This study is an optimization of hybrid energy system in Nigeria, the energy requirement of Ikot Inyang rural community is satisfied after carrying out the design and simulation of different variables, the optimal systems were a system that consisted of 5 wind turbines, solar models and a diesel generator as energy sources. Ikot Inyang is a rural community located in Akwa Ibom state, South-South Nigeria, the community is connected to the national electricity network (grid) but the power supply is rarely consistent. The load estimate analysis showed that Ikot Inyang had peak load 58.62kW and peak energy demand per day as 670.65kWh. Eight (8) different design plans were considered and simulations were carried out using HOMER software. Several factors were used to determine the most optimal system, which includes the Net Present Cost, Levelized Cost of Energy, Renewable Fraction and system emissions. This was carried out for the 25 years project life time. The design plans were made of stand-alone systems as well as combination of many generating sources with battery included in some systems, various simulations were carried out. HOMER Presented the most technical and economical solution to meet the load demand at the least Net Present Cost, least Levelized Cost of Energy and allowable Renewable fraction. The most optimal solution for Ikot Inyang involved a combination of a 50Kw diesel generator, 5 Bergey Excel 10 wind turbine, 134kW solar model, 204 strings of Hoppecke 12 OPzS 1500 battery and 2 Leonics MTP-413F 25kW converter. The dispatch method used for this system was the Load Following dispatch method. This method produced at least Net Present Cost of $1.7M (N349.36M), Levelized Cost of Energy of $0.228 (N74.74), considerably high Renewable Fraction of 84.7%, When this result was compared with a diesel generator only system, it showed 77.2% reduction in the diesel saving fuel cost. Comparison with a design plan consisting of diesel generator only showed that 202,155kg of carbon dioxide is saved per year and 1,262kg of carbon monoxide is saved per year when making use of the most optimal system design.