A Frequency-Stability-Enhanced Restoration Strategy for Power Electronics Systems With Load Inertia Contribution
Year: 2026
Type: article
Abstract: After a full or partial system outage, black-start (BS) serves as a critical measure to restore the system to the normal operation. In power electronics-dominated renewable energy systems, the inherent characteristic of low inertia on the generation side increases frequency stability risks during BS restoration. In this context, seen from a load-side perspective, this paper studies the potential of induction motors (IMs) after energization to enhance the frequency stability during BS operation. First, load pick-up sequences under mixed load types are explored in BS operation, revealing that early-energized IMs can provide effective inertia support and positive damping during subsequent disturbances. Accordingly, an inertia-oriented BS restoration strategy to enhance the frequency stability is proposed, which is formulated using mixed-integer linear programming and comprehensive frequency security constraints are incorporated. Specifically, the start-up dynamics of IMs are explicitly modeled as operational constraints, and the inertia contributions are further embedded into the frequency constraints, thereby enhancing the accuracy of the overall BS planning framework. Moreover, the two-layer design of objectives enables IMs to contribute inertia as early as possible during the BS. In this way, IMs are treated as inertia sources in the BS path planning. Case studies are performed in simulations and also on a hardware-in-the-loop (HiL) system for modified IEEE 14-bus and 39-bus systems. The HiL experimental test results verify that the proposed approach improves the frequency stability, ensures secure restoration under low-inertia conditions, and demonstrates scalability and adaptability.
Institutions: Zhejiang University, Aalborg University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7164825503
