The increasing number of electric vehicles (EVs) represents a huge burden on the electrical grid. EVs’ charging and discharging control through vehicle-to-grid (V2G) techniques is one of the best solutions to power problems and CO2 emissions. This study introduces a multi-objective power scheduling of a residential microgrid that consists of PV, wind generator (WG), EVs, and battery energy storage system (BESS). It also presents a comparison between two energy management techniques: renewable base control (RBC) and load base control (LBC) for controlling plug-in-electric vehicles’ charging and discharging. The novelty of this work depends on holding a comparison between four sizing scenarios of residential load to verify the economic feasibility and environmental viability of integrating EVs into microgrids; and introducing a control technique for charging and discharging battery energy storage system (BESS) with the consideration of ToU prices and EVs’ power. Also, conducting a comparison between two optimization algorithms for confirming the effectiveness of the control techniques. The obtained results verify the effect of EVs control in reducing the total system cost and CO2 emissions. Integrating controlled EVs saves $ 0.728 million and deducts 213.23 kg of CO2 emissions. The controlled BESS integration reduces the total system cost by $ 0.835 million and CO2 emissions by 360.68 kg. The semi-isolated microgrid had the lowest overall cost of $ 1.421 million.