A current control approach for an abnormal grid supplied ultra sparse Z-Source matrix converter with a particle swarm optimization proportional-integral induction motor drive controller

A rotational d-q current control scheme based on a Particle Swarm Optimization-Proportional-Integral (PSO-PI) controller, is used to drive an induction motor (IM) through an Ultra Sparse Z-source Matrix Converter (USZSMC). To minimize the overall size of the system, the lowest feasible values of Z-source elements are calculated by considering the both timing and aspects of the circuit. A meta-heuristic method is integrated to the control system in order to find optimal coefficient values in a single multimodal problem. Henceforth, the effect of all coefficients in minimizing the total harmonic distortion (THD) and balancing the stator current are considered simultaneously. Through changing the reference point of magnitude or frequency, the modulation index can be automatically adjusted and respond to changes without heavy computational cost. The focus of this research is on a reliable and lightweight system with low computational resources. The proposed scheme is validated through both simulation and experimental results

Improved differential evolution-based MPPT algorithm using SEPIC for PV systems under partial shading conditions and load variation

Photovoltaic arrays subject to partial shading conditions have more than one maximum power point (MPP), and conventional algorithms are unable to track the global maximum power point (GMPP) accurately. Thus, an improved global search space differential evolution algorithm for tracking the GMPP is introduced in this paper. The main contribution of the proposed algorithm are the following: capability in tracking GMPP and faster respond against load variation; optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter; and easy tuning as less parameter has to be set in the algorithm. The proposed system is first simulated in PSIM to ensure its capability. The feasibility of the approach is validated through physical implementation and experimentation. Results demonstrate that the proposed algorithm has the capability to track the GMPP within 2 s with an accuracy of 99% and respond to load variation within 0.1 s