This paper presents a simple methodology to optimize the size of a hybrid wind generator (WG), photovoltaic (PV) module and battery storage system for a given demand. The method utilizes typical meteorological year (TMY) data to calculate hourly power output of a PV module and a WG throughout the year. By changing the combination of PV and WG, the generated energy is matched with the hourly average load of a year. This is done in such a way that the maximum of the total energy deficit in a cluster of hours in between hours of excess energy generations becomes minimum. The required number of batteries is calculated from that maximum of the total energy deficit among these clusters. The combination of WG, PV and battery that satisfies the desired loss of power supply probability (LPSP) and has the lowest total cost is considered as the optimum. A case study has been carried out to size a hybrid renewable energy system (HRES) optimally. The size obtained by this method is verified using an iterative algorithm and a genetic algorithm (GA). It is found that all of these methods give the same result for the same demand.