Open AccessPrediction of Diesel Fired Power Plant Feeder Performance using First Order Fuzzy Time Series
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k1144.09811s19
Subject(s) - reliability engineering , fuzzy logic , reliability (semiconductor) , power (physics) , power station , series (stratigraphy) , electricity , variable (mathematics) , time series , mains electricity , automotive engineering , duration (music) , engineering , computer science , statistics , mathematics , electrical engineering , art , paleontology , mathematical analysis , physics , literature , quantum mechanics , artificial intelligence , biology , voltage
Power outages caused by factors outside the established policy will have an impact on the decline in electricity supply services and other cost related impacts. The reliability of the power plant feeder, in this case, is very important to monitor and maintain. The performance of power plant feeder can be reviewed based on the variable duration of power outage and power which fails to distribute. In this study, 1st order FTS (Fuzzy Time Series) is used to predict the feeder's performance through the predictive activity of both those variables in the actual year and the following year. The prediction results state that in 2017 there was a 20.54% decrease in performance