Analyzing the Impact of Demand Response on Short-Circuit Current via a Unit Commitment Model
Peng Wang, Zhengmao Li, Luis Badesa

TL;DR
This paper investigates how demand response impacts short-circuit current levels in power systems with high renewable penetration, highlighting the importance of coordinated load management for system stability and cost efficiency.
Contribution
It introduces a novel unit commitment model incorporating demand response and short-circuit current constraints, revealing the trade-offs between cost savings and system stability.
Findings
Demand response can reduce total system costs by adjusting demand.
Improper DR coordination may lead to inadequate short-circuit currents.
Properly coordinated DR increases total costs by only 0.3%, maintaining stability.
Abstract
In low-carbon grids, system flexibility can be enhanced through mechanisms such as Demand Response (DR), enabling the efficient utilization of renewable energy. However, as Synchronous Generators (SGs) are being replaced by renewable energy sources characterized by Inverter-Based Resources (IBR), system stability is severely affected. Due to the limited overload capability of IBRs, their Short-Circuit Current (SCC) contribution is much smaller than that of SGs. As a result, protection devices may fail to trip during faults. Consequently, the remaining SGs play a key role in providing sufficient SCC. Since the commitment of SGs is closely related to system loading conditions, DR can indirectly affect their SCC provision, a relationship that has not yet been investigated in the literature. Therefore, this paper incorporates both DR and SCC constraints into a unit commitment problem and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMicrogrid Control and Optimization · Optimal Power Flow Distribution · Smart Grid Energy Management
