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http://hdl.handle.net/10773/35003
Title: | Generalized maximum entropy in electrical energy price modeling for households and non-households in Portugal |
Author: | Costa, Maria Conceição Madaleno, Mara Macedo, Pedro |
Keywords: | Electrical energy prices Ill-conditioned problems Info-metrics Regression modeling |
Issue Date: | 2022 |
Publisher: | Elsevier |
Abstract: | In a high tax burden environment related to electricity prices in Portugal, it is needed to establish fiscal and economic-political measures to lower the electrical price weight imposed on both households and non-households. The most effective way is to first be aware of its determinants. This paper contributes to the existent literature by analyzing how important are fuel costs, emissions, gross domestic product, and renewable energy share in energy consumption in explaining the variations in Portuguese electricity prices for both households and non-households, using generalized maximum entropy estimation. Results suggest that when income increases, electrical energy prices increase 0.0026 Euro/kilowatt-hour for households and 0.0034 Euro/kilowatt-hour for non-households. Fuel costs even lead to higher electricity prices for both, with the highest burden being on the non-household side. Results also point that carbon emissions negatively influence electricity prices and that reductions in electricity bills for non-households may be achieved through the increased share of the industrial sector energy in gross final energy consumption. Thus, increased renewable energy shares do not seem to be the solution to lower electricity prices, despite being necessary to reach sustainability goals. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/35003 |
DOI: | 10.1016/j.egyr.2022.01.091 |
ISSN: | 2352-4847 |
Publisher Version: | https://www.sciencedirect.com/science/article/pii/S2352484722000919?via%3Dihub |
Appears in Collections: | CIDMA - Artigos PSG - Artigos |
Files in This Item:
File | Description | Size | Format | |
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CostaMadalenoMacedoEnergyReports.pdf | 252.79 kB | Adobe PDF | View/Open |
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