Technology development and increase in residential energy consumption cause moving toward automation and smart home (SH) to be inevitable. Recently, PVs and WTs resources attachment and CHP and Battery energy storage to SH equipment come to some challenges such as output power uncertainty to the energy management system (EMS). Usually, SH has a connection to the city distribution system and can buy or sell energy from or to the utility at the appropriate time. Therefore, this paper presents the new robustness of SH EMS considering real-time energy pricing at the retail power market, which is solved using genetic algorithm technique. The objective function is the summation of CHP emission cost and energy consumption cost for non-interruptible, interruptible and thermostatic loads. Finally, simulation results and numerical studies are applied on test SH, and conceptual results are discussed.