Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization

Fei Liu, Shaokang Qi (), Shibin Wang, Xu Tian, Liantao Liu and Xue Zhao
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Fei Liu: Economic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, China
Shaokang Qi: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Shibin Wang: Economic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, China
Xu Tian: Economic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, China
Liantao Liu: Economic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, China
Xue Zhao: Economic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, China

Energies, 2025, vol. 18, issue 2, 1-24

Abstract: In the context of a high proportion of new energy grid connections, demand-side resources have become an inevitable choice for constructing new power systems due to their high flexibility and fast response speed. However, the response capability of demand-side resources is decentralized and fluctuating, which makes it difficult for them to effectively participate in power market trading. Therefore, this paper proposes a robust transaction decision model for demand-side resource aggregators considering multi-objective clustering aggregation optimization. First, a demand-side resource aggregation operation model is designed to aggregate dispersed demand-side resources into a coordinated aggregated response entity through an aggregator. Second, the demand-side resource aggregation evaluation indexes are established from three dimensions of response capacity, response reliability, and response flexibility, and the multi-objective aggregation optimization model of demand-side resources is constructed with the objective function of the larger potential market revenue and the smallest risk of deviation penalty. Finally, robust optimization theory is adopted to cope with the uncertainty of demand-side resource responsiveness, the robust transaction decision model of demand-side resource aggregator is constructed, and a community in Henan Province is selected for simulation analysis to verify the validity and applicability of the proposed model. The findings reveal that the proposed cluster aggregation optimization method reduces the bias penalty risk of the demand-side resource aggregators by about 33.12%, improves the comprehensive optimization objective by about 18.10%, and realizes the optimal aggregation of demand-side resources that takes into account both economy and risk. Moreover, the robust trading decision model can increase the expected net revenue by about 3.1% under the ‘worst’ scenario of fluctuating uncertainties, which enhances the resilience of demand-side resource aggregators to risks and effectively fosters the involvement of demand-side resources in the electricity market dynamics.

Keywords: demand-side resource; benefits and risks; aggregation optimization; robust optimization; trading decision (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: 2025
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