Model Predictive Black Start for Dynamic Formation of DER-Led Microgrids with Inrush Current Impacts

TL;DR

This paper introduces a model predictive black start framework for DER-led microgrid restoration that accounts for inrush current impacts, improving safety and efficiency during system energization.

Contribution

It develops an inrush current feasibility module integrated into a model predictive control framework for dynamic, real-time microgrid black start procedures.

Findings

Inrush current estimation accuracy exceeds 90% in simulations.

The framework prevents protection misoperations during restoration.

It reduces unnecessary DER energy consumption and improves load restoration efficiency.

Abstract

Black start (BS) of the distribution system (DS) with high penetration of distributed energy resources (DERs) requires advanced control frameworks to ensure secure and efficient restoration. This paper proposes a model predictive black start (MPBS) framework incorporating an inrush current feasibility module to dynamically generate real-time feasible and optimal restoration sequences. Short-term forecasts of DER output and transmission grid (TG) availability are utilized to construct adaptive cranking paths. The inrush current feasibility module analytically estimates the transient inrush current caused by energizing no-load distribution transformers (DTs). To mitigate excessive inrush current and avoid potential misoperations of protection devices, an emergency operation-inspired voltage control strategy and a switch blocking mechanism are developed. The proposed inrush model is validated against electromagnetic transient (EMT) simulations in PowerFactory with estimation accuracies exceeding 90 %. Case studies on a modified IEEE 123-node feeder demonstrate that the MPBS framework prevents misoperations of fuses and reclosers, reduces unnecessary DER energy consumption, and enhances load restoration efficiency during DER-led BS processes.