A Virtual Resistance Optimization Method Based on Hybrid Index in Low-Voltage Microgrid

Abstract

Introduction: The introduction of virtual resistance can effectively suppress the circulating current between micro-sources and improve power allocation in low-voltage microgrid, but it also causes the voltage deviation of micro-sources’ inverters. An optimization method of virtual resistance based on hybrid index is proposed in order to suppress circulating current and improve voltage deviation at the same time in this paper. The gradient descent method is used to design the virtual resistance optimization process, aiming at the optimization of hybrid index composed of circulating current and voltage deviation. The constraints are deduced with power quality requirements, capacity limitation and static stability, and then virtual resistance values are optimized. The effects of switching load and micro-source on the optimization results are analyzed through the simulation of low-voltage microgrid, and the simulation results show that the virtual resistance optimization method can significantly suppress circulating current while improving power quality. When distributed generators are connected to utility grid through inverters and feeders, differences in feeder parameters and inverter control strategies easily cause circulating current and uneven power distribution among micro-sources. The introduction of virtual resistance can effectively suppress the circulating current between micro-sources and improve power allocation in low-voltage microgrids, but it also causes the voltage deviation of micro-sources’ inverters. An optimization method of virtual resistance based on hybrid index is proposed in order to suppress circulating current and improve voltage deviation. Methods: The gradient descent method is used to design the virtual resistance optimization process, aiming at the optimization of hybrid index composed of circulating current and voltage deviation. The constraints are deduced with power quality requirements, capacity limitation and static stability, and then virtual resistance values are optimized. Result: In the simulation scenario of two micro-sources and three micro-sources, the virtual resistance obtained by the method proposed in this paper has more obvious improvement on the system operation index, and is not affected by the load type. Conclusion: The method of optimizing virtual resistance based on the hybrid index can achieve the effect of restraining circulating current and improving power sharing degree on the premise of guaranteeing power quality and satisfying system stability. The optimization of virtual resistance is affected by the number of feeders. It is necessary to re-optimize the virtual resistance after changing the number of feeders, but the process of switching micro-source and adjusting load does not affect the optimized resistance value.