Duncan Maina, S. Shirzadi, S. Al-sachit, Leo Liu, N. Nair
{"title":"Electricity Distribution Resilience Assessment for Potential Seismic Event in New Zealand","authors":"Duncan Maina, S. Shirzadi, S. Al-sachit, Leo Liu, N. Nair","doi":"10.1109/POWERCON48463.2020.9230572","DOIUrl":null,"url":null,"abstract":"With the growing number of disasters, it is necessary not only to consider their effects on the electricity network infrastructure but also on the recovery strategies to be applied. The term resilience covers a wide range of time-bound activities ranging from disaster progression to infrastructure recovery. NZ lies on the Australia and Pacific plate boundary commonly referred to as the Alpine Fault (AF). It ruptures on average every 300 years and the last time it ruptured was 1717 thus its probability to rupture in the foreseeable future is high. This study presents results on a study conducted on the impact of AF earthquake of magnitude 7.9 (AF8) onto one of the local distribution networks that lie on the fault line. 2 sections of the study will be summarized in this paper: Mapping of AF8 onto the electricity infrastructure and re-energization analysis in formation of a microgrid. A simple damage analysis has been undertaken based on assuming the component fragility functions to be binary and disaster level to be a spread of MMI levels. Different trajectories of the earthquake are considered. With regards to re-energization, a small hydro power plant (SHPP) with the capability of blackstart, is used to re-energize the network. Detailed models of the network components have been included in order to obtain an accurate response. Re-energization of the different components assuming a particular restoration sequence is shown. MATLAB/SIMULINK has been used as the simulation platform due to its flexibility in modelling.","PeriodicalId":306418,"journal":{"name":"2020 IEEE International Conference on Power Systems Technology (POWERCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Power Systems Technology (POWERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERCON48463.2020.9230572","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With the growing number of disasters, it is necessary not only to consider their effects on the electricity network infrastructure but also on the recovery strategies to be applied. The term resilience covers a wide range of time-bound activities ranging from disaster progression to infrastructure recovery. NZ lies on the Australia and Pacific plate boundary commonly referred to as the Alpine Fault (AF). It ruptures on average every 300 years and the last time it ruptured was 1717 thus its probability to rupture in the foreseeable future is high. This study presents results on a study conducted on the impact of AF earthquake of magnitude 7.9 (AF8) onto one of the local distribution networks that lie on the fault line. 2 sections of the study will be summarized in this paper: Mapping of AF8 onto the electricity infrastructure and re-energization analysis in formation of a microgrid. A simple damage analysis has been undertaken based on assuming the component fragility functions to be binary and disaster level to be a spread of MMI levels. Different trajectories of the earthquake are considered. With regards to re-energization, a small hydro power plant (SHPP) with the capability of blackstart, is used to re-energize the network. Detailed models of the network components have been included in order to obtain an accurate response. Re-energization of the different components assuming a particular restoration sequence is shown. MATLAB/SIMULINK has been used as the simulation platform due to its flexibility in modelling.