Pub Date : 2021-10-28DOI: 10.1109/ICSGTEIS53426.2021.9650372
A. Syakur, Jumrianto Jumrianto, D. Ariyanti, M. Riyadi, Devi Devi, Lusianna Silalahi, Wisnu Puji Rahayu
An insulator is one of the most important equipment in an electric power system. It serves to separate the live conductors from the tower body. Leakage current often occurs in an insulator, especially when there are contaminants flowing on its surface, so it is necessary to look for an insulator material that has a low leakage current. One of them is silicone rubber (SiR) polymer material. In this study, a silicone rubber insulating material was tested without filler and with 5% and 10% TiO2 (Titanium Dioxide) as filler. The test was carried out using the Incline-Planed Tracking (IPT) measurement method according to the IEC standard 587:1984. The parameters analyzed were the average leakage current in various filler materials and the leakage current before and after exposure to ultraviolet. The test results show that the duration of ultraviolet irradiation affects the average leakage current. It was concluded that the test sample which has a high average leakage current is a sample of silicone rubber with filler 5% TiO2 before exposed by UV of 0.099 mA, and sample which has a high average leakage current after exposed by UV for 48 hours was 1.558 mA.
{"title":"A Study of Leakage Current Characteristic of Silicone Rubber Surface after Subjected to Ultraviolet Light","authors":"A. Syakur, Jumrianto Jumrianto, D. Ariyanti, M. Riyadi, Devi Devi, Lusianna Silalahi, Wisnu Puji Rahayu","doi":"10.1109/ICSGTEIS53426.2021.9650372","DOIUrl":"https://doi.org/10.1109/ICSGTEIS53426.2021.9650372","url":null,"abstract":"An insulator is one of the most important equipment in an electric power system. It serves to separate the live conductors from the tower body. Leakage current often occurs in an insulator, especially when there are contaminants flowing on its surface, so it is necessary to look for an insulator material that has a low leakage current. One of them is silicone rubber (SiR) polymer material. In this study, a silicone rubber insulating material was tested without filler and with 5% and 10% TiO2 (Titanium Dioxide) as filler. The test was carried out using the Incline-Planed Tracking (IPT) measurement method according to the IEC standard 587:1984. The parameters analyzed were the average leakage current in various filler materials and the leakage current before and after exposure to ultraviolet. The test results show that the duration of ultraviolet irradiation affects the average leakage current. It was concluded that the test sample which has a high average leakage current is a sample of silicone rubber with filler 5% TiO2 before exposed by UV of 0.099 mA, and sample which has a high average leakage current after exposed by UV for 48 hours was 1.558 mA.","PeriodicalId":345626,"journal":{"name":"2021 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132908565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1109/icsgteis53426.2021.9650378
{"title":"ICSGTEIS 2021 Technical Program Committee","authors":"","doi":"10.1109/icsgteis53426.2021.9650378","DOIUrl":"https://doi.org/10.1109/icsgteis53426.2021.9650378","url":null,"abstract":"","PeriodicalId":345626,"journal":{"name":"2021 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS)","volume":"93 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115829136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1109/ICSGTEIS53426.2021.9650376
A. Andang, Tri Cahyo Adi Pamungkas, N. Busaeri, R. S. Hartati, Ida B. G. Manuaba, I. Kumara
The need to convert electric power from dc to ac is due to the growing development of renewable energy generation connected to an electric power distribution system. The power conversion is carried out with power inverters where a three-phase four-leg inverter, apart from being an electric power converter, turns out to stabilize the output voltage supplied to the load. The voltage on the distribution network can experience imbalance due to connection with an unbalanced three-phase load. This article presents a four-leg three-phase inverter using an LC filter using an MPC control to produce a sinusoidal output voltage and balance the voltage. From the simulation results, it is obtained that when the load is balanced, the THD of the output voltage is 0.3% - 0.5%, while in unbalanced load conditions, the THD of the output voltage is 0.2% - 1.7%, with a percentage of voltage imbalance of 0.1% - 0.9%.
