# Passive Solar Solutions for Buildings: Criteria and Guidelines for a Synergistic Design
## 4 Results
Looking at the orientation impact, south-facing systems showed the highest values, but they must deal with summer overheating risk. The sensibility decreases as the latitude increases, with Rome gaps between standard and rotated configurations higher than Frankfurt ones. The influence of different building axis depends on building use: for Frankfurt latitude, the impact of orientation moved from 7.7% of energy saving variation in direct systems, 7.9% in indirect, and 5.9% in isolated ones in the office study to lower values in the residential analysis, 5.6%, 6.1%, and 2.8% respectively. In Rome, the effect of orientation in residential application was higher than in office buildings, moving from 11.2% to 9.9% in direct systems and from 12.8% to 11.3% in indirect systems. Isolated sunspace solution represents an exception, as the residential gap of performance between standard and rotated configurations, 7.2%, was higher than the office one, 5.9%. The lower residential building performance and the consequent lower sensitivity to orientation and latitude was attributable to the lack of optimization for the heat storage system. Analysing the results from the perspective of the systems, direct solutions showed the highest efficiency in reducing building energy demand, but they had higher sensitivity to orientation, 6 to 10 percentage points of variation, and latitude, 9-13%, than indirect or isolated solutions. Moving to the case study of the office building, four different strategies have been studied and results are shown in Table 4. As a reference, the basic case, with no shading systems, determined an energy demand per total building area of 115.52 kWh/m\({}^{2}\), with an almost equal energy consumption for heating and cooling purposes, 47.59 kWh/m\({}^{2}\) and 45.66 kWh/m\({}^{2}\), respectively. Due to the east and west exposure, the effectiveness of fixed overhangs was negligible, while the impact of external blinds to reduce the summer undesired heat gain while guaranteeing proper lighting levels for office work was relevant. The results show that while fixed shadings led to a very low energy demand variation, with only 1.28% energy saving in cooling, blinds cut off one third of the cooling energy demand, with an impact of 12.58% on total energy consumption. This result highlights the hidden potential of passive solar solutions that can provide a reduction in embodied and operational energy requirements over a life cycle [31]. As shown in Figure 10, indoor air temperatures in the office zone in free running conditions rise compared to the basic case due to the higher thermal resistance of the windows: results show a reduction around 15% in heating demand, but the lower heat losses during the night generated a higher demand of energy in the cooling season. The analyzed synergy effect of the combined strategies individually, external blinds and low-e glasses, reduced by around a quarter the energy demand of the building, with a share for heating and cooling close to the highest values previously detected, 14.91% and 32.74%, respectively. Regarding the investigation of the office module, as in the previous analysis, the combined case showed a higher share of energy savings on the cooling side, with a reduction of 13.78% of energy demand, and zero effect on heating for the single office module. Replacing half of the wall-wide window with a Trombe wall drastically reduced the heating demand, more than half of the required energy in the basic case and cut off one third of the cooling demand. Figure 11a shows the results of the simulations. The lighting load moved from 2.28 kWh/m\({}^{2}\) in the full window configuration to just 2.65 kWh/m\({}^{2}\) in the half-window one. The naturally ventilated indirect system reached a higher share of energy savings for building heating, around 62%, but without a proper control system, its integration could be counterproductive: the cooling energy demand, indeed, rose from 3.21 to 3.91 kWh/m\({}^{2}\).