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Several studies have demonstrated the capability of data-driven modelling based on on-site measurements to characterise the thermal performance of building envelopes. Currently, such methods include steady-state and dynamic heating experiments and have mainly been applied to scale models and unoccupied test buildings. Nonetheless, it is proposed to upscale these concepts to characterise the thermal performance of in-use buildings based on on-board monitoring (OBM) devices which gather long-term operational data (e.g., room temperatures, gas and electricity consumption...). It remains, however, to be proven whether in-use data could be a cost-effective, practical and reliable alternative for the dedicated tests whose more intrusive measurements require on-site inspections. Furthermore, it is presently unclear what the optimal experimental design of the OBM would be and which data analysis methods would be adequate. This paper presents a first step in bridging this knowledge gap, by using on-board monitoring data to characterise the overall heat loss coefficient (HLC) [W/K] of an occupied, well-insulated single-family house in the UK. With the aid of a detailed building physical framework and specifically selected data subsets a sensitivity analysis is carried out to analyse the impact of the measurement set-up, the duration of the measurement campaign and the applied data analysis method. Although the exact HLC of the building is unknown and no absolute errors could hence be calculated, this paper provides a new understanding of the decisions that have to be made during the process from design of experiment to data analysis. It is demonstrated that such judgements can lead to differences in the mean HLC estimate of up to 89.5%. [ABSTRACT FROM AUTHOR]

• Overheating regulations and calculation methods in 26 European countries were compared. • Most of the existing calculation methods are outdated and do not fit climate-proof buildings. • France requires a mixed-mode operation of naturally ventilated households. • The UK developed a heatwave-based calculation approach. • Comfort-based, multi-zonal, and time-integrated calculation approaches are needed. With the ongoing significance of overheating calculations in the residential building sector, building codes such as the European Energy Performance of Building Directive (EPBD) are essential for harmonizing the indicators and performance thresholds. This paper investigates Europe's overheating calculation methods, indicators, and thresholds and evaluates their ability to address climate change and heat events. e study aims to identify the suitability of existing overheating calculation methods and propose recommendations for the EPBD. The study results provide a cross-sectional overview of twenty-six European countries. The most influential overheating calculation criteria are listed the best approaches are ranked. The paper provides a thorough comparative assessment and recommendations to align current calculations with climate-sensitive metrics. The results suggest a framework and key performance indicators that are comfort-based, multi-zonal, and time-integrated to calculate overheating and modify the EU's next building energy efficiency regulations. The results can help policymakers and building professionals to develop the next overheating calculation framework and approach for the future development of climate-proof and resilient residential buildings. [ABSTRACT FROM AUTHOR]

• Drain water heat recovery potential of commercial kitchens is examined. • Financially feasible potential in the hospitality sector in the UK is 1.24 TWh / yr. • This can be achieved at 2.94 p £/ kg Ce saved , over a 10-year lifetime. • This leads to 344 k tons Ce / yr reduced emissions. • 160 GWh (a reduction of 44 k tons Ce / yr) remains commercially unexploitable. In order to meet ambitious greenhouse gas reduction targets, the reduction of fuel consumption in the heating sector is necessary. This paper assesses the impact of introducing direct drain water heat recovery systems in commercial kitchens in the UK, based on a commercially available heat exchangers. The recoverable heat from these kitchens was estimated using Monte Carlo simulation, sector consumption data, and data measured in the field. A financial criterion, the Net Present Value calculated over 10 years, was used to estimate feasibility threshold values for the kitchen water consumption, varying with the heating fuel used in each premises. This analysis resulted in a total financially feasible potential for drain water heat recovery in the hospitality and food service sector in the UK of approximately 1.24 TWh / yr , leading to a reduction in GHG emissions of 344 k tons Ce / yr. This could be achieved at a cost of approximately 2.94 p £/ kg Ce saved , over a 10-year lifetime, which was several orders of magnitude smaller than traditional renewable heat sources such as heat pumps. Commercially available drain water heat recovery systems could, when installed, exploit around 88% of current potential in drain water heat in commercial kitchens (1.40 TWh / yr) in a manner that is financially profitable. However, this paper assumes the availability of a 2 m vertical drop in the kitchen drain, required to install the heat exchanger, and thus achieve optimal effectiveness. In case this head is not available, the heat recovery potential would be untapped, as in approximately 160 GWh , in kitchens where the hot water consumption is too small for financial profitability. This corresponds to a reduction in GHG emissions of 44 k tons Ce / yr and leaves a gap in the market for inexpensive DWHR devices, which could exploit this potential at lower efficiencies. [ABSTRACT FROM AUTHOR]

Highlights • The first stochastic models of manual overrides were developed from measured data. • Measurements were collected in ten UK dwellings and analysed over a heating season. • The drivers of manual heating override behaviour are investigated. • The models can be implemented in building performance simulation applications. Abstract This paper investigates the physical environmental (indoor and outdoor temperature and relative humidity, wind speed, solar radiation and rainfall) and contextual drivers (time of day) affecting occupants' manual space heating override behaviour during the heating season based on measurements collected in ten UK dwellings. Logistic regression modelling is used to understand the probability of occupants manually overriding their scheduled heating periods. To the authors' knowledge, these are the first stochastic models of manual heating override behaviour developed for residential buildings. The work reported in this paper suggests that occupants' manual overrides are influenced by indoor and outdoor temperature, indoor relative humidity, and solar radiation. In addition, the effects of the physical environmental variables varied in relation to the time of day. At night, none of the physical environmental variables influenced manual overrides. In the morning, afternoon and evening, manual overrides were governed by a mix of indoor air temperature, indoor relative humidity and solar radiation. The models presented can be used in building performance simulation applications to improve the inputs for space heating behaviour in residential buildings and thus the predictions of energy use and indoor environmental conditions. [ABSTRACT FROM AUTHOR]

In the face of a changing climate, a growing number of construction firms are adopting carbon reduction targets on individual projects and across their portfolios. In the wake of the Paris Agreement, some firms are seeking a means of aligning their targets with sectoral, national and international mitigation commitments. There are numerous ways by which such an alignment can be achieved, each requiring different assumptions. Using data from the UK construction industry, this paper reviews current company commitments and progress in carbon mitigation; analyses the unique challenges in aligning construction targets, and presents a series of possible sectoral decarbonisation trajectories. The results highlight the disparity between current company targets and the range of possible trajectories. It is clear that a cross-industry dialogue is urgently required to establish an appropriate response that delivers both a widely-accepted target trajectory and a plan for its delivery. This paper is intended to stimulate and support this necessary debate by illustrating the impact of different methodological assumptions and highlighting the critical features of an appropriate response. [ABSTRACT FROM AUTHOR]

There has been general recognition within the construction industry that there is a discrepancy between the amount of energy that buildings actually use and what designers considered that they should use. This phenomenon is termed “The Performance Gap” and is normally associated with new buildings. However, existing and older buildings contribute a greater amount of operational carbon. In response to the Performance Gap, CIBSE have developed the TM54 process which is aimed at improving energy estimates at design stage. This paper considers how the TM54 process can also be used to develop energy management procedures for existing buildings. The paper describes an exercise carried out for a university workshop building in which design energy use has been compared with the actual building energy use and standard benchmarks. Moreover, a sensitivity assessment has been carried out using different scenarios based on operation hours of building/equipment, boiler efficiency and impact of climate change. The analysis of these results showed high uncertainty in estimates of energy consumption. If carbon challenges are to be met then improved energy management techniques will require a more systematic approach so that facilities managers can identify energy streams and pinpoint problems, particularly where they have assumed responsibility for existing buildings which often have a legacy of poorly metered fuel consumption. [ABSTRACT FROM AUTHOR]

