Abstract
Climate change directly make the demand for electricity diversified and uncertain, which increase the risk of power grid operation. This paper attempts to explore the impact of extreme climate change on the fluctuation of China's electricity energy demand from the perspective of climate change. Based on the panel data of 90 prefecture-level cities in China from 1989 to 2017, the author builds an econometric model to test the impact of extreme low temperature and extreme high temperature on electricity demand. The results show that the occurrence of extreme high temperature weather has a positive effect on residential electricity demand while the emergence of extreme low temperature weather has a negative effect.
Highlights
Due to the diversity and uncertainty of power demand, the power generation capacity set to meet the maximum demand of customers is largely idle, which increases the cost and operation risk of power enterprises, and increases the electricity burden of customers
Energy consumption is affected by temperature, weather and even extreme weather (Kraft et al, 1978[6]; Ihara et al, 2008[7]; Tarek et al, 2016[8])
Based on the panel data of 90 prefecture-level cities in China in 1989-2017, this paper conducts an empirical analysis on the relationship between extreme weather and residential electricity demand
Summary
Due to the diversity and uncertainty of power demand, the power generation capacity set to meet the maximum demand of customers is largely idle, which increases the cost and operation risk of power enterprises, and increases the electricity burden of customers. The sample used by Yating Li et al (2019) [12] is the daily data of a certain district of Shanghai, and it is found that there is a symmetrical U-shaped relationship between residential electricity consumption and daily temperature in Shanghai, China. The contributions of this article include three aspects: Firstly, from the perspective of index construction, this paper constructs an extreme value model based on high-frequency data samples to describe the extreme temperature. From the perspective of research content, different from the current study focusing on the impact of extreme high temperature on power demand, this study included both extreme high temperature and extreme low temperature into the model, so as to capture the impact of temperature more perfectly
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