Large-scale renewables are weak-feed and their output current is controlled. That doesn't play nice with traditional pilot protection, which only looks at power-frequency components. When a fault happens, the current from these sources has a "low fundamental, high transient" signature—so the protection often ends up tripping when it shouldn't. This paper proposes a novel adaptive protection scheme utilizing a hierarchical weighted Euclidean distance. It constructs a duallayer feature vector from low-frequency (50Hz) and high-frequency (1kHz) current components measured at both line ends. A composite fault indicator is calculated by adaptively weighting the Euclidean distances within each layer based on real-time signal-to-noise ratio and line attenuation. This approach leverages complementary fault information across frequency bands. Simulation results in PSCAD/EMTDC demonstrate that the proposed method significantly outperforms traditional differential protection in sensitivity and reliability, effectively mitigating maloperation risks under highimpedance faults and weak-infeed conditions, offering a viable software upgrade path for existing infrastructures.
Ying Zou, Luyun Zhang, Chenyang Wang et al.· International Conference on...· 0 citations
With the large-scale integration of inverter-based resources (IBRs), the types and operating characteristics of power sources on both sides of transmission lines have changed significantly, rendering traditional fault-type selection methods inadequate. To address this, this paper proposes a neural network-based multi-parameter fault type identification strategy. The method constructs a 16-dimensional feature vector from local three-phase voltage/current magnitudes, phase angles, and zero-sequence components, and designs a lightweight fully-connected neural network with two hidden layers to learn the complex nonlinear mapping between these comprehensive inputs and fault types. Extensive training and testing data are generated using the PSCAD/EMTDC simulation platform, covering multiple scenarios including double-ended synchronous generator (SG), single-ended IBR, and double-ended IBR. The results show that the proposed strategy achieves identification accuracy exceeding 95% across all scenarios, significantly outperforming traditional current-based methods, especially in IBR-dominated cases. Moreover, the method exhibits strong robustness against variations in fault location, transition resistance, and source type, providing a reliable and adaptive protection solution for evolving hybrid power grids.
Luyun Zhang, Rui Xiong, Rui Hou et al.· International Conference on...· 0 citations