A Domestic Operational Rating (DOR) scheme is presented for assessing the energy performance of occupied dwellings. The DOR is complementary to the method used to generate the asset rating of UK dwellings: the Standard Assessment Procedure (SAP). The DOR is transparent, easy to calculate, based on readily available information, producible from daily smart meter data, calculable for any period on a rolling year basis and applicable across all UK homes. The DOR method was developed using a new primary data set collected from 114 homes as part of the DEFACTO project. All were semi-detached, gas centrally heated, privately owned and internet connected properties, located in the English Midlands. The mean daily energy demands are analysed alongside information gathered through an energy survey and household questionnaires. These data are presented and analysed for the first time in this paper. The DOR method, which is described in full, generates metrics that indicate the absolute and relative energy demands, greenhouse gas emissions and energy costs of homes. The DOR ratings for the D114 homes were stable from year to year. Comparing the DOR with homes' asset (SAP) ratings, indicates that the SAP rating poorly reflects the inter-home variation of households' actual energy demand. For the D114 homes, it was possible produce a reduced data Domestic Operational Rating, rdDOR, using the energy demands measured on only a few cold days. Although developed in the UK context, the DOR is generally applicable to national, regional or local housing stocks in which daily energy demand is metered. Potential improvements to the DOR, and the need for trials using smart meter data from diverse homes and locations, are discussed. [ABSTRACT FROM AUTHOR]

Building stock modelling usually deploys representative building archetypes to obtain reliable results of annual energy heating demand and to minimise the associated computational cost. Available methodologies define archetypes considering only the physical characteristics of buildings. Uniform occupancy schedules, which correspond to national averages, are generally used in archetype energy simulations, despite evidence of occupancy schedules which can vary considerably for each building. This paper presents a new methodology to define occupancy-integrated archetypes. The novel feature of these archetype models is the integration of different occupancy schedules within the archetype itself. This allows building stock energy simulations of national population subgroups characterised by specific occupancy profiles to be undertaken. The importance of including occupant-related data in residential archetypes, which is different than the national average, is demonstrated by applying the methodology to the UK national building stock. The resultant occupancy-integrated archetypes are then modelled to obtain the annual final heating energy demand. It is shown that the relative difference between the heating demand of occupancy-integrated archetypes and uniform occupancy archetypes can be up to 30%. [ABSTRACT FROM AUTHOR]

• EV presents a technical challenge to the grid and an opportunity to introduce sustainable and novel solutions. • A sustainable energy strategy is proposed to exploit the synergy between EV batteries and heat pumps. • Electrification of transport and heat in buildings can reduce typical householder carbon footprint by up to 87%. The demand for electricity has been increasing worldwide and it is predicted that this trend will be particularly reinforced in developing countries by the gradual electrification of the transport sector and heat generation in buildings. The energy supply infrastructure required to meet the additional electricity demand should be carefully managed in light of the climate change carbon emission targets and commitments. A large proportion of the new electricity loads will be met from renewable sources. Therefore, means of power storage become vital to smooth out the intermittent nature of these energy supplies. The introduction of Electric Vehicles (EVs) could provide a viable and dynamic power storage solution through the concept of Vehicle-to-everything (V2X). This involves the storage of renewable energy (RE) in EV batteries during the charging cycle and restitution to the grid (V2G) or homes (V2H) when needed. In this context, this paper presents a methodology involving several strategies to stabilise the grid system and examines the impact of various types of EVs and heat pumps (HPs) for supplying heat in buildings. The results of this research approach show that the synergy of using V2H could reduce the carbon footprint of a typical domestic building in the United Kingdom (UK) by up to 87% and potentially recover up to 21.9 kWh/day of surplus renewable energy. [ABSTRACT FROM AUTHOR]

• Households change their heating patterns when they switch to a heat pump. • Typically, a setback temperature 2–5 °C lower than the desired thermostat setting. • We calculate the increase in heat demand with varied parameters. • The increase in heat demand is determined by heat loss and thermal mass. • This would be a useful metric for 'heat pump readiness'. Heating with air source heat pumps is an important step in the transition to Net Zero Carbon for many households. When predicting the resulting energy consumption it is frequently assumed that heating demand is unchanged from before the switch from gas heating. However, heating patterns usually change, with a net increase in heating demand to achieve the same level of thermal comfort. This paper discusses the change in pattern and uses modelling to determine the resulting increase in energy demand. It shows that the increase can be predicted with information about dwelling heat loss and thermal mass as well as weather and the pre and post switch heating pattern. The increase can be 20% or more for homes with high heat loss. It proposes that the metric for heating demand increase would be a useful measure of heat pump readiness, and that the parameters required to assess this should be provided on energy performance certificates. [ABSTRACT FROM AUTHOR]

This paper investigates the potential for incorporation of human commercial building design modelling into the pig production industry. During the last decades pig building design has relied heavily on building manufacturers compared to human commercial buildings that regulate standards to improve the sustainability of the building. Thus, the aim of this paper was to gain a greater understanding of the design requirements for sustainable forms of pig housing, which could potentially improve the welfare of the pig and promote greater resource use efficiency. Part of an existing mechanically ventilated UK pig production building, which represents three adjacent fully-slatted units each capable of holding approximately 292 pigs and measuring approximately 18 m x 14m, was used as a basis to create a dynamic thermal model of the building. The model takes into account the possibility of future rises in environmental temperature and the effect of this climate change on building performance and pig growth, feed efficiency and welfare. The results of the model showed that as the finishing pigs increased in size they have the potential to be subject to increasingly poor indoor air quality, during the winter months. The model also shows that improving the thermal properties of the building not only helps with reducing the amount of time that the pigs could potentially spend at extreme low temperatures, by approximately 1115 h (46 days), but can also help with reducing the number of hours the pigs spend above 26 °C during the summer months, by approximately 8 h. [ABSTRACT FROM AUTHOR]

Highlights • A method is presented for non-intrusively inferring a building Heat Loss Coefficient using smart meter data. • For the sample data from the UK Energy Demand Research Project, a median Heat Loss Coefficient of 0.14 kW/°C and uncertainty of 15% was estimated. • The method was demonstrated to be reliably scalable to large numbers of buildings, enabling rapid thermal performance evaluation at a regional or national scale. • The method was demonstrated to produce stable results across several years, indicating its robustness to climate variation and occupant effects. Abstract Dwellings in the UK account for about 25% of global energy demand, of which 60% is space heating making this a key area for efficiency improvement. Dwelling UK Energy Performance Certificates (EPC) are currently based on surveyed data, rather than energy use monitoring. The installation of smart meters provides an opportunity to develop an EPC based on in situ dwelling thermal performance. This paper presents 'Deconstruct' – a method of estimating the as-built Heat Power Loss Coefficient (HPLC) of occupied dwellings as a measure of thermal performance, using just smart-meter and meteorological data. Deconstruct is a steady-state grey box building model combined with a data processing pipeline and a model fitting method that limits the effects of confounding factors. Smart meter data from 780 UK dwellings from the UK Energy Demand Research Project (EDRP), was used to calculate a median HPLC of 0.28 kW/°C (±15%). The stability of the estimate across multiple years of data with different weather and energy use was demonstrated. Deconstruct was found to be suitable for large scale inference of dwelling thermal properties using the UK's new smart metering data infrastructure. [ABSTRACT FROM AUTHOR]

