The residential electrical energy scheduling of solar Photovoltaics (PV) is an important research area of the modern green buildings. On the demand side, factors such as building load, and the renewable PV energy resources are integrated together as a nonlinear, indefinite and time varying complex system, which is very difficult to forecast and optimize. These energy sources are greatly depending on the climatic conditions. It further makes the residential building energy management complex. To address this problem, we present statistical models for the effective utilization of the renewables and reducing the burden on the distribution network. The effect of weather parameters such as temperature, dust in the air, humidity and solar irradiation on the green buildings energy infrastructure is taken into account. The details are analyzed and presented in the manuscript. The real time data is analyzed in the SPSS software tool. The presented results show that the statistical models are necessary for the controller to take action for the efficient and reliable integration of the renewables.