Online measurements of the battery impedance provides valuable information on the battery state-of-charge and state-of-health which can be utilized for improving the safety and the performance of the associated system. The electrochemical-impedance- spectroscopy (EIS) is widely used for battery impedance measurements but it is not the most applicable solution for online measurements due to its slowness and complexity. These drawbacks can be improved using broadband signals, such as, pseudo-random-sequences (PRS), which are fast and easily implementable. However, the non- linear behavior of batteries have significant effect on the impedance measurements and the selection of the PRS signal. Majority of the PRS signals are applicable for measurements of linear systems but also signals for non-linear system identification do exist. Moreover, the reduced accuracy and signal-to-noise ratio of the PRS signals compared to the EIS make the filtering of the results as well as the amplitude design important aspects. This paper demonstrates the use of two PRS signals, the pseudo-random-binary-sequence (PRBS) and a ternary- sequence with better toleration to battery non-linear effects, with comprehensive amplitude and filtering design for battery impedance measurements. The results are referenced and validated to practical EIS measurements in various operating conditions for lithium-iron-phosphate cell.

Grid impedance affects the stability and control performance of grid-connected power electronic devices, such as inverters used to integrate wind and solar energy. Adaptive control of such inverters, to guarantee stability under different grid conditions, requires online measurement of the grid impedance performed in real time. Such online measurement can be performed by injecting a current perturbation from the inverter into the grid and by reading the grid voltage responses. To minimize the impact on the inverter operation, the injection must be kept as small as possible while producing enough voltage perturbation that can be reliably measured and processed to extract its various frequency components. This paper proposes the use of a discrete-interval binary sequence (DIBS) for this application to minimize the injection. The DIBS is a computer-optimized binary sequence, where the energy is maximized at specified harmonic frequencies based on the expected grid-impedance characteristics. Experimental results based on a three-phase grid-connected inverter are presented to demonstrate the effectiveness of the proposed methods.

Grid impedance and the output impedance of grid-connected inverter are important parameters for the operation of grid-connected systems, such as solar, wind, and other distributed-generation resource systems. The impedance mismatch between the grid and the interfacing circuit often generates harmonic resonances that lead to reduced power quality and even instability. Since the impedances usually vary over time as a function of many parameters, online measurements are required for stability assessment and adaptive control of the inverters. Several methods have been proposed for quick, accurate measurements of impedances, but the use of multiple-input multiple-output (MIMO) identification techniques have not been considered. Applying the MIMO techniques, different components of the inverter output impedance or grid impedance can be simultaneously measured during a single measurement cycle. Therefore, the operating conditions of the system can be kept constant during the measurements, and the overall measurement time is significantly reduced. This paper shows the use of orthogonal binary sequences to simultaneously measure the “d” and “q” components of grid-connected inverter output impedance and/or grid impedance. Experimental results based on a three-phase grid-connected inverter are presented and used to demonstrate the effectiveness of the proposed methods.

Grid impedance is an important parameter for the operation and control of grid-connected inverters used for the integration of solar, wind, and other distributed generation resources. Since the grid impedance usually varies over time and with grid operation conditions, online measurement is required for adaptive control of grid-connected inverters. Existing online measurement methods based on impulse perturbation and Fourier analysis require large current or voltage injection that may interfere with normal operation of the inverter. This paper proposes the use of maximum-length binary sequence (MLBS) injection and averaging Fourier techniques to overcome the drawbacks of impulse injection. Experimental results based on a three-phase grid-connected inverter are presented and used to demonstrate the effectiveness of the proposed methods.

Grid impedance affects the stability and control performance of grid-connected power-electronics devices, such as inverters, used to integrate wind and solar energy. Adaptive control of such inverters, to guarantee stability under different grid conditions, requires online measurement of the grid impedance performed in real time. Wideband frequency-response-measurement techniques based on the pseudo-random binary sequence (PRBS) or impulse injection have been often applied for grid-impedance measurements. However, while using the PRBS or impulse, it is assumed that the system under study is linear. Because such an assumption does not typically hold for grid-connected systems, the measured impedances are usually prone to distortions caused by nonlinearities. This paper proposes the use of periodic ternary sequences for online grid-impedance measurements. Using appropriately designed periodic ternary signals, the linear component of the grid impedance can be identified, eliminating errors from even-order nonlinear distortions. In addition, the ternary sequences can be designed for a much wider range of sequence length compared to the conventional PRBS, enabling more efficient optimization of computing power and frequency resolution. Experimental measurements are shown from a grid-connected photovoltaic inverter.

Grid impedance has a major effect on the operation of inverter-connected systems, such as renewable energy sources. Stability of such system depends on the ratio of the inverter output impedance and the grid impedance at the point of common coupling. Because the grid impedance varies over time with many parameters, online grid-impedance measurement acquired in real time is most preferred method for observing the stability. Recent studies have presented methods based on multiple-input-multiple-output (MIMO) identification techniques where the stability of grid-connected system is rapidly assessed in the dq domain. In the methods, orthogonal injections are used with Fourier techniques, and the grid impedance d and q components are measured. The Nyquist stability criterion is then applied to assess the stability. This paper extends previous studies, and presents a real-time implementation for the online stability analysis using MIMO-identification methods. The practical implementation is discussed in detail and experimental results based on a grid-connected threephase inverter are provided to demonstrate the effectiveness of the methods.