Abstract In the UK, housing has been identified as a major sector for contributing to the 80% reduction in carbon emissions over the 1990 baseline by 2050, required by the Climate Change Act 2008. However, pre-1919 housing stock is the least energy efficient and consequently poses challenges to meeting this target. Using a mixed methods approach, the current study demonstrates that, in actuality, there is a significant potential for reducing emissions among this sub-sector of housing, and that the major barriers to energy efficiency retrofits concern a lack of funding, the payback period for the investment, disruption to home life and finding a trustworthy and skilled installer. Moreover, this study finds that homeowners are motivated primarily by the desire to improve home comfort and aesthetics along with a reduction in energy bills rather than in reducing carbon emissions. The paper concludes with recommendations for improving the viability of retrofitting pre-1919 homes through enhanced financial resources, policy support and the promotion of social and economic benefits. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the influence of building fabric, services and occupant related factors on actual energy use of six case study dwellings, located in three new low energy social housing developments in UK, covering a variety of built forms and construction systems (timber frame, hempcrete, steel-frame). Physical monitoring of indoor environment and window-opening is cross-related with building fabric and systems’ performance, and qualitative data gathered through occupant surveys, review of control interfaces and handover guidance, to understand the causes of the gap between modelled and measured energy use. Actual energy use is found to exceed design expectations by a factor of three, questioning the need for whole-house mechanical ventilation heat recovery (MVHR) systems at measured air permeability rates of 6 m³/(h.m²) against the design target of 3 m³/(h.m²). Lack of proper commissioning of MVHR and heating systems, combined with inadequate user comprehension about their operation and control leads to occupant ‘misuse’ wherein systems are de-activated, thereby negatively affecting indoor air quality. This is confounded by occupant factors related to higher demand temperatures, unexpected opening of windows during winters due to under-performance of MVHR combined with habitual behaviours, and over-use of heating systems to compensate for higher than expected air permeability. [ABSTRACT FROM AUTHOR]

This paper provides an analysis of the relationships between dwelling, household and motivation, behaviour and perception characteristics and thermostatic radiator valve (TRV) settings in living rooms ( n  = 187) and bedrooms ( n  = 159) in UK social housing. The work capitalises on primary data from a socio-technical household survey undertaken in Plymouth, UK during 2015, which was coupled with building audit data. The mean reported TRV setpoint temperatures in the living rooms and bedrooms were 23.4 °C and 21.9 °C, implying that occupants prefer cooler conditions in bedrooms. There were systematic variations according to dwelling, household, and motivation, behaviour and perception characteristics. In general, the setpoint temperatures in individual rooms were higher than the whole house thermostat setpoint temperature, implying that there may be a misunderstanding of the role of TRVs in the home heating system. The research could enable social housing providers, the government and commercial organisations to target energy efficiency measures (i.e. thermal upgrades) and social interventions (i.e. behaviour change) at those dwellings and households where their impact may be most beneficial. The results presented could also be used to improve the assumptions of zonal heating behaviour in energy models, which could result in more realistic predictions of the heating demands of social housing. [ABSTRACT FROM AUTHOR]

The four Higher Education Funding Councils in the United Kingdom want all universities to reduce CO 2 emissions by 34% by 2020 compared to a 2005 base. Universities that have installed Combined Heat and Power (CHP) technology are making good moves towards achieving their CO 2 reduction target. For a CHP project to be successful, a detailed technical, economic and environmental assessment is required. Generally, this assessment is carried out using a computer-based model. Currently, available CHP models have limitations in terms of flexibility, accuracy, reliability and complexity and their use could result in an undersized or oversized CHP scheme that could lead to a complete failure of the project. Therefore, there is an urgent need for a robust and user-friendly model, which integrates multiple features that are missing in the currently available models. This paper presents the development of a spreadsheet based CHP sizing model for a single or multiple university buildings. The major strengths of the model are its simplicity, flexibility of data entry, selection of multiple electrical and thermal demands, an in-built real database for a range of CHP sizes, multiple control strategies, multiple investment routes and their life cycle cash flow analysis, and the potential for detailed sensitivity analysis of payback period using the Monto Carlo Simulation technique. The model, which we call the London South Bank University (LSBU) CHP model, has been tested with three other CHP models for different control modes for the same building and the comparisons are discussed. [ABSTRACT FROM AUTHOR]

This paper provides an analysis of the appliance ownership and use factors contributing to high electrical energy demand in UK homes. The data were collected during a large-scale, city-wide survey, carried out in Leicester, UK, in 2009–2010. Annual electricity consumption and appliance ownership and use were established for 183 dwellings and an odds ratio analysis used to identify the factors that led to high electricity consumption. Many of the appliance ownership and use factors have not previously been studied for the UK domestic sector. The results of this study should be of key interest to government policy makers and energy supply companies interested in the underlying drivers of the highly positively skewed distribution of UK domestic electricity use. The study identifies those appliances that could be targeted for technical improvements or subjected to campaigns to encourage more energy efficient use in order to reduce electricity consumption among high demand households. This paper builds on earlier work by the current authors which identified the households (socio-demographic and dwelling characteristics) most likely to be high electricity consumers. The current work provides the basis for advice and guidance to those households that would enable them to, over time, reduce their electricity use. [ABSTRACT FROM AUTHOR]

[Display omitted] • A whole system approach to studying a low-temperature HGSHP system. • 3D coupled TH model with realistic boundaries and dynamic heat pump COP. • Design of a HGSHP system to support a 5th generation DHC network. • Different factors on performance of the HGSHP system and ground thermal behaviour. • Ground moisture transfer, cooling process and buried depth are important. Exploitation of shallow ground and its low-grade heat potential is fundamental to designing 5th generation district heating and cooling (DHC) networks. Horizontal ground-source heat pump (HGSHP) systems are a common way to utilize shallow geothermal energy. Realistic estimation and prediction of performance of a HGSHP system and shallow ground thermal behaviour should consider the whole system including building heating and cooling load, heat pump and ground heat exchanger, and the ground. This should be accompanied by realistic atmospheric and ground conditions. In this paper, a three-dimensional coupled thermal–hydraulic model with realistic boundary conditions adopting a whole system approach is presented. Dynamic heat pump coefficient of performance (COP) that depends on seasonal variation of heating/cooling demand and ground conditions are also considered. Model validations are conducted against experimental and analytical results in literatures. The model is applied for evaluating a HGSHP system to support development of a 5th generation DHC network on a potential site in the UK. Several influencing factors, such as ground moisture transfer, building thermal load mode, buried depth of ground loops, and initial ground temperature profile are studied to assess performance efficiency of the HGSHP system and evolution of ground thermal behaviour in response to heat extraction or rejection into the ground. The results show that 5% of the monthly total heat demand of the site could be met by the designed HGSHP system, consisting of 200 U-shaped ground loops buried at the depth of 3 m and pure water as the heat carrier. Overlooking the ground moisture transfer or hyperbolizing the ground saturation would overestimate the load-carrying capacity of the HGSHP system. The HGSHP system is more efficient with a higher heat pump COP under the heating and cooling mode than under the heating-only mode. Predicted performance of the HGSHP system improves with buried depth of the ground loops. The results also show that a 1 ℃ increase in the undisturbed ground temperature could suffice up to 8% of the monthly total heat demand of the site. [ABSTRACT FROM AUTHOR]

