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In light of the global energy and climate crises, integration of low-carbon technologies into energy systems is being considered to mitigate the high energy costs and carbon footprint. The wide range of available capacities, efficiencies, and investment costs of these technologies and their different possible operating schedules can unlock several pathways towards decarbonisation. This paper presents an optimisation framework for a public healthcare facility to determine the optimal operation schedule of the site's energy system. A detailed techno-economic analysis of low-carbon power generation, conversion, and energy storage technologies that can be incorporated into the system based on real historical data was carried out for different scenarios. The results reveal that a heat pump with a capacity of 1800 kW can replace gas boilers on-site to meet the heat demand while recovering the investment in 5 years and providing an operating and carbon cost saving of 22.47% compared to the base case. The analysis shows that a more electrified mode of operation is favoured during high gas prices, thus making electrical energy storage more attractive than thermal energy storage. While handling real data, the optimisation algorithm was sensitised to discriminate conventional energy supplies from clean energy sources by considering their carbon impact so that it minimises energy bills in a smart and eco-friendly way. The optimisation algorithm and the subsequent techno-economic analysis provide a comprehensive framework to decision-makers for facilitating energy investment decisions. The framework can be used based on the short and long term goals of the energy system, visualising the evolution of financial benefits over equipment lifetime, and understanding the environmental impacts of integrating renewable energy. • Heat pumps are the most favourable decarbonisation technology for the hospital. • The moderate variations in energy demand limit the scope of energy storage. • Fuel price surcharge favours EES over TES and reduces payback period of retrofits. • PVT's savings scale linearly with roof space until 3 times the available capacity. • Monetising the carbon footprint shortens the DPP of clean retrofit technologies. [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]

[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]

Electric heat pumps (HPs), hybrid heating technology and district heating networks (DHN) are the main low-carbon heating technologies that can deliver the ambitious carbon reduction target in the UK. The optimal design of the heating system on a national scale to maximize the economic benefits regarding both investment cost and operation cost while satisfying the carbon target remains an open question. This paper aims to compare the economic advantages as well as the associated impacts on the electricity system under the full deployments of ASHP (air source HP), hybrid HP-Bs (ASHP and gas boilers) and DHNs. To do so, a novel whole-system approach is applied with the explicit consideration of the coordinated operation between heat and electricity system. The optimized strategy for heat sector decarbonisation is also demonstrated, providing an outline of the optimal deployment for different heating technologies in terms of their penetrations and deployed areas. The UK case study suggests the significant economic advantage of the hybrid HP-B over the other two heating technologies, while DHN may play an important role in urban areas under the optimized heat decarbonisation strategy. The results also clearly demonstrate the changes on the electricity side driven by the different decarbonisation strategies in the heating system. [ABSTRACT FROM AUTHOR]

Residential demand response using low carbon technologies can potentially offer energy flexibility to the electricity network along with integration of renewable generation. This paper seeks to empirically evaluate the effectiveness of residential demand response trials on a low voltage feeder of a secondary substation in Barnsley (UK). The study used a sample of 14 well-insulated dwellings equipped with home batteries, heat pumps and solar photovoltaic systems coordinated using automated control. Statistical analysis was undertaken using time-series monitoring data obtained at the individual dwelling level, dwelling sample and at the feeder level of the local low voltage network. Resident experience of the trials was assessed through qualitative data obtained from household telephone surveys. Over three weeks of trials, daily demand response interventions of 2 h duration were applied to the sample of 14 dwellings. For evening peak times, the mean reduction in grid electricity import was found to be 1.3 kWh (67%) per dwelling for turn-down interventions which aimed to minimise import. For turn-up interventions between 1 and 3 pm, the mean increase in grid electricity import was found to be 5.8 kWh (645%) per dwelling. The effect of interventions was measured at the low voltage network level for two single-phase feeders, where penetration of trial homes was approximately one-third. A reduction in mean real power up to 21% was observed for turn-down interventions as well as an increase in real mean power up to 307% for turn-up interventions. In general, the trials had little effect on residents in terms of thermal comfort, hot water availability, noise disturbance or disruption to routines, and where such effects were noticed, they were broadly acceptable. The widespread implementation of residential demand response schemes will require increased roll-out of time-of-use tariffs, enhanced resident support and extensive monitoring of low voltage feeders in electricity substations. [ABSTRACT FROM AUTHOR]

