Dynamic Restoration of Active Distribution Networks by Coordinated Repair Crew Dispatch and Cold Load Pickup
Kaiyuan Pang, Chongyu Wang, Nikos Hatziargyriou, Fushuan Wen
Abstract
This article presents a dynamic restoration strategy for active distribution networks (ADNs) by coordinating repair crew dispatch and frequency-constrained cold load pickup. To incorporate the stochastic repair time, the repair crew dispatch is formulated as “event-driven” with the implementation of model predictive control (MPC). The stochastic repair time is estimated, convexified, and updated dynamically with each MPC execution. The finish of a repair task triggers the subsequent cold load pickup model, where the frequency dynamics are computed and linearly constrained with the help of a uniform frequency response model for low-inertia systems. Next, a co-optimization framework of the two models is developed to coordinate the repair crew dispatch and cold load pickup under a unified time scale. Numerical results on a modified IEEE 33-node test feeder and a real-world 136-node distribution system have verified the effectiveness of the proposed model.