Abstract
The work described in this article results from a problem proposed by the company EDP—Energy Solutions Operator, in the framework of ESGI 119th, European Study Group with Industry, during July 2016. Markets for electricity have two characteristics: the energy is mainly no-storable and volatile prices at exchanges are issues to take into consideration. These two features, between others, contribute significantly to the risk of a planning process. The aim of the problem is the short-term forecast of hourly energy prices. In the present work, GLM is considered a useful technique to obtain a predictive model where its predictive power is discussed. The results show that in the GLM framework the season of the year, month, or winter/summer period revealed significant explanatory variables in the different estimated models. The in-sample forecast is promising, conducting to adequate measures of performance.
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Acknowledgements
This work was supported by Portuguese funds through the Center of Naval Research (CINAV), Portuguese Naval Academy, Portugal and The Portuguese Foundation for Science and Technology (FCT), through the Center for Computational and Stochastic Mathematics (CEMAT), University of Lisbon, Portugal, project UID/Multi/04621/2013.
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Teodoro, M.F., Andrade, M.A.P., Silva, E.C.e., Borges, A., Covas, R. (2018). Energy Prices Forecasting Using GLM. In: Oliveira, T., Kitsos, C., Oliveira, A., Grilo, L. (eds) Recent Studies on Risk Analysis and Statistical Modeling. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-76605-8_23
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