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Highlights • Calibrated models used to improve accuracy of predicted absolute savings from deep retrofit solutions. • Calibration method using in situ test results validated against pre- and post-retrofit measurements. • In situ test results presented for fabric performance of solid wall no-fines concrete dwellings and for traditional and innovative external wall insulation systems. • Co-pressurisation test results shown to have a significant impact on modelled energy performance. Abstract There remains a significant number of occupied and uninsulated solid wall dwellings in the UK. Deep retrofit is often required for these buildings to become energy efficient but it is difficult to determine how these buildings will respond to retrofit without a detailed understanding of their fabric thermal performance Greater certainty can however be achieved by combining theoretical models and practical field tests, prior to the design of retrofit programmes. This type of approach can then be used to inform and optimize the design of retrofit interventions. This paper presents results from a series of in situ fabric performance tests undertaken on two no-fines concrete, conjoined dwellings pre- and post-retrofit and demonstrates how empirical data can be used to inform and calibrate the thermal performance of dynamic simulation models (DSMs). This is a particularly pragmatic calibration method as it eliminates the need for actual weather data, which is expensive and prohibitive to collect and collate. The DSM inputs and outputs were compared with those obtained from Standard Assessment Procedure (SAP) calculations. The results illustrate how the fabric performance of no-fines concrete can vary between similar house types within the same development. This research also validates the effectiveness of the calibration methodology that uses the whole house Heat Transfer Coefficient (HTC) as the qualifying metric. Furthermore, results also emphasize the importance of appropriately characterizing the physical properties of existing buildings before designing retrofit strategies. This paper contributes to the growing knowledge base concerned with the energy performance gap. In this instance, SAP predicts higher absolute savings then measured in situ which is problematic when assessing the financial viability of retrofits. [ABSTRACT FROM AUTHOR]

This paper investigates factors associated with variation in daily total (electricity and gas) energy consumption in domestic buildings using linked pre-COVID-19 smart meter, weather, building thermal characteristics, and socio-technical survey data covering appliance ownership, demographics, behaviours, and attitudes for two nested sub-samples of 1418 and 682 British households selected from the Smart Energy Research Laboratory (SERL) Observatory panel. Linear mixed effects modelling resulted in adjusted R2 between 63% and 80% depending on sample size and combinations of contextual data used. Increased daily energy consumption was significantly associated (p -value < 0.05, VIF < 5) with: households living in buildings with more rooms and bedrooms, that are older, more detached, have air-conditioning, and experience colder (more heating degree days) or less sunny weather; households with more adult occupants, more children, older adult occupants, higher heating temperature setpoints, and that do not try to save energy. The results demonstrate the value of smart meter data linked with contextual data for improving understanding of energy demand in British housing. Accredited UK researchers are invited to apply to access the data, which has recently been updated to include over 13,000 households from across Great Britain. This paper provides guidance on appropriate methods to use when analysing the data. [ABSTRACT FROM AUTHOR]

• Over the technologies' typical 20-year lifetime, most UK dwellings have a cost optimum low-carbon heating system using air source heat pumps. • Dwelling properties and spatiotemporal variabilities significantly change the optimum low-carbon technology from blue hydrogen boilers, direct electrical heating, and air source heat pumps, to ground source heat pumps. • Direct electrical heating is economically preferred over heat pumps in lower demand dwellings and with analysis over shorter timescales. • Incentives for low-carbon heating need to target adoption of efficient technologies to reduce the greater increase in network demands. An understanding of heating technologies from the consumers' perspective is critical to ensure low-carbon technologies are adopted for reducing their current associated emissions. Existing studies from the consumers' perspective do not compare and optimise the full range and combinations of potential heating systems. There is also little consideration of how spatiotemporal and dwelling variations combined alter the economic and environmental effectiveness of technologies. The novelty of this paper is the creation and use of a new comprehensive framework to capture the range of heating technologies and their viability for any specific dwelling's traits and climate from customers' perspective which is missing from current studies. The model optimises combinations of prime heaters, energy sources, ancillary solar technologies and sizes, thermal energy storage sizes and tariffs with hourly heating simulation across a year and compares their operation, capital, and lifetime costs alongside emissions to realise the true preferential heating systems for customers, which could be used by various stakeholders. Using the UK as a case study, the results show electrified heating is generally the optimum lifetime cost solution, mainly from air source heat pumps coupled with photovoltaics. However, direct electrical heating becomes more economically viable as dwelling demands reduce from smaller dwellings or warmer climates, as shorter durations of the ownership are considered, or with capital cost constraints from lower income households. Understanding this is of high importance, as without correctly targeted incentives, a larger uptake of direct electrical heating may occur, which will burden the electrical network and generation to a greater extent than more efficient heat pumps. [ABSTRACT FROM AUTHOR]

The modeling and simulation of domestic hot water systems, including solar thermal and co-generation technologies, relies on accurate, high time-step resolution water consumption profiles. Due to the expensive nature of field studies, previous profiles have been limited in number of participants, or have been generated synthetically using probabilistic modelling techniques. The Solar City program in Halifax has measured hot water flow rate and temperature data in 119 homes at a time-step of 1 min; and includes a survey of occupancy rates and other relevant meta-data. In this paper, we discuss the data acquisition and processing (with a focus on flow rate data), and conduct analysis to reveal consumption trends and produce a new set of time-step profiles for modeling and simulation. Average hot water consumption per household is 172 L/day with a strong dependency on number of occupants. The hourly profile peaks twice daily, and shifts by several hours on Sunday. The average draw temperature was found to be 51.8 °C, which is lower than the default value of 55 °C applied by many building modeling/simulation packages. The average cold water supply temperature was found to be roughly sinusoidal about 12.4 °C with approximately one-month lag compared to ambient air temperature. [ABSTRACT FROM AUTHOR]