Multifunctional grid-connected inverters are able to modulate their output current by utilizing the harmonic detection
therefore are commonly used to improve the power quality in strong grids. However
under weak grid conditions and grid impedance fluctuations
significant background harmonics of grid voltage will be generated
distorting the output current of these inverters. The background harmonic problem under weak grid can be effectively suppressed by using existing capacitor voltage feed-forward control strategy
but the existence of feedforward path will worsen the system stability. To address these issues
this paper proposes a weighted resonant capacitive voltage feedforward control strategy
which can effectively suppress the background harmonics and improve the system stability. Firstly
a multifunctional grid-connected inverter control system based on the existing capacitive voltage feedforward control strategy is mathematically modeled
and the system stability is analyzed by using the magnitude/phase-frequency characteristic curve. Secondly
a PR controller is connected in series in the second-order feedforward path to reshape the magnitude/phase-frequency characteristic curve of the system
so as to improve the power quality
suppress the harmonics and improve the system stability. At the same time
the coupling effect between the system output impedance and the grid impedance is taken into consideration
and the impedance analysis method is used for system impedance modelling to analyze the causes of instability of the multifunctional grid-connected inverter system with improved control strategy under a weak grid. On this basis
a weighted resonant capacitive-voltage feedforward control strategy is proposed. A simulated annealing algorithm is used to calculate the weighting factor and the proportional feedforward and second-order feedforward paths are introduced to further improve the robustness of the system under impedance fluctuations. Finally
the effectiveness of the proposed control strategy under impedance fluctuation is verified by simulations.