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The Smart Readiness Indicator (SRI) is a framework introduced by the EU in 2018 to assess smart buildings in various aspects. However, the SRI has been criticized for several limitations, including its ambiguous service definitions. This paper proposes the application of Non-Intrusive-Load Monitoring (NILM) technology to enhance SRI evaluation on the example of SRI service E-12. NILM can be used to disaggregate energy consumption data to end use levels and allows for granular non-intrusive energy consumption measurement. The study involves a rigorous methodology using open sensor data and NILM algorithms to evaluate device-specific energy consumption We evaluate the IDEAL dataset and three different frequencies (5s, 15min, 1h), three different algorithms (CO, RNN, Seq2Point) and one data imputation strategies (forward filling). The results show that with a higher frequency, the performance metrics (F-score, normalized absolute error) increase. Regarding further considerations, we identify a trade-off between resource and energy efficiency, as well as privacy considerations with increasing measurement frequency. To achieve its aims for awareness, the SRI needs to consider interoperability and appropriate aggregations (frequency and spatial).
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Rehmann et al. (2024) studied this question.
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