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• 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]

[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]

• 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]

• 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]

• 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]

Abstract: This paper outlines the development and application of a domestic heat pump model for space heating and cooling energy. The model is intended to bridge the gap between the single coefficient of performance parameter currently used in the UK procedures for the assessment of the energy efficiency of dwellings and the dynamic simulation models frequently developed for the academic estimation of heat pump energy use. It is responsive to variations in source and sink temperatures whilst being simple enough to be embedded in a spreadsheet model. The model was developed by: building a regression model, using heat pump performance test results, relating heat pump coefficient of performance to the differential between source and sink temperatures – “lift”; deriving estimating rules for monthly supply temperature estimates for commonly-used heat pump sources and for demand temperatures for normal wet central heating sinks to give a monthly estimate for the source/sink differential; embedding the regression model in the UK standard model for domestic energy estimation, with additional routines to estimate energy consumption for additional heat and for space cooling. The model developed was validated by comparison with the existing BREDEM model. Compared with the standard BREDEM estimates, the resulting model showed correct response to changes in ambient temperatures, allowing correct estimating of consumption for additional heat under conditions of climate change. It showed variation of heat pump coefficient of performance across the year, allowing better estimation of winter peak load. [Copyright &y& Elsevier]