Multidimensional comprehensive evaluation of power energy systems based on GRA-GNN

被引:0
|
作者
Shan, Maohua [1 ]
Zhang, Hao [1 ]
Huang, Longda [1 ]
Ma, Zhanming [2 ]
机构
[1] China Elect Power Res Inst Co Ltd, Nanjing 210000, Jiangsu, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Big Data Anal Technol, CICAEET, Nanjing 210044, Peoples R China
关键词
Gray correlation analysis; graph convolutional neural network; comprehensive evaluation; power energy systems; CCHP;
D O I
10.1145/3674225.3674292
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Power market performance evaluation is a key link in the market-oriented reform of the electric power industry, which provides market participants with a basis for decision-making and market regulators with policy recommendations through economic analysis of the operating conditions of the electric power market, so as to promote the development of the electric power market and the efficient allocation of electric power resources. Power market performance evaluation faces two difficulties: first, the specificity of the power market makes the performance evaluation need to comprehensively consider a variety of influencing factors; second, the diversity of the power market makes the performance evaluation of the differences between the difficult to develop a unified evaluation standards and methods. In order to overcome these difficulties, this paper takes into account three dimensional indicators such as energy value sustainability index, power generation efficiency, and total life cycle cost, and constructs a comprehensive evaluation system for the sustainability of the electric energy system taking into account the energy value based on the gray correlation analysis (GRA) method and the graph convolutional neural network (GNN), and quantitatively analyzes the performance of the five different power generation modes in different dimensions.
引用
收藏
页码:376 / 381
页数:6
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