{"title":"基于加权因子-模糊逻辑的变压器剩余寿命估计模型","authors":"Edwell T. Mharakurwa, S. Juma","doi":"10.1109/PowerAfrica52236.2021.9543460","DOIUrl":null,"url":null,"abstract":"Further utilization of ageing fleet of power system assets can be enhanced by acquiring better knowledge of life-threatening factors. In this paper, further exploration of power transformer residual life estimation is articulated. Previously, focus has been on diagnostic capabilities and degradation agencies in forecasting the remnant life of a power transformer. In this study, a weighting factor approach cascaded with fuzzy inference system was adopted in realizing the residual life of a power transformer. Instead of using individual attributes, the proposed model utilizes the grouping factor of technical life threatening agencies. A multi-criteria analysis was employed in developing the model, whereby the outcome of the model is accomplished by including the collective effect of distinct sub outcomes using fuzzification of all the active grouping attributes. Assessment of the developed residual life model was confirmed by utilization of data set attained from several in-service mineral oil immersed transformers. The simulation results were comparable with utility expert's outcome, thus confirming the applicability of the proposed model.","PeriodicalId":370999,"journal":{"name":"2021 IEEE PES/IAS PowerAfrica","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Weighting Factor-Fuzzy logic based Transformer Residual Life Estimation Model\",\"authors\":\"Edwell T. Mharakurwa, S. Juma\",\"doi\":\"10.1109/PowerAfrica52236.2021.9543460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Further utilization of ageing fleet of power system assets can be enhanced by acquiring better knowledge of life-threatening factors. In this paper, further exploration of power transformer residual life estimation is articulated. Previously, focus has been on diagnostic capabilities and degradation agencies in forecasting the remnant life of a power transformer. In this study, a weighting factor approach cascaded with fuzzy inference system was adopted in realizing the residual life of a power transformer. Instead of using individual attributes, the proposed model utilizes the grouping factor of technical life threatening agencies. A multi-criteria analysis was employed in developing the model, whereby the outcome of the model is accomplished by including the collective effect of distinct sub outcomes using fuzzification of all the active grouping attributes. Assessment of the developed residual life model was confirmed by utilization of data set attained from several in-service mineral oil immersed transformers. The simulation results were comparable with utility expert's outcome, thus confirming the applicability of the proposed model.\",\"PeriodicalId\":370999,\"journal\":{\"name\":\"2021 IEEE PES/IAS PowerAfrica\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE PES/IAS PowerAfrica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PowerAfrica52236.2021.9543460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE PES/IAS PowerAfrica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PowerAfrica52236.2021.9543460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Weighting Factor-Fuzzy logic based Transformer Residual Life Estimation Model
Further utilization of ageing fleet of power system assets can be enhanced by acquiring better knowledge of life-threatening factors. In this paper, further exploration of power transformer residual life estimation is articulated. Previously, focus has been on diagnostic capabilities and degradation agencies in forecasting the remnant life of a power transformer. In this study, a weighting factor approach cascaded with fuzzy inference system was adopted in realizing the residual life of a power transformer. Instead of using individual attributes, the proposed model utilizes the grouping factor of technical life threatening agencies. A multi-criteria analysis was employed in developing the model, whereby the outcome of the model is accomplished by including the collective effect of distinct sub outcomes using fuzzification of all the active grouping attributes. Assessment of the developed residual life model was confirmed by utilization of data set attained from several in-service mineral oil immersed transformers. The simulation results were comparable with utility expert's outcome, thus confirming the applicability of the proposed model.