• Isolating the impact of heat pumps on national electricity under historic weather. • Validations with measured data indicate the best heat demand generation method. • 41 % heat pumps would increase Great Britain's winter electricity demand by 30 TWh. • Year-to-year variability of electricity demand increases by 37 %. • 25 % inaccuracy of future peak electricity demand estimates. Amongst all future developments it is the electrification of heat that is anticipated to have the largest impact on seasonal and interannual electricity demand. There is therefore a need to accurately quantify and assess this impact. This paper uses a combination of existing advanced techniques to modify the historic electricity demand to incorporate the impact of heat pumps alone for long-term historic weather data using Great Britain as an example. The methods for generating time series were compared and extensively validated. This includes comparisons with measured data that have not been used previously for this purpose. The research reveals that for predicted 2050 heat pump penetration levels the monthly demand for electricity doubles in winter. This leads to an increase of approximately 30 TWh for each winter month and a 37 % increase in year-to-year variability of electricity demand due to weather. Peak electricity demand is very sensitive to the method of generating heat demand and the assumptions on hourly heat pump operating profiles, suggesting inaccuracies of 25 % in estimates of future peak demand. This work, rather than just assessing the impact of projected changes provides a reference case for policy makers to guide the decision process and planning for future scenarios. [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]

Energy load forecasting is essential to effectively optimise the use of energy for the purpose of smart grid operation. In this work, a focus is placed on Short-Term Load Forecasts (STLF) using measured heat pump data from the UK utilising the Long Short-Term Memory (LSTM) method. A load forecasting program is developed to forecast the electricity consumption of heat pumps based on historical data. LSTM is compared to Backpropagation Neural Network (BPNN), Seasonal Autoregressive Integrated Moving Average (SARIMA), Random Forest (RF) and Holt-Winters Exponential Smoothing (ES). The best average Mean Absolute Percent Error (MAPE) of 1.59% is achieved for the test data set by LSTM, which outperforms other models compared and a number of models presented in papers in the literature. By conducting the Wilcoxon signed-rank test, it is proven that the prediction accuracy improvement of LSTM compared to other models is statistically significant with the exception when comparing with RF with the training data. The impact of data aggregation resolution to forecast accuracy is investigated. The proposed LSTM model performs best on 1-h resolution data compared with other resolution time periods. The results of the LSTM model are integrated with Home Energy Management Systems (HEMS). The electricity costs of the HEMS are compared when using forecasted and measured heat pump data respectively. The results indicate an average percentage difference of 2.06% between the predicted and the actual electricity cost of HEMS for the test data. Furthermore, this paper presents a combined neural network and Particle Swarm Optimisation (PSO) model to develop an optimised energy management system while proving the effectiveness of the LSTM algorithm. • A LSTM algorithm is used to forecast the electricity consumption of heat pumps. • The proposed forecast model outperforms models found in the literature. • The Wilcoxon signed-rank test is used to prove the effectiveness of LSTM model. • The impact of data aggregation resolution to forecast accuracy is investigated. • The load forecast model is integrated with a Home Energy Management System model. [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]

This paper presents an advanced stochastic analytical framework to quantify the benefits of smart electric vehicles (EVs) and heat pumps (HPs) on the carbon emission and the integration cost of renewable energy sources (RES) in the future UK electricity system. The typical operating patterns of EVs/HPs as well as the potential flexibility to perform demand shifting and frequency response are sourced from recent UK trials. A comprehensive range of case studies across several future UK scenarios suggest that smart EVs/HPs could deliver measurable carbon reductions by enabling a more efficient operation of the electricity system, while at the same time making the integration of electrified transport and heating demand significantly less carbon intensive. The second set of case studies establish that smart EVs/HPs have significant potential to support cost-efficient RES integration by reducing: (a) RES balancing cost, (b) cost of required back-up generation capacity, and (c) cost of additional low-carbon capacity required to offset lower fuel efficiency and curtailed RES output while achieving the same emission target. Frequency response provision from EVs/HPs could significantly enhance both the carbon benefit and the RES integration benefit of smart EVs/HPs. [ABSTRACT FROM AUTHOR]

