Efficient probabilistic geomagnetically induced current (GIC) analysis in power grids provides tools for assessing and mitigating small-probability tail risks of geomagnetic disturbances, especially in early warning and real-time scenarios. This letter employs the reduced nodal admittance matrix (RNAM) to speed up GIC calculation based on Kron reduction. Moreover, the proposed RNAM method is used to achieve a more efficient analysis of probabilistic GICs, which considers the uncertainty of the substation grounding resistances. The novel method is compared with the classical algorithms including the nodal admittance matrix method, the Lehtinen-Pirjola method, and the bus admittance matrix method, and its efficiency improvement is illustrated with several power grid test cases.

Reduced Nodal Admittance Matrix Method for Probabilistic GIC Analysis in Power Grids / Liu, Minzhou; Xie, Yan-zhao; Yang, Yi-fan; Trinchero, Riccardo; Stievano, Igor S.. - In: IEEE TRANSACTIONS ON POWER SYSTEMS. - ISSN 0885-8950. - STAMPA. - 38:5(2023), pp. 1-4. [10.1109/TPWRS.2023.3280392]

Reduced Nodal Admittance Matrix Method for Probabilistic GIC Analysis in Power Grids

Minzhou Liu;Riccardo Trinchero;Igor S. Stievano
2023

Abstract

Efficient probabilistic geomagnetically induced current (GIC) analysis in power grids provides tools for assessing and mitigating small-probability tail risks of geomagnetic disturbances, especially in early warning and real-time scenarios. This letter employs the reduced nodal admittance matrix (RNAM) to speed up GIC calculation based on Kron reduction. Moreover, the proposed RNAM method is used to achieve a more efficient analysis of probabilistic GICs, which considers the uncertainty of the substation grounding resistances. The novel method is compared with the classical algorithms including the nodal admittance matrix method, the Lehtinen-Pirjola method, and the bus admittance matrix method, and its efficiency improvement is illustrated with several power grid test cases.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2978852