A Computationally Efficient Method to Design Probabilistically Robust Wide-Area PSSs for Damping Inter-Area Oscillations in Wind-Integrated Power Systems

作者：Zhou, Jingsen; Ke, Deping^*; Chung, C. Y.; Sun, Yuanzhang

来源：IEEE Transactions on Power Systems, 2018, 33(5): 5692-5703.

DOI：10.1109/TPWRS.2018.2815534

• Gaussian mixture
• mathematical programming
• probability
• robust
• wide-area power system stabilizer

This paper proposes an efficient method that tunes wide-area power system stabilizers (WPSSs) to have probabilistic robustness for damping inter-area electromechanical oscillations in power systems with incorporated random wind power. Specifically, the efficiency of this method benefits fromunique consideration and deduction of the analytic forms of cumulative distribution functions (cdfs) of two types of random variables and their derivatives with respect to tunable parameters of the conventionally structured WPSSs, based on approximations of wind power probability density functions by Gaussian mixtures. These cdfs then compose the objective function of an optimization that can rapidly solve for optimal parameters of WPSSs by a sequential quadratic programming algorithm. The optimized WPSSs are probabilistically robust because they enhance the probability of two commonly desired control effects. Simulation studies on a modified IEEE 10-machine and 39-bus system validate the superior efficiency of the proposed tuning method and the excellent performance of the derived WPSSs.

• 出版日期2018-9
• 单位Saskatoon; 武汉大学; Saskatchewan