An effective design of hybrid renewable energy system using an improved Archimedes Optimization Algorithm: A case study of Farafra, Egypt

The Improved Archimedes Optimization Algorithm (IAOA) is presented and applied to design a hybrid renewable energy system (HRES) for a microgrid system in the Farafra region of Egypt. The studied microgrid consists of three scenarios based on PV panels, wind turbine systems, diesel generators, and a battery energy storage system (BESS). The objective is to minimize the design function of the net present cost (NPC) that englobes all expenses during the project lifetime, respecting three constraints: the renewable fraction index, loss of power supply probability, and availability. The simulation results are compared with several known algorithms, such as the original Archimedes optimization algorithm (AOA), artificial electric field algorithm (AEFA), Equilibrium optimizer (EO), Grey Wolf optimizer (GWO), and Harris Hawks Optimization (HHO) algorithms. The results prove the ability of the proposed algorithm to solve the problem design, and they also demonstrate its superior efficiency to competing algorithms. The best-found HRES is the PV panel/wind turbine/diesel generator/battery storage system HRES, the NPC is $187,181, equivalent to cost energy (LCOE) of 0.213 $/kWh. The constraints are respected, the reliability is approximately 5%, the renewable fraction index is close to 90%, and the availability is approximately 100%. From the results, it is observed that the synergy of PV and wind systems is mandatory in such areas, and the battery also plays an important role in managing and arranging the energetic flow in HRES systems. The benchmark functions are tested using 23 functions, which proved that the IAOA performed better than the original AOA algorithm.