An online clustering-based optimal distributed damping controller design

Abstract

Inter-area low-frequency oscillations with poor damping have long presented challenges in interconnected power systems, leading to the development of various damping control strategies. This paper introduces a novel method for designing Optimally Distributed Damping Control (ODDC) to enhance the damping ratios of critical inter-area modes while minimizing communication links, thereby increasing system stability. The non-convex nature of structural constraints adds complexity to identifying the optimal communication topology among control units in distributed frameworks. To address this, a computationally efficient Semi-Definite Programming (SDP) relaxation technique is applied to solve the non-convex ODDC problem. Additionally, a combined clustering framework is proposed to dynamically update controller coefficients based on mode identification using wide-area measurement data, ensuring effective damping of inter-area oscillations. The IEEE New England 39-bus system, simulated in MATLAB, serves as the validation platform, demonstrating the ODDC method’s effectiveness. Simulation results indicate that an optimal distributed configuration with a single communication link substantially enhances small-signal stability. Moreover, the adaptive updating module successfully provides new coefficients to restore adequate damping ratios when pre-designed controllers lose effectiveness under varying operating conditions.