
In retail, the energy problem is rarely an individual store: it is that there are many stores, they are similar, and nobody can say which one is consuming more than it should.
This is also the sector's opportunity. When dozens of stores with the same format are managed, every improvement identified in one can be applied to all the others, multiplying the return by the number of locations.
Energy consumption varies considerably between a clothing store and a supermarket, but the main categories remain the same: refrigeration, lighting, air conditioning and, in food retail, in-store preparation areas such as bakeries, delicatessens and butcher shops.
Sector guidelines developed by ENEA and Federdistribuzione for energy audits in large-scale retail indicate an approximate breakdown: 35–45% for food refrigeration, 20–30% for lighting and 10–18% for air conditioning. This concentration simplifies the task: the starting point is clear and concerns systems that operate continuously.
In non-food retail, lighting and air conditioning account for a larger share, with one particularity: shop windows and signs often remain illuminated well beyond opening hours.
For a single building, load profiles are analysed. For a network of stores, there is a faster approach: compare the stores with one another.
Two stores with the same floor area, format and opening hours but different consumption levels raise a question with a specific answer. The cause may be a poorly calibrated system, overly frequent defrosting, a door left open or a schedule that was never updated after a management change.
For the comparison to work, two conditions are necessary:
| What | Why | Useful indicator |
|---|---|---|
| Electricity consumption per store | The basis for comparing stores | kWh per square metre and per opening hour |
| Sub-metering by utility | Separates refrigeration, lighting and air conditioning | Share of each utility in the store's total consumption |
| Temperatures of display cases and cold rooms | Energy consumption and food safety are measured together | Temperature for each display case, with thresholds and alerts |
| Base consumption when the store is closed | Shows what remains switched on at night | Average kW during closing hours |
| Indoor conditions | Checks that savings do not worsen customer and staff comfort | Temperature and humidity in the sales area |
The instrumentation is the same as that described in the guide to smart meters and IoT sensors, with dedicated probes on display cases and cold rooms.
This is the specific feature that makes monitoring easier to approve in a food retail chain. Display-case temperatures must be checked anyway to meet food safety requirements and prevent stock losses.
The same sensors that record these temperatures also reveal whether a system is operating poorly: a display case struggling to maintain its setpoint, an excessively long defrost cycle or a compressor starting more frequently than usual are signs of excess consumption even before they indicate a risk to the products.
An alert received in time for a cold room can prevent three things at once: abnormal energy consumption, stock losses and non-compliance. This is a case where return on investment is measured in more than just kWh.
The prioritisation principle is the one described in the guide to energy efficiency improvements: first correct operating practices, then make changes to the systems.
In retail, the main limitation is rarely technical. A store may be leased, located in a shopping centre with shared systems, operated as a franchise or managed directly: in each arrangement, who decides on the intervention and who benefits from it will differ.
Two precautions can help:
For stores located inside shopping malls, the content on shopping centres is also relevant, as shared systems follow their own operating principles.
An individual store does not have a BMS and never will: the cost of a wired system cannot be justified for just a few hundred square metres. But a chain of fifty stores needs the same level of control as a large building, spread across fifty addresses. The complete process, from measurement to verification of savings, is described in the energy management guide.
This is the context in which UTwin's energy management software operates: smart meters and IoT sensors supplied with the platform, data collected in the cloud from all sites, comparisons between stores, anomaly alerts and remote system adjustments based on outdoor weather and occupancy.
The integrated maintenance software (CMMS) turns an anomaly into a work order assigned to the area maintenance technician, with a history for each store. This approach is described in the content on retail store and supermarket maintenance, applied to energy management.
For stores, supermarkets and small premises, the platform works as a light BMS, with CAPEX up to 70% lower than traditional systems: these are the types of buildings where the cost difference is most significant.
Food refrigeration. ENEA and Federdistribuzione guidelines for energy audits in large-scale retail place it at 35–45% of consumption, ahead of lighting (20–30%) and air conditioning (10–18%), with in-store preparation areas also contributing in facilities that have them.
Use normalised figures: consumption per square metre and per opening hour, comparing stores with the same format and in the same climate zone. Comparing absolute consumption always puts the largest stores at the bottom of the ranking and provides no useful insight.
No, and that is the point. Chains benefit precisely from standardisation: the same instrumentation, the same terminology and the same indicators. This means that an improvement identified in one store can be applied to the others without repeating the analysis.
No, and that is why it is approved first in many chains. The same measurements support food safety, prevent stock losses and document storage conditions.
The first step for a network of stores is not to install sensors everywhere: it is to rank annual consumption by store, divided by floor area, and examine the stores at the top of the list. In almost every case, the three or four highest-consuming stores have a specific problem, and that problem is repeated at other locations in the network.
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