Abstract:
Background High-altitude electromagnetic pulses and geomagnetic disturbances can induce extreme geomagnetic perturbations, generating geomagnetically induced currents (GIC) in power transmission systems. These currents drive transformers into deep magnetic saturation, threatening equipment safety and potentially triggering cascading grid failures. Effective GIC mitigation is thus critical for power system resilience.
Purpose To overcome the limitations of single-measure mitigation strategies, this study proposes a collaborative optimization framework integrating substation grounding resistance adjustments and neutral blocking device installations. The goal is to minimize total system GIC levels under safety, economic, and operational constraints, providing a practical decision-support tool for GIC risk management.
Methods A multi-parameter collaborative optimization model based on the Grey Wolf Optimizer (GWO) is established using the GIC-Benchmark standard test case, which is first converted into a full-node equivalent network to serve as the simulation environment. Three optimization scenarios are successively investigated: optimal allocation of substation grounding resistance values under safety limits, optimal placement of neutral blocking devices under economic budget constraints, and simultaneous optimization of both measures. The objective function is defined as the minimization of the total GIC magnitude across the system, with penalty terms incorporated to handle violations of the prescribed constraints.
Results The GWO-based model shows excellent convergence and stability. Under grounding resistance optimization, total GIC decreases by 56.7% and 74.6% under eastward and northward 1 V/km electric fields, respectively. For blocking device placement, reductions reach 71.1% and 77.1%. Collaborative optimization identifies prioritized installation sequences matching node sensitivity rankings and allocates resistance values among remaining nodes via a sensitivity-gradient principle. Diminishing marginal mitigation effects are observed near saturation thresholds.
Conclusions The proposed framework effectively addresses the grounding configuration optimization problem in GIC mitigation, enabling cost-effective, layered protection strategies that preferentially allocate resources to the most sensitive nodes while providing compensatory resistance adjustments for secondary sites, thereby significantly enhancing overall system resilience against GIC. The model offers theoretical foundations and engineering guidance for differentiated, precision-oriented GIC mitigation planning and is scalable to larger grids or varying geomagnetic conditions. Future work may incorporate dynamic topology changes and probabilistic geomagnetic scenarios to further refine the framework.
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