The Smart by Powerhouse & SRI Framework: Towards a Smarter Norwegian Building Stock

The focus on enhancing the interaction between buildings, users, and the grid is a cornerstone of the green energy transition. By evaluating the smartness in existing buildings, their legacy systems can be identified and targeted for potential upgrades. This process can lead to the development of new criteria for assessing smartness in buildings.

Keywords: Smart Readiness Indicator, Smart by Powerhouse, Smart buildings, Building stock, Energy use, Norway, Non-residential buildings, Digitalization

Motivations

Recently, the focus on solutions for the green energy transition is attracting attention across various sectors. The building sector is far behind, but stakeholders, policymakers, and users are looking to adopt solutions that can enhance the sector’s efficiency without interfering with the satisfaction, health and well-being of the end users. Moreover, the building sector’s focus on smarter solutions is not only motivated by the user experience and energy efficiency. A smarter interaction with the electrical grid can indeed boost the electrification of the demand sector, allowing the deployment of renewable generation at a large scale [1]. On a neighbourhood scale, it can lead to an increase in social welfare since smart buildings and grid interaction help alleviate the grid [2].

On the global scale, 30% of the end energy usage is in the building sector [3]. In Norway, only the non-industrial building sector uses a share of 55% of the electricity use [4]. The latter and considering that the heating system of up to 80% of the households is electrified [5], shows the level of electrification on the demand side, which can be mirrored in the future in other European countries to comply with the clean energy transition targets.

The current benefits of deploying smart solutions, such as “digitalization” and “IoT device integration”, can only be fully understood when a thoughtful analysis of the smartness of the existing building stock is performed. With those purposes, the authors proposed [6] a benchmarking framework that joints together the Smart Readiness Indicator (SRI) [7], developed under the umbrella of the European Union (UE), and the Smart by Powerhouse assessment [8], created by a Norwegian consortium of stakeholders focused on developing future proof climate buildings.

Framework Development

The proposed framework contemplates the use of the SRI for measuring smart readiness and the Smart by Powerhouse (hereon known as the Smart assessment) for assessing the smartness of a building (see Figure 1). By using these tools, stakeholders (e.g., building managers, building owners) or energy policers can gain an overall understanding of the smartness of a portfolio of buildings and present the potential for improving the buildings’ capacities based on their own limitations.

Figure 1. Assessment methodology for the proposed framework [6].

Buildings in Norway are used as a study case due to the presence of highly electrified buildings; thus, modifications in the assessments were proposed to truly represent the characteristics of Norway’s building stock. In these adjustments the focus has firstly been put on the SRI assessment, where the scoring methodology is based on two main items: building category and geographical location. With these two inputs, the weights utilized for calculating the scores are defined, and they are mainly calculated based on the energy usage per domain (heating, cooling, etc.). However, the lack of specific energy-related data led the SRI’s developers to provide a simplified classification of these two inputs for dealing with this issue. Hence, the building category is subsequently split into residential and non-residential categories, while the geographic location is limited to large sub-continental zones in Europe, with Norway placed in “North Europe”. Consequently, the first modification proposed in the SRI methodology is the involvement of dedicated energy data for non-residential buildings in Norway. In Figure 2, the adaptation of the weights is presented.

Figure 2. Proposed adaptation of the weighting factors for the SRI assessment considering the local conditions of energy use and variance in the non-residential building categories [6].

Next, the energy balance weights that influence the calculations for domains such as heating, cooling, and ventilation also provide the weights for the impact of “Energy flexibility and storage”. Under the highly electrified building stock, the importance of this impact needs to be redefined to highlight the importance of the building/grid interaction. Moreover, “flexibility” corresponds to an active operational measure; thus, it should be seen in that context and not calculated based on yearly energy usage. Consequently, a new “Power balance” is proposed (see Figure 3) to account for the hourly impact of the different domains, which represent some characteristics of energy flexibility such as “power curtailment” or “grid congestion”.

Figure 3. Proposed changes in the energy balance weighting factors for the SRI assessment [6].

The second assessment part of the framework, the Smart by Powerhouse, was originally developed to measure commercial buildings’ smartness at the design stage. This involved updating the definition of the functional requirements to make it applicable to general non-residential buildings and extending its use to already constructed buildings. In order to enhance the comprehensiveness of the assessment, a new scoring system was implemented. Additionally, two new levels of technological smartness were defined as “No Technological Equipment” and ”Pre-Automated.” These levels augment the existing ones: “Automated”, ”Smart Ready”, ”Smart Standard”, ”Smart Predictive”, and ”Smart Cognitive”.

