Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization
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 fluctuat...
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| Format: | Article |
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2025-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/2/236 |
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| author | Fei Liu Shaokang Qi Shibin Wang Xu Tian Liantao Liu Xue Zhao |
| author_facet | Fei Liu Shaokang Qi Shibin Wang Xu Tian Liantao Liu Xue Zhao |
| author_sort | Fei Liu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e193b5a23f534a60af012106536e9f86 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-e193b5a23f534a60af012106536e9f862025-01-24T13:30:44ZengMDPI AGEnergies1996-10732025-01-0118223610.3390/en18020236Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation OptimizationFei Liu0Shaokang Qi1Shibin Wang2Xu Tian3Liantao Liu4Xue Zhao5Economic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaEconomic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, ChinaEconomic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, ChinaEconomic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, ChinaEconomic and Technical Research Institute of State Grid Qinghai Electric Power Company, Xining 810001, ChinaIn 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.https://www.mdpi.com/1996-1073/18/2/236demand-side resourcebenefits and risksaggregation optimizationrobust optimizationtrading decision |
| spellingShingle | Fei Liu Shaokang Qi Shibin Wang Xu Tian Liantao Liu Xue Zhao Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization Energies demand-side resource benefits and risks aggregation optimization robust optimization trading decision |
| title | Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization |
| title_full | Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization |
| title_fullStr | Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization |
| title_full_unstemmed | Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization |
| title_short | Robust Trading Decision-Making Model for Demand-Side Resource Aggregators Considering Multi-Objective Cluster Aggregation Optimization |
| title_sort | robust trading decision making model for demand side resource aggregators considering multi objective cluster aggregation optimization |
| topic | demand-side resource benefits and risks aggregation optimization robust optimization trading decision |
| url | https://www.mdpi.com/1996-1073/18/2/236 |
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