Coordinated Scheduling of DER Aggregators Driven by Unbalanced Distribution LMP
The imbalance issue in distribution systems becomes more severe due to the high penetration of distributed energy resources (DERs). Meanwhile, the distribution-level market has been proposed, and the three-phase distribution locational marginal price (DLMP) is regarded as a promising approach for quantifying three-phase imbalance costs. In this context, this paper proposes utilizing unbalanced DLMPs to incentivize DERs across different phases to adjust their schedule and mitigate the phase-to-phase imbalance in a market environment. A bi-level programming model is formulated to capture the interaction between the DER aggregator and the distribution system operator (DSO). The lower level incorporates voltage imbalance constraints into the DSO’s market-clearing model, generating unbalanced marginal cost incentives for phase balancing. At the upper level, the revenue of DER aggregators is maximized based on DER aggregation constraints and unbalanced DLMPs. To make the bi-level model tractable, Karush-Kuhn-Tucker (KKT) conditions and strong duality theory are used to reformulate the bi-level problem into a single-level problem. Simulation results demonstrate that the bi-level model benefits both DER aggregators and the DSO. In addition, DER aggregators strategically contribute to phase balancing by leveraging unbalanced DLMPs, which can not only improve their revenue but also mitigate imbalances for the DSO.
Authors
- Menglin Zhang (ORCID: https://orcid.org/0000-0001-7853-9354)
- Qiuwei Wu (ORCID: https://orcid.org/0000-0001-7935-2567)
- Xiaofei Wang (ORCID: https://orcid.org/0000-0001-7783-4204)
- Jian Gong (ORCID: https://orcid.org/0009-0005-3641-0225)
- Fangxing Li (ORCID: https://orcid.org/0000-0003-1060-7618)
- Bo Zhou (ORCID: https://orcid.org/0000-0002-0793-3968)
- Jinyu Wen (ORCID: https://orcid.org/0000-0002-0288-727X)
Institutions
- Queen's University Belfast (GB)
- University of Michigan (US)
- China University of Geosciences (CN)
- Huazhong University of Science and Technology (CN)
- University of Tennessee at Knoxville (US)
Publication Details
- Journal
- IEEE Transactions on Smart Grid
- Published
- 2025-10-08
- DOI
- https://doi.org/10.1109/tsg.2025.3619404
- Primary Topic
- Scheduling and Optimization Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00