The main purpose of this paper is to analyze the control algorithms’ performances under the various sensitive loading conditions. The focus is on maintaining direct current (DC)-link voltage stability, reactive power compensation and minimizing error indices to improve power quality in distribution networks by the DSTATCOM system.
A novel adaptive control algorithm is developed to accurately extract the fundamental positive-sequence components from the load currents. These extracted components are utilized to generate appropriate reference signals and switching pulses, enabling the effective operation of the DSTATCOM under diverse loading conditions. The tuning of proportional–integral (PI) controller gains of least mean fourth (LMF)/least mean square (LMS) are initially performed using the classical Ziegler–Nichols (ZN) method for improving dynamic performance. To further enhance its control accuracy and robustness, a metaheuristic optimization technique – particle swarm optimization (PSO) is used to optimally tune the PI gains.
The proposed LMF–PI–PSO control has advantages over conventional approaches, namely, LMS–PI–PSO, conventional LMF/LMS, synchronous reference frame (SRF)–ZN–PI and SRF–ZN–PI–PSO. The proposed controller ensures robust DC-link voltage regulation with minimal steady-state deviation and faster dynamic recovery under varying operating conditions. It achieves effective reactive power compensation, thereby maintaining a near-unity power factor and significantly reducing harmonic distortion across balanced, unbalanced and nonlinear load scenarios. Furthermore, detailed performance evaluation in terms of DC-link voltage error indices and transient response parameters such as settling time, overshoot, peak time and rise time confirm the enhanced dynamic stability and regulation accuracy of the proposed method.
The key features of this proposed LMF–PI–PSO control scheme are (i) faster convergence, (ii) reduction in harmonics, (iii) reduction of transient parameters such as overshoot and settling time and (iv) reactive power compensation. These results are verified both using OPAL RT and the MATLAB/SIMULINK platform.
