Benefit Evaluation of Carbon Reduction in Power Transmission and Transformation Projects Based on the Modified TOPSIS-RSR Method

Yinan Wang, Heng Chen (), Shuyuan Zhao, Lanxin Fan, Cheng Xin, Xue Jiang and Fan Yao
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Yinan Wang: School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
Heng Chen: School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
Shuyuan Zhao: School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
Lanxin Fan: School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China
Cheng Xin: State Grid Economic and Technical Research Institute Ltd., Beijing 102209, China
Xue Jiang: Economic and Technical Research Institute of State Grid Liaoning Electric Power Co., Shenyang 110015, China
Fan Yao: Economic and Technical Research Institute of State Grid Chongqing Electric Power Co., Chongqing 404100, China

Energies, 2024, vol. 17, issue 12, 1-23

Abstract: In order to fully achieve energy saving goals, it is necessary to establish a comprehensive evaluation system for carbon reduction in transmission and transformation projects. Subsequently, weights were assigned to these indicators using a combination of the fuzzy analytical hierarchy process (FAHP) and the entropy weight method (EWM) through both subjective and objective methods. Finally, the ultimate weights were obtained by applying the principle of minimum information. During the construction of the evaluation model, the rank–sum ratio (RSR) method was introduced into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for approximating ideal solution ranking. And the Euclidean distance in TOPSIS was replaced with standardized Euclidean distance, effectively avoiding evaluation discrepancies caused by different dimensions. The modified TOPSIS-RSR method was utilized to evaluate and rank power transmission and transformation projects in four regions. By comparing the test values of the two models, the superiority of the enhanced model was confirmed. Furthermore, the GM (1,1) model is used to predict the electricity sales volume of the optimal ranking area. This evaluation model can also be applied to the benefit evaluation of carbon reduction benefits in power transmission and transformation projects in other regions.

Keywords: power transmission and transformation projects; fuzzy comprehensive evaluation; entropy weight; modified TOPSIS-RSR; project ranking (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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