Fault characteristics analysis normally provides a theoretical foundation for the protection design. Although conventional fault analysis of inverter-interfaced renewable energy sources (IIRESs) can characterize post-fault steady-state at the power frequency, it might not effectively present the fault transient. This can negatively affect the protection based on fault transient data within 20–30 ms after a grid fault. Thus, the fault transient of IIRESs needs to be fully investigated. Given this, the nonlinear effect of controller saturation is considered in this study. The domain of attraction (DOA) is first established to estimate the practical working state of the controller within the current loop. The transient fault current (TFC) analytical model is then proposed in accordance with the nonlinear control response of the controller under different working stages, which reveals a detailed transient transition of the fault current. Meanwhile, the proposed model is low-order and presents high applicability in different fault scenarios. Simulation results indicate that the TFC analytical accuracy obtained using the proposed method is improved by at most 50% relative to the accuracy reported in published studies. Field short-circuit test data are ultimately used to verify the performance of the proposed TFC analytical model.

The renewable energy sources (RESs) are directly or indirectly connected to the grid through power electronic devices and the short-circuit current exhibits characteristics such as limited amplitude, non-power frequency and controlled phase angle, which may lead to the malfunction of the RES-side distance protection on the transmission line. In order to solve this problem, a distance protection method based on the high-frequency fault component is proposed. The voltage drop caused by the fault has a full frequency component, the high-frequency impedance models of the inverter-interfaced renewable energy generator (IIREG) and the doubly-fed induction generator (DFIG) are established and the frequency selection principle that makes them have the stable phase angle is determined. On this basis, the internal and external faults can be determined by comparing the magnitude of high-frequency operating voltage and high-frequency voltage at the fault point. This method eliminates the influence of frequency offset and weak feed of RESs by using high-frequency signals generated by voltage sags at the fault point and can tolerate some noise. At the same time, due to the larger radius of impedance circle at the high-frequency range, this method has a strong ability to withstand the fault resistance. The experimental results and field-testing data verify the effectiveness of the method.

This paper proposes a fault-section location method based on sparse measurements, aimed at asymmetrical faults. A virtual current vector is defined to indicate the faulted section, which is sufficiently sparse except that the fault position corresponding entries are nonzero. To simplify the algorithm, the virtual vector is fixed by amplitudes of voltages and impedances and the feasibility is demonstrated. The Bayesian Compressive Sensing theory is introduced to reduce the number of required intelligent electronic devices (IEDs). In addition, the minimal number of IEDs and their allocation are discussed. The performance of the proposed method is validated in a 69-bus, 12.66 kV distribution system with six distributed generations (DGs) in response to various fault scenarios. The simulation results show that the method is robust for single-phase, double-phase, and double-phase to ground faults with high resistance under noisy condition. Furthermore, the method is applicable for networks with inverter interfaced DGs.

The modular multilevel converter-based high voltage direct current transmission (MMC-HVDC) technology has become an effective integrating method for large-capacity offshore wind farms. However, if AC side faults occur between the MMC and the wind farm, conventional current differential protection methods based on phasor measurements might not detect the large fault current at the wind farm and the MMC, resulting in poor protection performance. In the worst case, MMC blocking may occur during faults near the MMC station, causing relay refusal. The fault currents provided by both converters are analyzed in detail. Due to the fault-ride-through control objectives, it is proved that the singularity of fault current between wind farms and MMC is different. Therefore, a novel singular value decomposition (SVD) based pilot protection is proposed to solve this problem. A Hankel matrix is established for the short-circuit current at each end of the AC line. The Hankel matrix rapidly detects the singularity of the signal and its derivative, and the SVD method uses a short time window to extract the waveform features. This approach enables the detection of the fault features before MMC blocking in the worst-case fault scenario and prevents the incorrect fault identification caused by the minor amplitude of fault current provided by the converters. A detailed model of an offshore wind farm connected to the MMC-HVDC system is established in the real-time digital simulator (RTDS). A protection device compliant with industry standards is used to implement the SVD-based protection algorithm. Hardware-in-loop dynamic experimental tests are conducted to verify the performance of the proposed protection method. The experimental results demonstrate that the SVD-based protection method has excellent performance during various fault scenarios.

To adapt to the operation under asymmetric conditions, an increasing number of grid-following inverter-interfaced renewable energy sources (IIRESs) start to employ the decoupled sequence control (DSC). However, due to the variety and complexity of the positive and negative sequence components calculation (PNSCC) modes used for DSC, the fault response of IIRESs with DSC has rarely been studied using the analytical method. To this end, this article proposes a Laplace domain fault modeling method to investigate fault characteristics of IIRESs with DSC. The high-order and coupling features of commonly used PNSCC modes are analyzed, and then they are taken into account to establish a detailed fault model of IIRESs with DSC. To further apply the fault model to the practical fault analysis, different PNSCC modes are generalized to obtain a unified form, and thus a reduced-order fault model of IIRESs with DSC covering the complete fault phases can be yielded. Based on this model, contributing factors of the IIRES's fault response within different fault phases can be explored. Simulation and hardware-in-loop experiments indicate that this model can be applied to various fault scenarios with an error less than 7%, providing a theoretical foundation to support the protection scheme.

The accurate analytical fault analysis model of the emerging inverter-interfaced renewable energy sources (IIRESs) is an important basis for protection of power system with RESs. However, factors of dynamic characteristics of the control system (DCCS) such as the controller saturation and phase-locked loop (PLL) dynamics have rarely been simultaneously studied in the existing analytical models of IIRESs. As a result, the accurate analytical models can hardly be guaranteed. To address this issue, this paper proposes an analytical model for IIRESs taking DCCS into account to characterize the complex fault responses of IIRESs. Both the controller saturation and PLL dynamics are considered in the transient and steady-state phases to investigate the fault current characteristics. On this basis, the analytical fault current formulations under the influences of DCCS are yielded using the piecewise linearization method. Field short-circuit and simulation tests indicate that the proposed model is applicable to various fault conditions and its calculation accuracy can be improved by at most 55% in comparison with the existing IIRESs’ analytical models.