• Energy Research
• 13. Climate action close
• 2. Zero hunger close

This work considers the potential reduction in the carbon dioxide emissions associated with the operation of Air Source Heat Pump which could be achieved by using demand side management. In order to achieve significant reductions in carbon dioxide emissions, it is widely envisioned that electrification of the heating sector will need to be combined with decarbonisation of the electrical supply. By influencing the times at when electric heat pumps operate such that they coincide more with electricity generation which has a low marginal carbon emissions factor, it has been suggested that these emissions could be reduced further. In order to investigate this possibility, models of the UK electrical grid based on scenarios for 2020 to 2050 have been combined with a dynamic model of an air source heat pump unit and thermal models of a population of dwellings. The performance and carbon dioxide emissions associated with the heat pumps are compared both with and without demand side management interventions intended to give preference to operation when the marginal emissions factor of the electricity being generated is low. It is found that these interventions are unlikely to be effective at achieving further reductions in emissions. A reduction of around 3% was observed in scenarios based around 2035 but in other scenarios the reduction was insignificant. In the scenarios with high wind generation (2050), the DSM scheme considered here tends to improve thermal comfort (with minimal increases in emissions) rather than achieving a decrease in emissions. The reasons for this are discussed and further recommendations are made.

This dataset contains data, analysis and results generated in research reported in "Energy saving potential of high temperature heat pumps in the UK Food and Drink sector" in Energy Procedia and presented at the International Conference on Sustainable Energy & Resource Use in Food Chains (17-19 October 2018, Paphos, Cyprus). This includes performance data for heat pumps, parameters and calculations for selected dairy processes, energy use data for the UK Food and Drink sector and calculation steps used in the analysis. The heat pump performance data consists of the nominal Coefficient of Performance (COP) that can be achieved at specified temperature conditions by several high-temperature heat pumps (HTHPs) that are considered representative for the study. The dairy processes selected are pasteurisation of liquid milk, cheese production, yogurt production, milk drying and cleaning in place. For each process, a representative diagram is provided and temperature bounds for each sub-process are used to calculate the COP that the HTHPs would achieve. UK air temperature data is provided and binned into seven 5K bands to enable these calculations. Data on the relative energy uses within the dairy processes (from the Useable Energy Database and other referenced sources) are used with these COP results, to estimate the overall energy savings that are possible. This is repeated at a more aggregated level for the UK Food and Drink sector. The GHG and fuel cost implications of these energy savings are presented in table and graphical format. The dairy process data was collected through literature review. The heat pump data was based on expert review of published test data. The results were based on calculations described in spreadsheet. Please see the references in the spreadsheet for the sources of the background data used. Spreadsheet is in Microsoft Excel 2007+ format.

Abstract The greenhouse gas emissions associated with bioenergy are often temporally dispersed and can be a mixture of long-term forcers (such as carbon dioxide) and short-term forcers (such as methane). These factors affect the timing and magnitude of climate-change impacts associated with bioenergy in ways that cannot be clearly communicated with a single metric. This is critical as key comparisons that determine incentives and policy for bioenergy are based upon climate-change impacts expressed as carbon dioxide equivalent calculated with GWP100. This paper explores these issues further and presents a spreadsheet tool to facilitate quick assessment of these temporal effects. The potential effect of (i) a mix of GHGs and (ii) emissions that change with time are illustrated through two case studies. In case study 1, variations in the mix of greenhouse gases mean that apparently similar impacts after 100-years, mask radically different impacts before then. In case study 2, variations in the timing of emissions cause their climate-change impacts (integrated radiative-forcing and temperature change) to differ from the impacts that an emissions-balance would suggest. The effect of taking alternative approaches to considering “CO2-equivalence” are also assessed. In both cases, a single metric for climate-change effects was found to be wanting. A simple tool has been produced to help practitioners evaluate whether this is the case for any given system. If complex dynamics are apparent, it is recommended that additional metrics, more detailed inventory, or full time-series impact results are used in order to accurately communicate these climate-change effects.