Estimation of location and coordinated tuning of PSS based on mean-variance mapping optimization

Proper location and adjustment of power system stabilizers (PSSs) is of great concern to achieve effective enhancement of overall power system damping performance. Thus, the problem of optimal location and coordinated tuning of PSSs (OLCTP) requires the fulfillment of several specifications to ensure system operation with adequate security margins for different operating conditions. This paper presents a comprehensive approach to tackle the OLCTP based on a combination of probabilistic eigenanalysis (PE) and the mean-variance mapping optimization (MVMO). PE is employed to assess the probabilistic attributes of the system eigenstructure associated to the statistics of nodal injections. Next, a combined technique of principal component analysis and fuzzy c-means clustering is applied to select a reduced subset of relevant scenarios to be considered in the formulation of the OLCTP. The number of PSSs, as well as the set of parameters that ensure robustness for operating condition change, are determined through MVMO. Numerical results demonstrate the effectiveness of the proposed approach. In addition, an adaptive controller coordination scheme, which can be used online, is suggested.