestis Antoniadis and published by Birkhäuser. This book was released on 2024-09-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph explores a set of statistical and machine learning tools that can be effectively utilized for applied data analysis in the context of electricity load forecasting. Drawing on their substantial research and experience with forecasting electricity demand in industrial settings, the authors guide readers through several modern forecasting methods and tools from both industrial and applied perspectives – generalized additive models (GAMs), probabilistic GAMs, functional time series and wavelets, random forests, aggregation of experts, and mixed effects models. A collection of case studies based on sizable high-resolution datasets, together with relevant R packages, then illustrate the implementation of these techniques. Five real datasets at three different levels of aggregation (nation-wide, region-wide, or individual) from four different countries (UK, France, Ireland, and the USA) are utilized to study five problems: short-term point-wise forecasting, selection of relevant variables for prediction, construction of prediction bands, peak demand prediction, and use of individual consumer data. This text is intended for practitioners, researchers, and post-graduate students working on electricity load forecasting; it may also be of interest to applied academics or scientists wanting to learn about cutting-edge forecasting tools for application in other areas. Readers are assumed to be familiar with standard statistical concepts such as random variables, probability density functions, and expected values, and to possess some minimal modeling experience.

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 Short Term Load Forecasting by Artificial Intelligent Technologies written by Wei-Chiang Hong and published by MDPI. This book was released on 2019-01-29 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Short-Term Load Forecasting by Artificial Intelligent Technologies" that was published in Energies

Download or read book Forecasting U S Electricity Demand written by Adela Maria Bolet and published by Routledge. This book was released on 2019-08-30 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the energy headlines of 1985 proclaim the waning of OPEC, the collapse of oil prices, and the demise of the nuclear power industry, few policy analysts are examining the dynamic challenges and opportunities that may confront the electric power industry during the remainder of this century. In this pioneering work, Adela Maria Bolet attempts to do exactly this, namely, to reconcile the differences among forecasters as to the future of electricity demand in the industrial, commercial, and residential sectors.