Fuzzy Reliability Assessment of Distribution System with Wind Farms and Plug-in Electric Vehicles. Issue 19 (14th December 2019)

• Record Type: Journal Article
• Authors: Reddy, Galiveeti Hemakumar; Kiran, Malepati Krishnmurthy; Kumar, Pulumithi Sunil; Goswami, Arup Kumar; Choudhury, Nalin B. Dev
• Is Part Of: Electric power components and systems. Volume 47:Issue 19/20(2019)
• Page Start: 1791
• Page End: 1804
• Publication Date: 2019-12-14
• Subjects: fuzzy theory -- wind farms -- plug-in electric vehicles -- fuzzy severity index -- probability-possibility transformation -- distribution systems -- reliability -- generalized fuzzy number; Electric machinery -- Periodicals; 621.3104205
• DOI: 10.1080/15325008.2020.1731871
• Languages: English
• ISSNs: 1532-5008

Abstract

Abstract: The equipment failures are highly uncertain in nature and simple average failure rate will not reflect this uncertainty. The uncertainty level further increases in reliability evaluation due to the integration of wind farm (WF) because of the intermittent nature of wind speed and random charging patterns of plug-in electric vehicles (PEVs). In this work, the uncertain variables in the distribution system (failure rate, repair time, WF output, PEVs charging and system load factor) are represented as fuzzy numbers to handle the uncertainty. The available uncertain data are used to find the probability distribution function (PDF) of that parameter and is converted into fuzzy membership function using transformation techniques. Failure rate of equipment is converted into failure probability using Monte Carlo simulation (MCS) method. Sampling method is applied to create the PDF of a variable which has average value. Fuzzy severity index (FSI) is proposed to find the importance of an equipment on reliability and is evaluated by measuring the fuzzy distance between the fuzzy reliability indices. The proposed assessment method is validated on modified RBTS bus 2 by comparing with analytical and MCS methods. The proposed method has been tested with integration of WFs and PEVs.