Gemma Kelly, Alan Thomson Evaluating the use of geomagnetic indices for identifying potential damage to power grids Gemma Kelly, Alan Thomson

GICs Geomagnetically induced currents (GICs) are the main space weather risk to power grids We would like a way to categorise GICs, particularly for the UK, to better identify times when the system is at risk. Ideally we could then provide a forecast with a focus on GICs We generally assume GIC is most closely related to dB/dt – how true is this?

GIC data Not particularly extensive – relies on a close relationship with Scottish power – they don’t save the data so we have to remember to ask for it in a timely manner Max measured ~40A

dH/dt and GIC So first assumption look like it holds, GIC follows the dB/dt pretty well. Unfortunately…… March 2012 – Torness GIC data (red) against dH/dt at Eskdalemuir (blue)

dH/dt and known GIC impacts Storms in red are identified in Erinmez – or in the case of 2003, engineers at the time reported some effect (noise, heating etc) Erinmez et al., J. Atmos. Sol-Terr. Phys. 2002

Problem Our earlier GIC data need reprocessing dB/dt at individual stations is very hard to predict (at the moment) We would like to develop an index to identify when there is a risk of large GIC We start by investigating what existing indices GIC (dB/dt) in the UK relates to.

NOAA G scales and Kp Widely used and recognised We use them to forecast and to categorise past activity Based on Kp, the 3-hourly geomagnetic index Commonly used – supply forecasts and post-event analysis in terms of Kp – how useful is that for GIC? NG tell us they aren’t concerned until well into G5 – how good an assumption is that? Is that sensible?

dH/dt and Kp So Kp 8 predicts events in the red zone – but also a lot of times when dH/dt didn’t get larger than 200 in that period At the moment with our current data we don’t know whether any of the other Kp 8 or 9 events caused lesser effects in the power grid (maybe later on or degradation rather than instant effects)

Max dH/dt at 24 observatories dH/dt and Kp 24 observatories with >16 years data Largest dH/dt at Kp = 9o for only 8 of 24 observatories. dH/dt > 1000nT/min was measured at 4 observatories: BRW, ABK, ESK and FCC (all > ±57° geomag latitude) Max dH/dt at 24 observatories Selection of global observatories with at least 16 years of data Important to note that the largest variations in X and Y do not always occur on the same dates. Unsurprisingly a mid-latitude measure of activity not great for near poles

dH/dt and K Regional K better – in that it at least identifies all events as K=9….but still a large range of dH/dt at K=9

dH/dt and AE AU AE AO AL 1 minute AE against 1minute dB/dt AL is westward electrojet AU eastward

dH/dt and AL Interesting that we only see dH/dt > 600 when AL is small – is this a sign that the auroral oval has moved too far south of the AE stations?

dH/dt HSD Hourly standard deviation – rolling for last hour

So how does this help? We can try using some thresholds to see if that helps narrow down times of increased GIC, for example: Kp > 8 AL > -1000 HSD > 100

Selected data We identify all the storms with dH/dt > 600nT/min Fewer times identified where there is no large dB/dt at some point during the storm

Future work = GIC measuring location Reprocess the GIC data we hold and repeat and expand the process with that do the other indices add value to dB/dt? Build regression relationships between GIC and other variables Better proxy than ‘just’ dB/dt Forecasts and validation? Do something similar with NZ data? Comparative study, similar latitudes Investigate whether the dB/dt at Esk is best for UK GIC or whether some combination of data from UK observatories is better

Quiet High GIC risk Medium risk

Very simple approach => large number of false alarms All data Points Accuracy (fraction correct) = correct/total = (15772076 + 8)/15779517 = 0.9995 Predicted Observed No storm Storm 15772076 7433 storm 8 False alarm ratio = false alarms/(hits + false alarms) 7433/(7433 + 8) = 0.9989 Max per day Predicted Observed No storm Storm 10888 66 storm 4