• A well-functioning space heating system can operate below 70 °C for 98% of the year and below 55 °C for 71% of the year. • The performance gap between measured and calculated energy use is widening across building age groups, with a clear increase for post-1980 buildings. • Pre-1980 buildings can operate with supply temperatures below 70 °C for 96–99% of the year and below 55 °C for 67–71% of the year. • Building envelope improvement, whilst recommended, is not a pre-requisite for using low-temperature supply in pre-1980 buildings. • Post-1980 buildings could have limitations in respect of using low-temperature heat under windy conditions. Decarbonising heat in the UK by 2050 will require the wider adoption of low-temperature heat. Current systems, largely relying on gas boilers, have design operating temperatures of 82/71 °C (supply/return) while new standards for 4th Generation District Heating are 55/25 °C. Local authorities must set-up strategies to get their buildings "Heat network ready" but this raises the question of the ability for existing buildings to use low-temperature heat. The aim and the novelty of this paper is to establish a relationship between an energy 'performance gap' in Scottish public buildings and their ability to use low-temperature heat. This performance gap has been evaluated for 121 non-domestic buildings, primarily schools, operated by The City of Edinburgh Council. Space heating system are assumed oversized by 10%. The results show that renovation of the building envelope, while highly desirable, is not a pre-requisite for using low-temperature heat in pre-1980 constructed buildings, which represent 64% of the stock. It also highlights that post-1980 buildings, predominantly utilising mechanical ventilation systems, demonstrate an increasing performance gap which could limit their ability to use reduced operating temperature, especially in windy conditions. [ABSTRACT FROM AUTHOR]

• GB domestic heat pump electricity demand in 2050 is modelled. • Modelling is based on monitored data from heat pumps and gas boilers in homes. • Uptake of heat pumps in all homes more than doubles peak GB electricity demand. • Moderate improvements in HP performance and dwelling fabric reduce peak GB demand. • Flexibility in DHW and space heating provision also reduce peak GB demand. To meet net zero carbon targets by 2050s, countries with cold winters, such as Great Britain (GB), will turn to low carbon domestic heating systems such as electric heat pumps. In this paper, a statistical model is developed using measured performance data from over 550 heat pumps installed in GB homes in 2012. The model is used to predict the additional load on the GB electricity generation and distribution infrastructure for various current and future (2050) climates, dwelling energy efficiencies and heat pump deployment scenarios. For a cold year in the 2020s, a 100% uptake of heat pumps in the existing GB dwelling stock gave a peak electricity demand for the heat pumps of 78 GW and an annual electricity demand of 189 TWh. When added to the other, existing electricity demand, this represents an increase in the GB peak electricity demand in excess of 100% and an annual electricity demand increase of around 60%. Making reasonable assumptions about heat pumps' future efficiency and use, and the future climate and dwelling stock fabric efficiency, and assuming 80% heat pump uptake and no load shifting, the peak heat pump electricity demand for a cold year in the 2050s halved to 37 GW. By shifting demand for water and space heating the 2020s cold year peak demand reduced by 15%. The work provides a more robust estimate of future GB heat pump electricity demands than any previously available. The predicted future ramp rates, peak and annual total electricity demands, are lower than predicted by previous analysts. [ABSTRACT FROM AUTHOR]

Residential buildings account for significant proportions of energy demand and greenhouse gas emissions. The dwelling and occupants together have a strong impact on the temporal characteristics of energy demand. This paper presents and validates a new stochastic electricity, space heating (SH) and domestic hot water (DHW) model for UK residential buildings, called CREST Heat and Power (CHAP). The open source model is easily adaptable to over 14,000 different building configurations, which represent the UK residential building stock. A validation with empirical data on domestic hot water, gas demand, and internal temperatures demonstrates the accuracy of the new SH and DHW parts of the model. Notwithstanding some uncertainties in extracting the DHW run-off profiles, the energy consumption, water volume, and the dependency on the number of residents are all well considered. The CHAP model produces mean SH, DHW and temperature profiles that are broadly in agreement with the employed field studies. Future work should focus on the consideration of appliances at the heat/power interface, improving the DHW calibration and extending the approach to other national contexts. [ABSTRACT FROM AUTHOR]

This paper presents the methodological approach and findings of a simulation study of advanced energy conservation, generation and management technologies applied to two case study dwellings in the UK, so as to achieve net zero energy (NZE) target that includes a reduction of net regulated energy (HVAC) to 0 kWh/m 2 per year and energy generation of at least 50 kWh/m 2 per year. The performance of the dwellings are also tested for a change in energy use and risk of summertime overheating in future climates in the short (2030s), medium (2050s) and long term (2080s). The findings indicate that to meet the NZE targets, regulated loads need to reduce by about half (over current Building Regulations) with community (rather than building-level) renewables playing a major role. It is also found that the NZE targets, given current regulations, are not particularly difficult to achieve in design with regard to energy efficiency but are highly expectant with regard to renewable energy. Further, summertime overheating is projected to be a risk for net zero energy dwellings by the 2050s. Despite this the regulated energy use of both dwellings is projected to reduce by 11 kWh/m 2 /yr, accompanied by a small increase in renewable generation (2 kWh/m 2 /yr). [ABSTRACT FROM AUTHOR]

This paper presents results of a research study into improving energy performance of small-scale district heat network through water supply and return temperature optimization technique. The case study involves establishing the baseline heat demand of the estate’s buildings, benchmarking the existing heat network operating parameters, and defining the optimum supply and return temperature. A stepwise temperature optimization technique of plate radiators heat emitters was applied to control the buildings indoor thermal comfort using night set back temperature strategy of 21/18 °C. It was established that the heat network return temperature could be lowered from the current measured average of 55 °C to 35.6 °C, resulting in overall reduction of heat distribution losses and fuel consumption of 10% and 9% respectively. Hence, the study demonstrates the potential of operating existing heat networks at optimum performance and achieving lower return temperature. It was also pointed out that optimal operation of future low temperature district heat networks will require close engagement between the operator and the end user through incentives of mutual benefit. [ABSTRACT FROM AUTHOR]

Airtightness testing is widely undertaken to assess the as-built performance of dwellings, in support of achieving energy and ventilation strategies. Mandatory schemes operate in some countries, such as the UK, to ensure that dwellings are built in accordance with their design air permeability. However, testing is only useful if the results give a true picture of the airtightness of the building. Previous literature has investigated factors which could influence airtightness test results but has not questioned data quality, despite the pressure on builders to achieve design targets. This paper presents air permeability results from the largest UK dataset, comprising 144,024 dwellings tested under the Air Tightness Testing and Measurement Association (ATTMA) scheme. The data show an unexpected distribution of test results with narrow peaks just within test targets. Such results were not expected theoretically but do reflect findings in other fields where performance-based targets are in place. Such a close match between design and tested airtightness may be achieved by remedial works taking place during the test rather than afterwards. Recommendations are made with respect to quality assurance systems, design guidance and on-site sealing practices to increase the likelihood of long-term airtight buildings being constructed first time. [ABSTRACT FROM AUTHOR]

