There are many companies in Ethiopia that are ever-growing fast. One of the leading companies is Ethiopian telecommunication which provides a quality telecom service to citizens and supports the development of the country. To ensure this quality service, one of the most driving agents is electrical power which can be generated from different sources of energies like Diesel Generator (DiG=20KVA), Main Grid (MG) and Photo Voltaic (PV=11.5kW) generator along with the backup Battery Banks (BB) in the form of hybrid power system with 48VDC volt system for a typical site of GINDE WOYN MW. Doing such type of power combination may secure the power supply to the required load demand but still this hybrid energy system has its own problem on its controlling system. Since the company operate its DiG automatic with the MG without considering PV power and the backup battery. These forces the company costs more for diesel fuel as well as billing for Ethiopian Electric Utility Company (EEU). Hence, this thesis is going to solve the problem by applying Fuzzy Logic Controller (FLC) based Energy Management System (EMS) for power source selection. The proposed EMS prioritizes the power source according to the availability of each sources unit. The first selection of FLC is the renewable energy source of PV power, the second selection is backup battery within its upper and lower limit of SOC of the battery and the third selection is the mains grid if any lastly the diesel generator if no mains available. FLC is used to choice among different power sources in a hybrid system. Maximum Power point tracking (MPPT) based on artificial neural network (ANN) for PV system to maximize output power of the PV generator under different environmental conditions such as solar irradiance and temperature. Since renewable energy is green unlike diesel generator, it doesn't emit carbon dioxide which causes global warming. Modelling all existing components like solar panel, diesel generator, converters, grid power, different MPPT trackers and simulations have been executed with Matlab/Simulink software. Simulation result shows the ability of EMS based on FLC to optimize the system performance and certified the effectiveness of the proposed system which achieves by reducing 72.92% fuel consumption and 41.67% commercial billing for EEU also.