TY - GEN
T1 - Sustainability Pathway Assessment of East China Power Grid Toward 2030 Carbon-Peaking Targets Using AHP-Entropy and TOPSIS
AU - Yang, Nan
AU - Zhang, Xiahui
AU - Jin, Yexuan
AU - Liu, Ziqiu
AU - Sun, Yanan
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - Translating global Sustainable Development Goals into regional grid planning requires frameworks balancing sustainability targets with local operational constraints. This paper develops a locally adapted SDG assessment methodology for East China Power Grid integrating historical-panel normalization, composite weighting, and dual evaluation. A five-dimensional indicator system operationalizes SDG7 and SDG13 into grid-level metrics-renewable absorption, carbon intensity, energy efficiency, supply reliability, and economic sustainability-normalized against decade-long operational data (2014-2023). Composite weighting synthesizes AHP-derived policy priorities with entropy weights from historical panels, avoiding instability of scenario-only calculations. Three policy scenarios toward 2030 carbon targets are evaluated through Sustainable Development Index for absolute performance and TOPSIS for relative ranking. Results show the high-renewable scenario achieves superior overall sustainability despite economic efficiency trade-offs, with sensitivity analysis confirming ranking robustness across substantial weight variations. The framework provides empirically grounded decision support for regional grid sustainability planning under decarbonization constraints.
AB - Translating global Sustainable Development Goals into regional grid planning requires frameworks balancing sustainability targets with local operational constraints. This paper develops a locally adapted SDG assessment methodology for East China Power Grid integrating historical-panel normalization, composite weighting, and dual evaluation. A five-dimensional indicator system operationalizes SDG7 and SDG13 into grid-level metrics-renewable absorption, carbon intensity, energy efficiency, supply reliability, and economic sustainability-normalized against decade-long operational data (2014-2023). Composite weighting synthesizes AHP-derived policy priorities with entropy weights from historical panels, avoiding instability of scenario-only calculations. Three policy scenarios toward 2030 carbon targets are evaluated through Sustainable Development Index for absolute performance and TOPSIS for relative ranking. Results show the high-renewable scenario achieves superior overall sustainability despite economic efficiency trade-offs, with sensitivity analysis confirming ranking robustness across substantial weight variations. The framework provides empirically grounded decision support for regional grid sustainability planning under decarbonization constraints.
KW - composite weighting
KW - East China Grid
KW - multi-criteria decision-making
KW - regional power grid
KW - sustainability assessment
KW - sustainable Development Goals
UR - https://www.scopus.com/pages/publications/105043980751
U2 - 10.1109/SGAI69026.2026.11566058
DO - 10.1109/SGAI69026.2026.11566058
M3 - Conference contribution
AN - SCOPUS:105043980751
T3 - 2026 3rd International Conference on Smart Grid and Artificial Intelligence, SGAI 2026
SP - 129
EP - 134
BT - 2026 3rd International Conference on Smart Grid and Artificial Intelligence, SGAI 2026
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Smart Grid and Artificial Intelligence, SGAI 2026
Y2 - 15 May 2026 through 17 May 2026
ER -