Norouzi Nima, Zarazua de Rubens Gerardo, Choupanpiesheh Saeed, Enevoldsen Peter
Department of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, PO. Box 15875-4413, Tehran, Iran.
Center for Energy Technologies, Department of Business Development and Technology, Aarhus University, Denmark.
Energy Res Soc Sci. 2020 Oct;68:101654. doi: 10.1016/j.erss.2020.101654. Epub 2020 Jun 20.
Despite all the scientific and technological developments in the past one hundred years, biologic issues such as pandemics are a constant threat to society. While one of the aspects of a pandemic is the loss of human life, the outbreak has multi-dimensional impacts across regional and global societies. In this paper, a comparative regressive and neural network model is developed to analyze the impacts of COVID-19 (coronavirus) on the electricity and petroleum demand in China. The environmental analysis shows that the epidemic severeness significantly affects the electricity and the petroleum demand, both directly and indirectly. The outputs of the model stated that the elasticity of petroleum and electricity demand toward the population of the infected people is -0.1% and -0.65%, respectively. The mentioned results show that pandemic status has a significant impact on energy demand, and also its impacts can be tracked into every corner of human society.
尽管在过去的一百年里科技取得了诸多发展,但诸如大流行病之类的生物学问题始终对社会构成威胁。虽然大流行病的一个方面是人员生命的损失,但疫情爆发对区域和全球社会有着多维度的影响。本文构建了一个比较回归和神经网络模型,以分析新冠病毒对中国电力和石油需求的影响。环境分析表明,疫情严重程度对电力和石油需求有着直接和间接的显著影响。该模型的输出结果表明,石油和电力需求对感染人群数量的弹性分别为-0.1%和-0.65%。上述结果表明,疫情状况对能源需求有重大影响,而且其影响能够波及人类社会的方方面面。