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Long Term Residential Load Forecasting
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Book Synopsis Long-term Residential Load Forecasting by : University of California, San Diego. Department of Economics
Download or read book Long-term Residential Load Forecasting written by University of California, San Diego. Department of Economics and published by . This book was released on 1978 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 A Stochastic Approach to Short-term Residential Load Forecasting by : Ali Hussein Noureddine
Download or read book A Stochastic Approach to Short-term Residential Load Forecasting written by Ali Hussein Noureddine and published by . This book was released on 1992 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Long-term Load Forecasting in Electric Power Industry by : Esmaeil Oufi
Download or read book Long-term Load Forecasting in Electric Power Industry written by Esmaeil Oufi and published by . This book was released on 1997 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Residential Load Forecasting for Small Utilities by : G. Mayo
Download or read book Residential Load Forecasting for Small Utilities written by G. Mayo and published by . This book was released on 1985 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Smart Meter Data Analytics by : Yi Wang
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.
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 Overview of Long Range Load Forecasting by : James B. Woodard
Download or read book Overview of Long Range Load Forecasting written by James B. Woodard and published by . This book was released on 1972 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Electric Load Forecasting by : Stanford University. Energy Modeling Forum
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 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Changes in energy markets over the last decade have made capacity planning by electric utilities increasingly difficult, but also increasingly important to producers and users of energy. In particular, long-range forecasts f the use of electricity have received greater scrutiny, forecasting prolems and methods have become more complex, and results have been subject to greater uncertainty and challenge than before. EPRI, in the Energy Modeling Forum, brought together a working group from utilities, research institutes, government agencies, universities and consulting firms to identify the issues that could have significant impacts on future electricity consumption.
Book Synopsis Science & Engineering Researches by : Emre ÖZDEMİRCİ
Download or read book Science & Engineering Researches written by Emre ÖZDEMİRCİ and published by Livre de Lyon. This book was released on 2023-12-24 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Science & Engineering Researches
Book Synopsis Advanced Models of Energy Forecasting by : Xun Zhang
Download or read book Advanced Models of Energy Forecasting written by Xun Zhang and published by Frontiers Media SA. This book was released on 2022-11-23 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence Enabled Computational Methods for Smart Grid Forecast and Dispatch by : Yuanzheng Li
Download or read book Artificial Intelligence Enabled Computational Methods for Smart Grid Forecast and Dispatch written by Yuanzheng Li and published by Springer Nature. This book was released on 2023-05-05 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch. Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts. (1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch. (2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast. (3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch. The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.
Book Synopsis Demand Response Potential of Residential Load Equipments by : Oriol Sementé Tarragó
Download or read book Demand Response Potential of Residential Load Equipments written by Oriol Sementé Tarragó and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis was conducted inside the Smart Grids and Energy Markets (SGEM) project and as a continuation of SGEM Task 6.11, which aims to investigate the utilization of AMRs for spatial load analysis for long term load forecasting of households providing calculating mechanism of hourly level appliance consumptions in the modelling of Demand Response. The goals of this study are to disaggregate electrical loads of a sample of Finnish households to load device groups. Subsequently to divide these loads into critical and non-critical loads, which enables timely changes in operation, and as the final outcome, to present the Demand Response Potential of these households. Data for this study was obtained from a database consisting of hourly metered power consumption (AMR) data from 1630 households from Kainuu (Finland) and background information of those costumers. The final dataset is compound by 337 households from the original data, those which have District Heating as their primary heating system. Conditional Demand Analysis (CDA) is performed using regression analysis as a tool. The analysis was computed with MATLAB and the used regression technique is the Stepwise regression. The regression analysis consists of 24 independent equations multilinear regression for different models and as outcome the daily load profiles of the appliances included in each different model were obtained. The obtained load profiles for different appliances and models are presented in the CDA results and appendices, in both graphic and numeric format, this last in tables containing the obtained estimated coefficients and the INMODEL matrix. Subsequently, the obtained loads are divided into critical and non-critical loads, the latter ones being ones to allow for timey changes in operation. Demand Response (DR) analysis is performed defining the maximum allowed postponement in time of each load use within different scenarios. Subsequently, the DR potential for each scenario are graphically presented, according the defined time spans and seasons models and using the appliances load profiles obtained from the CDA. Finally, in the conclusions chapter, the main finding are summarized and the author's conclusions are presented, not only regarding the CDA and DR studies, but also about improvements in data collection and data analysis as well as further steps recommendations.
Book Synopsis Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence by : Hamido Fujita
Download or read book Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence written by Hamido Fujita and published by Springer Nature. This book was released on 2022-08-29 with total page 932 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 35th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2022, held in Kitakyushu, Japan, in July 2022. The 67 full papers and 11 short papers presented were carefully reviewed and selected from 127 submissions. The IEA/AIE 2022 conference focuses on focuses on applications of applied intelligent systems to solve real-life problems in all areas including business and finance, science, engineering, industry, cyberspace, bioinformatics, automation, robotics, medicine and biomedicine, and human-machine interactions.
Book Synopsis Long-Term Electric Load Demand Forecasting and Modeling by : Reza Sedaghati
Download or read book Long-Term Electric Load Demand Forecasting and Modeling written by Reza Sedaghati and published by LAP Lambert Academic Publishing. This book was released on 2015-01-06 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: The major concern for every electrical utility is the ability to provide reliable and uninterrupted service to their customers. Load forecasting is an important component for power system energy management system. Precise load forecasting helps the electric utility to make unit commitment decisions, reduce spinning reserve capacity and schedule device maintenance plan properly. Besides playing a key role in reducing the generation cost, it is also essential to the reliability of power systems. There are three types of load forecasts: short-term, medium-term and long-term. This book focuses on study of short term load forecasting. Long-term demand forecasting presents the first step in planning and developing future generation, transmission and distribution facilities. In this book study of a real sample (Shiraz power distribution network) for forecasting load growth is done, also evaluated various compensation methods from perspectives of long-term load forecasting.
