M.A. Thesis:

Multi-Objective Optimization of Hybrid Wind-Solar-Diesel System Considering Component Availability Using Grey Wolf Optimizer Algorithm

In this thesis, multi-objective optimization of hybrid wind-solar-diesel system with battery storage to minimize the annual cost of the system and taking into account the reliability and the amount of CO2 pollution is studied. System cost includes the cost of purchase and installation of equipment, maintenance and replacement and reliability for the possibility of power supply system is considered. In this study a new method known as algorithms for optimization problem of the gray wolf (GWO) is used. The optimization objective was to determine the optimal capacity of decision variables, including solar panels, wind turbines, batteries and diesel, which results in system cost to be minimized under the constraints of the system operators. The verification method for GWO, the results with theresults obtained using particle swarm (PSO) werecompared. Results have shown that GWO method has bettercapability to optimize the convergence speed higher than the PSO is to achieve a lower cost hybrid systems. Also back in the effect of some of the factors of the availability of solar and wind, changes the efficiency of the inverter and the load demand on the optimization of the system is evaluated

Keywords: Hybrid systems, optimization, availability, algorithms gray wolf