Heymann F, Bessa R, Liebensteiner M, Parginos K, Duenas P (2022)
Publication Language: English
Publication Type: Journal article, Original article
Publication year: 2022
Book Volume: 8
DOI: 10.1016/j.egyai.2022.100154
Open Access Link: https://doi.org/10.1016/j.egyai.2022.100154
Dealing with scarcity events is nowadays gaining relevance in electricity market studies, as traditionally predictable generation and consumption patterns are fading. Policymakers and system planners use therefore adequacy studies to a) understand if the current market design will attract sufficient generation capacity to meet electricity demand in the future and b) to comprehend what drives system inadequacy or resource scarcity when future scenarios lack adequate capacity. This work addressed the latter and showcases a first in-its-kind rulebased methodology that filters scarcity events from a large set of electricity market simulations. In this proof-ofconcept, a rule-mining algorithm is applied to outputs from ENTSO-E’s Pan-European electricity market model, which is run for 700 model scenarios, each covering 8760 time steps. The developed methodology shows how to unveil potential reasons behind scarcity events in an automated, interpretable, and scalable manner.
APA:
Heymann, F., Bessa, R., Liebensteiner, M., Parginos, K., & Duenas, P. (2022). Scarcity events analysis in adequacy studies using CN2 rule mining. Energy and AI, 8. https://dx.doi.org/10.1016/j.egyai.2022.100154
MLA:
Heymann, Fabian, et al. "Scarcity events analysis in adequacy studies using CN2 rule mining." Energy and AI 8 (2022).
BibTeX: Download