Graham Paul, service delivery director at TEAM Energy explores the key role of data in net zero, the complexity and necessity for energy benchmarking in buildings, and the emerging technologies that can support energy managers in their net zero goals.
The built environment makes up a substantial share of the UK’s total greenhouse gas (GHG) emissions and electricity use. Including direct and indirect emissions from sourced energy, buildings account for 23% of total emissions; alone, they are responsible for 59% of UK electricity consumption.
At the national level, policy frameworks are being implemented to reduce these figures to achieve net zero, including requirements to improve energy efficiency in buildings while electrifying processes that can be subsequently powered by renewables. However, at a company level, many organisations struggle with the demand of such changes, whether they’re voluntary or required.
Like any significant undertaking, net zero requires both a clear understanding of a business’s current situation, and the steps and tools needed to reach its goal. Simply balancing the emissions produced by your estate with purchased carbon credits to become ‘carbon neutral’ isn’t enough. Net zero requires organisations to do much more than this, and it is in this context that data emerges as key – both in the insights it provides for buildings, and the cutting-edge tools it now enables.
Data driven decision making and energy benchmarking
For a long time, energy management has relied on estimations, historical averages, and in some cases, basic spreadsheets. And while well-intentioned, such an approach wouldn’t be enough to help an organisation reach net zero. For example, to achieve the SBTi (Science Based Targets initiative) Net-Zero Standard, organisations must achieve at least a 90% emissions reduction across their value chain, and only then offset what remains.
Few organisations could meet this demand without precise, granular data that’s collected on a regular basis. Those with varied building stock of any complexity have little to no chance. To make real progress, energy managers need comprehensive data. They need to be able to focus on what they can control, and work systematically to address it – starting with a full understanding of their building stock.
When assessing their building stock’s energy consumption, energy managers must compare consumption levels to ‘benchmarks’ that can meaningfully guide their actions. This process of benchmarking is key to achieving net zero emissions, allowing organisations to highlight buildings that are consuming more energy (and producing more emissions) than they should be, and targeting them with energy saving measures. By doing so, organisations can start to reduce their emissions through data driven decision making.
While some data will be useful from the outset, much will need to be ‘normalised’ to make it meaningful; a complex task given the varied nature of most organisations’ building stock. For example, an old but sprawling hospital complex with round-the-clock critical operations has vastly different energy demands to a newly built, small community health centre or a university research laboratory. To make comparisons that can meaningfully guide their actions, energy managers need sophisticated methodologies to make their data useful. It is little surprise, therefore, that many energy managers turn to energy and net zero consultants for support to process this mission-critical data.
New data driven technologies
It’s sometimes said that in business, we must continually adapt to changes of our own making. Net zero and energy management is no exception to this rule. Businesses commit to making meaningful progress on net zero, then suddenly find they need this vast amount of insight about their building stock. Then, when swimming in new data, they realise their need for normalisation and analysis to make benchmarking useful. This isn’t to say they’re making a rod for their own backs, but every new ambitious target brings with it new challenges to overcome. However, several new technologies – namely smart meters, AI, digital twins, and BI platforms – are helping business to more easily use their new data while maximising its value.
Smart meters are already widespread in the UK, with 57% penetration among non-domestic users. But with changes like the upcoming market-wide half-hourly settlement (MHHS), their usefulness will only increase. Moving beyond simple consumption readings, smart meters provide granular real-time data that provides a much more sophisticated understanding of energy demand, peak load, or possible anomalies within an organisation’s building stock. Combined with market incentives, they’ll soon make time-of-use tariffs common, helping to further incentivise smart energy use that leads to reduced emissions.
However, the data that smart meters provide could be overwhelming, which is why many organisations are starting to see AI play a role. Providing unparalleled analytical power, alongside the ability to automate processes, AI lets energy managers identify patterns across their building stock that manual analysis would overlook, while enabling the real-time management of assets. For example, AI-powered algorithms can automatically manage HVAC systems in response to actual and predicted weather patterns, or flag potential peaks in demand that could incur an excess capacity charge. Ultimately, AI’s power lies in its ability to identify and address energy efficiency issues better than human analysis can.
Energy managers can also gather invaluable insight through the use of digital twins: dynamic, virtual replicas of real buildings that simulate the performance of buildings under different conditions. By integrating real-time data from building management systems (BMS) and Internet of Things (IoT) sensors, digital twins allow energy managers to identify energy inefficiency, and test potential energy-saving measures before they’re implemented. Such technologies will likely become fundamental, as they enable forward-thinking energy managers and organisations to plan far into the future, decades from now, by modelling the performance of their buildings under substantially different scenarios.
Towards the future
As UK organisations navigate the path to net zero, the built environment demands more data. The business intelligence gathered from energy benchmarking, despite its complexities across diverse building types, is indispensable to the net zero goal.
Yet as more data is gathered – especially thanks to smart meters – the process is understandably becoming too complex for many energy managers to handle. Emerging technologies like AI-powered analytics and digital twins are transforming energy reporting and management, offering new opportunities for optimisation, and ways to test future scenarios for the best energy and emissions savings.