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Large geomagnetic storms are a space weather hazard to power transmission networks due to the effects of Geomagnetically Induced Currents (GICs). GIC can negatively impact power transmission systems through the generation of even-order current and voltage harmonics due to half-cycle transformer saturation. This study investigates a decade of even-order voltage total harmonic distortion (hereon referred to as Even-Order Total Harmonic Distortion (ETHD)) observations provided by Transpower New Zealand Ltd., the national system operator. We make use of ETHD measurements at 139 locations throughout New Zealand, monitored at 377 separate circuit breakers, focusing on 10 large geomagnetic disturbances during the period 2013–2023. Analysis identified 5 key substations, which appeared to act as sources of ETHD. The majority of these substations include single phase transformer banks, and evidence of significant GIC magnitudes. The ETHD from the source substations was found to propagate into the surrounding network, with the percentage distortion typically decaying away over distances of 150–200 km locally, that is, at a rate of −0.0043 %km−1. During the study period some significant changes occurred in the power network, that is, removal of the Halfway Bush (HWB) single phase bank transformer T4 in November 2017, and decommissioning of the New Plymouth substation in December 2019. Decommissioning of these two assets resulted in less ETHD occurring in the surrounding regions during subsequent geomagnetic storms. However, ETHD still increased at HWB with increasing levels of GIC, indicating that three phase transformer units were still susceptible to saturation, albeit with about 1/3 of the ETHD percentage exhibited by single phase transformers.

Reducing the impact of Geomagnetically induced currents (GICs) on electrical power networks is an essential step to protect network assets and maintain reliable power transmission during and after storm events. In this study, multiple mitigation strategies are tested during worst-case extreme storm scenarios in order to investigate their effectiveness for the New Zealand transmission network. By working directly with our industry partners, Transpower New Zealand Ltd, a mitigation strategy in the form of targeted line disconnections has been developed. This mitigation strategy proved more effective than previous strategies at reducing GIC magnitudes and durations at transformers at most risk to GIC while still maintaining the continuous supply of power throughout New Zealand. Under this mitigation plan, the average 60-min mean GIC decreased for 27 of the top 30 at-risk transformers, and the total network GIC was reduced by 16%. This updated mitigation has been adopted as an operational procedure in the New Zealand national control room to manage GIC. In addition, simulations show that the installation of 14 capacitor blocking devices at specific transformers reduces the total GIC sum in the network by an additional 16%. As a result of this study Transpower is considering further mitigation in the form of capacitor blockers. We strongly recommend collaborating with the relevant power network providers to develop effective mitigation strategies that reduce GIC and have a minimal impact on power distribution.

PURPOSE: Exercise has been underutilized in people with advanced or incurable cancer despite the potential to improve physical function and reduce psychosocial morbidity, especially for people with bone metastases because of concerns over skeletal complications. The International Bone Metastases Exercise Working Group (IBMEWG) was formed to develop best practice recommendations for exercise programming for people with bone metastases on the basis of published research, clinical experience, and expert opinion. METHODS: The IBMEWG undertook sequential steps to inform the recommendations: (1) modified Delphi survey, (2) systematic review, (3) cross-sectional survey to physicians and nurse practitioners, (4) in-person meeting of IBMEWG to review evidence from steps 1-3 to develop draft recommendations, and (5) stakeholder engagement. RESULTS: Recommendations emerged from the contributing evidence and IBMEWG discussion for pre-exercise screening, exercise testing, exercise prescription, and monitoring of exercise response. Identification of individuals who are potentially at higher risk of exercise-related skeletal complication is a complex interplay of these factors: (1) lesion-related, (2) cancer and cancer treatment-related, and (3) the person-related. Exercise assessment and prescription requires consideration of the location and presentation of bone lesion(s) and should be delivered by qualified exercise professionals with oncology education and exercise prescription experience. Emphasis on postural alignment, controlled movement, and proper technique is essential. CONCLUSION: Ultimately, the perceived risk of skeletal complications should be weighed against potential health benefits on the basis of consultation between the person, health care team, and exercise professionals. These recommendations provide an initial framework to improve the integration of exercise programming into clinical care for people with bone metastases.

Geomagnetically induced currents (GICs) produced during geomagnetic disturbances pose a risk to the safe operation of electrical power networks. One route to determine the hazard of large and extreme geomagnetic disturbances to national electrical networks is a validated model to predict GIC across the entire network. In this study we improve upon an earlier model for New Zealand, expanding the approach to cover transformers nationwide by making use of multiple storms to develop national scaling factors. We exploit GIC observations which have been made and archived by Transpower New Zealand Ltd, the national grid operator. For some transformers the GIC observations span nearly 2 decades, while for others only a few years. GICs can vary wildly between transformers, particularly due to differences in the electrical network characteristics , transformer properties, and ground conductivity. Modeling these individual transformers is required if an accurate representation of the GIC distribution throughout the network is to be produced. Here we model the GIC during 25 disturbed periods, ranging from large geomagnetic storms to weakly active periods. We adopt the approach of scaling model output using observed GIC power spectra, finding that it improves the correlations between the maximum model and observed GIC by between 10-40% depending on the transformer. The modeled GIC at the 73 transformers which have measured GIC are analyzed to create local and national scaling curves. These are used to allow modeling for transformers without in-situ GIC. We present approaches to utilise this technique for future storms, including non-monitored transformers.

