A peak demand analysis shows you when each site reaches its highest electricity draw, why it happens and what it costs you. You do it with half-hourly meter data: find the highest readings, line them up against what was running at the time, then decide what to shift, smooth or switch off. This guide walks through the method, the usual causes, the levers that work and how to prove the savings afterwards.
TL;DR
- Peak demand is the highest power your site draws in a short interval. In Great Britain that interval is the half-hour, and the highest half-hour in a billing period can drive what you pay.
- Most business peaks come from things switching on together: shift starts, plant start-up surges, heating and lighting schedules. Rarely from one huge machine running steadily.
- Start with 12 months of half-hourly data, find your top 10 to 20 readings, and match each to site activity. Patterns appear quickly.
- Spreading start-ups, controlling motors and heating, and joining flexibility schemes are the usual fixes. Verify savings against the same half-hourly baseline.
- You can run this analysis for free on a Starter plan, across multiple sites.
Table of Contents
- What peak demand means for a business
- What you need before you start
- How to run a peak demand analysis, step by step
- What typically causes a business peak
- Ways to manage and reduce peak demand
- How peak demand shows up on your bill
- A worked example
- Verify the savings
- Peak demand and your net-zero reporting
- Run it on your own sites
- Our perspective
- FAQ
- Sources
What peak demand means for a business
Peak demand is the highest level of power a site draws from the grid over a short, defined interval, measured in kilowatts (kW) or kilovolt-amperes (kVA). With half-hourly metering the interval is 30 minutes, so your peak is the single busiest half-hour in the period you are looking at.
Peak load is a close cousin. People use it for the same site-level maximum, but it is also used for the total demand on grid infrastructure at its busiest. When you read a supplier guide or network document, check which one is meant. If you want the metrics side by side, our piece on baseload vs peak load covers how each shows up on a bill.
Why the peak matters more than the average: your consumption in kWh tells you how much energy you used. Your peak tells you how much capacity the network had to hold ready for you. Government research on non-domestic metering notes that maximum demand charges are levied monthly and are based on the highest recorded usage in any half-hourly period. One bad half-hour can therefore set the cost of a whole month.
Not every contract works this way. Smaller sites are often billed mainly on unit rates and a standing charge, and the charge structure depends on your supply capacity and tariff. Your bill and contract tell you which demand-related lines apply. If you are unsure how the fixed and variable parts split, standing charge vs unit rate is a good starting point.
What you need before you start
You need three things.
- Half-hourly consumption data for at least a full year, so you capture summer and winter behavior. Sources include your half-hourly meter, your supplier or data collector, or smart meter data. Our guide to smart meter data access for UK businesses lists the routes.
- Clean data. Missing reads and estimated values distort peaks. Check for gaps first; spotting meter data gaps explains how.
- A site activity log. Shift patterns, opening hours, production schedules, maintenance days, heating and cooling set points. The data says when. The log says why.
Smart meter data helps here too. Government guidance on smart meters says the data can help organisations monitor and manage energy use, identify variations and quantify the benefits of projects. That last point matters later, when you need to prove a saving.
There is also a regulatory push behind half-hourly data. Ofgem explains that moving to half-hourly settlement encourages businesses to take control of their usage and spread consumption across the day, which in turn reduces network costs and bills. If your meters are already half-hourly, the data to act on this is waiting for you.
How to run a peak demand analysis, step by step
1. Find the peaks
Sort your half-hourly readings from highest to lowest and list the top 10 to 20 for each site. Note the date, time, day of week and value. Do this per month too, because a monthly charge responds to each month's own peak, not just the annual maximum.
Government research confirms the approach: daily demand profiles from half-hourly datasets reveal patterns in energy use and peaks. Look for clusters. If seven of your top ten readings fall between 07:30 and 08:30 on Mondays, you already have a lead.
2. Compare the peak to the baseload
Calculate your overnight or weekend minimum, your baseload, and compare it with the peak. A large gap means your demand is spiky and there is potential to flatten it. A small gap means your demand is steady, and your savings are more likely to come from reducing the baseload itself. Pair this with a look at half-hourly meter checks to make sure the readings behind your figures are the ones you are billed on.
3. Build a typical day profile
Plot an average weekday and an average weekend for each season. The shape tells you more than any single peak: a morning ramp, a midday plateau, a late-afternoon spike. Then overlay your worst days on top. The gap between a typical day and a peak day is what you are trying to explain.
