Robust Power Flow Control of Micro grid-Connected Inverters
Keywords:
Uncertainty and disturbance estimator (UDE), model uncertainties, fluctuation of DC-link voltage, variation of the impedance, micro grid disturbancesAbstract
In this paper an uncertainty and disturbance estimator (UDE)-based robust power flow control is developed for micro grid-connected inverters (GCI) to achieve accurate power delivery to the micro grid. The model of power delivering with both frequency dynamics and voltage dynamics is derived at first. The UDE method is introduced into the controller design to deal with model uncertainties (e.g., output impedance, power angle), coupling effects, and external disturbances (e.g., the fluctuation of the DC-link voltage, the variation of output impedance/line impedance, and the variations of both frequency and amplitude in the micro grid voltage). Also this controller does not need a voltage regulator or a current regulator, and is easy for the implementation and parameter tuning through the design of the desired tracking error dynamics and the UDE filters. Experimental results are provided to show the effectiveness of the proposed method for different disturbance rejection scenarios, the low-voltage fault-ride through capability and the weak micro grid operation capability. The good robustness of the UDE-based control is also demonstrated through the comparison with the proportional integral (PI) controller. The integration of renewable energy sources into micro grids has gained significant attention in recent years due to the increasing demand for clean and sustainable energy. Micro grid-connected inverters play a crucial role in the efficient operation and power flow control of micro grids. However, the dynamic nature of renewable energy sources and uncertainties associated with their generation pose challenges to the robust power flow control of these inverters. This report/thesis presents a comprehensive study on the robust power flow control techniques for micro grid-connected inverters, considering the uncertainties and variations in renewable energy generation. The aim is to develop effective control strategies that ensure reliable and efficient operation of micro grids while accommodating the variability of renewable energy sources.
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