A dq-Domain Impedance Measurement Methodology for Three-Phase Converters in Distributed Energy Systems

• Main Authors: Muhammad Saad, Husan Ali, Huamei Liu, Shahbaz Khan, Haider Zaman, Bakht Muhammad Khan, Du Kai, Ju Yongfeng
• Format: Article
• Language: English
• Published: MDPI AG 2018-10-01
• Series: Energies
• Subjects: AC impedance; distributed energy system; shunt current injection; dq domain; measurement
• Online Access: http://www.mdpi.com/1996-1073/11/10/2732

A distributed energy system (DES) using controlled power electronics converters delivers power to loads, via conventional, as well as a number of renewable, energy sources. However, stability concerns retard the integration of power electronics converters into an existing DES. Therefore, due to the high penetration of power converters, the overall network analysis of DES is becoming increasingly difficult. Impedance-based DES modeling emerged as an effective technique as it reduces the system into source and load subsystems and offers easier analysis of the dynamic interactions between them. These models can be obtained using either analytical calculations, simulations, or experimental measurements. In this work, firstly, a line-to-line current injection technique is used for the measurement of alternating current (AC) impedances. Since it requires repeated injections, a d q -domain impedance measurement methodology based upon a set of independent perturbations and measurements is proposed. The perturbation is injected via a sweep signal which is preprocessed by the digital signal processor (DSP) prior to injection. The d q reference frame is synchronized with the three-phase AC system using a low-bandwidth phase-locked loop (PLL). The close matching of impedance parameters measured in simulation using the proposed approach with those obtained using analytical expressions and the line-to-line current injection technique verifies the effectiveness of the approach. Furthermore, the method was also implemented experimentally, and the close matching of the results with the analytical and simulation results validates the overall modeling and measurement procedure.