Improving resilience index quantification using weighted sum method
This paper discusses the performance of existing resilience matrix. The calculation of the resilience metrics is simulated on channel 6 of the RBTS bus using the Typhoon Vicente disturbance event in 2012. The estimation of the resilience index employed the sequential Monte Carlo method and is based...
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my.utm.1076732024-09-25T07:48:44Z http://eprints.utm.my/107673/ Improving resilience index quantification using weighted sum method Hasna Satya Dini, Hasna Satya Dini Jamian, Jasrul Jamani Eko Supriyanto, Eko Supriyanto TK Electrical engineering. Electronics Nuclear engineering This paper discusses the performance of existing resilience matrix. The calculation of the resilience metrics is simulated on channel 6 of the RBTS bus using the Typhoon Vicente disturbance event in 2012. The estimation of the resilience index employed the sequential Monte Carlo method and is based on the transmission line's fragility curve. The two parameters considered in estimating resilience are the ratio of restoration speed to length of disturbance and the area of the comparison area on the system performance curve under fault conditions and normal conditions. Combining these two equations utilizes the weighted sum method, in which the weighting arrangement is carried out by simulating disturbance events in 3 scenarios. Scenario variations that are consider in this study are transmission line designed wind speed, repair speed, and the number of repair teams. Based on the simulation, it was found that the most appropriate weighting for the parameter area is 0.5, and for the speed of repair per length of time of disturbance is 0.5. 2023 Conference or Workshop Item PeerReviewed Hasna Satya Dini, Hasna Satya Dini and Jamian, Jasrul Jamani and Eko Supriyanto, Eko Supriyanto (2023) Improving resilience index quantification using weighted sum method. In: 2023 IEEE Conference on Energy Conversion (CENCON), 23 October 2023-24 October 2023, Kuching, Malaysia. http://dx.doi.org/10.1109/CENCON58932.2023.10369704 |
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TK Electrical engineering. Electronics Nuclear engineering Hasna Satya Dini, Hasna Satya Dini Jamian, Jasrul Jamani Eko Supriyanto, Eko Supriyanto Improving resilience index quantification using weighted sum method |
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This paper discusses the performance of existing resilience matrix. The calculation of the resilience metrics is simulated on channel 6 of the RBTS bus using the Typhoon Vicente disturbance event in 2012. The estimation of the resilience index employed the sequential Monte Carlo method and is based on the transmission line's fragility curve. The two parameters considered in estimating resilience are the ratio of restoration speed to length of disturbance and the area of the comparison area on the system performance curve under fault conditions and normal conditions. Combining these two equations utilizes the weighted sum method, in which the weighting arrangement is carried out by simulating disturbance events in 3 scenarios. Scenario variations that are consider in this study are transmission line designed wind speed, repair speed, and the number of repair teams. Based on the simulation, it was found that the most appropriate weighting for the parameter area is 0.5, and for the speed of repair per length of time of disturbance is 0.5. |
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Conference or Workshop Item |
author |
Hasna Satya Dini, Hasna Satya Dini Jamian, Jasrul Jamani Eko Supriyanto, Eko Supriyanto |
author_facet |
Hasna Satya Dini, Hasna Satya Dini Jamian, Jasrul Jamani Eko Supriyanto, Eko Supriyanto |
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Hasna Satya Dini, Hasna Satya Dini |
title |
Improving resilience index quantification using weighted sum method |
title_short |
Improving resilience index quantification using weighted sum method |
title_full |
Improving resilience index quantification using weighted sum method |
title_fullStr |
Improving resilience index quantification using weighted sum method |
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Improving resilience index quantification using weighted sum method |
title_sort |
improving resilience index quantification using weighted sum method |
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2023 |
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http://eprints.utm.my/107673/ http://dx.doi.org/10.1109/CENCON58932.2023.10369704 |
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