Across European markets, suppliers increasingly offer — and regulation increasingly mandates — tariffs settled on an hourly basis. For facilities with flexible load this opens a very useful path to cost reduction. But a dynamic tariff on its own is only an opportunity — one realized only by automation that shifts consumption into cheaper hours.
That role is filled by Percee®, an Energy Management and Optimization System (EMOS): it correlates hourly prices with the facility's load profile and controls flexible loads with no operator decision required.
A dynamic tariff means the price of electricity changes in hourly intervals — either directly with exchange quotations (day-ahead and intraday markets such as EPEX SPOT or Nord Pool) or through a supplier contract indexed to them (for example, "exchange price + a margin"). The customer no longer pays one rate all month. They pay what energy costs at the moment of use — a different amount each hour.
Larger commercial consumers with hourly metering are typically the first able to use such tariffs. A fixed tariff eliminates risk, but it also eliminates the opportunity. Hourly settlement introduces volatility — and volatility is an opportunity, provided the company has a tool to exploit it. Without automation, a dynamic tariff is an unstable bill. With automation, it is a controlled mechanism for cutting cost.
Spot-market prices now have a clear, repeatable daily structure, shaped in many countries by solar generation:
| Time of day | Price characteristic |
|---|---|
| Morning (approx. 7:00–9:00) | a local peak — before PV ramps to full output |
| Midday (approx. 11:00–15:00) | the valley — the PV surplus pushes prices to their lowest; in some markets, on sunny days, even to zero or below |
| Evening (approx. 17:00–22:00) | the daily peak — the sun sets while demand stays high; energy is most expensive |
| Night | moderate prices at low demand |
The amplitude is what matters: the difference between the midday valley and the evening peak can be enormous — on extreme days, energy in the evening costs several times more than a few hours earlier, in the middle of the day. That difference is the source of savings. A company that shifts part of its consumption from the expensive evening into the cheap, sunny valley pays much less for the same energy — and it cannot be done by hand every day. Hence the role of automation, and of Percee.
Percee pulls real-time price data from the relevant power exchange. It then processes it in the context of the contract (tariff) for the specific facility. The algorithm prioritizes flexible loads — those that can be moved in time without affecting the operational process — and runs them when the price drops below a defined threshold. It is the same control layer as in automated energy consumption optimization — here driven by the hourly price signal.
Example: a logistics facility with three EV charging stations and a cold store. A cold store has large thermal inertia — it can be "charged" with cold during the price valley and draw less during the peak. EV chargers need not run between 17:00 and 21:00 if the fleet returns to base at 16:00 and leaves at 6:00 the next day. The Percee platform manages both processes at once — with no operator intervention, on rules set once at deployment.
The spot price is only one line on an electricity bill. Alongside it sit network and distribution fees and — in many countries — additional demand, capacity or grid charges whose incentives can point in the opposite direction from the spot price. Chasing the single cheapest spot hour can quietly raise another component, so the headline saving evaporates.
Percee accounts for this. Instead of optimizing one line in isolation, it shifts loads to minimize the total delivered cost — energy plus network and capacity charges — across the whole bill, under whatever tariff and charge structure applies in a given market. Reconciling signals that pull in different directions, day after day, is precisely the trade-off a person cannot balance by hand — and the reason a control layer earns its keep.
The effect depends on three variables: the volume of consumption, the share of flexible loads in the profile, and the daily amplitude of spot prices. The more energy a company can move from the expensive evening peak into the cheap, sunny valley — and the larger the difference between them — the greater the saving.
For a facility that shifts roughly 20% of its monthly consumption from peak hours into the price valley, the saving on active energy alone reaches a few percent of the bill. On a bill of, say, €25,000 a month, that means thousands of euros monthly — the figure being higher the deeper the daily valley and the more loads can be shifted.
These figures concern the energy component alone. Where other charges apply — network, demand or capacity fees — their effect is calculated separately and, as noted above, does not always move in the same direction; this is why Percee optimizes the total bill rather than a single line item. One platform handles every layer with no extra integration cost.
The risk must be accounted for, though: in periods of unexpected price spikes (generation-unit failures, cold snaps) a dynamic tariff can mean higher rates than a fixed contract. Automation limits this risk — the system withdraws from consumption when the price exceeds a set limit. It does not eliminate it entirely. Hourly settlement without a managing system such as Percee is speculation, not optimization.
Want to check how much your facility could gain on a dynamic tariff? Talk to a Percee expert — we will analyze your load profile and show concrete scenarios.
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