Microgrids are becoming more favourable each day due to the emerging need of reducing fossil fuel waste and emission. Therefore, there is more need for renewable energy resources, such as solar generation and wind generation, as well as Plugged-in Electric Vehicles (PEV). However, due to the intermittent nature of renewable energy resources and PEVs, there are concerns regarding the output fluctuations and financial uncertainties of microgrid operations. In this dissertation, two modes of operation for microgrids are studied: grid-tied and islanded modes. To address the financial concerns of operating a PEV integrated microgrid, an optimized scheduling method is deployed. A Genetic Algorithm-based method is presented to optimize an objective function, including the cost of energy production and the profit of the PEV owners, which has been overlooked in most of the existing strategies. The proposed method guarantees the best possible energy consumption profile for both the microgrid operator and the consumers. Moreover, in a competitive energy market, the reliability of the microgrid plays a vital role, as the households will have the option to choose between utility companies. Thus, it is essential for the microgrid operator to operate the microgrid in the most reliable way. To this end, the reliability of the microgrid in the grid-tied and islanded modes of operation is evaluated with and without considering PEVs and renewable energy resources, such that the effects of these elements on reliability are portrayed. Furthermore, smart microgrids enables households to have a more flexible and economically efficient way to control their energy usage, which is known as demand response program. Demand response program is also beneficial for the microgrid operator, since it can improve the flexibility of the microgrid, contribute to peak shaving, and enhance the economical efficiency of the microgrid. Hence, the financial effects of demand response program are evaluated from both the households’ and the microgrid operator’s point of views. In order to make the study more realistic, the grid constraints are taken into consideration in the proposed strategies. Simulation results are used to validate the effectiveness of the proposed approaches.