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This thesis describes a computer tool that was developed to compare different combinations of photovoltaic panels, solar thermal collectors and combined heat and power technologies for building applications to find the option with the lowest cost of emissions reduction. The novelty of this computer tool is that it addresses the uncertainty of building energy load profiles in the sizing of renewable energy and CHP technologies by applying the Monte Carlo Method. A database of historical building energy load profiles was collated for this purpose. However, little domestic hot water load profiles were found in the literature. Therefore, as part of this study, a survey was also carried out to collect some domestic hot water load profile data. The survey consisted of a questionnaire and monitoring study. The questionnaire consisted of two parts: a general questionnaire about the dwelling and a diary study. The questionnaire collected general information about the dwelling, enabling the load profiles collected to be classified into different building type categories. In the diary study the hot water consumption patterns were recorded. The hot water energy consumption data was also obtained from direct monitoring using temperature sensors attached to the hot water pipes of the different appliances to record when and from which appliance hot water was used throughout the day in the dwellings. Load profiles were formed using this data and the data from the diary study in the questionnaire together with typical hot water usages of different appliances which were calculated from hot water usage times and flow rates of the different appliances that were recorded by a clamp-on flow meter. The data collected from the survey and the literature was loaded into the computer tool database.