Variability of the geomagnetic field induces anomalous Geomagnetically Induced Currents (GICs) in grounded conducting infrastructure. GICs represent a serious space weather hazard, but are not often measured directly and the rate of change of the magnetic field is often used as a proxy. We assess the correlation between the rate of change of the magnetic field and GICs during Sudden Commencements (SCs), at a location in New Zealand. We observe excellent correlations (r2 ∼ 0.9) between the maximum one-minute rate of change of the field and maximum GIC. Nonetheless, though SCs represent a relatively simple geomagnetic signature, we find that the correspondence systematically depends on several factors. If the SC occurs when New Zealand is on the dayside of the Earth then the magnetic changes are linked to 30% greater GICs than if New Zealand is on the nightside. We investigate, finding that the orientation of the strongest magnetic deflection is important: changes predominantly in the east-west direction drive 36% stronger GICs. Dayside SCs are also associated with faster maximum rates of change of the field at 1 s resolution. Therefore, while the maximum rates of change of the magnetic field and GICs are well correlated, the orientation and sub-one-minute resolution details of the field change are important to consider when estimating the associated currents. Finally, if the SC is later followed by a geomagnetic storm then a given rate of change of the magnetic field is associated with 22% larger GICs, compared to if the SC is isolated.

Geomagnetically induced currents (GICs) are induced in electrical power transmission networks during geomagnetic disturbances. Understanding the magnitude and duration of the GIC expected during worst-case extreme storm scenarios is vital to estimate potential damages and disruptions to power networks. In this study we utilize the magnetic field waveforms measured during three large geomagnetic storms and scale them to expected worst case extreme storm magnitudes. Multiple methods are used to simulate the varying magnitude of the magnetic field across the different latitudes of New Zealand. Modeled GIC is produced for nine extreme storm scenarios, each covering 1-1.5 days in duration. Our industry partners, Transpower New Zealand Ltd provided GIC magnitude and duration levels which represent a risk to their transformers. Using these thresholds various extreme storm scenarios predict between 44 and 115 New Zealand transformers (13-35%) are at risk of damaging levels of GIC. The transformers at risk are largely independent of the extreme storm time-variations, but depend more on the latitude variation scenario. We show that these at-risk transformers are not localized to any specific region of New Zealand but extend across all regions and include most of the major population centers. A peak mean absolute GIC over a 60-minute window of 920-2210 A and an instantaneous one-minute time resolution maximum GIC of 1590-4920 A occurs for a worst-case extreme storm scenario. We believe this is one of the first studies to combine a reasonable worst-case extreme geomagnetic storm with validated GIC modeling and industry-provided GIC risk thresholds.

Geomagnetically induced currents (GICs) during a space weather event have previously caused transformer damage in New Zealand. During the 2015 St. Patrick's Day Storm, Transpower NZ Ltd has reliable GIC measurements at 23 different transformers across New Zealand's South Island. These observed GICs show large variability, spatially and within a substation. We compare these GICs with those calculated from a modeled geolectric field using a network model of the transmission network with industry‐provided line, earthing, and transformer resistances. We calculate the modeled geoelectric field from the spectra of magnetic field variations interpolated from measurements during this storm and ground conductance using a thin‐sheet model. Modeled and observed GIC spectra are similar, and coherence exceeds the 95% confidence threshold, for most valid frequencies at 18 of the 23 transformers. Sensitivity analysis shows that modeled GICs are most sensitive to variation in magnetic field input, followed by the variation in land conductivity. The assumption that transmission lines follow straight lines or getting the network resistances exactly right is less significant. Comparing modeled and measured GIC time series highlights that this modeling approach is useful for reconstructing the timing, duration, and relative magnitude of GIC peaks during sudden commencement and substorms. However, the model significantly underestimates the magnitude of these peaks, even for a transformer with good spectral match. This is because of the limited range of frequencies for which the thin‐sheet model is valid and severely limits the usefulness of this modeling approach for accurate prediction of peak GICs.

During space weather events, geomagnetically induced currents (GICs) can be induced in high-voltage transmission networks, damaging individual transformers within substations. A common approach to modeling a transmission network has been to assume that every substation can be represented by a single resistance to Earth. We have extended that model by building a transformer-level network representation of New Zealand’s South Island transmission network. We represent every transformer winding at each earthed substation in the network by its known direct current resistance. Using this network representation significantly changes the GIC hazard assessment, compared to assessments based on the earlier assumption. Further, we have calculated the GIC flowing through a single phase of every individual transformer winding in the network. These transformer-level GIC calculations show variation in GICs between transformers within a substation due to transformer characteristics and connections. The transformer-level GIC calculations alter the hazard assessment by up to an order of magnitude in some places. In most cases the calculated GIC variations match measured variations in GIC flowing through the same transformers. This comparison with an extensive set of observations demonstrates the importance of transformer-level GIC calculations in models used for hazard assessment.