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Using the fundamentals of open, shared data to improve the accuracy of predictions will be central to effectively managing power networks as we rapidly adapt to and enable a net zero world.

Data-driven predictions, artificial intelligence, data science – the value and power of data is increasingly apparent and the positive impact of opening up data in other sectors, including transport, is now challenging “business as usual” in the energy sector.

With growing concerns over climate breakdown and the enormous complexity of data-driven climate modelling that goes with it, the value we place on big data is only set to become more noticeable. This is perhaps most pronounced when planning the future of our energy networks. The effective development of power networks is reliant on collaboration between stakeholders. To plan, we must agree on what the most likely future scenarios are, based on all the best data, plans and information available. Without comprehensive data, the agreed consensus could be wrong, resulting in misplaced resources – or worse, a network struggling to manage demand.

As an industry we’ve become exceptionally good at managing fluctuating energy demand and matching supply to it. Access to stakeholder information flows has been central to our success. However, there are new challenges on the horizon. Transport, heat, industry – these are all sectors rapidly turning to electrification to decarbonise, ahead of the UK’s net zero 2050 commitment. For example, according to National Grid’s Future Energy Scenarios (FES), the number of electric vehicles (EVs) in the UK could reach 36 million by 2040 and contribute an additional 6.5GW in increased peak demand, posing a huge challenge for network operators. To prepare, we must try to find out which sectors are likely to electrify first, how fast, and understand the areas of the network in need of additional capacity. That means to prepare the network today, we must predict how many people will be driving an EV in ten years’ time, where they will be driving, and what type of EV they will buy. We believe that for energy to work in that world, we need to stop thinking in terms of power and move to a smarter, more flexible world in which we manage energy across the system, “match-making” between supply and demand while optimising for cost and minimising carbon.

Data and information have proved valuable assets for energy networks, helping us make more informed predictions. In fact, we already have a very good idea of what kind of network constraints to expect over the next 30 years. However, the stakes are high – if consensus with our stakeholders on the most likely future scenarios is built on an incomplete picture, our assumptions could be wrong, and our network planning won’t be as reliable as we hope. That’s why we need to overcome a ­persistent problem in the industry – data siloes.

We’re seeing the rapid development of charging infrastructure by local authorities, housebuilders, and EV charging companies alike. There are already more than 3,000 charging points installed in our region alone – undoubtedly a great success story for the decarbonisation of transport. Nevertheless, there is a risk that future local strategies are designed independently, built on individual data points and siloed from each other. The result? These chargers could be planned without consulting the network operator, meaning that when a connection request is made, deployment could be delayed. The value of stakeholders sharing plans, information and data early is that we, as an infrastructure provider, can plan ahead, and enable the sector to move at pace.

Energy networks, local authorities, EV charging companies, home builders, and anyone else planning activity on the electricity network must work together to share activity, plans and data to actively break down these data siloes. Using the fundamentals of open, shared data to improve the accuracy of predictions will be central to effectively managing power networks as we rapidly adapt to and enable a net zero world. Further, by centralising this data and making it truly accessible to all via easy-to-use online tools and combining it with multiple scenarios of varying decarbonisation rates – for example National Grid’s FES – we can confidently prepare our network for the approaching wave of multi-industry electrification, maximising resources and protecting customers’ energy bills.

Demonstrating how this type of open-access platform could work, Northern Powergrid has led the way by mapping and making publicly available a swathe of raw data as part of its 2019 Distribution Future Energy Scenarios (DFES) project. Cross-referenced against National Grid’s FES and presented in easy-to-understand and visually engaging interactive time-lapse maps, the data is truly accessible to all, clearly displaying predictions on a number of parameters – including EVs, heat pumps and domestic solar PV – between today and 2050.

We’re now calling for all local authorities, academics and renewable energy project leaders to review this data and share any projects that will impact the underlying assumptions. By doing this, we will demonstrate how cross-industry collaboration can help ensure efficient network and system planning, as the region’s stakeholders mobilise to tackle the challenge of decarbonisation.