The UK housing stock is responsible for some 27% of national energy demand and associated carbon dioxide emissions. 80% of this energy demand is due to heating (60%) and domestic hot water (20%), the former reflecting the poor average thermal integrity of the envelope of the homes comprising this stock. To support the formulation of policies and strategies to decarbonise the UK housing stock, a large number of increasingly sophisticated Housing Stock Energy Models (HSEMs) have been developed throughout the past 25 years. After describing the sources of data and the spatio-temporal granularity with which these data are available to represent this stock, as well as the physical and social phenomena that are modelled and the range of strategies employed to do so, this paper evaluates the 29 HSEMs that have been developed and deployed in the UK. In this we consider the models’ predictive accuracy, predictive sensitivity to design parameters, versatility, computational efficiency, the reproducibility of predictions and software usability as well as the models’ transparency (how open they are) and modularity. We also discuss their comprehensiveness. From this evaluation, we conclude that current HSEMs are lacking in transparency and modularity, they are limited in their scope and employ simplistic models that limit their utility; in particular, relating to the modelling of heat flow and in the modelling of household behaviours relating to investment decisions and energy using practices. There is a need for an open-source and modular dynamic housing stock energy modelling platform that addresses current limitations, can be readily updated as new (e.g. housing survey) calibration data is released and be readily extended by the modelling community at large: improving upon the utilisation of scarce developmental resources. This would represent a considerable step forward in the formulation of housing stock decarbonisation policy that is informed by sound evidence. [ABSTRACT FROM AUTHOR]

In the UK, 20% of houses were built before 1919 and are protected from energy efficiency requirements that would unacceptably alter their character. To meet carbon emission reduction targets, however, it is necessary to keep the number of buildings exempt from energy efficiency improvements to a minimum. The need to preserve the aesthetic and structural qualities of historic buildings makes energy retrofit complicated and costly but these arguments should not be used to resist change. The research presented in this paper investigates how conservation professionals in the UK approach and sanction energy retrofit measures in historic buildings. It provides an overview of the current UK legislation and guidance relating to energy efficiency in heritage buildings and presents findings from a study focused on the approach of conservation professionals to retrofit slim profile double glazing (SPDG). It finds that there is regional variation to energy retrofit in historic buildings between Scotland and the rest of the UK, and that individual conservation professionals hold different views on the use of SPDG, which leads to inconsistencies in its application. Recommendations are made for a more consistent approach to window upgrade as a means of improving the energy efficiency and comfort of historic buildings and for greater interdisciplinary cooperation to align conservation of energy with conservation of heritage. [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]

The ability to accurately model and predict timing and duration of activities for different individuals is essential for successful and widespread Demand Side Response (DSR) policies, especially in the residential sector. Understanding what people do during the day and what factors influence their activity participation decisions is important for planning an effective DSR strategy to harness the end-user flexibility. The recent Covid-19 pandemic has shown how much activities can be shifted to a virtual mode in the presence of mobility restrictions. Further, participation in activities via digital devices (virtual activity participation) has spread across society. Such virtual activities, including teleworking, online shopping, and virtual social interactions, are observed to explicitly impact travel behaviour and activity scheduling. And yet, activity-based models of mobility and energy demand do not accommodate the trade-offs between activity types, location and virtual activity participation. This paper presents a model of activity participation that captures the relationship between the three dimensions of: activity type (such as work, study, shopping), activity location (in-home, out-of-home), and activity modality (in-person, virtual). A Multiple-Discrete Continuous Extreme Value (MDCEV) model structure is applied, and the empirical analysis is undertaken using the 2015 United Kingdom Time Use Survey (UKTUS). The model results provide insights for better understanding of the trade-offs made by individuals as they participate in and allocate time across a set of activity type-location-modality alternatives, and the heterogeneity in these trade-offs. Further, holdout sample validation and policy scenario analysis exercises are presented to demonstrate the reliability and suitability of the model for policy implications. The empirical results presented in our paper suggest that this framework embedded in an activity and agent-based simulator of energy demand will enable us to test a variety of scenarios related to end-user flexibility and activity behaviour change, including consideration of virtual activity participation trends. [ABSTRACT FROM AUTHOR]

Increasing demand for housing is one of the biggest challenges facing the world. Affordable housing is a key priority of the UK government in addressing this challenge, which calls for innovative construction methods to address the issue of fuel poverty at an affordable cost. Timber-based modern methods of construction are one of the key solutions to resolve the existing housing crisis while managing climate change. Therefore, this paper presents a case study of "Integra House", which is a proof of concept of a novel truss technology. The case study is an affordable housing prototype that performs well in both life cycle carbon and cost. The proposed construction uses a novel timber truss technology which makes up the floor, walls and roof of the house, thereby reducing on-site operations and waste while providing a low-carbon low-cost design. The prototype underwent design optimisation and evaluation of options; workshop-based production and performance evaluation of elemental prototypes; production and performance evaluation of a full-scale dwelling prototype; and comparison of capital and life cycle costs and environmental impacts. Further, it underwent a simulation-based optimisation to maximize its performance in cost and carbon by replacing milled timber trusses with whole timber trusses and Rockwool insulation with wood wool insulation. The optimised design option (whole timber) has an EC of 261kgCO 2 per m2 and costs £682 per m2 (excludes substructure, services and fitout) and its operational carbon is 7.9 kgCO 2 per m2/annum and costs £3.30 per m2/annum to operate. Life cycle costs and carbon comparison of the two design prototypes concluded that the whole timber design outperformed the milled timber design in both cost and carbon aspects, by 23% and 30% respectively due to being extremely inexpensive and requiring minimal processing compared to the milled timber option. [ABSTRACT FROM AUTHOR]

Decarbonisation of the energy industry and enforcement of strict targets for operational energy consumption means that non-operational greenhouse gases (GHG) emissions, also known as embodied carbon (EC), will soon represent the majority of whole life carbon associated with buildings. EC assessments are often presented as deterministic, single-point values but contain a high degree of variability which is typically unacknowledged. Common sources of uncertainty are variability, data gaps, measurement error and epistemic uncertainty such as absence of detailed material specification (e.g. manufacturer, concrete mix, recycled content etc). Particularly during early design stages when such information is unconfirmed, average material data is used by necessity. While some material databases and LCA software can provide ranges of embodied carbon coefficients (ECC) between some materials and/or the uncertainty within individual manufacturers' carbon data, the practice of reporting this is uncommon and has limited practicality for whole building assessments. This paper presents a simple procedure that selects the highest impact materials of the EC of an asset and implements a Monte-Carlo simulation to estimate the uncertainty behind the product stage EC assessment. Material coefficients of variation (CoV) are obtained from database values where available, and interpolated values are used in the absence of such data. A product stage EC assessment of a UK educational building, initially undertaken using single data points for each material, gave an EC prediction of 525 kgCO 2 e/m2 GIFA. Two scenarios were then assessed using our proposed procedure: 1) the full building scope and 2) substructure and superstructure only. It was demonstrated that, for scenario one, the EC can range from 50 to 140% of the original result when considering the extreme results from the Monte-Carlo simulation. Scenario one (considering the full building scope) resulted in an average EC value (mean ± CoV) of 526 kgCO 2 e/m2 GIFA ± 10.0%. The second scenario (sub- and super-structure only) resulted in an average EC value of 312 kgCO 2 e/m2 GIFA ± 11.9% with a full range of 45–155% of the original result. This paper shows that a straightforward uncertainty analysis procedure can support designers in understanding the possible range of asset product-stage EC and, therefore, inform construction product selections at an early stage where detailed information is not known. The variation also gives a degree of confidence/caution in the average EC prediction in lieu of a single-point result. The construction product CoV results can be used to set target ECCs on projects to help ensure reliable low-carbon products are specified. If these target ECCs were met, a minimum of 29% and 33% (excl. EPD uncertainty) in product stage EC reductions could be achieved. Future work should extend this method to include additional life cycle assessment (LCA) stages and other uncertainty factors. And, the method could be applied to comparative life cycle assessments and optioneering exercises, as well as including more specific construction product variability data. [ABSTRACT FROM AUTHOR]

