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The aim of this work is to generate Test Reference Year/Design Reference Year data from UKCP09 for a variety of future time slices and carbon emission scenarios and to apply the data to the simulation modelling of a variety of building case studies in order to investigate probable patterns of overheating and likely changes in cooling and heating demands over time. The aim is achieved by accomplishing the objectives stated in chapter 1.

A preliminary study was conducted in chapter 3 using CIBSE future weather data (‘morphing’ data according to UKCIP02 projections) to represent the linear relationships between outdoor air temperatures and indoor operative or air temperatures for non-domestic buildings. Results indicate a strong linear relationship between internal operative temperature increase and corresponding external dry bulb temperature increase. The gradient of this increase was found to vary between 0.767 and 1.009 for a wide range of contrasting commercial building types with differing constructions and is consistent for either dry bulb or operative temperature results. The results were found to agree with similar findings of an earlier study (Coley & Kershaw, 2010) which dealt with housing,

schools and offices. This work also helps verify the building models created by author.

Thirdly, a tool has been developed in Matlab to generate future Test Reference Year (described in chapter 4) and Design Reference Year (described in chapter 6) weather files from UKCP09 Weather Generator outputs. The results were verified using data from alternative tools produced by Manchester University and Exeter University as well as with CIBSE’s future weather data which are based on earlier (UKCIP02) climate change scenarios and are currently used by practitioners. The Northumbria tool is computationally efficient and can extract a Test Reference Year and two Design Reference Years at different risk levels from 3000 years of raw data in less than 6 minutes on a typical modern PC. Data from the new UKCP09 Weather Generator can be more easily and directly translated into ready for use files suitable for building energy simulation compared to previous data sets of this kind. The tool uses an established ISO method for generating Test Reference Year data, and an alternative method of constructing future Design Reference Years data has been proposed. Northumbria’s method for generating future Design Reference Years consisting of near extreme summer months and near extreme winter months woven into an existing Test Reference Year is described. Three near extreme months are selected for each season in order to provide results that are suitable for buildings with high thermal mass. Data are selected from 3000 years of raw data from UKCP09 based on the 85th and 99th percentile risk thresholds.

Fifteen ‘real’ UK buildings have been identified with varying occupancy, thermal insulation, user activity and construction details. Two investigations were carried out using the 15 case study buildings.

The first involved applying TRYs generated for London, Manchester and Edinburgh for a variety of carbon emission scenarios and at time horizons of 2030, 2050 and 2080. The TRYs were developed into a weather data format readable by the EnergyPlus energy simulation program and results were generated for simulated summer average internal operative temperatures, overheat percentage of occupied hours over 28 °C, winter average internal operative temperatures, cooling demands and heating demands. All results were compared with a control data set of nominally current weather data, together with the same results produced using the alternative weather data generators of Manchester University, Exeter University and the CIBSE data.

Results revealed a good agreement in both cooling and heating energy demands, and average temperatures between the various methods. They showed that significant increases in internal summer operative temperatures in non-air-conditioned buildings can be expected throughout this century, as well as increased air conditioning cooling demands and small reductions in winter heating demand.

The second investigation involved simulating two buildings using DRYs/DSYs data produced by Northumbria University, Manchester University, Exeter University and the CIBSE data. The remaining (thirteen) buildings were simulated using Northumbria data only. Results of DRY simulations indicate that

there are significant increases in overheat hours with advancing timeline and carbon emission scenarios. Increases in design cooling loads are also shown in the results, and there is no evidence of a change in heating design loads with advancing timeline and carbon emission scenarios.

The cooling design loads from the simulations using single DRY files are not able to reflect the whole picture of all the probabilities of future weather data which might occur. The resources of time and effort to conduct simulations and to analyse the results for all probabilities (3000 in UKCP09 for example) are not trivial particularly when applied during the early design and planning processes that most new building proposal undergo. Therefore the availability of a simpler approximate method would be invaluable to practitioners. In chapter 8, the development of such a method is considered and applied to the calculation of future room design cooling loads. The method is based on regression analysis of dependent variables (hourly cooling loads) and independent variables, such as temperature, solar radiation and so on. A simple linear equation with nine coefficients to be fixed was proposed to calculate building cooling loads. The design cooling load at any design risk required could be calculated by this method.