Optimal Control Tuning of Grid Connected Voltage Source Converters using a Multi-Objective Genetic Algorithm

摘要

Given their wide-range power ratings and flexible control capabilities, voltage-source converters (VSCs) will most likely constitute the basic building block for the ac-dc conversion in future smart grids and high-voltage direct current (HVdc) supergrids. Furthermore, when it comes to the integration of solar and wind energy to the AC network, VSCs are usually the technology of choice. Hence, it is extremely important to know with high precision how VSCs behave dynamically. However, the dynamic behavior of such converters is widely influenced by their control strategy and its tuning. The present paper seeks to optimize the control tuning of VSCs by utilizing a multi-objective genetic algorithm (GA). The GA optimization is performed on a small-signal linear model which includes the converter hardware and complete control structure. The results from the multi-objective optimization are tested in a 5-kVA converter and the measurements are compared with a non-linear model and the small-signal linear model.