Control of UPQC Based on Steady State Linear Kalman Filter for Compensation of Power Quality Problems


A frequency lock loop (FLL) based steady state linear Kalman filter (SSLKF) for unified power quality conditioner (UPQC) control in three-phase systems is introduced. The SSLKF provides a highly accurate and fast estimation of grid frequency and the fundamental components (FCs) of the input signals. The Kalman filter is designed using an optimized filtering technique and intrinsic adaptive bandwidth architecture, and is easily integrated into a multiple model system. Therefore, the Kalman state estimator is fast and simple. The fundamental positive sequence components (FPSCs) of the grid voltages in a UPQC system are estimated via these SSLKF-FLL based filters. The estimation of reference signals for a UPQC controller is based on these FPSCs. Therefore, both active filters of a UPQC can perform one and more functions towards improving power quality in a distribution network. In addition to the SSLKF-FLL based algorithm, a bat optimization algorithm (based on the echolocation phenomenon of bats) is implemented to estimate the value of the proportional integral (PI) controller gains. The bat algorithm has a tendency to automatically zoom into a region where a promising alternative solution occurs, preventing the solution from becoming trapped in a local minima. The complete three-phase UPQC is simulated in the Matlab/Simulink platform and the hardware is tested under various power quality problems.


  1. Damping factor, echo-location
  2. FPSC
  3. Harmonics
  4. ITSE
  6. Power quality



Figure. 1 Configuration of UPQC


Fig. 2 Dynamic behavior of control algorithm and shunt converter used in UPQC

Fig. 3 Steady state and dynamic response of UPQC with SSLKF-FLL


SSLKF based control is conducted for a three-phase UPQC system under a nonlinear load to achieve PQ compensation. SSLKF control is able to identify the FPSCs (in-phase and quadrature) and grid frequency accurately for the UPQC system, providing fast and smooth steady-state and dynamic responses. The combination of FLL with steady state linear Kalman filters demonstrates superior behavior when compared to other types of single phase PLL techniques published in the literature. It shows that the phase angle and amplitude of a distorted waveform can be precisely and rapidly determined via the Kalman filters. The PI controller parameters, which are tuned in this study using BA optimization, seek minimized DC bus voltage variations, even with upset value of current or voltage. After the 20 iterations, the PI controller proportional (Kp) and integral (Ki) gain are obtained as 200.15 and 1.0, respectively, which maintains the DC bus voltage levels at their desired magnitude. The simulation and test results determine the validity of the proposed UPQC algorithm. The proposed UPQC and BA demonstrates the potential for performance enhancement of the system and PQ improvement of the distribution networks. The presented work can be investigated and evaluated in the future with different linear (or a combination of both linear and nonlinear) loads via the same control algorithm. Similarly, soft computing techniques, such as fuzzy control, artificial neural networks, or intelligent control algorithms, can be used for three-phase UPQCs to improve the system’s effectiveness. Renewable energy sources, such as wind and solar power can be integrated with this (or other) topologies of UPQC.


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[5] S S Reddy. Determination of optimal location and size of static VAR compensator in a hybrid wind and solar power system. International Journal of Applied Engineering Research, 2016, 11(23): 11494-11500.

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