Utility Week

38 | JANUARY 2022 | UTILITY WEEK Analysis Ready to face the weather In the wake of storms Arwen and Barra, we take a sector-wide snapshot of innovation in climate adaptation, including a recent collaboration between National Grid and the Met Office. A t the back end of 2021 the UK was hit by two destructive storms. The first, Storm Arwen, battered parts of the country with winds reaching 98mph and at one point le• 800,000 homes and businesses without electricity. Storm Barra followed hot on its heels – dubbed a "weather bomb", it too le• a trail of destruction, first across Ire- land and then the UK. With the World Meteorological Organi- sation's professor Petteri Taalas forecast- ing that "extreme events are the new norm" in the body's 2021 The State of the Climate report, it seems clear that utilities will inevi- tably have to make climate adaptation part of their business as usual when managing assets and key infrastructure. Factoring in climate data In late September National Grid announced that it had partnered with the Met Office to explore the value of using higher specifica- tion weather forecasts to boost capacity on overhead transmission power lines – also allowing more renewable energy to flow. According to the company, the trans- mission system is limited by the individual power rating of its circuits. Additionally, conservative standard weather condition assumptions have seen assets operate at rat- ings lower than their actual capacity. Consequently, the £545,000 project – funded through Ofgem's Network Innova- tion Allowance mechanism – has assessed the integration of an advanced, cloud-based, weather forecasting service into National Grid's Dynamic Line Rating (DLR) calcula- tion method, which gauges both physical and environmental factors such as wind speed, direction, ambient temperature and solar radiation. According to Ian Pearman, senior sci- entist for the Met Office, DLR is principally concerned with how efficiently the heat gen- erated by the current in the conductor might be removed by the atmosphere. If environmental conditions are favour- able enough to cool the conductors suffi- ciently, more power can be pushed through the lines, relieving some of the network constraints and helping to meet the coun- try's energy needs. Therefore, he explains, lower ambient temperatures will accelerate the exchange of heat between the conduc- tor and the surrounding atmosphere – "so the colder the better", he says. "Solar radia- tion will heat the line and act to counteract atmospheric cooling, so an absence of solar radiation due to an overcast of cloud or night time is best." He adds that a circuit considered for DLR will be many kilometres in length, meaning that how conditions vary along the route also needs to be considered and any up rating will depend on the point on that circuit with the least favourable local conditions. "Since wind flow is most important for cooling it is particularly important to identify points where local shelter might inhibit ven- tilation and heat removal," he says. Higher specification weather forecasts? According Pearman, "higher specification" weather forecasts mean using the full range of high resolution computer weather forecast modelling operationally available. "In this project, we looked to use the Met Office UK 2km model together with the UK configura- tion of the Met Office Global and Regional Ensemble Prediction System (MOGREPS)," he tells Utility Week Innovate. "Ensemble forecasts quantify uncer- tainties in weather prediction and estimate risks of particular weather events to enable the user to assess the risks more accurately. Instead of running just a single forecast, the computer model is run a number of times from slightly different starting conditions." In the UK, Pearman explains that the Met Office runs four simulations using the latest weather observations every hour up to five days ahead. "We can utilise all of these simulations of the atmosphere to improve the forecast by understanding the uncertainty across all those different simulations – what aspects of the coming weather are we confident in; where and when are there uncertainties and what scenarios are plausible," he adds. "Connecting that directly into a weather- dependent application such as DLR allows us to directly translate an expression of the spread of likely weather into an expression of the plausible range of outcomes for DLR and from that determine the optimal DLR strategy." Combining weather forecasting data Having established the initial feasibility of integrating this weather forecasting tech- nology into National Grid's rating calcula-

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