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Many global problems have recently arisen regarding rising electrical power consumption resulting in increased costs of electricity, raising concerns about non-renewable energy consumption. Unregulated electrical power generation, climate variation and global warming have all been shown to directly impact environmental degradation, leading to an emergence of severe economic and political repercussions, worldwide [1]. Thus, nations have striven towards clean energy production. Renewable energy production can assist countries in meeting sustainable energy production goals by providing access to safe, cost-effective and clean energy [2]. Despite the benefits of renewable energy, it has limitations due to weather variations, instability and other anomalies which reduce generation efficiency and reliability [3]. Thus, hybrid renewable energy systems could address limitations like efficiency, reliability and economics to satisfy overall energy demands [4]. Many studies have attempted to optimize size, design, control and economic aspects of hybrid renewable energy systems through utilization of technology such as wind turbines and solar modules in conjunction with alternative energy storage systems [5]. To bypass limitations associated with such solutions, various optimization methods, software and analytical methods have been previously applied [6]. However, the utilization of hybrid resources is a contested topic, making a global optimum solution hard to find. To address this, 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 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.

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