Predicting average annual electricity outage using electricity distribution network operator's performance indicators

Silva, C; Saraee, MH

Abstract

Electricity Distribution network operators (DNO) may receive a monetary reward or have a penalty reliant on their performance against the target set by the regulators. Customer minutes lost (CML) is one of the primary performance indicators which lead to the financial reward or penalties. Therefore, it is paramount important to understand CML behaviour. In this study, authors are trying to accurately understand the behaviour of CML performance indicator and trying to predict the annual Customer Minutes Lost (CML) figure using other annual financial and network performance indicators such as no. of customers, Totex, Network load, etc. The overall aim of this study is to improve DNOs CML figures for better performance. The exploratory case study research methodology has been used for this study with two distinct case studies from the UK and Australia. Correlation methods and regression models were built and analysed to find the correlation and linear relationship between the variables.

Citation

Silva, C., & Saraee, M. (2020, February). Predicting average annual electricity outage using electricity distribution network operator's performance indicators. Presented at 2020 Advances in Science and Engineering Technology International Conferences (ASET), Dubai, United Arab Emirates

• Presentation Conference Type: Other
• Conference Name: 2020 Advances in Science and Engineering Technology International Conferences (ASET)
• Conference Location: Dubai, United Arab Emirates
• Start Date: Feb 4, 2020
• End Date: Apr 9, 2020
• Online Publication Date: Jun 16, 2020
• Publication Date: Jun 16, 2020
• Deposit Date: Oct 2, 2020
• Journal: 2020 Advances in Science and Engineering Technology International Conferences (ASET)
• Pages: 1-6
• Book Title: 2020 Advances in Science and Engineering Technology International Conferences (ASET)
• ISBN: 9781728146409
• DOI: https://doi.org/10.1109/ASET48392.2020.9118383
• Publisher URL: https://doi.org/10.1109/ASET48392.2020.9118383
• Related Public URLs: https://doi.org/10.1109/ASET48392.2020
• Additional Information: Event Type : Conference