The role of demand response in the energy transition

What is demand response?

Before diving into what demand response (DR) is and how it can be effectively leveraged, let’s start with a simple definition and toy example. DR is a system where customers alter their energy consumption as and when needed by the electricity grid. In short, this means using less energy when demand is high and more when supply peaks due to renewables.

I like comparing this to aeroplane travel. Say you’ve booked your flight and get to the airport to check in but the airline informs you they are overbooked for this flight and only have a set number of passengers they can take. They provide an option where, if you can delay your travel and take a flight a few hours later, you receive a voucher along with some airmiles as a reward. Now it is up to you to decide whether the ‘payoff’ is worth the delay. By opting to take the flight a few hours later, the airline is benefitting from avoiding bad publicity and you are benefiting financially for your sacrifice.

Of course this is a basic example and the consequences of what you decide to do may be non-trivial, however the underlying concept is the same for the energy sector. In order to function, electricity grids have to perfectly maintain a real-time equilibrium between supply and demand. A sudden spike in demand or a drop in supply can lead to power outages which can be catastrophic. However, the opposite is also true—sudden spikes in supply, such as strong winds generating an excess of wind power, can overload the grid if demand can’t keep up.

Therefore in order to avoid this from happening, utilities or grid operators will incentivise commercial and industrial consumers to modulate their energy consumption in response to peaks in electricity demand and supply. By doing this, both parties benefit as the utility operator avoids the cost of having to build additional power plants to cope with peak demand and the users benefit by turning their ability to be flexible into a new revenue stream. This means they have the added benefit of lower energy costs when they use the grid during off-peak hours.

So how does demand response work?

DR programmes work by balancing the supply and demand of electricity. It allows energy consumption to be shifted away from high-demand peak periods and can also boost demand when renewable energy is readily available.

For industrial clients this may look to follow a similar format to the diagram below, where the operator predicts a grid stability problem and sends a notification to the client to reduce their energy consumption. The client then modulates their consumption/generation level and the load modulation is made available to the grid operator. In return, the client would then receive a payment as agreed under the contract.

While large industrial and commercial electricity users have been providing demand side response since the 1980s, in recent years households have also been able to take part and this has had growing traction.

In November 2022, Octopus Energy, a UK energy supplier invited all of its 1.4 million electric smart meter customers to join their ‘Saving Session’ programme, an energy reduction scheme that allows households to get paid for shifting their energy usage out of peak time (find out more about peak shaving from Senior Data Scientist, Dr Ivona Veroneckaja). The first test session took place on the 15th November between 5-6pm where over 200,000 customers opted in and chose to not actively use electricity in this period.

The average customer managed to reduce their energy usage by well over half (59%) of their regular usage during that time period, earning them just over £1 on average. Together, they managed to reduce the UK’s energy demand during the one-hour period by 108 MW—equivalent to the output of a typical gas power station.

Why is demand response important?

Now you may ask why this matters, so lets look at the key reasons why DR is critical:

1. Enhances grid reliability and stability

During periods of high demand, the electrical grid is under significant stress. DR programs reduce load at peak times, helping prevent blackouts and ensuring the grid remains stable.

2. Reduces the need for expensive “peaker” power plants

Utilities typically depend on costly, fossil-fuel-based peaker plants (plants that only operate during peak demand), driving up costs and emissions. Demand response reduces the need for these plants, saving money and lowering carbon emissions.

3. Promotes cost savings for consumers and utilities

DR helps stabilise and lower electricity rates by reducing the need for costly infrastructure investments. Consumers can save money through lower rates or direct incentives, such as time-based pricing, which rewards shifting usage to off-peak hours. For example, within a 24-hour period, electricity prices can vary widely—from as low as 11p per unit at 4:30 am to around 30p per unit during peak times, like 6 pm (as seen in graphic below).

Example of price per unit of electricity across different time periods

4. Supports the integration of renewable energy

Wind and solar power are inherently variable and may not always be available during peak demand periods. DR offers the flexibility to adjust demand in real time, enabling grid operators to optimise the use of renewable energy sources.

Impact evaluation

DR offers substantial benefits by helping lower household energy costs and could save the UK electricity system £3-8 billion annually by 2050. For consumers, DR provides bill savings by enabling reduced usage during peak hours and offering incentives for off-peak consumption. On a national level, it reduces the need for costly infrastructure, minimises operational costs, and enhances renewable energy integration by aligning demand with renewable generation.

