Energies (Jul 2023)

Evaluation of the Maturity of Urban Energy Internet Development Based on AHP-Entropy Weight Method and Improved TOPSIS

  • Yongli Wang,
  • Xiangyi Zhou,
  • Hao Liu,
  • Xichang Chen,
  • Zixin Yan,
  • Dexin Li,
  • Chang Liu,
  • Jiarui Wang

DOI
https://doi.org/10.3390/en16135151
Journal volume & issue
Vol. 16, no. 13
p. 5151

Abstract

Read online

With the rapid development of communication technology and information processing technology, the construction of the Urban Energy Internet (UEI) has become one of the important construction elements of the new power system, and it is necessary to assess and analyse its development status and potential. However, the results of the current assessment of the maturity of UEI development are relatively rare, and the transformation path of urban smart energy construction needs to be studied in depth. On this basis, this study aims to propose an improved and comprehensive evaluation model for the maturity of UEI development. This study first considers the dynamic development process of the UEI and proposes an evaluation index system for the maturity of UEI development that includes three dimensions of development status, development benefits and development prospects. Secondly, a comprehensive evaluation model based on GRA-KL-TOPSIS is constructed by using the AHP-entropy weighting method to calculate the combined weights of indicators and considering the Kulla back-Leibler distance to replace the Euclidean distance in the traditional evaluation method. Finally, the maturity of Energy Internet development is calculated for five typical first-tier cities in China (Beijing, Shanghai, Guangzhou, Tianjin and Shenyang), and the final ranking of the five cities is Shanghai > Beijing > Guangzhou > Tianjin > Shenyang. The results of the study prove the scientific validity of the model. Compared to the unimproved Topsis method, the evaluation results calculated based on the improved Topsis evaluation model are more objective and realistic in reflecting the score and rating of the cities. The analysis of the empirical results shows that cities at different stages of development should make up for their shortcomings and increase their investment in infrastructure development, technological innovation and the introduction of talents in order to accelerate the digital and intelligent development of energy.

Keywords