Data-driven three-step optimal frequency scheme for alleviating grid frequency regulation in MT-HVDC linked grids
2026 · International Journal of Electrical Power & Energy Systems
저자
Jae-Sung Lim, Sung-Wook Lee, Do-Hoon Kwon, 이규섭 (Gyu‐Sub Lee), Seung‐Il Moon
연구주제
HVDC Systems and Fault Protection · Microgrid Control and Optimization
NTIS 과학기술표준분류
에너지/자원만에너지·환경·원자력 확장
배정 근거: AI 키워드가 잡은 NTIS 과제의 분류(정책 연계 맵과 같은 방법).
AI 연구 키워드·방법
kalman filter 최적화 system identification
키워드 (OpenAlex)
grid frequency regulation multi-terminal HVDC data-driven system identification Kalman filter eigensystem realization algorithm small-signal modeling LQG control DC bus voltage regulation
초록
The increasing penetration of renewable energy sources and the deployment of multi-terminal high-voltage direct-current (MT-HVDC) systems complicate reliable grid frequency regulation. This paper proposes a data-driven three-step optimal frequency control scheme for MT-HVDC systems. The first step focuses on data-driven state-space modeling using observer/Kalman filter identification and the eigensystem realization algorithm. The data-driven approach constructs reduced-order small-signal models that accurately capture system dynamics using only input–output data, independent of first-principles descriptions. In the second step, an optimal linear quadratic Gaussian (LQG) control scheme is synthesized based on the identified model. The LQG control algorithm minimizes deviations in frequency and DC-link voltage via a quadratic optimal-control formulation. Concurrently, the embedded Kalman f…
이 논문을 지원한 국가R&D 과제 (NTIS 성과)
NTIS 성과DB(2020–24)에서 DOI 매칭 없음
인접 그래프
노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동