Environmentally, DR helps cut carbon emissions by reducing reliance on fossil-fuel power during high-demand periods, supporting the UK’s net-zero goals. Long-term, as DR adoption grows, these financial and environmental benefits will strengthen grid resilience and make energy more affordable, reliable, and sustainable across the UK.

The role of data and AI in demand response

Data and artificial intelligence (AI) play an important role in optimising DR systems, particularly through the use of time series forecasting, machine learning, and AI-driven automation. I’ll outline a few areas where value can be added and how below;

1. Enhanced forecasting for demand shifts

Time series forecasting can be used to analyse historical and real-time data to accurately predict demand patterns and renewable energy availability. Since we’re moving toward a “weather-driven energy system”, these forecasts rely heavily on weather data to anticipate renewable energy generation, like wind and solar output. This allows utilities to optimise DR interventions, aligning demand with renewable peaks and reducing reliance on costly “peaker” plants. Building robust forecasting models is essential to effectively manage this varaibility and make the most of renewable resources.

2. AI-driven automation for consumers

With the rise of IoT devices in homes, managing a whole network of appliances—like EV chargers, smart thermostats, and more—would be a complex and time-consuming task without automation. AI-powered devices can step in here, automatically shifting usage to low-demand periods based on real-time electricity prices and demand forecasts, which makes DR more accessible and cost-effective for consumers.

However, simple rules alone often don’t deliver a smooth experience, as they lack the flexibility to adapt to a household’s unique usage patterns. Intelligent systems that learn and respond to individual routines and energy needs are essential for an efficient, user-friendly setup. With AI-driven automation, homeowners can achieve optimal energy savings and comfort without constantly adjusting each device, making smart energy management a seamless part of daily life.

3. Real-time grid resilience

DR programs benefit from real-time data streams that monitor grid health, renewable energy output, and current demand levels. AI algorithms can process these data streams quickly, making on-the-fly adjustments to balance supply and demand and to prevent overloads. For example, during extreme weather, AI models can detect impending stress on the grid and trigger demand reduction actions before the peak hits, maintaining grid resilience and reliability.

4. Targeted customer engagement

Data analytics help utilities understand the needs and behaviours of different customer segments. This understanding allows utility companies to tailor DR programs to match different lifestyle patterns, consumer behaviours and home setup. For example, clustering customers together that work from home or have young children. This allows incentive structures to be customised based on usage data and flexibility levels.

5. Aligning DR with renewable integration

AI models, using time series forecasting, can help align energy use with renewable energy surges by predicting when renewable output will peak. This enables grid operators to shift demand accordingly, maximising the use of clean energy and reducing emissions, which supports environmental goals.

Food for thought

Demand response isn’t equally accessible to everyone, as consumers have varying levels of flexibility in their energy use. While activities like charging an electric vehicle (EV) can be easily shifted to off-peak hours (when demand is lower), tasks such as cooking dinner are less adaptable.

However, by integrating AI and data, the orchestration of different energy tasks becomes much easier. AI can intelligently manage and automate when and how energy is used, optimising for off-peak periods and renewable energy availability. This makes it simpler for consumers to participate in DR, improving grid efficiency and supporting renewable energy integration.

How to get involved in demand response today

If you’ve got to this point in the article, firstly well done. Secondly if this peaks your interest in participating in DR and contributing to a smarter, more sustainable energy system, here are a few simple actions you can take right now:

1. Check with your energy provider

Many energy providers offer DR programs that allow you to reduce energy use during peak times in exchange for incentives, as well as time-of-use pricing plans that reward consumers for using energy during off-peak hours. Contact your provider to see if these options are available and consider switching to save money and help reduce strain on the grid.

2. Use a smart EV charger

If you own an EV, consider using a smart charger that can be scheduled through an app. This lets you charge your EV during off-peak hours, reducing your energy costs while helping balance grid demand.

3. Install a smart thermostat

A smart thermostat can adjust your heating and cooling systems based on real-time energy prices, weather forecasts, and your schedule. This small change can help you optimise energy usage and take advantage of lower rates during off-peak periods.

4. Use energy-efficient appliances

Have a look at your electric appliances and see if they can be scheduled to run during times of low demand. For example, my dishwasher and washing machine have delay-start options, which allows me to run them overnight.

To find out more about energy insights and how data & AI supports the transition to net-zero, listen to the Hypercube Podcast.