Inter-country comparisons of energy system performance with the energy trilemma index: An ensemble ranking methodology based on the half-quadratic theory

被引:24
作者
Fu, Yelin [1 ]
Lu, Yihe [2 ]
Yu, Chen [3 ]
Lai, Kin Keung [3 ]
机构
[1] Shenzhen Univ, Coll Econ, Shenzhen, Peoples R China
[2] Jinan Univ, Sch Management, Guangzhou, Peoples R China
[3] Univ Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Energy Trilemma Index; Ensemble ranking; Half-quadratic theory; Consensus index; Trust level; AGGREGATION; MINIMIZATION; EFFICIENCY; RECOVERY; MODEL;
D O I
10.1016/j.energy.2022.125048
中图分类号
O414.1 [热力学];
学科分类号
摘要
The World Energy Council annually publishes the Energy Trilemma Index (ETI) to highlight an economy's challenges in balancing the Trilemma and opportunities for improvements in meeting energy goals at present and in the future. The ETI is constructed by taking the arithmetic average of energy security, energy equity (accessibility and affordability), environmental sustainability. This paper proposes an ensemble ranking methodology based on the half-quadratic theory, for measuring and comparing country-wide energy system performance using the ETI data. Specifically, all possible importance orders among energy security, energy equity, environmental sustainability are described as the ranked dimension weights to derive a new decision matrix with the country-specific rankings as elements. Then a half-quadratic programming approach is presented to estimate the ensemble ranking, along with the development of consensus index and trust level to indicate the level of agreement and reliability of the final ensemble ranking. An empirical study using the ETI 2020 data of 30 International Energy Agency (IEA) member countries is performed to demonstrate the implementation of the our methodology.
引用
收藏
页数:8
相关论文
共 32 条
[1]   A highly scalable algorithm for weak rankings aggregation [J].
Aledo, Juan A. ;
Gamez, Jose A. ;
Rosete, Alejandro .
INFORMATION SCIENCES, 2021, 570 :144-171
[2]   Approaching rank aggregation problems by using evolution strategies: The case of the optimal bucket order problem [J].
Aledo, Juan A. ;
Gamez, Jose A. ;
Rosete, Alejandro .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2018, 270 (03) :982-998
[3]   Using extension sets to aggregate partial rankings in a flexible setting [J].
Aledo, Juan A. ;
Gamez, Jose A. ;
Molina, David .
APPLIED MATHEMATICS AND COMPUTATION, 2016, 290 :208-223
[4]   A spatial-temporal decomposition approach to performance assessment in energy and emissions [J].
Ang, B. W. ;
Su, Bin ;
Wang, H. .
ENERGY ECONOMICS, 2016, 60 :112-121
[5]   Multi-country comparisons of energy performance: The index decomposition analysis approach [J].
Ang, B. W. ;
Xu, X. Y. ;
Su, Bin .
ENERGY ECONOMICS, 2015, 47 :68-76
[6]   Aggregation of Individual Rankings Through Fusion Functions: Criticism and Optimality Analysis [J].
Bustince, Humberto ;
Bedregal, Benjamin ;
Jesus Campion, Maria ;
da Silva, Ivanosca ;
Fernandez, Javier ;
Indurain, Esteban ;
Raventos-Pujol, Armajac ;
Santiago, Regivan H. N. .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 30 (03) :638-648
[7]   A DATA ENVELOPMENT MODEL FOR AGGREGATING PREFERENCE RANKINGS [J].
COOK, WD ;
KRESS, M .
MANAGEMENT SCIENCE, 1990, 36 (11) :1302-1310
[8]  
Demsar J, 2006, J MACH LEARN RES, V7, P1
[9]   Multi-nation comparisons of energy architecture performance: A group decision-making method with preference structure and acceptability analysis [J].
Fu, Yelin ;
Lai, Kin Keung ;
Yu, Lean .
ENERGY ECONOMICS, 2021, 96
[10]   Comprehensive resilience assessment of electricity supply security for 140 countries [J].
Gasser, Patrick ;
Suter, Johannes ;
Cinelli, Marco ;
Spada, Matteo ;
Burgherr, Peter ;
Hirschberg, Stefan ;
Kadzinski, Milosz ;
Stojadinovic, Bozidar .
ECOLOGICAL INDICATORS, 2020, 110