In today’s domestic energy landscape, consumers face a myriad of challenges to negate the cost of rising bills and best manage their energy use.
Already in 2024, we’ve seen the energy price cap for gas and electricity rise to £1,928, as the fallout of the energy crisis continues to impact the price of consumption for end users. Expect to see further increases in costs throughout the year, as Ofgem’s struggle to manage the expectations of consumers and providers persists.
The reality is that the responsibility has fallen on consumers to understand how they can limit consumption and minimise the total cost of their energy bills. This begins by understanding some of the barriers that stand in their way and considering how technology can contribute to lower monthly energy costs.
Managing demand flexibility
As is the case with many services we utilise, the price of energy varies depending on the demand at the time it is being consumed. Just as rail fares are more costly on a packed Monday morning commuter train compared to the same sparsely populated Sunday train, energy use at peak times will cost more than consumption when very few appliances are in use in the wider area.
Generally speaking, demand flexibility causes monthly bills to increase, as households with standard working hours and standard routines see their energy usage spike at a similar time to households around them. However, savvy homeowners will understand how they can use demand flexibility to their advantage and keep costs lower than the average in their area.
Firstly, there are government schemes in place that allow householders to save during periods of especially high demand. Signing up to the Demand Flexibility Service (DFS) and limiting consumption during times when the Electricity System Operator is trying to manage use can see households receive financial rewards.
Households should also consider how they can use appliances outside of peak hours, so that the cost of running a given device is lower.
Domestic electricity use is on the rise
As we transition away from fossil fuels to renewable sources of energy, expect to see consumption of electricity increase, as this can be generated from sustainable sources. A prime example of this is the increase in Electric Vehicle (EV) uptake, with more EVs sold in 2023 than in any previous year.
Despite savings on fuel and government incentives that can be obtained through the purchase of an EV, the cost of running EVs can still be extremely high. According to Voltaware data, the average EV owner spends around £1,750 each year on charging their vehicle.
Similarly, households are using electric heaters with increasing regularity in the winter months to keep homes warm at a palatable price. Yet, the running of these devices can still come at a high cost − the average UK household spends anything up to £1200 a year on powering electric heaters.
As a result, it is important that households understand how they can keep electricity bills at a manageable level with their consumption likely to increase over the coming years.
Minimising rising costs through technology
While limiting the cost of energy bills is often an uphill battle for households, new tech solutions are coming to the fore that individuals can rely on for guidance that limits the cost of consumption.
Many public utility companies offer an approximate breakdown of energy consumption for households, based on common home profiles. To provide a more tailored level of service, AI-powered solutions are using a process called energy disaggregation to work out the total cost of individual appliances and provide suggestions that reduce the amount of cash required to run each device.
All electrical appliances generate their own unique power pattern, and energy disaggregation sifts through this mass of energy signals to identify each appliance’s ‘energy fingerprint.’ Consequently, energy disaggregation gives households a clear indication of exactly what is contributing to the home’s total electrical load on a device-by-device basis.
Energy disaggregation relies on a specific kind of AI machine learning called ‘non-intrusive load monitoring’ (NILM), whereby systems are constantly training themselves to recognise the signals from appliances and accurately reflect energy usage.
If we once again use the example of EVs, we can see just how much households can save by leveraging the insights provided by energy disaggregation technology. These solutions show that EV charging costs can be cut by charging vehicles to around 80 per cent rather than full capacity, while charging in off-peak hours of 23:30 to 05:30 is also significantly cheaper. Households can save between £175 and £350 on EV charging a year by implementing these simple suggestions.
Ultimately, this illustrates the importance of full visibility that guides energy users to make smart decisions that reduce the overall cost of consumption.
Sergey Ogorodnov is co-founder and CEO of Voltaware
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