UK Insights: The Evolution of Electricity Demand and Smart Meter Data Analytics

The evolution of electricity demand in the UK and the business potential in data analytics

Author: Guest article contributed by UK-based independent energy researcher Tony Day

The entire energy system is in transition. With governments now setting strong carbon reductions targets, and investors around the world demanding that major corporates take urgent action, momentum is building towards a rapid transformation in both energy consumption and generation.

Principle among all the ongoing changes is the electrification of services. In this article we explore three key areas where the electricity system will be under pressure to deliver secure, affordable, and low carbon energy across the existing network – the growth of electric vehicles (EVs), the roll out of domestic and commercial heat pumps, and the installation of local photovoltaics (PV) and energy storage.

Whereas the decarbonisation of electricity supply is largely an upstream industry activity (with the exception perhaps of rooftop solar PV,) electrification is very much dependent on the end user – the energy supply company customers. This makes the challenge even more complex. To that end, this article will also discuss how meter level energy data analytics will be key to rising to the challenge and meeting evolving customer needs.


The sales of EVs are growing rapidly around the world. While still a small share of the total, EV sales are expected to reach a 30% share of new sales by 2030. In 2020 UK EV sales increased by 185% over the previous year; in some months this reached over 10% of all new car sales. With new charging stations arising, greater battery capacities being delivered, and the much higher efficiency of EVs over the internal combustion engine, consumers are turning in greater numbers to the new technology. The key barriers of cost and range anxiety are being overcome, and anecdotal evidence suggests that even the most ardent petrol heads enjoy the EV driving experience.

The overall impact on electricity generation capacity is expected to be relatively small. However, local impacts on the network could be much more significant. McKinsey analysis suggests that if 25% of homes served by a particular transformer have EVs, there could be an increase in evening peak demand of up to 30%. They further say that this addition to the peak could be strongly influenced by pricing structure and could be halved by the introduction of time-of-use-tariffs (ToUTs).

This analysis raises several questions: what network strengthening costs might this lead to, and can peaks be further ameliorated through more active network management? A further question might be over what timescales can ToUTs be introduced to provide the necessary responses? At the heart of these questions is data, and the need to understand real time power flows right down at the individual meter level to ensure not only network stability and security, but also ensure seamless customer service.



The electrification of heat is a thornier issue. While consumer behaviour is notoriously difficult to change rapidly, it is easy to be excited by a shiny new car, but less so when swapping a gas boiler for a heat pump. The heat source in our homes is only ever thought about when it breaks down, and if it does need replacing, we tend to want to do this at least cost with minimal disruption. Replacing a gas boiler is relatively quick and cheap, and consumers go with what they know and understand – regardless of the carbon implications that may be associated with the purchase.

Heat pumps are much more efficient than fossil fuel burning boilers. Whereas the latter can be up to 90% efficient, electric heat pumps can deliver between two and four times as much heat as the electricity they use. However, heat pumps do present several challenges when it comes to adoption.

Because heat pumps are poorly understood by the general lay person, increasing and maintaining confidence in them is paramount. Active energy management could be an important component in this, and smart meters can provide the data for remote monitoring and analytics to deliver additional services to the customer. There is a significant opportunity here for energy suppliers to use smart meter data analytics to identify suitable customer for heat pumps and provide customers guidance on how best to use their heat pumps.

The UK government has set a target for 600,000 heat pumps to be installed every year by 2028. This poses significant challenges, not only for consumer engagement as discussed above, but also for the operation of the networks. As with EVs, heat pumps represent a new set of demands on the grid (electric resistance heating has been in use for decades but is a small proportion of UK heating provision). The winter peak demand on the gas grid is up to three or four times higher than the electricity demand. Switching the heating load from gas boilers to heat pumps, even with very high COPs being maintained, will double the peaks on the network, leading to needs to strengthen the network. The costs to add capacity would inevitably be passed back to the consumer.