{"title":"Three-phase Four-leg Inverter LC Filter Using FCS MPC","authors":"A. Andang, Tri Cahyo Adi Pamungkas, N. Busaeri, R. S. Hartati, Ida B. G. Manuaba, I. Kumara","doi":"10.1109/ICSGTEIS53426.2021.9650376","DOIUrl":"https://doi.org/10.1109/ICSGTEIS53426.2021.9650376","url":null,"abstract":"The need to convert electric power from dc to ac is due to the growing development of renewable energy generation connected to an electric power distribution system. The power conversion is carried out with power inverters where a three-phase four-leg inverter, apart from being an electric power converter, turns out to stabilize the output voltage supplied to the load. The voltage on the distribution network can experience imbalance due to connection with an unbalanced three-phase load. This article presents a four-leg three-phase inverter using an LC filter using an MPC control to produce a sinusoidal output voltage and balance the voltage. From the simulation results, it is obtained that when the load is balanced, the THD of the output voltage is 0.3% - 0.5%, while in unbalanced load conditions, the THD of the output voltage is 0.2% - 1.7%, with a percentage of voltage imbalance of 0.1% - 0.9%.","PeriodicalId":345626,"journal":{"name":"2021 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122300207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1109/ICSGTEIS53426.2021.9650390
Jingyi Wang, Liliang Wang, Jiaqi Qu, Zheng Qian
The existing fault diagnosis methods of photovoltaic modules have some limitations: they only consider the influence of the area size of fault array when determining the fault level, and ignore the impact of the strength of fault factor itself. Addressing the issues, and in order to surmount the limited performance caused by the reliance on a single method simultaneously, this study proposes a novel fault diagnosis method of photovoltaic modules based on heterogeneous ensemble learning using current-voltage characteristic curves and ambient conditions. Moreover, a selection strategy considering both accuracy and diversity comprehensively is used to screen base learners to acquire superior diagnostic performance. The optimal integration members are incorporated adopting the probabilistic strategy and stacking algorithm respectively. In order to validate the effectiveness of the proposed method, two datasets are obtained based on a laboratory experiment platform and the corresponding simulation model respectively. The results demonstrate that the ensemble model based on probabilistic strategy proposed in this paper achieves more comprehensive diagnosis ability compared with the individual classifiers and the ensemble model based on stacking algorithm.
{"title":"Novel Application of Heterogeneous Ensemble Learning in Fault Diagnosis of Photovoltaic Modules","authors":"Jingyi Wang, Liliang Wang, Jiaqi Qu, Zheng Qian","doi":"10.1109/ICSGTEIS53426.2021.9650390","DOIUrl":"https://doi.org/10.1109/ICSGTEIS53426.2021.9650390","url":null,"abstract":"The existing fault diagnosis methods of photovoltaic modules have some limitations: they only consider the influence of the area size of fault array when determining the fault level, and ignore the impact of the strength of fault factor itself. Addressing the issues, and in order to surmount the limited performance caused by the reliance on a single method simultaneously, this study proposes a novel fault diagnosis method of photovoltaic modules based on heterogeneous ensemble learning using current-voltage characteristic curves and ambient conditions. Moreover, a selection strategy considering both accuracy and diversity comprehensively is used to screen base learners to acquire superior diagnostic performance. The optimal integration members are incorporated adopting the probabilistic strategy and stacking algorithm respectively. In order to validate the effectiveness of the proposed method, two datasets are obtained based on a laboratory experiment platform and the corresponding simulation model respectively. The results demonstrate that the ensemble model based on probabilistic strategy proposed in this paper achieves more comprehensive diagnosis ability compared with the individual classifiers and the ensemble model based on stacking algorithm.","PeriodicalId":345626,"journal":{"name":"2021 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131095412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1109/icsgteis53426.2021.9650359
{"title":"ICSGTEIS 2021 Organizing Committee","authors":"","doi":"10.1109/icsgteis53426.2021.9650359","DOIUrl":"https://doi.org/10.1109/icsgteis53426.2021.9650359","url":null,"abstract":"","PeriodicalId":345626,"journal":{"name":"2021 International Conference on Smart-Green Technology in Electrical and Information Systems (ICSGTEIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125701143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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