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Financial hazard assessment for electricity suppliers due to power outages: the revenue loss perspective

Khosa, Ikramullah, Taimoor, Naveed, Akhtar, Jahanzeb, Ali, Khurram, Rehman, Ateeq Ur, Bajaj, Mohit, Elgbaily, Mohamed, Shouran, Mokhtar ORCID: https://orcid.org/0000-0002-9904-434X and Kamel, Salah 2022. Financial hazard assessment for electricity suppliers due to power outages: the revenue loss perspective. Energies 15 (12) , 4327. 10.3390/en15124327

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Abstract

The electrical power infrastructure of the modern world is advanced, efficient, and robust, yet power outages still occur. In addition to affecting millions of people around the world, these outage events cost billions of dollars to the global economy. In this paper, the revenue loss borne by electricity-supplying companies in the United States due to power outage events is estimated and predicted. Various factors responsible for power outages are considered in order to present an exploratory data analysis at the U.S. level, followed by the top ten affected states, which bear over 85% of the total revenue loss. The loss is computed using historic observational data of electricity usage patterns and the tariff offered by the energy suppliers. The study is supplemented with reliable and publicly available records, including electricity usage patterns, the consumer category distribution, climatological annotations, population density, socio-economic indicators and land area. Machine learning techniques are used to predict the revenue loss for future outage events, as well as to characterize the key parameters for efficient prediction and their partial dependence. The results show that the revenue loss is a function of several parameters, including residential sales, percentage of industrial customer, time-period of the year, and economic indicators. This study may help energy suppliers make risk-informed decisions, while developing revenue generation strategies as well as identifying safer investment avenues for long-term returns.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Additional Information: This is an open access article distributed under the Creative Commons Attribution License
Publisher: MDPI
ISSN: 1996-1073
Date of First Compliant Deposit: 30 August 2022
Date of Acceptance: 8 June 2022
Last Modified: 10 Feb 2024 02:10
URI: https://orca.cardiff.ac.uk/id/eprint/152071

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