A4 Conference proceedings

Electricity demand forecasting 2030 by decomposition analysis of open data


Open Access publication

Publication Details
Authors: Räisänen Otto, Haakana Juha, Haapaniemi Jouni, Lassila Jukka, Partanen Jarmo
Publication year: 2019
Language: English
Related Journal or Series Information: Conference proceedings CIRED
Title of parent publication: CIRED 2019 Proceedings
Journal acronym: CIRED
ISBN: 978-2-9602415-0-1
eISSN: 2032-9644
JUFO-Level of this publication: 1
Open Access: Open Access publication

Abstract

The demand of electrical energy in the household sector followed a nearly linear growth trend for a long time making demand forecasting relatively simple. However, in the last decade the growth has stalled due to energy efficiency policies, structural changes in the society and emergence of new technologies. In sparsely populated areas the population is continually declining which affects electrical energy consumption and increases average conductor length per customer. These changes in the operational environment pose challenges to demand forecasting. Historical data relating to the change factors could be used to improve demand forecasts. This study introduces a method that uses decomposition and timeseries analysis of open data to forecast future electrical energy demand. The method is used to forecast the electrical energy consumption for the household sector i na group of Finnish municipalities which have a declining population.


Last updated on 2020-20-03 at 10:03