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Multivariate Scenario Generation -An Arima and Copula Approach

Abstract

In mathematical optimization uncertainty is expressed through scenarios. auto-regressive integrated moving average (ARIMA) is one of the known practice to generate scenarios. This paper is about scenario generation using multivariate data: electrical power demand, wind power generation and energy market price. An ARIMA model along with Copula is implemented for scenario generation. The results are presented and discussed.
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Category

Academic article

Language

English

Author(s)

  • Sambeet Mishra
  • Chiara Bordin
  • Christoph Würsig
  • Ivo Palu

Affiliation

  • Tallinn University of Technology (TalTech University)
  • SINTEF Energy Research / Energisystemer
  • Gottfried Wilhelm Leibniz Universität Hannover

Year

2019

Published in

International Journal of Modeling and Optimization

ISSN

2010-3697

Publisher

International Association of Computer Science and Information Technology Press

Volume

9

Issue

3

Page(s)

146 - 149

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