Smartness and Smart Readiness Assessment in Non-Residential Norwegian Buildings

The framework was tested in ten non-industrial pilot buildings (“Care facility”, “Sport building”, “School”, and “Health centre”) in Ålesund, Norway, provided by Ålesund Commune as part of the COLLECTiEF project [9]. These buildings were selected to represent a diverse range of energy systems and construction dates.

The proposed modifications of the SRI assessment are represented by the results of the SRI and aggregated scores presented in Table 1. The results show that using dedicated building category data for the specific country, as well as modifying the “flexibility” related calculation weights, results in a negative variation of the SRI score, ranging between 0% and 3.4%. Moreover, energy-related aggregated scores mostly led to negative variations but highlighted the larger variations in the “Grid” score, indicating that the importance of “flexibility” was addressed.

Table 1. Overall SRI scores. The difference between the calculated SRI with the customized weights and the SRI based on the original weights defined for non-residential buildings in Northern Europe is presented in parenthesis [6].

For the general assessment, a comparison between the Smart by Powerhouse and the overall SRI score is shown in Figure 4. The results indicate that the complete sample of buildings is located just above the “Automatized” level of smartness. The same sample shows an overall performance for the SRI in the range of 20-35%, where 100% indicates a total smart-ready building.

Figure 4. Overall score for the Smart/SRI framework [6].

Conclusion

The study proposed a novel framework by jointly assessing the smart readiness (SRI) and smartness (Smart by Powerhouse) in buildings with a modified version of the SRI and Smart by Powerhouse assessments, respectively. The proposed modifications led to a more building- and country-specific SRI assessment by highlighting a dedicated representation of energy usage and the importance of “flexibility” participation. Next, the results of applying the framework in the building samples indicate a low smartness and smart readiness in the buildings independently of the corresponding category (sport buildings, health centres etc.). Moreover, the building sample shows that physical tools such as sensors, actuators, and data collection exist in the buildings; thus, the buildings present the potential to become “Smart buildings”. Similarly, the low “Grid” aggregated scores indicate that the interaction between buildings and the grid needs to be addressed by updating the legacy systems in the buildings.

Acknowledgment

This work has been written with the LifeLine-2050 project, funded by the Faculty of Engineering (IV) at the Norwegian University of Science and Technology (NTNU). The LifeLine-2050 project is a flagship project with the NTNU’s Centre for Green Shift in the Built Environment (Green2050). The authors gratefully acknowledge the support of Green2050’s partners and the encouragement of the innovation committee of IV faculty at NTNU. The authors acknowledge the COLLECTiEF project that has received research funding from European Union’s H2020 research and innovation programme under Grant Agreement No 101033683. The authors wish to thank Ålesund Kommunale Eigedom (ÅKE) and EM Systemer for providing access to the pilot buildings and data.

References

[1]        IRENA (2019). Demand-side flexibility for power sector transformation: Analytical Brief. International Renewable Energy Agency, Abu Dhabi.

[2]        Hajati, M., et al. (2024). Maximizing social welfare in local flexibility markets by integrating the value of flexibility loss (VOFL). Electr. Power Syst. Res., vol. 235, p. 110840, Oct. 2024. https://doi.org/10.1016/j.epsr.2024.110840.

[3]        IEA (2023). World Energy Outlook. International Energy Agency (IEA), France.

[4]        SSB, (2024). Production and consumption of energy, energy balance and energy account. SSB. [Online. Accessed: Aug. 13, 2024]. Available: https://www.ssb.no/en/energi-og-industri/energi/statistikk/produksjon-og-forbruk-av-energi-energibalanse-og-energiregnskap

[5]        Energifakta Norge. Energy use by sector. Norwegian Energy. [Online. Accessed: Aug. 13, 2024]. Available: https://energifaktanorge.no/en/norsk-energibruk/energibruken-i-ulike-sektorer/

[6]        Campodonico Avendano, I. A. et al. (2024). A novel framework for assessing the smartness and the smart readiness level in highly electrified non-residential buildings: A Norwegian case study. Energy Build, vol. 314, p. 114234. https://doi.org/10.1016/j.enbuild.2024.114234.

[7]        Ma, Y. et al. (2023). Smart Readiness Indicator (SRI): Assessment Package: Practical Guide SRI Calculation Framework v 4.5.

[8]        Powerhouse (2019). Smart by Powerhouse. Powerhouse.

[9]        M. Aghaei et al.(2023). Collective Intelligence for Energy Flexibility – Collectief: An EU H2020 Project for Enhancing Energy Efficiency and Flexibility in Existing Buildings. 2023 International Conference on Future Energy Solutions (FES). Jun. 2023, pp. 1–6. https://doi.org/10.1109/FES57669.2023.10182779.