A direct method with Kharitonov’s Theorem for the computation of robust stability delay margins of microgrids with superconducting magnetic energy storage system
Results in Engineering, cilt.32, 2026 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 32
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.rineng.2026.113005
- Dergi Adı: Results in Engineering
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
- Anahtar Kelimeler: Delay-dependent stability, Direct method, Kharitonov’s Theorem, Microgrids, RSDM, SMES
- Gazi Üniversitesi Adresli: Evet
Özet
The study evaluates the robust stability delay margins (RSDMs) of a microgrid (MG) incorporating superconducting magnetic energy storage (SMES). Frequency stability is vital for the dependable and uniform operation of power systems, particularly because power infrastructure must balance provide and required. The utilization of communication systems to manage and coordinate distributed energy resources inherently introduces time delays (TDs) that adversely impact MG frequency stability. Moreover, stability is a significant challenge alongside TDs because of parameter uncertainty in MGs. SMES is an effective way to address these kinds of problems, as it can absorb excess energy and release it to the grid to maintain stable frequency and power levels. This research first examines incorporating SMES into an MG to improve its frequency responsiveness. A direct method combined with Kharitonov’s Theorem (KT) is then employed to determine the RSDMs of the MG with SMES. RSDMs are tested under varying PI controller gains and parameter uncertainty to assess how SMES and system variability affect delay-dependent stability (DDS). The results demonstrate that adding SMES significantly improves the SDMs, by about 44.59% to 98.38% under normal conditions. On the other hand, increasing uncertainty makes the SDMs much worse, by 7.377% to 44.147% for 2% uncertainty and 14.455% to 98.920% for 4% uncertainty. Time-domain (TDO) simulations, backed by a quasi-polynomial mapping-based root-finding algorithm (QPmR), further confirm the robustness results.