Fig. 2 shows the share of the annual thermal energy requirement that can be met directly by the useful solar yield per house type. Thermal savings in the range of 9% to 22% could be achieved without thermal energy storage technologies. To achieve higher solar fractions, the use of TES technologies is required. Fig 5 shows the predicted storage capacities required per house type in

order to achieve 50% solar fraction for a range of collector areas. For this example the collector considered is the same for all house types and is south facing with 45o tilt.

The graphs show a generally very clear threshold of the collector area needed per house; absorber areas larger than this threshold would not contribute to much higher thermal savings or smaller TES sizes. Figure 5 also shows that in certain cases (e. g. house 12) very few m2 of collector would suffice to achieve the 50% solar fraction, while for others (e. g. house 3) more m2 than were available would be required in order to meet 50% of the total thermal energy needs with reasonable store sizes. The optimum balance between TES capacities and collector areas will be defined by the economics of the systems and the space limitations regarding collector mounting (available roofs, external walls and other external space) and TES volumes.

presents the percentage of the roofs’ area (or external walls’ area for models 5 &12) that remains unused for each house type. This figure reveals that if more collectors’ sizes become available in the future, then a larger solar thermal yield could be achieved. The overshadowing

analysis is conducted in Ecotect. The results reveal the portion of the total collectors’ area which remains non-shaded for every hour of the year and for each one of the roofs of each house type.

The I-beam solar radiation each of the roofs is then calculated in TRNSYS in Kj/hr*m2. The collectors’ yield is adjusted with the non-shade coefficient and with the efficiency of the collector which is taken as 0.7.

Figure 3 contains 12 graphs, one for each of the 12 houses modelled, showing the monthly thermal energy requirement in relation to the monthly collectors’ yield. All graphs show predictions using the tmy2 weather data. On two of the houses (with the highest and lowest demands) the predicted demands with the actual weather data of year 2007 are compared to those with the tmy2. Year 2007 was a significantly warmer year than average for Cardiff and therefore the predicted space heating demand is much lower than average and the solar thermal energy availability calculated with this data is much higher. This comparison reveals a much larger potential for solar thermal as average temperatures increase.