1.合肥工业大学电气与自动化工程学院，安徽省合肥市 230009;2.光伏系统教育部工程研究中心（合肥工业大学），安徽省合肥市 230009
1.School of Electrical and Automation Engineering, Hefei University of Technology, Hefei 230009, China;2.Research Center for Photovoltaic System Engineering of Ministry of Education (Hefei University of Technology), Hefei 230009, China
The real-time power grid impedance information obtained by grid-connected inverters can be used in power grid status monitoring, fault diagnosis, and grid-connected equipment stability control, to improve the intelligent level of grid-connected equipment and power grid regulation. Since the injected disturbance signal is often applied to the current control loop of the inverter, the impedance measurement frequency band is limited by the bandwidth of the controller. In order to improve the accuracy of high-frequency impedance measurement, this paper proposes a power grid impedance measurement method based on Sobol quasi-random pulse width modulation (SQRPWM) by taking advantages of the characteristic of frequency spectrum shift of random pulse width modulation and the uniformity of Sobol quasi-random sequence. The frequency boundary of SQRPWM is optimized and designed according to the system bandwidth and stability constraints. The feasibility of the proposed impedance measurement scheme based on SQRPWM and the mixed impedance measurement scheme combined with the single pulse and SQRPWM is verified on the experimental platform of Starsim. The results show that the proposed impedance measurement scheme has the advantages of small disturbance and high measurement accuracy at a high frequency. Moreover, if the proposed method is combined with the current-disturbance based impedance measurement method, the frequency band of the power grid impedance measurement can be further expanded and the broadband impedance information can be obtained.
DU Yan, WU Houbo, YANG Xiangzhen, et al. Power Grid Impedance Measurement Method Based on Sobol Quasi-random Pulse Width Modulation[J/OL]. Automation of Electric Power Systems, http://doi. org/10.7500/AEPS20200225010.