4. Match each peak to an event
Take each of the top readings and ask what changed in the 30 minutes before. Was it a shift start, a compressor cycle, a cold morning with every heater coming on, a cleaning crew with lighting and vacuums, an EV charger bank, a test run? Write the answer next to the reading.
5. Rank causes by cost and fixability
Group the peaks by cause and score each on two things: how much it adds to your highest demand, and how easy it is to change. A scheduling fix that costs nothing and trims 40 kW beats a capital project that trims 50 kW. Do the free fixes first.
What typically causes a business peak
If your data shows a sharp spike rather than a long plateau, you are in good company. The government's scoping study on non-domestic demand found that peaks are often caused by many small items switching on together, start-up surges from plant and machinery, and shift-change routines, rather than sustained high-load operation.
In practice that translates to a handful of familiar culprits:
- Daily switch-on. Lighting, IT, HVAC and production equipment all starting at 07:00.
- Motor and compressor start-up. Inrush current for large motors can far exceed running load for a few seconds, and it lands inside a half-hour reading.
- Heating and cooling. Pre-heating on a cold morning, or every chiller running on the hottest afternoon.
- Overlapping processes. Ovens, washers, injection moulding, and charging all coinciding.
- EV charging. Fleet vehicles plugged in at the end of the working day, just as the site is still busy.
Sector matters as well. Ofgem's work on demand side response found that retail, education and commercial offices together account for over 50% of peak demand from non-industrial non-domestic buildings. If you run a multi-site estate in those sectors, comparing sites against each other is one of the fastest ways to find the outliers.
Ways to manage and reduce peak demand
The same government study lists practical measures that still hold: staff awareness campaigns, efficient appliances, variable speed drives and automatic building controls, plus moving high-energy tasks out of peak windows. Here is how to turn that into a working list.
Stagger start-ups
The cheapest fix is the one that costs nothing: do not start everything at once. Ramp HVAC from 06:00, start compressors in sequence at five-minute intervals, delay non-urgent equipment until after the shift handover. A building management system can enforce this automatically.
Control motors and plant
Variable speed drives soften start-up surges and cut running energy on fans and pumps. They suit sites where analysis shows motor start-ups at the top of your peak list.
Shift flexible loads
Not all loads are equally movable. Ofgem's research notes that loads with built-in inertia or storage, such as space heating, water heating and air conditioning, offer the most flexibility, while loads like computing offer little. Pre-cool a cold store or pre-heat a hot water tank earlier, then let it coast through the busiest half-hours.
Manage EV charging
If chargers are part of your peaks, schedule them or cap their combined draw. One practical overview of EV charging load management shows how capping total charging load can avoid costly electrical upgrades, and the same logic applies to a depot or car park.
Add storage or on-site generation
Batteries can shave peaks by discharging in your highest half-hours. It is a capital project, so use your analysis to size it: you need to know how tall and how long your typical peaks are before specifying anything.
Get paid to flex
The Demand Flexibility Service lets the system operator incentivise businesses to shift electricity use away from a specific time. NESO says it moved from a winter-only scheme to a year-round service on 27 November 2024. Participation is usually through a supplier or aggregator, and your half-hourly analysis tells you how much load you could realistically move.
Expect some resistance. Ofgem found significant potential for non-domestic demand side response, reducing winter peaks by 1 to 4.5 GW, provided businesses overcome barriers such as awareness gaps and worries about service impact. Test any change on one site before rolling it out, and protect production and customer comfort first.
How peak demand shows up on your bill
Where your contract has demand-related charges, the bill typically carries a capacity element, an element linked to the highest half-hour in the month, and sometimes a penalty for exceeding an agreed import capacity. The practical point is that your analysis should end at the bill, not at the chart.
A simple check each month:
- Take the highest half-hourly reading in your data for the billing period.
- Compare it with the maximum demand figure on the bill.
- If they differ, find out why: different unit (kW vs kVA), estimated reads or a data error.
- Compare the maximum demand with your agreed capacity. If you sit far below it month after month, ask your supplier or network operator whether the capacity can be reduced. If you exceed it, find the cause before the next period.
Automated bill validation is useful here, because a peak reading that looks wrong on paper is often wrong in the billing system. Our half-hourly cost forecasting guide shows how to project those costs forward so a spike does not become a budget surprise.
