J. Hübert, C. D. Beggan, G. S. Richardson, N. Gomez-Perez, A. Collins, A. W. P. Thomson
{"title":"Validating a UK Geomagnetically Induced Current Model Using Differential Magnetometer Measurements","authors":"J. Hübert, C. D. Beggan, G. S. Richardson, N. Gomez-Perez, A. Collins, A. W. P. Thomson","doi":"10.1029/2023sw003769","DOIUrl":null,"url":null,"abstract":"Extreme space weather can damage ground-based infrastructure such as power lines, railways and gas pipelines through geomagnetically induced currents (GICs). Modeling GICs requires knowledge about the source magnetic field and the electrical conductivity structure of the Earth to calculate ground electric fields during enhanced geomagnetic activity. The electric field, in combination with detailed information about the power grid topology, enable the modeling of GICs in high-voltage (HV) power lines. Directly monitoring GICs in substations is possible with a Hall probe, but scarcely realized in the UK. Therefore we deployed the differential magnetometer method (DMM) to measure GICs at 12 sites in the UK power grid. The DMM includes the installation of two fluxgate magnetometers, one directly under a power line affected by GICs, and one as a remote site. The difference in recordings of the magnetic field at each instrument yields an estimate of the GICs in the respective power line segment via the Biot-Savart law. We collected data across the UK in 2018–2022, monitoring HV line segments where previous research indicated high GIC risk. We recorded magnetometer data during several smaller storms that allow detailed analysis of our GIC model. For the ground electric field computations we used recent magnetotelluric (MT) measurements recorded close to the DMM sites. Our results show that there is strong agreement in both amplitude and signal shape between measured and modeled line and substation GICs when using our HV model and the realistic electric field estimates derived from MT data.","PeriodicalId":22181,"journal":{"name":"Space Weather","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Space Weather","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1029/2023sw003769","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Extreme space weather can damage ground-based infrastructure such as power lines, railways and gas pipelines through geomagnetically induced currents (GICs). Modeling GICs requires knowledge about the source magnetic field and the electrical conductivity structure of the Earth to calculate ground electric fields during enhanced geomagnetic activity. The electric field, in combination with detailed information about the power grid topology, enable the modeling of GICs in high-voltage (HV) power lines. Directly monitoring GICs in substations is possible with a Hall probe, but scarcely realized in the UK. Therefore we deployed the differential magnetometer method (DMM) to measure GICs at 12 sites in the UK power grid. The DMM includes the installation of two fluxgate magnetometers, one directly under a power line affected by GICs, and one as a remote site. The difference in recordings of the magnetic field at each instrument yields an estimate of the GICs in the respective power line segment via the Biot-Savart law. We collected data across the UK in 2018–2022, monitoring HV line segments where previous research indicated high GIC risk. We recorded magnetometer data during several smaller storms that allow detailed analysis of our GIC model. For the ground electric field computations we used recent magnetotelluric (MT) measurements recorded close to the DMM sites. Our results show that there is strong agreement in both amplitude and signal shape between measured and modeled line and substation GICs when using our HV model and the realistic electric field estimates derived from MT data.