Fuzzy logic control of DSTATCOM for improving power quality and dynamic performance

Distribution power system has poor power quality and dynamic performance due to insufficient reactive power support during disturbances. Distribution Static Compensator (DSTATCOM) can improve the power quality and dynamic performance of distribution power system. Proportional and Integral (PI) controllers are often used to control the operation of the DSTATCOM for the distribution power system. However, since the power system is highly nonlinear and subject to various disturbances, the PI controlled DSTATCOM cannot provide optimal performance for different operating points. More robust controllers such as the one based on fuzzy logic approach are required for the DSTATCOM to provide adequate dynamic voltage control and to improve power quality and stability of the distribution power system. This paper presents the design of a fuzzy logic based controller of a 3MVA DSTATCOM for improving the power quality and stability of a distribution power system. Grey Wolf Optimisation (GWO) algorithm has been used to tune the scaling factors of the fuzzy logic controllers. Comparison study of PI controlled and fuzzy logic controlled DSTATCOM for improving the power quality and dynamic performance of a distribution power system is simulated using SimPowerSystem in MATLAB/Simulink environment. The performances of the DSTATCOM controllers are evaluated during grid side voltage sag and load variation. The simulation results in MATLAB/SimPowerSystems show that the fuzzy logic controlled DSTATCOM controller provides better system dynamic response and hence improves power quality and stability for the distribution power system.

I. Introduction

Low voltage poor power quality can be caused by the demand in reactive power as it loads up the supply system unnecessarily. This can also be due to harmonic pollution and load imbalance as these cause extra stress on the networks and excessive voltage imbalance causing stress on other loads connected to the same network [1]. Flexible AC Transmission Systems (FACTS) devices such as Static Synchronous Compensator (STATCOM) can address the power quality issues related to transmission lines while DSTATCOM can improve the power quality and dynamic performance in a distribution network [2]. A DSTATCOM is a shunt connected bidirectional converter based device which can provide adequate level of reactive power to improve the quality of electrical power featured as the voltage at the point of common coupling (PCC) in distribution network [3]–[5]. Various control structure and algorithms for DSTATCOM converter such as phase shift control with PI controller, carrier based PWM control with PI controller, and carrier less hysteresis control with PI controller have been proposed to address the power quality issues [2]. In the work by Singh and Solanki [6], instantaneous reactive power theory, a synchronous reference frame theory, and an Adaline-based algorithm have been compared for extracting reference current signals. Kora [7] presented fuzzy logic controller for three-phase DSTATCOM to compensate for AC and DC loads. However, the fuzzy logic controller is only proposed for controlling the dc-link voltage based on the energy of a dC-link capacitor. In this paper, carrier-based PWM control with fuzzy controllers are designed for controlling the DC voltage, AC voltage, and current regulators. In [8], a Mamdani type of fuzzy controller was employed whereas a Sugeno type of fuzzy logic controller is designed in this paper. Our previous research results show that a Sugeno type of fuzzy logic controller for STATCOM has many advantages over the Mamdani type [9]–[13]. A Sugeno type of fuzzy logic controller can overcome the computational problem a complex system such as distribution power system encounters in both software simulation and real-time implementation. A Sugeno type fuzzy controller can be analysed and implemented more effectively than the Mamdani type fuzzy controller. In addition, it is more convenient in mathematical analysis and in system analysis for a DSTATCOM equipped with a Sugeno type fuzzy controller as the membership functions for the output are singletons. After designing the fuzzy controller, fine tuning can be made in order to improve the performance of the controller. Tuning can be made either to the membership functions or to the scaling factors (note that it is common to use normalised inputs and outputs for fuzzy controller and hence scaling factors are required to normalise these inputs and outputs). However, as the rule-base conveys a general control policy, it is preferred to keep the rule-base unchanged and the tuning exercise is focused on the scaling factors. In this paper, the scaling factors of the designed fuzzy controllers are tuned using Grey Wolf Optimisation (GWO) algorithm.