LAPSE:2023.28783
Published Article
LAPSE:2023.28783
Improving Energy Transition Analysis Tool through Hydropower Statistical Modelling
April 12, 2023
Abstract
Reservoir and pumped hydro storage facilities represent one of the best options for providing flexibility at low marginal cost and very low life cycle carbon emissions. However, hydropower generation is subject to physical, environmental and regulatory constraints, which introduce complexity in the modelling of hydropower in the context of transition energy analysis. In this article, a probabilistic model for hydropower generation is developed in order to improve an hourly-resolved tool for transition path analysis presented in previous research. The model is based on time series analysis, which exploits the fact that the different constraints affecting hydropower generation were met in the past. The upgraded version of the transition path analysis tool shows a decrease in the hydropower flexibility as compared with previous published results, providing a better picture of the benefits and drawbacks associated with a specific transition path under analysis, for example in terms of assessing the probability of unserved energy. The upgraded version of the tool was employed to analyse the Spanish National Energy and Climate Plan (NECP), finding consistence between proposals associated with the power system and related CO2 reduction and share of renewable electricity targets.
Keywords
energy modelling, energy transition, hydropower, renewable grid integration, Spain, time series models
Suggested Citation
Gallego-Castillo C, Victoria M. Improving Energy Transition Analysis Tool through Hydropower Statistical Modelling. (2023). LAPSE:2023.28783
Author Affiliations
Gallego-Castillo C: Aircraft and Space Vehicles Department, Universidad Politécnica de Madrid, Plaza Cardenal Cisneros 3, 28040 Madrid, Spain [ORCID]
Victoria M: Department of Engineering, Aarhus University, Inge Lehmanns Gade 10, 8000 Aarhus, Denmark; iCLIMATE Interdisciplinary Centre for Climate Change, Aarhus University, 8000 Aarhus, Denmark [ORCID]
Journal Name
Energies
Volume
14
Issue
1
Article Number
E98
Year
2020
Publication Date
2020-12-27
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14010098, Publication Type: Journal Article
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LAPSE:2023.28783
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https://doi.org/10.3390/en14010098
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