  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.