This paper uses a socio-technical building performance evaluation (BPE) approach to assess the pre- and post- actual performance of two discrete deep low energy retrofits in the UK – a Victorian solid-wall house and modern 1990s cavity-wall house. A ‘low-energy first, then low-carbon’ approach was adopted in both cases, to achieve an 80% reduction in annual CO 2 emissions. Pre-retrofit, both houses had lower measured annual gas consumption as compared to predictions made by energy models, although the electricity consumption in the modern house was higher than modelled, due to occupancy pattern and occupant behaviour. Post-retrofit, it was found that the Victorian house achieved nearly 75% CO 2 reduction, while the modern house achieved only 57% CO 2 reduction over the baseline emissions. Key reasons were higher than expected air permeability rates, installation issues with micro-renewable systems, lack of proper commissioning, usability of controls, occupant preferences and behaviour. Despite the gap between expected and actual carbon emissions, occupant comfort and satisfaction was significantly improved across both retrofits. This evidence-based understanding of the process and outcomes of deep low carbon retrofits is vital not only for learning and innovation, but also for scaling-up deep retrofit programmes for meeting national and international carbon targets. [ABSTRACT FROM AUTHOR]

This paper presents a systematic, socio-technical and empirical evaluation of the actual energy and environmental performance of a sustainably-designed institutional building (Southeast England), intended to be a teaching tool and ‘living laboratory’ of sustainability. Despite the building being designed to high sustainability standards (Energy Performance Certificate rating of A, low reliance on fossil fuels, natural ventilation and rainwater harvesting) and also being under-utilised during the in-use stage (lower hours of occupation and number of occupants), its actual energy-related carbon dioxide-equivalent emissions are four times more than predicted. This is due to poor energy management of the building, underperformance of the biomass boiler and wasteful energy practices in terms of excessive winter overheating in the atrium, inappropriate lighting controls, and electrical equipment being left on standby. Due to lack of training and understanding of the energy manager, the building management system was not used adequately and issues with installation, commissioning and maintenance of the biomass boiler led to its disuse; however the photovoltaic system generated electricity as expected. Findings from the study show how a mixed-methods approach of building performance evaluation (BPE) should be embedded as part of the build process, to ensure that performance outcomes are met in reality. [ABSTRACT FROM AUTHOR]

This paper provides an analysis of the relationships between dwelling, household, and motivation, behaviour and perception characteristics and winter heating setpoint temperatures (n = 111) and heating periods (n = 148 and 145) used in UK social housing. The work capitalises on primary data from a socio-technical household survey, undertaken in Plymouth, UK, during 2015, which was merged with building audit data collected by the social housing association managing the properties. The mean reported heating setpoint temperature was 20.9 °C and the average weekday and weekend day heating periods were 9.5 h and 11.2 h respectively. The results suggest that heating setpoint temperatures and periods vary greatly among UK social houses, but there are clear systematic variations according to dwelling, household, and motivation, behaviour and perception characteristics. The research could enable social housing providers, the government and commercial organisations to target energy efficiency measures (i.e. thermal upgrades) and social interventions (i.e. behaviour change) at those dwellings and households where their impact may be most beneficial. The results presented could also be used to better inform the assumptions of heating preferences in energy models, which could result in more realistic predictions of the space heating demands of social housing and the potential energy savings from refurbishment measures. [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]

• Implementation of a model predictive control scheme for HVAC systems is presented. • The hardware/software solution is generalisable to most building management systems. • Cloud solutions can offer low-cost, scalable control in commercial buildings. • Economic MPC reduced energy usage by 1.7% compared to baseline control. • Building thermal performance strongly affects viability of MPC schemes. Many businesses are looking for ways to improve the energy and carbon usage of their buildings, particularly through enhanced data collection and control schemes. In this context, this paper presents a case study of a food-retail building in the UK, detailing the design, installation and cost of a generalisable model predictive control (MPC) framework for its Heating, Ventilation and Air Conditioning (HVAC) system. The hardware/software solution to collect relevant data, as well as the formulation of the MPC scheme, is presented. By utilising cloud-based microservices, this approach can be applied to all modern building management systems with little upfront capital, and an ongoing monthly cost as low as $6.39/month. The MPC scheme calculates the optimal temperature setpoint required for each Air-Handling Unit (AHU) to minimise its overall cost or carbon usage, while ensuring thermal comfort of occupants. Its performance is then compared to the existing legacy controller using a simulation of the building's thermal behaviour. When simulated across two months the MPC approach performed better and achieved the same thermal comfort for a lower overall cost. The economic optimisation resulted in an energy saving of 650 kWh, with an associated cost savings of $240 (an improvement of 1.7% compared to the baseline), while the carbon optimisation gave negligible CO 2 savings due to the inability of the building to shift heating to low-carbon periods. Findings from this study indicate the potential for improving building performance via MPC strategies, however the level of impact will depend on specific building attributes. [ABSTRACT FROM AUTHOR]

This paper provides an analysis of the socio-economic and dwelling factors contributing to high electrical energy demand in UK domestic buildings. The socio-economic, dwelling and electricity consumption data were collected during a large-scale, city-wide survey, carried out in Leicester, UK, in 2009–2010. Annual electrical energy demand was estimated for 315 dwellings and an odds ratio analysis used to identify the socio-economic and dwelling factors that led to high electricity consumption. The effects of a number of socio-economic and dwelling factors which have not previously been studied for the UK domestic sector are included. Thus, for the first time, presence of teenagers, having electric space heating as the primary form of heating, portable electric heating and electric water heating were identified as significant drivers of high electricity demand in UK homes. The employment status and education level of the Household Representative Person, the number of floors in a dwelling, presence of fixed electric heating, and the proportion of low-energy lighting were shown to have no effect on high electricity consumption in UK homes. Given the impetus to reduce electricity consumption and CO 2 emissions from the domestic sector, these observations can help shape energy saving campaigns and future energy policy. [ABSTRACT FROM AUTHOR]

Electricity consumption in the administration buildings of a typical higher education campus in the UK accounts for 26% of the campus annual electricity consumption. A reliable forecast of electricity consumption helps energy managers in numerous ways such as in preparing future energy budgets and setting up energy consumption targets. In this paper, we developed two models, a multiple regression (MR) model and a genetic programming (GP) model to forecast daily electricity consumption of an administration building located at the Southwark campus of London South Bank University in London. Both models integrate five important independent variables, i.e. ambient temperature, solar radiation, relative humidity, wind speed and weekday index. Daily values of these variables were collected from year 2007 to year 2013. The data sets from year 2007 to 2012 are used for training the models while 2013 data set is used for testing the models. The predicted test results for both the models are analyzed and compared with actual electricity consumption. At the end, some conclusions are drawn about the performance of both models regarding their forecasting capabilities. The results demonstrate that the GP model performs better with a Total Absolute Error (TAE) of 6% compared to TAE of 7% for MR model. [ABSTRACT FROM AUTHOR]

