For developing nations such as Iraq, electricity access in rural areas, especially those which are remote, is limited. Thus, the present study explores the electrical needs of the city of Zerbattiya, Iraq. The proposed system's components include solar panels, wind turbines, diesel generators, and batteries. This research proposes a techno-economically feasible and optimal sizing for each component to generate electricity for the city. Particle swarm optimization (PSO) algorithm was used in this research by using MATLAB. The ideal setting of a hybrid renewable energy system (HRES) is achieved by considering the lowest possible cost of energy (COE) with the highest reliability (REL) and possible value of renewable energy penetration (REP). Results showed that the respective optimal values for NPV (30), NWT (30), NDG (3), NBT (281), cost of energy (COE) was (0.142 US$/KWh), loss of power supply probability (LPSP) was (0.0534 %), reliability (REL) was (99.9466 %) and renewable energy penetration (REP) was (56.35 %). The findings further demonstrate that the algorithm was able to achieve optimal solutions to reduce overall cost, quickly and accurately. In conclusion, implementation of HRES was found to be an apt method of meeting electrical needs of remote rural areas in Iraq, and other developing nations with similar climates.
