Techno-Economic Feasibility to Generate Electricity by Using PSO Technique for the Urban City in Iraq: Case Study

Abstract

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 village. 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 COE with the highest reliability and possible value of renewable energy factors. Reliability is gauged on the basis of “loss of power supply probability†(LPSP). Results showed that the respective optimal values for NPV (30), NWT (30), NDG (3), NBT (281), COE (US$0.142), LPSP (0.002085), reliability (99.791) and renewable factors (21.42%). 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, not only in Iraq, but also other developing nations with similar climates.