High Performance dual control feed forward based fuzzy logic technique & finite set control model predictive control for a grid-connected PV system

The converters interfacing PV system with the grid involves some major drawbacks appear in simulation studies such as: An important overshoot in the steady state, the long response time, a bad power and a bad THD that exceeds IEEE standards (> 5%). That’s why in this paper two novel approaches have been proposed in order to overcome these drawbacks. As a first step, a bad tracking of the DC-link regulator is particularly apparent when the solar irradiance varies severely or suddenly, this problem leads us to develop the extension of the DC-link control using the Feed Forward based Fuzzy Logic (FF-FL) to improve transient performance of the DC-link. More developed in term of minimization error, the fuzzy is used to compensate the DC-link losses with remarkable improved performances are noted by setting DC-link voltage reference. Where in the DC link voltage Feed Forward was adapted by adjusting reference DC link voltage according to CPI (common point of interconnection). The grid side converter enables to control the active and reactive power flow to the grid and improving the output power quality by reducing total harmonic distortion (THD). The other task is dedicated to control the connection to the grid using the three-level converter in order to achieve high voltage using low voltage switching devices. In this case, Neutral Point Clamped (NPC) has been proposed to provide high output power to feed the PV source into an existing three-phase power grid via an RL filter. So, the second proposed approach deals principally with the behavior of the grid currents variation, Finite Set Control Model Predictive Control (FCS-MPC) has been proposed to exhibit the high dynamic efficiency for multilevel converters that keeps a unitary power factor injection to the grid and maximizes the energy harvested from solar. A comparison has been made between the PI and FF-FL controllers to prove the performance and the efficacy of the proposed strategy using detailed simulation studies.