Estimation of Harmonics in Microgrid using Unscented Kalman Filter Pravati Nayak 1 and Sasmita Jena 2 1 Department of Electrical Engineering, Siksha O Anusandhan University,Bhubaneswar,Odisha. pravatinayak@soauniversity.ac.in 2 Department of Electrical Engineering, Siksha O Anusandhan University,Bhubaneswar,Odisha. sasmita.jena500@gmail.com Abstract This paper recounts adoption of Unscented Kalman Filter (UKF) in micro-grid for harmonics estimation. Vigorous application of nonlinear loads due to induction of emanating power electronics technologies leads to inject harmonics into the system and hence an assessment tool is needed for its estimation and elimination. This can be achieved by several algorithms such as KF(the Kalman Filter), EKF(the Extended Kalman Filter),AKF(the Adaptive Kalman Filter) etc. have come into focus. The estimation of phase, frequency, amplitude and contents of harmonics from a noisy signal can be done by using Extended Kalman Filter(EKF). But its performance regresses whenever a highly nonlinear signal is being considered as it suffers from uncertainty because of linearization and severe calculation of Jacobean matrices. On account of this, the paper suggests an Unscented Kalman Filter(UKF) to conquer the linearization and differentiation problem of EKF for dynamic tracking of harmonics in a Micro-grid. The selection of the micro-grid model and the parameters of UKF as well as the measurement error covariance matrices Q and R is done . The algorithm is applied to a selected micro-grid model and outcomes are studied in MATLAB/SIMULINK environment. Key Words: EKF(Extended Kalman Filter),UKF(Unscented Kalman Filter), Filter Modeling, Distributed Generation, Microgrid. International Journal of Pure and Applied Mathematics Volume 114 No. 9 2017, 73-81 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu 73