TY - GEN
T1 - Framework for Risk Assessment of the Electrical Power Grid under Extreme Weather Conditions
AU - Martins, João
AU - Rijo, Thomas
AU - Mar, Adriana
AU - César, André
AU - Fortes, Patricia
AU - Calvão, Teresa
AU - Raiyani, Kashyap
AU - Pereira, Pedro
AU - Pires, V. Fernão
N1 - info:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F50021%2F2020/PT#
info:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F00066%2F2020/PT#
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00066%2F2020/PT#
Funding Information:
Authors would like to acknowledge e-redes DSO for providing EPG data and IDL team (IDL, Faculty of Sciences, University of Lisbon) for providing the climate data used in the study. This work was supported by contract 03040122-DCEA.PS.613.E-Redes.MJS with major Portuguese DSO (e-redes) and national funds through FCT Fundação para a Ciência e a Tecnologia with reference UIDB/50021/2020, UIDB/00066/2020 and UIDP/00066/2020.
Publisher Copyright:
© 2024 IEEE.
PY - 2024/7/30
Y1 - 2024/7/30
N2 - This paper presents a framework to assess the vulnerability of the electrical power grid (EPG) to extreme weather events. The paper presents a methodology based on the Extra-Trees classifier and historical weather data to identify the EPG assets that are most likely to be affected in future extreme weather conditions under various climate change scenarios. The developed methodology considers the EPG different asset classes (lines, towers, poles, transformers, substations...) and identifies the weather parameters that are most relevant to their vulnerability. The paper presents results concerning wind speed, wind gusts, soil type, and altitude, which are used to train a model that predicts the probability of an asset being damaged based on the future weather parameters. The methodology was developed has been applied to a dataset of historical events in Portugal, from the major Portuguese DSO, thus assessing the future vulnerability of the EPG under three different scenarios of climate change. The developed methodology is a successful tool, that would not only help prevent occurrences of faults/failures in the Electrical Power Grid and its recovery from these occurrences, but also to have a better perception of a geographically safe future expansion of infrastructures. In this way it contributes to a continuous, non-faulty EPG operation, fulfilling society's demands by generating maps that identify the most vulnerable areas for each future climate scenario.
AB - This paper presents a framework to assess the vulnerability of the electrical power grid (EPG) to extreme weather events. The paper presents a methodology based on the Extra-Trees classifier and historical weather data to identify the EPG assets that are most likely to be affected in future extreme weather conditions under various climate change scenarios. The developed methodology considers the EPG different asset classes (lines, towers, poles, transformers, substations...) and identifies the weather parameters that are most relevant to their vulnerability. The paper presents results concerning wind speed, wind gusts, soil type, and altitude, which are used to train a model that predicts the probability of an asset being damaged based on the future weather parameters. The methodology was developed has been applied to a dataset of historical events in Portugal, from the major Portuguese DSO, thus assessing the future vulnerability of the EPG under three different scenarios of climate change. The developed methodology is a successful tool, that would not only help prevent occurrences of faults/failures in the Electrical Power Grid and its recovery from these occurrences, but also to have a better perception of a geographically safe future expansion of infrastructures. In this way it contributes to a continuous, non-faulty EPG operation, fulfilling society's demands by generating maps that identify the most vulnerable areas for each future climate scenario.
KW - Climate Change Scenarios
KW - Electrical Power Grid
KW - Extreme Weather Events
KW - Risk Index
UR - http://www.scopus.com/inward/record.url?scp=85201540200&partnerID=8YFLogxK
U2 - 10.1109/CPE-POWERENG60842.2024.10604340
DO - 10.1109/CPE-POWERENG60842.2024.10604340
M3 - Conference contribution
AN - SCOPUS:85201540200
SN - 9798350318272
SP - 1
EP - 6
BT - 2024 IEEE 18th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)
A2 - Detka, Kalina
A2 - Gorecki, Krzysztof
A2 - Gorecki, Pawel
PB - Institute of Electrical and Electronics Engineers (IEEE)
CY - Gdynia, Poland
T2 - 18th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2024
Y2 - 24 June 2024 through 26 June 2024
ER -