The reality is that this increase in demand will not happen overnight, but the urgent need to decarbonise the heat sector will inevitably mean an acceleration in heat pump deployment in the next decade. The network operators and the energy supply companies will need to gear up to this change. Heat pumps can provide an opportunity for active network management. Because of their operating temperatures they are often better left to run at lower output for longer periods of time, which makes their inherent operation less ‘peaky’. This means their control systems need to be correctly set up, and that they are not simply run in the same way as a boiler that they replace. As with EVs, this might be better encouraged by ToUTs, but also adds to the case for remote monitoring and active energy management as an additional service using smart meter data analytics personalised to the customer.

PVs and Energy Storage

Two more technologies are set to have a significant influence on the operation of the grid, those of distributed electricity generation (mainly PV), and energy storage (both electrical and thermal). With the introduction of feed in tariffs (FiTs) in the UK, the residential PV market became buoyant until they were removed to new applicants in 2019. While this has supressed the market demand, the installed price of PV has reduced dramatically, and the drive for Near Zero Energy Buildings (NZEB) is likely to strongly revive interest and uptake.

In the later years of the FiT scheme, it became common to include electric battery storage as part of the installation. This has provided technologies at the edges of the network that can deliver an increasing amount of electricity generation, and with an ability to store and release energy according to needs. The consumer thus becomes a prosumer and is an active player in the electricity system. These domestic operators do not necessarily want to manage this activity but are keen to benefit from the services they can supply to the grid (electricity generation, network load management, provision of flexibility). This active participation extends to the owners of EVs, who can now offer their car batteries as part of the network storage capacity.

One study in Ireland looking at a group of houses equipped with PV and batteries showed significant savings on imported energy from the grid could be made if the optimised operation of the systems could be controlled together. This required a third-party aggregator working with the network operator and the energy supplier, giving rise to a whole new business model. Data driven businesses have been operating for some time in the commercial and industrial sectors, where demand flexibility has traditionally been more accessible and cost effective. Extending this to residential consumers opens vast new opportunities.

Data analytics

As referenced throughout this paper, smart meters are an important part of the new digitised energy system. They provide the data that can deliver the analytics, feed machine learning algorithms, and monitor performance. One key role of meter level data analytics will be mitigating the extent of grid reinforcement required by facilitating market solutions to demand peaks. A second, and even more critical role meter data analytics will play is the transformation of energy consumers from passive bill payers to proactive participants in the whole energy system.

There are significant trust issues to be overcome before this becomes commonplace in the UK. However, right now, detailed analytics of customer energy usage can already be used to provide powerful insights for enhanced customer service. As discussed above, aggregators are already showing the value of analysing and controlling energy flows on the network. This will undoubtedly move into the EV market as it picks up. All electric buildings that employ heat pumps will extend this to whole-house solutions. As customers electrify their heat and transport their electricity bills (if not their overall energy costs) will get bigger and they will therefore be looking for more cost management and cost reduction solutions from their suppliers. Meter level energy usage analysis will be key to meeting these customer requirements.

For example, heat pumps develop an identifiable operational profile (typically weather dependent). If a heat pump starts to depart from its usual behaviour, this indicates a fault in the system somewhere. Finding faults early mean they can be fixed, and substantial wastage can be avoided. These principles have been widely adopted in industry and commercial buildings, but only now with smart meter infrastructure is this available for the residential market.

The next decade is critical for the energy supply industry to put in place the systems and structures to enable us to meet our Net Zero 2050 goals. Visibility into energy data analytics, right down to each individual meter point, is critical to many facets of these changes. This transformation will be a gradual process, but it is important to start now, using the best available customer insights.

About the author:

Tony Day is an independent energy researcher specialising in low carbon solutions in the built environment. Tony started his career in hospital engineering before joining London South Bank University to teach and research building services engineering. At LSBU he established the MSc in Sustainable Energy Systems, and was instrumental in setting up the Centre for Efficient and Renewable Energy in Buildings (CEREB). In 2012 he joined the newly established International Energy Research Centre (IERC) at the Tyndall National Institute in Cork, Ireland. As Executive Director of the IERC he built a successful research team with a focus on strong industry collaboration in areas such as smart grids, peer-to-peer energy trading, low carbon buildings, and enhanced deployment of low carbon solutions. He is the immediate past chair of the CIBSE HVAC Systems Special Interest Group, and Vice-Chair of the CIBSE Nominations Panel.

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