| Title |
A Real-Time AC Sensitivity-Based Optimal Curtailment Framework for Renewable Generation to Mitigate Transmission Line Overloads and N-1 Contingencies |
| Authors |
김주홍(JooHong Kim) ; 차준상(JunSang Cha) ; 송성윤(SungYoon Song) |
| DOI |
https://doi.org/10.5370/KIEE.2026.75.9.2049 |
| Keywords |
AC sensitivity; Drop-One Refinement; mixed-integer linear programming; renewable energy curtailment; transmission line overload |
| Abstract |
This paper proposes an AC sensitivity-based mixed-integer linear programming (MILP) optimization method for minimum renewable energy curtailment to relieve transmission line overloads. While DC power transfer distribution factor (PTDF) methods offer fast computation, they introduce approximation errors by neglecting voltage variation, reactive power, and line losses. AC exhaustive search guarantees accuracy but suffers from combinatorial explosion. The proposed method computes sensitivities by perturbing each candidate generator output and re-solving the AC power flow, then formulates a MILP for minimum curtailment. A Drop-One Refinement post-processing step is introduced to remove unnecessary curtailments caused by linear superposition errors. Case studies on IEEE 9-, 59-, and 118-bus standard systems and a KPG 193-bus Korean power grid model demonstrate that the proposed method achieves overload relief with computation time comparable to DC PTDF and curtailment levels comparable to AC exhaustive search, providing a practical balance between accuracy and efficiency. N-1 contingency analysis on IEEE 118 and KPG 193 systems confirms that the proposed method provides higher resolution rates than DC PTDF under N-1 conditions while maintaining real-time feasibility. |