This paper optimally determines the configuration of the system, as well as each component capacity, in order to design a cost-effective and environment-friendly AC mini-grid hybrid power system for a remote area in South Australia. To this purpose, a modified Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is applied. In each iteration of the modified proposed MOPSO, first, renewable power sources, including photovoltaic arrays and wind turbines along with energy storage components, are selected to form a hybrid power system along with the diesel generator. Then, the capacities of the components are optimized based on two objective functions, including Levelized Cost of Energy (LCOE) and CO2 emission, by analyzing the system using real data in hourly time-step for the load, solar insolation, ambient temperature, and wind speed over a 20-year timespan. Afterward, positions for system configuration and component capacities are updated according to the objective functions.