AI & ML
Priority-Aware Firm and Flexible Capacity Quantification for Large-Load Interconnection
arXiv cs.SY0 views
arXiv:2611.13673v1 Announce Type: new Abstract: We study how to unlock existing transmission capacity to accelerate large-load interconnection under differentiated quality-of-service (QoS) requirements. We establish an efficient framework to quantify firm and flexible hosting capacities and assess marginal values of grid upgrades. Specifically, we define multiple flexible capacity tiers with differentiated QoS limits and design a two-layer priority rule to allocate curtailment among tiers. We then formulate a mixed-integer chance-constrained model to jointly quantify firm and flexible capacities under QoS and priority constraints. To improve computational efficiency, we derive an equivalent aggregate formulation that eliminates individual curtailment variables and priority binaries without changing the feasible capacity set. Numerical results show the computational advantage of aggregation. Multi-tier flexible capacity increases total admitted capacity by 45.0\% over the firm-only hosting capacity.
Source:https://arxiv.org/abs/2611.13673PreviousEfficient control of multi-agent robust MDPs through tensor treesNextAeroelastically Constrained Optimal Path Planning of a Fixed-Wing Airborne Wind Energy System
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