Improved methods for quantifying energy savings in buildings need to be supported by empirical measures rather than modeled estimates of future annual energy demand. This paper uses power temperature gradient (PTG, W/K), or the slope of power demand in response to changes in external air temperature; first, to categorise dwelling energy performance from daily energy data (when 0–15 °C outside); second, to investigate variations in 24-h profiles of delivered power. Estimates of PTG were obtained from 567 UK dwellings with 118,000 days of gas and electricity data. From a multivariable regression model, PTG was predicted by dwelling characteristics (number of bedrooms, number of floors, dwelling type, and dwelling age category (all p < 0.001)) but not by number of occupants. When dwellings were grouped into quintiles of PTG, mean PTG had threefold increase from the first to fifth quintile (188 to 563 W/K, respectively). This was reflected in 24-h profiles of delivered power (30 min intervals): at 0 °C, each 100 W/K decline in PTG corresponded to ∼2.5 kW decline in mean morning and evening peak power. Using PTG to estimate reductions in peak power as equivalent ‘negawatts’ reframes potential benefits of energy efficiency retrofits and for grid resilience. [ABSTRACT FROM AUTHOR]

• An innovative retrofit Motivation-Objective-Criteria (MOC) approach integrating homeowners' engagement is proposed in this paper. • Retrofit motivations are categorised into three typical types: 1) Self-living, 2) Rental or sale, and 3) Investment. • A novel Multi-motivation Performance Factor (MPF) concept is proposed to assess the holistic post-retrofit building performance with comprehensive retrofit combinations. • Homeowners' retrofit priorities have an apparent influence on selecting optimised retrofit measures. • This decision-making supporting tool accelerate building retrofit user acceptance and market penetration According to the EU Commission projection (2016/547/EU), the current average renovation rate is far below the expected rate of 3% to achieve carbon neutrality in building sectors by 2050. This is due to the fact that, during the building retrofit optimisation process, the decision-making criteria and objectives are generally optimised separately, and homeowners' motivations are often ignored or not carefully defined in most research. Limitations existed with a lack of in-depth and comprehensive understanding of the homeowners' motivations in undertaking building retrofit. To address this, we propose an inclusive Motivation-Objective-Criteria (MOC) approach, aiming to bring forward optimised decision-making for building renovation, accommodating different homeowners' retrofit motivations, objectives and criteria. Retrofit motivations are categorised into three typical types: 1) Self-living, 2) Rental or sale, and 3) Investment, under five objectives: Energy Reduction Rate (ERR), Initial Investment (II), Discounted Payback Period (DPP), Bills Reduction Rate (BRR) and Carbon Reduction Rate (CRR). A novel Multi-motivation Performance Factor (MPF) concept is proposed to assess the holistic post-retrofit building performance with comprehensive retrofit combinations. A UK semi-detached house is applied as the reference building to investigate the impact of homeowners' engagement on the decision-making of various retrofit measures. According to the cost-optimal results neglecting homeowners' motivation, it is evident that the mismatch of optimal retrofit combinations occurs between the minimum Initial Investment (II) and Discounted Payback Periods (DPP), with optimal ERR of 72%-79% and 82%-93%, respectively. Comparing cost-optimal with multi-objective optimisation results, it is concluded that homeowners' retrofit priorities have an apparent influence on selecting optimised retrofit measures. Besides, party wall insulation is fundamental for self-living- and rental or sale-motivated types. The solar-assisted heat pump and air–water heat pump are not necessary under the retrofit motivation of the "investment" type. Moreover, the attic floor and external wall insulation are imperative for rental or sale- and investment-motivated types. The sensitivity analysis results are conducted in this research, indicating that the optimal retrofit measures and baseline energy consumption input are in good agreement, with a 10% discrepancy. Thus, the proposed inclusive Motivation-Objective-Criteria approach can incorporate homeowners' engagement in the building retrofitting design process, serving as a decision-making supporting tool to accelerate building retrofit with maximised user acceptance and market penetration. [ABSTRACT FROM AUTHOR]

• New building development projects underperform often. • Underperformance leads to increased energy consumption and CO 2 emissions in building operation. • The paper links building project development and building operational performance. • Two simulation methods are combined in a multi methodology framework in the paper. • The paper explores the implications of project partner collaboration for operational building performance in the case of a recent building project. The "performance gap" in the United Kingdom construction industry is a persistent problem as new building development projects underperform more often than not. The "performance gap" is partially attributed to the number of stages involved in building project development and the coordination difficulties of partners with different incentives. The project outcome is important for energy consumption, carbon emissions and occupant well-being. Thus, it is important to study the project management process in terms of the standard time, cost and quality parameters, but also in terms of project partner incentives and coordination, and the subsequent energy performance and resultant indoor environmental conditions. A system dynamics model of project management processes is developed to explore the implications of partner coordination for building quality. The system dynamics model is coupled to a building performance simulation model to explore building energy consumption and Indoor Environmental Quality, and apply this on a recent building project case study. Results show that greater project partner alignment can reduce annual energy consumption up to 12% and CO 2 emissions up to 37%, with greater emphasis in the design stage of the project subject to resource availability. The trade-offs involved on value appropriation are considered and discussion of results points to possible ways for improvement. [ABSTRACT FROM AUTHOR]

[Display omitted] • The profile DSR estimation method features a better balance of error compared with previous methods. • Clustering of detailed usage data to create profiles is a viable approach for improving DSR estimation. • Profiles can provide greater account of estimation uncertainty compared to existing deterministic methods. In principle, Demand Side Response (DSR) is increasingly seen as a critical component of a low-carbon electricity network with renewables as main sources of generation. In practice, DSR has been slow to emerge in most electricity markets of developed and developing countries. One of the main reasons for the slow penetration of DSR is the difficulty to assess the flexibility potential of individual sites. This paper develops a new DSR estimation method which uses detailed profiles information based on data on Heating, Ventilation and Air Conditioning (HVAC) chillers in five UK hotels between 2013 and 2017 and applies a combination of clustering analysis and subsequent stochastic sampling using cluster-weighted date-based predictors. Findings show that the profile DSR estimation method features a better balance of error compared with previous methods. [ABSTRACT FROM AUTHOR]

In this paper the findings from a long-term field study of the thermal performance of a circa 1950s dwelling are presented and discussed. The study aimed at evaluating the robustness of the QUB method in the field under UK climatic conditions. A series of 147 QUB tests were performed during the whole heating period (September 2016 – March 2017) in a detached house located in the University Park campus, University of Nottingham considering two distinct conditions: as-built and with increased airtightness. The QUB method was able to provide consistent and robust estimates of the Heat Transfer Coefficient (HTC) of the whole dwelling with approximately 80% of the results within ± 10% from the mean and more than 95% of the results within ± 15%. The need to treat heat losses occurring through the ground when assessing the thermal performance of buildings through experimental diagnostics methods was highlighted, especially in uninsulated concrete slab floors. The method devised to isolate the ground floor heat losses from the whole building losses resulted in reduced dispersion of the adjusted Heat Transfer Coefficient with a coefficient of variation of 5% and 98% of results within ± 10% from the mean. [ABSTRACT FROM AUTHOR]

