{"title":"Performance Assessment of Industrial Drives due to Power Quality Issues and its Potential Impacts on Electrical Drives","authors":"V. K, A. L","doi":"10.4108/eai.7-12-2021.2314562","DOIUrl":null,"url":null,"abstract":"Abstract. Power quality difficulties have been predicted since electronically powered drives have been the main component of any manufacturing process. Evaluating the same's informative quality has proven to be a big challenge. Because of non-linearity on the load side and an over-reliance on semiconductor technology, a good power quality could be crucial. The capabilities of the drives section employed in the business are also attracting attention in the current circumstances. As a result of the concerns mentioned above, several literary scientific studies show disturbances in the load side and the efficiency of electric drives. Weakness resulting from power quality is simply too significant, making it difficult for even the most sophisticated engineering to function effectively. A deep insight examination of grid side characteristics was performed in conjunction with investigating the inverter drive section responsiveness to grid variation to confirm the grid side issues for the artificial intelligence technique. This study work emphasized and proposed an answer to the possible artificial wise approach for administering fault deterrence prediction algorithm after clear proof from analysis and accounting grid side quality concerns relevant to electronic powered drives. The result is an accurate forecast of abnormal grid side behavior to offer safe and trustworthy grid operation, reducing the likelihood of shutdown or failure to a greater extent. Improvements in forecast accuracy based on previous data have been viable feedback to business equipment manufacturers, in addition to the aforementioned technique.","PeriodicalId":20712,"journal":{"name":"Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/eai.7-12-2021.2314562","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. Power quality difficulties have been predicted since electronically powered drives have been the main component of any manufacturing process. Evaluating the same's informative quality has proven to be a big challenge. Because of non-linearity on the load side and an over-reliance on semiconductor technology, a good power quality could be crucial. The capabilities of the drives section employed in the business are also attracting attention in the current circumstances. As a result of the concerns mentioned above, several literary scientific studies show disturbances in the load side and the efficiency of electric drives. Weakness resulting from power quality is simply too significant, making it difficult for even the most sophisticated engineering to function effectively. A deep insight examination of grid side characteristics was performed in conjunction with investigating the inverter drive section responsiveness to grid variation to confirm the grid side issues for the artificial intelligence technique. This study work emphasized and proposed an answer to the possible artificial wise approach for administering fault deterrence prediction algorithm after clear proof from analysis and accounting grid side quality concerns relevant to electronic powered drives. The result is an accurate forecast of abnormal grid side behavior to offer safe and trustworthy grid operation, reducing the likelihood of shutdown or failure to a greater extent. Improvements in forecast accuracy based on previous data have been viable feedback to business equipment manufacturers, in addition to the aforementioned technique.