Dianli jianshe (Jun 2025)
Optimization of Remote Backup Protection Coordination Logic Based on Dynamic Identification of Faulty Components in Transmission Grids
Abstract
[Objective] The integration of a high proportion of renewable energy generation has reduced the amplitude of fault currents and changes in their directionality in power grids. Traditional backup protection that relies on offline settings struggles to adapt to the complex conditions of looped networks. Additionally， the low-inertia and low-voltage ride-through （LVRT） control of renewable energy sources exacerbates the changes in the characteristics of positive- and negative-sequence networks， making it difficult to identify faulty components and often resulting in protection mismatch or excessive delay. This study addresses the dynamic adaptability of backup protection in power grids with renewable energy， overcoming the bottlenecks of looped network deadlocks and rigid setting values. [Methods] A dual-criteria approach based on wide-area measurements is proposed. For asymmetrical faults， negative-sequence voltage/current ranking is used to identify fault-associated buses and branches， enabling rapid identification through a regional centralized architecture. For symmetrical faults， a single traveling wave monitoring device at the substation， combined with the global traveling wave arrival time difference and a double-ended ranging algorithm， is utilized to achieve microsecond-level fault location identification. The backup-protection logic is further optimized by dynamically setting only the remote backup protection associated with the fault line， adjusting the impedance circle range， and fixing the action delay to two time intervals， thereby avoiding the cumulative delays of traditional step-by-step coordination. [Results] The PSCAD simulation results indicate that the accuracy rate of the negative-sequence criterion for asymmetrical faults was 100%， with reliable identification possible with a transition resistance of 30 Ω. For symmetrical faults， the traveling wave ranging error is less than 100 m， and the location time is reduced by 90% compared with traditional methods. After optimization， the remote backup-action delay was reduced from 4-7 intervals to 2 intervals， while the setting coverage increased by 18.4%， effectively avoiding misoperations owing to load intrusion. [Conclusions] The proposed method achieved rapid and dynamic identification of multiple types of fault components in renewable energy grids through the complementary use of negative sequence ranking and traveling wave time-difference criteria， overcoming the limitations of looped network deadlocks. The dynamic setting strategy significantly shortens the action delay of remote backup protection， thus considerably enhancing sensitivity and speed. Moreover， this strategy does not rely on high-sampling equipment or complex communication architectures， thus providing an efficient and reliable engineering solution for online backup protection in power grids with a high proportion of renewable energy.
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