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Forecasting and Assessing Risk of Individual Electricity Peaks

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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.

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Detail Information

Series Title

Mathematics of Planet Earth

Call Number

XII, 97

Publisher

Springer Cham : Springer Cham., 2020

Collation

-

Language

English

ISBN/ISSN

978-3-030-28669-9

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

1

Subject(s)

Energy Systems
Mathematics of Planet Earth

Specific Detail Info

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Statement of Responsibility

Maria Jacob, Cláudia Neves, Danica Vukadinović Greetham

Other Information

Cataloger

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Source

https://link.springer.com/book/10.1007/978-3-030-28669-9

Validator

Suwardi

Digital Object Identifier (DOI)

https://doi.org/10.1007/978-3-030-28669-9

Journal Volume

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Journal Issue

-

Subtitle

-

Parallel Title

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