The EU Smart Readiness Indicator (SRI) is one of the new assessment systems that incentivise greater levels of technological maturity of buildings in their transition to net-zero, with the deployment of smart technologies assumed to boost capacity and maximise the benefits provided by energy transition (e.g., managing energy storage to maximise load shifts). However, motivations to use smart technologies in practice are influenced by multiple actors and decision factors. Real-life project development navigates feasibility complexities involving considerations regarding building standards requirements, contractual obligations, budget constraints, available markets and technologies, and stakeholders’ interests [3], [4], [5], [6], [7], [8], [9], [10], [11]. Building owners want certainty on the rate of return on investment, local authorities and governments want to prove they are implementing appropriate policies, and building users are looking for decent and affordable indoor environments. This produces practical decision-making dilemmas at different stages of project development, including decisions about what levels of smartness are ‘good enough’ to achieve certain levels of energy performance [5], [12], [13], [14], [15].

This paper showcases an example of this highly dynamic decision-making process. We ‘reverse-engineer’ a social housing energy retrofit in Wales [16] to explore how and why design decisions determined specific levels of smart service delivery and residents’ controls, given the required levels of energy efficiency to be achieved in retrofit projects. Specifically, the following aspects are evaluated:

1. How design requirements were set and who decided on them in relation to implementation and operation;
2. How benefits and experiences were communicated to residents;
3. What decisions regarding the design of building operation services were taken and implemented, including how much was automated, what different degrees of automation were involved, and how much control was given to residents.

Through this case, we challenge the idea that the successful energy transition necessarily requires high levels of smartness. Rather, different SRI levels may be designed for different systems within a project to balance its technical and social performance and feasibility. We invite practitioners and policymakers to reflect on this whilst developing, promoting, and implementing smartness standards.

The case study

Inspired by whole-house low carbon retrofits delivered by the Centre for Low Carbon Built Environment (CLCBE) at the Welsh School of Architecture at Cardiff University, Swansea Council (SC) decided to increase the life and value of the assets in their own portfolio through the implementation of an affordable and replicable whole-house energy retrofit. The project aimed to implement climate-responsible, low-carbon solutions that would deliver social housing with low operational costs to tackle fuel poverty. While the choice of smart technologies was not explicitly part of the project specification, they were important to ensure that residents were able to operate the energy and indoor air quality services implemented effectively and confidently, so these services would perform as designed. The project focused on developing knowledge and guidelines for energy retrofits to be transferred and scaled up to the whole building stock [19], [20], [21]. The deep retrofit project comprised six bungalows in South Wales, built during the 1970s occupied mostly by elderly people with long-term tenancy [16].

Requirement setting and responses 

CLCBE and SC worked together to plan and design the works. Architects, engineers, asset managers, social scientists, housing officers and many other partners were engaged. The retrofit planning and design involved the assessment of the current building performance, in situ monitoring, resident needs questionnaires and semi-structured interviews, and building performance simulations. SC’s needs were addressed by establishing a co-design process through regular meetings to discuss and embed design requirements as well as to agree on the most appropriate combination of retrofit solutions to respond to the needs of the local authority and the residents. 

Figure 1 illustrates the design requirements with their respective responses for the six homes, based on ‘reverse engineering’ the project development through our analysis of project documentation and summaries of discussions from project meetings. Overarching design requirements (in white) tend to be present across the whole of SC’s portfolio of assets and beyond. The design responses, however, are context-based and were developed from sensitivity analyses which combined retrofitting building services, in grey, with retrofitting building fabric, namely loft and external wall insulation, double-glazed high-quality windows and doors, in white. They focus on delivering the best possible set of responses to fulfil project requirements listed on the left.  Constraints on these requirements included: 

1. Energy generation and heating distribution should be contained within each individual property so they could be sold separately in future if the SC needed or wanted;
2. Asset Standard Assessment Procedure (SAP) ratings to be achieved (B or higher) set by SC;
3. Building maintenance and operation specifications provided by SC to minimise additional call-out costs;
4. Resident acceptability thresholds. 

_{Figure 1. Summary of design requirements and responses for the case study.}

Design specifications were developed together between CLCBE and the SC team which differed from what was ultimately installed, as with any design process. The design process involved choosing, sizing, and specifying solutions to be procured. Through the procurement process, these options were amended according to what products were available on the market, and the additional guidance that was provided by experts working with solutions on a day-to-day basis [16], [19]. Installation, commissioning, and operation affected and changed design decisions, particularly because they involved adjusting service delivery to context and fine-tuning their operation to patterns of use. These decisions had a strong impact on how services are controlled and ultimately delivered, as well as how smart a building ends up becoming. 

The CLCBE and the SC teams worked together as decision-makers throughout the whole project, taking into account information from residents, housing officers, manufacturers, installers, commissioners and others when appropriate. This type of co-design approach was possible because the client was socially oriented, as it is a local authority, residents are long-term, and the design team had the opportunity to explore new solutions, monitor pre- and post-design, and to have conversations with the residents and client during the post-procurement stage. The CLCBE team oversaw post-occupancy evaluation (POE), monitoring energy performance and resident satisfaction for more than two years beyond the completion of the retrofit. Specifications were adjusted between procurement and installation. In addition, the opportunity to engage with residents allowed further adjustments to meet their needs and behavioural patterns. 

