Comparative analysis of MPPT algorithms bio-inspired by grey wolves employing a feed-forward control loop in a three-phase grid-connected photovoltaic system

Comparative analysis of MPPT algorithms bio-inspired by grey wolves employing a feed-forward control loop in a three-phase grid-connected photovoltaic system

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It is well-known that performance of photovoltaic (PV) systems can be severely deteriorated when PV arrays are subjected to partial shading conditions, once the traditional techniques used for maximum power point tracking (MPPT) could not operate in the global maximum power point (GMPP). Thus, to overcome this problem and achieve the GMPP, four MPPT techniques bio-inspired in the grey wolf optimisation (GWO) are presented. These MPPT techniques, which are named as GWO, GWO-Beta, GWO-IC (Incremental Conductance), and GWO-P&O (Perturb and Observe), are evaluated and compared to each other by employing a double-stage three-phase grid-connected PV system, which is composed of DC/DC converter and three-phase inverter. Commonly, the DC-bus voltage regulation of double-stage PV systems presents slow dynamic behaviour to avoid disturbances in the currents injected into the grid. As a result, MPPT algorithms suffer with this problem since they must be executed considering this condition. To overcome this problem, a feed-forward control loop (FFCL) is implemented to improve the DC-bus voltage regulation during abrupt solar irradiance changes, as well as accelerating the MPPT algorithms dynamics. By means of extensive experimental and simulation results, the performance and effectiveness of the four MPPT techniques, as well as the FFCL, are evaluated.


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