Spatial Flexibility Provision From Geographically Dispersed Data Centers Enabling Coordinated Operation of Multi-Local Flexibility Markets
In local flexibility markets (LFMs), distribution system operators (DSOs) can obtain flexibility from distributed energy resource aggregators (DERAs) to address operation problems of distribution systems (DSs). However, in a single LFM, the supply and demand of flexibility may not be balanced, leading DSOs to face significant economic challenges. In this paper, leveraging the geographically coupled flexibility (GCF) provided by geographically dispersed data centers (DCs), a coordinated operation framework for multi-LFMs is proposed. This framework enables wireless connections between multi-LFMs without geographical limitations, only requiring interactions between DSOs and their local DC. To clear the multi-LFMs, an optimization model is established with the objective of minimizing total operation costs of multi-LFMs. The optimization model is solved by ADMM to protect the data privacy. A settlement method for GCF is proposed to allocate the total cost fairly. Furthermore, the uncertain parameters are addressed using distributionally robust chance constraints based on Wasserstein metric. Three DCs, which are connected to three DSs adapted from IEEE 15-bus, 33-bus, and 69-bus DSs, respectively, are used in case studies. The results demonstrate that the GCF enables effective integration and utilization of DERAs’ flexibility across the three LFMs, facilitating the balance between flexibility supply and demand.
Authors
- Yanbo Che
- Mehmet Türker Takcı (ORCID: https://orcid.org/0000-0002-5417-6621)
- Meysam Qadrdan (ORCID: https://orcid.org/0000-0002-1688-0191)
- Yue Zhou
- Boyu Chen (ORCID: https://orcid.org/0000-0002-0689-0230)
Institutions
- Tianjin University (CN)
- State Grid Corporation of China (China) (CN)
- Cardiff University (GB)
Publication Details
- Journal
- IEEE Transactions on Smart Grid
- Published
- 2025-12-25
- DOI
- https://doi.org/10.1109/tsg.2025.3648617
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00