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Short-term Forecasting of Electricity Consumption in Maputo
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Ministry Of Science and Technology, Mozambique.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2013 (English)In: International Conference on Advances in ICT for Emerging Regions (ICTer) - 2013: Conference Proceedings, IEEE Computer Society, 2013, 132-136 p.Conference paper, Published paper (Refereed)
Abstract [en]

We present a short-term load forecasting model for Maputo. The model is based on the concept of multiple models. A clustering method is combined with expert’s knowledge to identify sub-models. The resulting model, which is the combination of several sub-models, is evaluated and compared to the model currently used by the Electricidade de Moçambique E.P (EDM). The results show that the developed model performs better accuracy than the one currently used by EDM. The results obtained by the application of the model when translated into financial figures demonstrate significant economic advantages. The social and environmental implications of the model are also analysed.

Place, publisher, year, edition, pages
IEEE Computer Society, 2013. 132-136 p.
Keyword [en]
Short-term load forecasting, Day-Ahead-Market, robust regression, multiple models, clustering, Mozambique
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-97748DOI: 10.1109/ICTer.2013.6761167ISBN: 978-1-4799-1274-2 (print)OAI: oai:DiVA.org:su-97748DiVA: diva2:679978
Conference
ICTer 2013, International Conference on Advances in ICT for Emerging Regions, 11-15 December 2013, Colombo (Sri Lanka)
Available from: 2013-12-17 Created: 2013-12-17 Last updated: 2016-03-17Bibliographically approved

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