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Minwu Chen

Publications and source records attributed to Minwu Chen.

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A Bi-Layer TSN Formulation for Separable Scheduling of Mobile Emergency Resources

Separable scheduling unleashes the deployment flexibility of mobile emergency resources by dispatching carriers and functional modules separately yet in a coordinated manner, offering a promising avenue to enhance power system resilience. However, this flexibility induces a distinct carrier-supported module routing structure, where non-self-mobile modules must be routed through compatible carrier movements. The resulting carrier-module spatio-temporal coupling makes exact and tractable optimization challenging. This letter identifies this structure and develops a novel exact bi-layer time-space network formulation as a mixed-integer linear program. The proposed formulation represents carrier and module trajectories as interacting network flows and enforces their support relations through explicit arc-level coupling. Compared with the prior logic-based model, the proposed formulation preserves exactness while improving modeling flexibility by eliminating mandatory post-arrival dwelling. Numerical studies validate its correctness and demonstrate substantial computational advantages.

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Optimal Distribution System Restoration via Tractable Modeling of Decision-Dependent Interruption Cost and Cold Load Pickup

Developing optimized restoration strategies for power distribution systems (PDSs) is critical to enhancing resilience. Prior knowledge of customer interruption cost (CIC) and load restoration behaviors, particularly cold load pickup (CLPU), is essential for effective decision-making. However, both CIC and CLPU are reciprocally influenced by the realized customer interruption duration (CID), making them decision-dependent and challenging to model, especially given the limited understanding of their underlying physical mechanisms. This paper proposes a novel and tractable modeling approach to capture the varying patterns of CIC and CLPU with CID - patterns derived from data that reflect observable surface - level correlations rather than underlying mechanisms - thereby enabling practical surrogate modeling of these decision-dependent factors. Specifically, quadratic functions are employed to model the increasing rate of CIC with respect to CID according to data fitting results. For CLPU, several defining characteristics are extracted and modeled in a piecewise linear form relative to CID, and the actual restored load accounting for CLPU is subsequently reconstructed. Building on these models, a PDS restoration optimization framework is developed, incorporating mobile energy storage systems (MESSs) and network reconfiguration strategies. Case studies validate the effectiveness of the proposed approach and highlight MESS's unique potential in accelerating CLPU-related restoration.

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