## 3 Results and Discussion  
It is critical for the sustainability of future projects that recommendations are provided, such that WWR can be optimized to reduce cooling and heating loads while still retaining an appropriate level of lighting. The impact of making active technologies more efficient than the suggested passive strategies can be identified by utilizing various techniques, one of which involves the use of simulation programs. The present study explores the effect of utilizing LED for lighting systems in residential structures on the optimum WWR purely based on energy consumed. Therefore, the simulation was performed and a general DesignBuilder report was produced for different WWR situations, as described in the methodology part. The results have been presented graphically to facilitate understanding. After this, a comparison between the results was made to make appropriate decisions. A simulation-based approach, utilizing DesignBuilder, was employed for studying and examining the impacts of lighting systems on the optimum WWR for a standard residential building in Jordan. The findings offer beneficial guidance that emphasizes the effects that lighting systems have on window sizes and their mutual impacts on the overall energy consumption. While the optimum WWR proposed in this research only pertains to the consumption of energy, if this is are integrated with the preferences of building occupants, a satisfactory WWR can be generated that meets both design quality criteria and ensures building performance. The overall site energy in the 0% and 80% scenarios exhibited strong similarities as shown in Figure 5. Although the overall site energy was elevated in the 0% case, it showed a significant decrease in the 10% case. Similar reductions were observed in the 20% and 30% cases, but the overall site energy began to increase in a linear manner after the 30% case, reaching the maximum value in the 100% case. Increasing WWR from 0% to 10% saves around 41% of the total energy consumption; increasing WWR from 10% to 20% saves around 18%; followed by almost 1% when increasing WWR from 20% to 30%; and afterward, an increase in the total energy consumption by 11%; on average, 18% for each 10% increment in WWR. Figure 4: (**a**) DesignBuilder lightning templates. (**b**) Linear control concept. The following equation (Equation (1)) represents the relation between total building energy consumption (kWh) with different WWR (\(x\)):  
_Total energy consumption_ (kWh) \(=-96465x^{5}+274531x^{4}-303110x^{3}+170105x^{2}-42863x+7231.1\) (1)  
Such variations in the overall building energy in different WWR scenarios imply that if glazing is not present, which prevents heat and light transfer from occurring, the energy consumption of the residential structure is greater due to the increased window-to-wall ration, but the addition of a lower percentage of WWR causes the overall site energy to decrease. As illustrated in Figure 6, as the WWR percentage increases, the cooling load rises; whereas decreases in lighting and loads occur. In the 0% case, the yearly consumption of lighting energy was elevated, but a significant decrease occurred in the 10% case. Nevertheless, from the 20% to 100% cases, only marginal differences were observed in terms of the diminishment of lighting energy. Figure 5: Total building energy consumption (kWh) for different WWR. Figure 6: Annual lighting, and space heating and cooling energy consumption (kWh) for different WWR. Prior to the 20% scenario, the yearly consumption of energy for cooling was insignificant. However, a linear increase was then observed, starting from the 30% scenario, which reached a peak in the 20% scenario. Conversely, the consumption of energy for heating exhibited a linear decrease in terms of WWR percentage, apart from in the 10% case. Nevertheless, the reduction began to be insignificant from the 40% scenario onwards. It was clear that the energy used for cooling spaces changed more significantly in comparison with the energy consumed for lighting and heating.