• Domestic energy mapping can rapidly and accurately target appropriate dwellings. • Dwelling-level data collection by local community improved input for energy model. • Multiple routes of targeting using high energy use, fuel poverty and typologies. • Projected 89–94% mean energy reduction using whole house retrofit package. • Funding programmes need to be customised for different household segments. A long-standing challenge for area-based mass retrofits has been the ability to rapidly and accurately target appropriate dwellings for energy improvements. This paper demonstrates the application of a data-driven localised Geographical Information System (GIS)-based domestic energy mapping approach to create house-by-house baseline energy models and predict the potential for whole house energy retrofits in a case study of 431 dwellings in Oxford (UK). Top - down spatial datasets on energy, housing, socioeconomics and fuel poverty are combined with bottom-up energy modelling underpinned by actual dwelling details gathered through questionnaire surveys by the local community group. Multiple routes to identify suitable dwellings were tested such as grouping dwellings with high energy use, those with high levels of fuel poverty and by common dwelling characteristics. About 300 dwellings were found to be suitable for a whole house retrofit package, equating to 89–94% mean energy reduction over baseline. While the most common dwelling typology, 1930s semi-detached had high retrofit need, it fell in an area with low annual household income. The second most common dwelling typology, 1930s terrace, was dominant in areas with median level of household income. Funding programmes will need to be customised for different household segments to increase the take-up of energy retrofits. [ABSTRACT FROM AUTHOR]

The energy performance gap in buildings is a well-known phenomenon. However, its actual definition and extent is dependent on the baseline used for defining the gap. In this paper a calibration-based methodology is used to identify and validate the root causes of the performance gap. Following analysis of the performance of four case studies in the UK, from different building sectors, cross sectoral learnings that are applicable in the wider industry context are uncovered. Through the model calibration process and in the overall performance assessment, Indoor Environmental Quality (IEQ) parameters have been used to improve the robustness of validation of the calibrated models and to highlight the interrelationship of energy and IEQ. The study shows the importance of contractual accountability to minimise performance issues, building a case for having IEQ in energy performance contracts to manage the trade-offs of IEQ against energy performance that leads to unintended health consequences for the occupants. [ABSTRACT FROM AUTHOR]

• Effects of multi-zone heating systems in residential buildings are assessed. • Data obtained from 336 scenarios in Mediterranean climates are evaluated. • Results are evaluated under economic and energy criteria. This paper explores the effects of multi-zone heating systems in residential buildings in different Mediterranean climates. The aim is to evaluate their potential in residential sectors to provide a general basis from the results (from the energy and economic point of view). In addition, if feasible, a further detailed evaluation of this management strategy for optimising the energy use in residential buildings would also be carried out. To do so, the effects of two different zoning controls in different types of apartment, occupancy patterns, building characteristics and locations in Spain, have been assessed. Different combinations of these parameters have resulted in 336 different scenarios that have been dynamically simulated using Design Builder software. The obtained energy results have been analysed in detail. Moreover, an economic analysis of these results has also been carried out to evaluate the economic feasibility of these systems in residential buildings located in temperate climates. This has been calculated by evaluating the maximum investment that can be assumed in each scenario to achieve different payback periods (namely 10 and 20 years). The results obtained show that these systems could be a cost-effective strategy aimed at reducing the energy consumption in residential buildings, not only in cold climates, such as is shown in the literature (the majority of the studies found are located in the UK and northern countries), but also in more temperate climates, such as that of Spain. Savings of around 20% were obtained in the most usual scenarios in Spain (coherent with results obtained in previous studies in the UK found in the literature), showing that in several cases, the initial investment in zone-controlled systems could be paid off in less than ten years, especially in large apartments and the coldest weather conditions. [ABSTRACT FROM AUTHOR]

This paper aims to study children's thermal comfort and related Adaptive Behaviours in UK primary schools. The study was carried out in 32 naturally-ventilated classrooms during Non-Heating (NH) and Heating (H) seasons. Alongside collecting environmental data, a self-reported questionnaire and an observation form were employed to record children's thermal comfort and adaptive behaviours. From eight primary schools, 805 children aged 9–11 were surveyed and 1390 questionnaires were collected. Children's Thermal Sensation Votes (TSVs), Thermal Preference Votes (TPVs) and adaptive behaviours were compared against temperature offset from comfort temperature by EN 15251 (T diff =T op -T C (CEN)). Results suggest that children's thermal comfort (T C (children)) is 1.9 K and 2.8 K lower than that for adults (T C (CEN)) during non-heating and heating seasons, respectively. Children have lower comfort temperature and higher sensitivity to temperature changes during heating seasons. This can be attributed to children's lower practice of personal behaviours and more consistent indoor conditions during heating seasons. The proportion of children engaged with personal behaviours is one-third lower during heating seasons. As indoor temperature goes above children's thermal comfort band, the proportion of children practising personal behaviours increases during non-heating seasons. Around 80% of window operation is carried out by teachers who have a higher comfort temperature than children. • Around 15% of children are overheated during both non-heating and heating seasons. • Children practice personal behaviours more than environmental behaviours. • The environmental behaviours are done based on teachers' thermal perception. • Only 16% of window operations are done based on children's thermal comfort. • TSV shifts one score by a temperature change of 11.1 °C (NH) and 7.7 °C (H). [ABSTRACT FROM AUTHOR]

Expert guidance in the UK suggests a limit to temperatures in bedrooms to of 26°C or less to avoid overheating. This short paper looks at the temperatures in bedrooms and uses data from comfort surveys combined with models which link comfort to the thermal environment. Evidence is given that people sleep comfortably where temperatures are 29–31°C in their personal space within the bed and they use bedclothes to allow them to attain these temperatures. The effect of the use of a mattress and the adaptive opportunities afforded by the bedclothes and sleepwear are briefly explored as are methods used in hot climates to offset high bedroom temperatures. [ABSTRACT FROM AUTHOR]

This paper describes a new method to swiftly model the dynamics of heating energy demand and indoor air temperatures of houses and housing stocks. The Reduced data Energy Model (RdDEM) provides a cost-effective alternative to steady-state modelling by enhancing the input dataset from the Reduced data Standard Assessment Procedure (RdSAP) – the method used to calculate Energy Performance Certificates (EPC) in the UK. This eliminates the main drawbacks associated with dynamic thermal simulation (DTS) of housing stocks, namely the large amount of required input data and the significant time required to model each house. The RdDEM algorithms create RdSAP-equivalent geometry, construction, thermal mass and boundary conditions in Energy Plus DTS software. The new inferences and methodological enhancements were first tested and then implemented at scale using a sample of 83 semi-detached houses. Most energy results from RdDEM were within 10% of those from RdSAP. The differences are explained by the different ways that indoor air temperature is calculated. The RdDEM method provides a dynamic alternative to RdSAP for understanding the dynamics of energy demand and indoor air temperatures in homes. This could include assessing the peak demand of a community energy scheme or assessing the summertime overheating risk in individual dwellings. Ultimately, it could provide a dynamic housing stock model using the data already collected from millions of houses to generate EPCs. [ABSTRACT FROM AUTHOR]