TY - GEN
T1 - Quantification of aleatory and epistemic uncertainty in bulk power system reliability evaluation
AU - Awadallah, Selma Khalid E.
AU - Milanovic, Jovica V.
PY - 2013
Y1 - 2013
N2 - Uncertainty can be generally classified as aleatory uncertainty, related to random behaviour, and epistemic uncertainty, related to a lack of information. This paper studies the uncertainty in bulk power system reliability assessment. It analyses the source of uncertainty in components outage model and refers it to the congruous uncertianty forms. This leads to the characterization of outage model uncertainty by a mixed aleatory-epistemic model. In consequence, the paper suggests two methods for representing and quantifying the effect of mixed aleatory-epistemic uncertainty on system reliability indices. These methods are second order probability and evidence theory. The paper validates the feasibility of the two methods by conducting case studies on the IEEE-RTS system using the non-sequential Monte Carlo simulation approach. The mixed aleatory-epistemic model is shown to provide more detailed estimate of uncertainty than the typical aleatory model.
AB - Uncertainty can be generally classified as aleatory uncertainty, related to random behaviour, and epistemic uncertainty, related to a lack of information. This paper studies the uncertainty in bulk power system reliability assessment. It analyses the source of uncertainty in components outage model and refers it to the congruous uncertianty forms. This leads to the characterization of outage model uncertainty by a mixed aleatory-epistemic model. In consequence, the paper suggests two methods for representing and quantifying the effect of mixed aleatory-epistemic uncertainty on system reliability indices. These methods are second order probability and evidence theory. The paper validates the feasibility of the two methods by conducting case studies on the IEEE-RTS system using the non-sequential Monte Carlo simulation approach. The mixed aleatory-epistemic model is shown to provide more detailed estimate of uncertainty than the typical aleatory model.
KW - Aleatory uncertainty
KW - Monte Carlo method
KW - epistemic uncertainty
KW - evidence theory
KW - power system reliability
UR - http://www.scopus.com/inward/record.url?scp=84890880434&partnerID=8YFLogxK
U2 - 10.1109/PTC.2013.6652164
DO - 10.1109/PTC.2013.6652164
M3 - Conference contribution
AN - SCOPUS:84890880434
SN - 9781467356695
T3 - 2013 IEEE Grenoble Conference PowerTech, POWERTECH 2013
BT - 2013 IEEE Grenoble Conference PowerTech, POWERTECH 2013
T2 - 2013 IEEE Grenoble Conference PowerTech, POWERTECH 2013
Y2 - 16 June 2013 through 20 June 2013
ER -