The Impact of Climate Change on National Energy

被引:0
|
作者
Yi, Zepu [1 ]
机构
[1] Sch North China Elect Power Univ, Baoding 071000, Peoples R China
关键词
BP Neural Network Model; Principal Component Analysis; Linear Regression Model (LRM); Genetic Algorithm;
D O I
10.1063/1.5089061
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
Climate change is one of the most serious challenges facing human society, and there is an urgent need to anticipate and respond to climate change. Climate change is a major issue of globalization that is of general concern to the international community at present, and it has a close interaction with energy systems. This paper takes the impact of climate change on energy system as the theme, and makes a comprehensive review and prospect of relevant international research. According to different object of action, the influence of climate change on energy system is expounded from the demand end and the supply side respectively, and the existing key research methods and their advantages and disadvantages are summarized from two perspectives of climate scenario prediction and supply and demand impact assessment. Finally, the need for further more deterministic impact prediction studies, climate change adaptation studies in energy systems and research on the impact of climate change on energy infrastructure and Energy transport was noted. To predict the vulnerability of climate and national energy issues, our team analyzed the literature based on a given query climate data and indicators, made multiple neuron fitting diagrams using BP neural network model and principal component analysis, and found the most reasonable analysis. Ultimately, climate change affects economic downturns, population pressures, public services and the main components of refugees and internally displaced persons, thus increasing the country's vulnerability and exacerbating the country's energy instability.
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页数:5
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