Service delivery and controls

We used OntoAgency [22] as a tool to analyse and visualise the amounts of smartness used to deliver the different building services from this project: mechanical ventilation with heat recovery (MVHR), heating, domestic hot water (DHW), and electricity generation and storage. OntoAgency is a relational ontology that enables us to see, among other things, what are the different levels of smartness associated with each building operation service being delivered in a project in connection with who controls each of these smart functionalities, together with the benefits they are designed to deliver. Once these are mapped, we can show how much smartness was needed in this project for residents to confidently and effectively operate the building operation services provided to reduce carbon emissions and energy bills whilst improving indoor air quality. 

Mechanical ventilation with heat recovery (MVHR)

Figure 2 shows six benefits provided by MVHR, as well as building operation services delivering them. Balanced ventilation is controlled at SRI level 0 through a continuous supply. Boosted ventilation is controlled via SRI level 3, through the MVHR control system via humidistat sensors, and can be topped up on demand manually by residents through a switch (SRI level 0). Heat recovery is controlled by a thermostat at SRI level 1, which bypasses the heat exchanger when the supply temperature exceeds 27°C.
 

_{Figure 2. MVHR service delivery together with its associated controls and degrees of smartness.}

These decisions were a product of intense interactions between the CLCBE team, the SC teams, and MVHR designers and installers. They show that when implementing MVHR, functionality levels of smart-service controls had to be disaggregated to enable balanced ventilation to:

1. Be continuously supplied via SRI level 0, enabling manual switch-off to ensure compliance with building regulations [23], [24] and wiring regulations [25];
2. Smartly controlled via SRI level 3 to ensure moisture removal at an adequate rate to prevent mould growth;
3. Manually boosted with on-off switch via SRI level 0 to ensure user control over increasing ventilation rates to, for instance, remove odours, which are difficult to detect, remove vapour from cooking, etc. 

Disaggregating the controls prevented the installation of an MVHR control panel and constrained residents' interaction with the MVHR system. Only a basic set of controls were available, so the delicate balancing for flow rates and temperatures, fine-tuned during commissioning to ensure optimal performance, could not be changed by residents.  

Heating and domestic hot water (DHW)

Figure 3 illustrates benefits and experiences, including thermal comfort, electricity savings, and hot water provision, with Legionella control provided by heating and DHW services. Heating services are provided by smart heating emission via smart radiators. Heat generation, with control of fluid temperatures, and domestic hot water storage charging is provided by a ground source heat pump (GSHP), with a control panel also reporting on heating performance. Heating emission is provided at SRI level 2 via thermostatic radiator valves connected to the GSHP, with an on-off heating option and fluid distribution temperatures pre-set by the installer, with SRI level 0 controlled automatically by the GSHP control system.
 

_{Figure 3. Heating and DHW service delivery together with its associated controls and degrees of smartness.} 
 

DHW services are fully automated with storage charging and a setback thermostat plus Legionella control [23], [26], [27]. They run on automatic on-off with scheduled charging set by installers during commissioning (SRI level 1), to ensure compliance with health and safety regulations as well as to allow GSHP and PV systems to operate at full capacity together at midday, coordinating energy demand with energy generation to maximise self-sufficiency. 

There was no cost benefit associated with a higher level of smartness to control the GSHP, as heating emission was dependent on a single-circuit thermostat. Higher levels of smartness would be cost-effective if intelligent thermostats were installed, so that loads could be predicted to anticipate demand. However, those thermostats were not chosen, as they would demand high levels of residents’ engagement and technology literacy.    

Electricity generation and storage 

Figure 4 shows benefits and experiences for electricity savings were provided by electricity optimisation and storage services via solar PV panels with an inverter plus a battery for energy storage. Optimisation and storage were controlled by SRI functionality level 1, with several reporting functions provided at SRI levels 2 and 3, but residents relied on smart meter readings providing information at SRI level 1 to make decisions related to energy use.  

_{Figure 4. Electricity generation and storage services together with its associated controls and degrees of smartness.}
 

Controls related to electricity optimisation and storage were capped at SRI level 1, despite an app being provided to residents and landlords, enabling electricity generation and storage to be effectively delivered at SRI levels 3 and 4. Increased levels of smartness were limited by contractual issues with the utility company. The owner, SC, could not be rewarded for energy export, as it did not have a customer account with the utility company for the property. The resident could opt in to an energy export tariff and receive export income, but this would be a decision for the resident to make, rather than the social landlord, SC. SC was reluctant to advise on the matter due to the very volatile electricity market and the need for staff to be constantly informed about market-leading options. Additionally, the SC was reluctant to provide residents with access to battery controls within the app, as knowledge was required to engage with the interface to prevent changes to system setup, which could result in maintenance issues and potential system errors.

Conclusions

Smart controls deployment requires a compromise between what the client and residents need, the project budget, building and services regulations, and technological limitations. Smart controls deployment is not only decided and implemented based on design stages. It also emerges from continuing negotiation between stakeholders during construction (including commissioning), hand-over and in-use stages, and is thus influenced by a range of different needs, expectations and experiences. Multiple variables formed part of the decision-making process in the case study outlined above: these were not merely technical. This case study has also revealed that:

• Control functions might need to be disaggregated to address different regulatory constraints, while at the same time ensuring adequate service provision for residents;
• Lower levels of smartness might be enough to achieve clients’ and residents’ needs;
• Smartness might need to be capped to support the ability to trade with the electricity grid.

A key overall lesson is that the choice of smart technology and levels of SRI needs to be balanced with many other factors under consideration, in their context-specific environment, and thus high levels of smartness do not need to be consistently and universally demanded or, indeed, necessarily expected to be ‘best practice’. Smart technologies should not be seen as an end goal, but as what they actually are, a tool that supports the energy transition.

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