Forecasting and assessing risk of individual electricity peaks / Maria Jacob, Cláudia Neves, Danica Vukadinović Greetham.
Jacob, Maria.; Neves, Cláudia.; Vukadinović Greetham, Danica.
2020
TK1005
Available Online

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Title Forecasting and assessing risk of individual electricity peaks / Maria Jacob, Cláudia Neves, Danica Vukadinović Greetham.
Author Jacob, Maria.
ISBN 9783030286699 (electronic book)
303028669X (electronic book)
DOI https://doi.org/10.1007/978-3-030-28
Published Cham : SpringerOpen, 2020.
Language English
Description 1 online resource (xii, 97 pages) : illustrations
Item Number 10.1007/978-3-030-28 doi
Call Number TK1005
Dewey Decimal Classification 621.31
Summary 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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 4, 2019).
Added Author Neves, Cláudia.
Vukadinović Greetham, Danica.
Series SpringerBriefs in mathematics of planet Earth - weather, climate, oceans.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Preface
Introduction
Short Term Load Forecasting
Extreme Value Theory
Extreme Value Statistics
Case Study
References
Index.

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