Advanced technology in communication and control enables electric utility customers to provide assistance to the grid through demand side management (DSM) and home energy management systems (HEMSs). This capability may mitigate the variability from increased penetration of variable resources, such as wind and photovoltaics (PV) leading to grid operation flexibility. Home load, distributed generation, and storage can assist in meeting such flexibility if they are managed properly. In this paper, we present an optimization model for HEMS based on mixed integer linear programming (MILP). The model schedules the operation of several home appliances, local generation, and home energy storage depending on the electricity price signal. The considered objective is minimizing the incurred cost by the household. Further, feed-in tariff policy is considered allowing the home to export and sell any surplus energy to the grid. Case studies show the reduction in imported energy and cost achieved after applying the HEMS. Further, superior execution times were recorded in all case studies indicating the effectiveness of the proposed model in terms of computational speed.