Charging rules also change. The Targeted Charging Review was set to move network charging toward higher fixed charges based on capacity and away from time-of-use charges, so confirm with your supplier which structure your current contract follows instead of assuming last year's logic still applies.
A worked example
Take a hypothetical three-site light manufacturer. The figures below are illustrative, not client data.
| Site | Top half-hourly reading | Typical weekday midday | Likely cause of the peak |
|---|---|---|---|
| Site A | 410 kW | 260 kW | Compressors and ovens starting at 06:30 |
| Site B | 180 kW | 150 kW | Steady load, small gap, little to shift |
| Site C | 320 kW | 140 kW | Pre-heat and EV chargers at 17:00 |
Site B has almost nothing to flatten, so its savings lie in baseload. Site C has the biggest gap between peak and typical load and one clearly separable cause, so staggering the charging and delaying pre-heat is the first move. Site A is a scheduling job: sequence the compressors and ovens. The analysis has turned a vague goal of cutting the peak into three different actions, in an order of priority.
Verify the savings
A saving you cannot show is a saving the finance team will not believe. Use the same method before and after:
- Fix a baseline: the top readings for the same months in the prior year.
- Record the date each change went live.
- Compare like for like: similar weather, similar production volumes and the same meter.
- Track the new top readings monthly and watch for drift, such as an old start-up habit creeping back.
Smart meter and half-hourly data make this quantifiable, as the government guidance on smart meters notes. Tie the result to your bill lines, and you have a figure finance can sign off.
Peak demand and your net-zero reporting
Flattening peaks is not only a cost story. Ofgem notes that reducing or shifting peak demand enables more efficient electricity production and savings in greenhouse gas emissions. The reported effect on your own Scope 2 figure is more modest, since it depends on how you account for emissions, but the half-hourly data you gather for peak analysis is exactly the data a robust carbon report needs. Heat is a related case: see our notes on boiler efficiency tracking and a heat decarbonisation plan for the next step.
Run it on your own sites
EnerlyticsAI is built for exactly this workflow. Upload or connect half-hourly data, and the Half Hourly Data view shows consumption and spikes by site, while bill validation flags anomalies against what you were charged. Our Starter plan is free forever and supports multiple sites, so you can run the analysis above before spending anything. Paid plans start at £49 per month (Eco), with Growth at £79, Professional at £149 and Scale at £299 per month. Create a free account to try it on your busiest site first.
Our perspective
Most businesses we talk to look at their monthly kWh total and nothing else. That total hides the thing that often matters most: the shape of the day. Two sites can use identical energy and have very different peaks, and very different bills.
Our view is that peak analysis should be boringly routine, not a one-off consultancy project. Check the top readings every month, compare sites against each other and treat every unexplained spike as a question for the site team. The savings are rarely dramatic in one go. They come from habits: staggered start-ups, sensible set points, chargers on a schedule. The tool matters less than the discipline, which is why we keep the starting point free.
— Chris
FAQ
How do I calculate peak demand?
Take your half-hourly readings for the billing period and find the highest one. If your meter reports in kWh per half-hour, doubling the figure gives the average kW over that interval. For kVA you also need reactive power, so check the unit your bill uses before comparing.
What is the difference between peak demand and peak load?
Peak demand usually means the highest draw of a single site or meter over an interval. Peak load is often used for the same thing, but also for the total demand on a network at its busiest. Read the context in a document to see which one is meant.
Can reducing peak demand really lower my bill?
It can if your contract has capacity or maximum demand charges, because those respond to your highest half-hour. It matters less on a simple unit-rate and standing-charge tariff. Check your bill for demand or capacity lines, then ask your supplier how they are calculated.
How much data do I need?
Twelve months of half-hourly data is the sensible minimum, since it captures both heating and cooling seasons. Shorter periods can still reveal daily patterns, but may miss your true annual peak.
Sources
- Scoping study for measuring peak electricity demand in the non-domestic sector (UK Government)
- Demand side response in the non-domestic sector (Ofgem)
- Moving to half-hourly energy reads: a guide for businesses (Ofgem)
- An introductory guide to smart meters for the public sector (GOV.UK)
- World-first Demand Flexibility Service exceeds expectations (NESO)
- Demand Flexibility Service explained (NESO)