A Balancing Group Construction Method Based on Combinatorial Empowerment TOPSIS Decision Making

Large-scale renewable and demand-side resource integration intensifies grid uncertainties, challenging centralized control. This paper proposes decentralizing grid balancing to regional/county-level balance groups, defined as fundamental regulatory units enabling internal generation-load balance. A comprehensive evaluation system is established, incorporating supply-demand balance metrics (source-load matching, power fluctuation, forecast deviation) and flexibility metrics (upward/downward adequacy/insufficiency). A weighted TOPSIS decision-making method combines subjective (AHP) and objective (improved CRITIC) weights to determine optimal balance unit configurations. The final example validates the effectiveness and superiority of this method in evaluating balanced group schemes.

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Publication Details

Published
2025-08-15
DOI
https://doi.org/10.1109/iccepe66357.2025.11193231
Primary Topic
Evaluation and Optimization Models
Type
article
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article

A Balancing Group Construction Method Based on Combinatorial Empowerment TOPSIS Decision Making

Na Li, Wei Zhou, Yuchun Sun, Qi Yuan
Evaluation and Optimization Models
article

A Balancing Group Construction Method Based on Combinatorial Empowerment TOPSIS Decision Making

Na Li, Wei Zhou, Yuchun Sun, Qi Yuan
article en

Abstract

Large-scale renewable and demand-side resource integration intensifies grid uncertainties, challenging centralized control. This paper proposes decentralizing grid balancing to regional/county-level balance groups, defined as fundamental regulatory units enabling internal generation-load balance. A comprehensive evaluation system is established, incorporating supply-demand balance metrics (source-load matching, power fluctuation, forecast deviation) and flexibility metrics (upward/downward adequacy/insufficiency). A weighted TOPSIS decision-making method combines subjective (AHP) and objective (improved CRITIC) weights to determine optimal balance unit configurations. The final example validates the effectiveness and superiority of this method in evaluating balanced group schemes.

Electric Power Research Institute (US), Dalian University of Technology (CN)
Openalex Percentile: Top 64%
Evaluation and Optimization Models
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