• Data-driven and comprehensive thermodynamic technology models are developed. • Multi-fidelity approaches are used to compare heat-generation solutions. • Centralised CHP systems appear to be the most profitable option at present. • Heat pumps can achieve a significant degree of heat decarbonisation (55–62%). • Thermodynamic models reduce uncertainty by 75% compared to black-box approaches. This paper presents a multi-scale framework for the design and comparison of centralised and distributed heat generation solutions. An extensive analysis of commercially available products on the UK market is conducted to gather information on the performance and cost of a range of gas-fired combined heat and power (CHP) systems, air-source heat pumps (ASHPs) and ground-source heat pumps (GSHPs). Data-driven models with associated uncertainty bounds are derived from the collected data, which capture cost and performance variations with scale (i.e. , size and rating) and operating conditions. In addition, a comprehensive thermoeconomic (thermodynamic and component-costing) heat pump model, validated against manufacturer data, is developed to capture design-related performance and cost variations, thus reducing technology-related model uncertainties. The novelty of this paper lies in the use of multi-fidelity approaches for the comparison of the economic and environmental potential of important heat-generation solutions: (i) centralised gas-fired CHP systems associated with district heating network; (ii) gas-fired CHP systems or GSHPs providing heat to differentiated energy communities; and (iii) small-scale micro-CHP systems, ASHPs or GSHPs, installed at the household level. The pathways are evaluated for the case of the Isle of Dogs district in London, UK. A centralised CHP system appears as the most profitable option, achieving annual savings of £13 M compared to the use of decentralised boilers and a levelised cost of heat equal to 31 £/MWh th. However, if the carbon intensity of the electrical grid continues to reduce at current rates, CHP systems will only provide minimal carbon savings compared to boilers (<6%), with heat pumps achieving significant heat decarbonisation (55–62%). Differentiating between high- and low-performance and cost heat pump designs shows that the former, although 25% more expensive, have significantly lower annualised costs (£4.9 M vs. £7.7 M) and 12% higher CO 2 -equivalent savings. The uncertainty propagation reveals that data-driven and detailed thermoeconomic models can reduce the uncertainty in the total annualised energy cost and emissions by more than 75% compared to simplified black-box approaches, while the economic comparison of centralised CHP systems and domestic heat pumps for various electricity and gas price scenarios provides guidance to support energy policy. [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]

• Techno-economic analysis of low-carbon heat supply options for UK supermarkets. • RIHC, an ASHP, and a thermal storage tank with advanced control is recommended. • Best investments provide a 16-to-18-year payback without a carbon price. • The UK renewable heat incentive subsidy (for ASHP) generates 89% of the 'savings' • When a £100/tCO2e tax is considered, paybacks are reduced to a 9–11 years. Eliminating the use of natural gas for non-domestic heat supply is an imperative component of net-zero targets. Techno-economic analyses of competing options for low-carbon heat supply are essential for decision makers developing decarbonisation strategies. This paper investigates the impact various heat supply configurations can have in UK supermarkets by using heat recovery principles from refrigeration systems under different climatic conditions. The methodology builds upon a steady-state model that has been validated in previous studies. All refrigeration integrated heating and cooling (RIHC) systems employ CO 2 booster refrigeration to recover heat and provide space heating alongside various technologies such as thermal storage, air-source heat pumps (ASHPs) and direct electric heaters. Seven cases evaluating various technology combinations are analysed and compared against a conventional scenario in which the building is heated with a natural gas boiler. The specific combinations of technologies analysed here contrasts trade-offs and is a first in the literature. The capital costs of these projects are considered, giving insights into their business case. Results indicate that electric heaters are not cost-competitive in supermarkets. Meanwhile, RIHC and ASHP configurations are the most attractive option, and if a thermal storage tank system with advanced controls is included, the benefits increase even further. Best solutions have a 6.3% ROI, a payback time of 16 years while reducing energy demand by 62% and CO 2 emissions by 54%. Such investments will be difficult to justify unless policy steers decision makers through incentives or the business case changes by implementing internal carbon pricing. [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]

• Tank size and temperature set point of 1.2 m3 and 75 °C are optimal system design. • Should charge storage at 3am and 2pm for morning and afternoon demands, respectively. • The best load shifting positively affects the grid. • Achieve running costs and CO 2 savings with the best load shifting, compared to oil boilers. Cascade air-to-water heat pumps may have good potential for retrofitting UK domestic buildings because they can directly replace existing fossil-fuel boilers without the requirement of considerable modifications to heat distribution systems. A widespread uptake of these heat pumps, however, would pose challenges to the grid. Furthermore, wind power generation has increased in the UK to achieve the target of decreasing CO 2 emissions by 2050, but there are high levels of wind curtailment due to the mismatch between electricity supply and demand. In this paper, a load shifting study for cascade heat pumps coupled with thermal energy storage addressing these issues is presented. The main objective is to find the best tariff-based schedule load shifting for cascade heat pumps, which can help to avoid peak demand periods while obtaining enhanced system energy efficiency with minimised running costs and reduced wind energy curtailment. How the retrofit performance of the cascade heat pumps with load shifting is further investigated. TRNSYS was used to simulate the system performance validated against experimental results. Northern Ireland (UK) was selected as the evaluated scenario. Simulation results showed that the tank temperature set point of 75 °C and the storage size of 1.2 m 3 could wholly shift the cascade heat pumps' operation to off-peak periods. The best times to start the cascade heat pumps to charge the storage were at 3 am and 2 pm for the morning and afternoon heating demands, respectively. Compared to oil boilers, the cascade heat pumps with load shifting could obtain lower running costs (16–34%) and carbon emissions (20–37%). [ABSTRACT FROM AUTHOR]