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How do we know we are really saving?
This question comes up in every serious conversation about deploying an energy management system — usually once we reach the wording of the contract. The customer has every right to ask it. The problem is that a credible answer takes far more than comparing two invoices.
Even the simplest case is not simple
Take an apparently obvious situation: a school or a public office. Fixed operating hours, a similar number of users, the same equipment. It looks as if all you need to do is set consumption after go-live against the previous year.
But is the lower figure the system's doing, or a milder winter?
Degree days are the right direction, but still an approximation
The first answer is usually degree days. That is a good lead, but it is still only an approximation. They account for outdoor temperature, usually as an average value. Yet heat consumption is also driven by wind, solar gain and humidity — in some buildings more than the temperature alone would suggest.
Then there is the choice of base temperature. 15°C, 17°C, or some other value? It depends on the heat gains from people, lighting and equipment, and on the building's insulation standard. Two facilities on the same street may require entirely different assumptions. One index for both produces a result that looks precise but is not necessarily true.
And that was the simplest case
What about a factory where the volume and mix of production change? How do you assess a hall in which the compressors were replaced halfway through the period? How do you separate the effect of the system from savings achieved through a parallel thermal retrofit?
Each of these problems can be analysed more closely: fit additional meters, extend the reference period, build models that account for more variables. It is just that the cost of measurement often rises faster than the accuracy of the result. Taking the analysis to laboratory level can cost more than the savings themselves.
The right question: how much accuracy do we actually need
Which is why the key question is not "could we calculate it more precisely?" but "what accuracy is sufficient for both parties, and how much is it worth paying for?".
These are only some of the problems of measurement and verification. But the conclusion is unambiguous: until we can measure savings credibly, we are only talking about them in the conditional.
Credible proof of savings is not a comparison of two invoices but a correction for the variables (weather, production, upgrades) and a deliberate choice of sufficient accuracy — because the cost of measurement rises faster than its precision.
Percee, as an EMOS-class system, supplies the data and models needed for credible verification of savings: it collects measurements at the right resolution, builds a conditional baseline corrected for weather and other variables, and maintains a multi-year history as the reference point (in line with IPMVP). The effect can therefore be demonstrated in an auditable way rather than merely asserted — which at Solwena's customers has added up to more than PLN 50 million of documented savings across more than 50 deployments.
See how Percee works →