Financial Hazard Prediction Due to Power Outages Associated with Severe Weather-Related Natural Disaster Categories

被引:4
|
作者
Ali, Rafal [1 ]
Khosa, Ikramullah [1 ]
Armghan, Ammar [2 ]
Arshad, Jehangir [1 ]
Rabbani, Sajjad [3 ]
Alsharabi, Naif [4 ,5 ]
Hamam, Habib [6 ,7 ,8 ,9 ]
机构
[1] COMSATS Univ Islamabad, Dept Elect Engn, Lahore Campus, Lahore 54000, Pakistan
[2] Jouf Univ, Coll Engn, Dept Elect Engn, Sakaka 72388, Saudi Arabia
[3] LCWU Lahore, Lahore Coll Women Univ, Dept Elect Engn, Lahore 54000, Pakistan
[4] Univ Hail, Coll Comp Sci & Engn, Hail 55476, Saudi Arabia
[5] Amran Univ, Coll Engn & Informat Technol, Amran 9677, Yemen
[6] Univ Moncton, Fac Engn, Moncton, NB E1A 3E9, Canada
[7] Int Inst Technol & Management, POB 1989, Libreville, Gabon
[8] Spectrum Knowledge Prod & Skills Dev, Sfax 3027, Tunisia
[9] Univ Johannesburg, Sch Elect Engn, Dept Elect & Elect Engn Sci, ZA-2006 Johannesburg, South Africa
关键词
electric power; severe weather disasters; revenue loss; prediction; CLIMATE-CHANGE; LANDSLIDE; SYSTEM;
D O I
10.3390/en15249292
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Severe weather conditions not only damage electric power infrastructure, and energy systems, but also affect millions of users, including residential, commercial or industrial consumers. Moreover, power outages due to weather-related natural disasters have been causing financial losses worth billions of US dollars. In this paper, we analyze the impact of power outages on the revenue of electric power suppliers, particularly due to the top five weather-related natural disasters. For this purpose, reliable and publicly available power outage events data are considered. The data provide the time of the outage event, the geographic region, electricity consumption and tariffs, social and economic indicators, climatological annotation, consumer category distribution, population and land area, and so forth. An exploratory analysis is carried out to reveal the impact of weather-related disasters and the associated electric power revenue risk. The top five catastrophic weather-related natural disaster categories are investigated individually to predict the related revenue loss. The most influencing parameters contributing to efficient prediction are identified and their partial dependence on revenue loss is illustrated. It was found that the electric power revenue associated with weather-related natural disasters is a function of several parameters, including outage duration, number of customers, tariffs and economic indicators. The findings of this research will help electric power suppliers estimate revenue risk, as well as authorities to make risk-informed decisions regarding the energy infrastructure and systems planning.
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页数:25
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