The Smart Readiness Indicator (SRI) is intended to make buildings fit for digitalization and energy efficiency, but the EU methodology is reaching its limits. The authors present a measurement-based approach that quantifies the actual impact of smart systems, in particular load flexibilization, and thus makes the SRI more meaningful.
Text Martin Hödl-Holl and Thomas Zelger,UAS Technikum Wien, 7.11.2025
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EU methodology and background
According to the Energy Performance of Buildings Directive (EPBD 2024[1], Recital 56), the Smart Readiness Indicator (SRI) is intended to assess the ability of buildings to use information and communication technologies and electronic systems in such a way that building operation is adapted to user needs and grid requirements and overall energy efficiency is increased.
The methodology proposed by the EU assesses smart readiness on the basis of 54 smart-ready services. Each of these services is scored from 0 to 4 points based on its functionality level. A fixed weighting system determines the relevance of the individual services in relation to seven impact categories, regardless of the building context.
Impact scores (0-100%) for these impact categories are formed from the weighted evaluations, which are then aggregated into three overarching key functions:
- Energy efficiency & operation
- User convenience & information
- Flexibility & network interaction
These three partial scores are included in equal parts in the overall SRI value. Put simply, the more Smart Ready Services with a high level of functionality are available, the higher the resulting SRI.
Limits of the existing methodology
As the assessment does not take into account structural, physical or use-specific properties, the SRI does not allow any statement to be made about the actual energy or emissions saving potential of the intelligent equipment. Buildings with reduced equipment that is particularly effective in the specific context achieve comparatively low SRI values, while extensive technical equipment leads to high ratings regardless of its effectiveness.
The underlying catalog of criteria can therefore be understood as a kind of “shopping list“: It lists those equipment features that are required to achieve maximum SRI. An integral, context-dependent system optimization – for example through the use of a digital building twin, as provided for in the EPBD 2024 (see Annex IV, para. 1) – is not taken into account.
In order to assess the informative value of the indicator, a fundamental distinction should be made between the smart readiness capability of a building and the indication of smart readiness by the SRI.
Smart readiness describes the technical, functional and operational ability of a building to adapt its energy systems to user requirements and grid conditions in order to optimize energy efficiency, COâ‚‚ savings and comfort. The SRI, on the other hand, is an evaluative indicator whose significance depends on how well the scoring system reflects the actual performance of a building.
Perspective of further development based on measured values
As early as 2020, Verbeke et al[2] – the authors of the EU methodology – proposed a measurement-based “Method C” as a potential future development to complement the points-based Methods A and B. This is intended to record the actual effect of intelligent systems in operation, for example in terms of energy savings, flexibility or comfort.
In view of the EPBD requirements and the problems described, such further development appears not only desirable but also necessary in order to verify the indication quality of the existing SRI. The following proposal is therefore intended as a contribution to the development of a measurement-based SRI method.
As some of the key functions pursue opposing goals – such as convenience and flexibility – aggregating them into an overall value considerably reduces the informative value. It is therefore recommended that the three key functionalities be reported separately. Only those aspects that can be validated by measurement within the same impact category should be evaluated together. The approach presented here relates specifically to the key function “Flexibility & network interaction“.
Proposed methodology for quantifying smart readiness
Instead of evaluating the functional scope of the technical equipment, the proposed methodology is based on simulating the effect of intelligent operating modes in the specific building context or recording them in real operation.
The key indicator is the reduction in COâ‚‚-equivalent emissions through load flexibilization, i.e. by shifting energy consumption to periods with high availability of renewable energy. The resulting emissions are calculated on the basis of hourly consumption and COâ‚‚eq intensity data (source: Electricity Maps) – either from smart meter data or from a simulated load curve.
In the simulation, heating and cooling is provided during the hours with the lowest COâ‚‚eq intensity. The number of hours required depends on the heat demand and the heating capacity. Higher insulation standards and larger thermal storage capacities extend the time windows for optimization, which are limited by comfort limits, and thus enable greater emission reductions.
In real operation, the hourly measured energy consumption is multiplied by the respective COâ‚‚eq intensity. The resulting emissions are then compared with the average emissions based on the energy consumption and the average COâ‚‚eq intensity.
Limits, application potential and scalability
The proposed method C only quantifies the effect of energy-flexible operation – but not the effects of intelligent efficiency improvements or demand-oriented control strategies. The latter could be estimated approximately by comparing them with the final energy demand stated in the energy performance certificate.
When measuring in real operation, it is not recorded which systems specifically contribute to the observed effect or which side effects – for example in terms of comfort – occur. It is assumed that the adaptability demonstrated to date represents a pragmatic indicator of future flexibility.
By voluntarily publishing the results on an open data platform, these could support aggregators and energy communities in particular in identifying interested and suitable participants and thus promote the development of a market for flexibility applications.
The existing EU methodology is primarily aimed at large non-residential buildings. The approach presented here, on the other hand, is also suitable for smaller buildings of all usage categories and can therefore expand the participant base, increase the available load flexibility and homogenize their distribution in the grid.
In addition to the electricity problem, the voltage problem limits the use of renewable energies, particularly in rural areas. If implemented correctly, intelligent measures can have a disproportionately high impact on a small scale by reducing grid expansion costs and improving the integration of renewable energies.
[1] Directive (EU) 2024/1275 available at: https://eur-lex.europa.eu/legal-content/DE/TXT/?uri=CELEX:32024L1275, accessed on 31.10.2025
[2] Final report on the technical support to the development of a smart readiness indicator for buildings, available at: https://op.europa.eu/en/publication-detail/-/publication/bed75757-fbb4-11ea-b44f-01aa75ed71a1/language-en, accessed on 31.10.2025
