Lessons from Texas for the UK’s interval data journey

Krishnan Kasiviswanathan, chief operating officer at Innowatts, explains why suppliers need the capability to leverage half-hourly smart meter data and discusses the lessons that can be taken from US states such as California and Texas.

In April, Ofgem set out its timetable to implement market-wide half-hourly settlements with an expectation for electricity suppliers to transition to meet this requirement by October 2025 – a move that Ofgem predicts could create net benefits for consumers in Great Britain of up to £4.5 billion to 2045.

In parallel, as the smart meter rollout continues at pace, billions of meter level interval data elements start to become available on a daily basis. Whilst interval data is not new, most energy suppliers are not able to leverage the data with the intent and purpose to optimise operational value across their businesses. When placed in the right hands, and with the right tools, this data can be leveraged to provide better engagement with customers and tailor products and services to each consumers’ specific needs, whilst simultaneously encouraging market flexibility in support of the energy transition to a net zero carbon economy.

However, this is not a mission for the faint hearted. It takes a substantial commitment of time and resources to develop the systems infrastructure and intelligence necessary to analyse and act upon half-hourly meter data in a meaningful financial and operational way. That said, there are several possible quick wins that energy suppliers can gain by leveraging insights and learnings from implementation of interval data in the US. These insights could be invaluable for accelerating the United Kingdom and Ireland’s journey. Notwithstanding the remaining European continent.

Building the infrastructure

While every supplier now has interval data, most do not have the data infrastructure or available resources to gain in-depth insights and intelligence to make informed and reliable actions from it. Determining what data and insights to collect is a complex but necessary first step.  A robust and scalable infrastructure with the intent to drive toward the outcomes intended also needs to be put in place in order to import data; run diagnostics; complete and validate curation of the data; then identify and fill any inherit gaps to subsequently reconcile the data elements to understand whether the interval data matches at the system level.

Once customer profiles are analysed on a half-hourly basis, suppliers can significantly improve their forecasting, pricing and risk management operational tactics, identifying ways to improve customer engagement and tailoring products suitable for each customer and market segment. Suppliers who are slower to react and wait until 2025 to implement the aforementioned capabilities and infrastructure, place their competitive advantage and, their relationships with the customer at risk.

Rebuilding profiles and forecasts

Although the industry has reasonable insight into how seasonal and extreme weather impacts consumer behaviour, as supply and demand become more unpredictable, it pays to have a more detailed understanding.  Electricity prices are one of the most financially volatile commodities on the planet. The recent outages and price spikes in Texas, and the weather events in the Pacific Northwest, illuminate the importance of having visibility of and the ability to analyse interval data in real time.

With the capability improve consumer profiling and demand forecasts tools such as the Innowatts platform help energy suppliers become more resilient to extreme weather and other related events that impact their customers and the corelated positions and pricing they take in the markets they serve.

During the extreme weather events in Texas which caused rolling blackouts and power shortages, Innowatts applied its AI-driven algorithms to meter data, in near real-time, to identify and illuminate customers that had been wrongly categorised as gas heating only, when electric heating was their principle source. Innowatts was also able to predict and highlight that customers in southern Texas would create a surge in demand as the temperature dropped and those customers deployed temporary heaters to keep warm. The energy suppliers were able to then reprofile these customers to create a much more accurate forecast and procurement strategy for the day ahead.

A more accurate day ahead forecast vastly improves the energy supplier’s ability to hedge their market positions thereby reducing pricing exposure on the spot market – where wholesale electricity prices soared to $9,500 per MWh.  Several suppliers with less accurate forecasts found themselves at the mercy of the spot market. Eventually unable to make the necessary payments to participate, they were barred – which in turn left thousands of Texans without power.

Ultimately, the catastrophe and the sky-high prices led several suppliers to file for bankruptcy. However, this is a situation that could have been avoided if those suppliers had collated and analysed previous years’ interval data to produce consumer insights to improve demand forecasts. While the UK and Ireland’s weather may not typically be quite so extreme, the volatility and unpredictability of the grid can be. More complex forecasting models will help energy suppliers better understand usage and plan for the future today.

The transition to electric heating and the impact of renewable energy

It’s not only weather events – decarbonisation and policy changes are also impacting consumer demand profiles. For example, the proliferation of behind the meter distributed energy. While a welcome trend, it still took energy suppliers in California several years to collect enough seasonal data to fully understand the impact of solar PV on a household’s electricity supply, observe how dramatically this could change from one interval to the next and establish how to accommodate it across its portfolio. These factors remain a primary problem that has yet to be fully understood or solved.

This is particularly important in the context of the UK’s forthcoming deployment of electric heating – and the 600,000 heat pumps installs per annum we can expect by 2028 – from which new patterns of consumer behaviour will emerge. Interval data will be crucial for tracking and forecasting this trend, hence enabling suppliers to understand how it is changing historical demand profiles and supporting them to offer alternative tariffs and improved hedging decisions.

Thanks to the lessons we can learn from states such as California and Texas and the Pacific Northwest, the UK and Ireland do not need to begin from a standing start. Innowatts already has the capability to disaggregate data to improve forecasting and create personalised engagement for customers that have heat pumps. However, for maximum impact, multiple seasons’ worth of data will be helpful in establishing seasonal trends to help forecast for this significant system change – therefore, it is advisable to start collecting and analysing interval data right away.

More accurate, more competitive

Pricing customers more accurately is one benefit that makes sense for every energy supplier to take advantage of as soon as possible. Understandably, when high and low variability consumption customers are combined, there is an element of socialisation that ‘hides’ the true profitability of a customer.

For many suppliers, this lack of differentiation means an inability to sort the wheat from the chaff when it comes to profitable and unprofitable customers. Interval data enables suppliers to price each customer based on their actual consumption patterns and create differentiation through more accurate subgroupings. Successful energy suppliers that invest in this capability will retain and eventually attract more profitable customers, leaving less data-driven suppliers with the unprofitable ones.

Finally, for those suppliers that are slow to move, they may begin to see some of their customer relationships disintermediated by new smart-tech entrants, particularly in the electric vehicle charging space. Ohme is a good example of a company that is using interval data to its advantage, offering to automatically optimise car charging times to take advantage of low and negative electricity prices. Its customers no longer need that relationship with the energy supplier to gain valuable insights into their electricity consumption. This will likely be a creeping threat that will only become more prolific as other manufacturers, such as for solar PV, offer to do the same.

We believe it is time for the UK and Ireland to unlock the multiple benefits of interval data. Gaining insights from interval data represents a hugely exciting opportunity for the UK and Ireland, not only to better engage customers, but to support the electrification and decarbonisation efforts for each country. Suppliers that are proactive and get themselves in position today stand to create stronger relationships with their customers that ultimately see them become more competitive while providing improved customer service and satisfaction.