INTELLIGENT BASED WIND-SOLAR HYBRID POWER GENERATION SYSTEM FOR RURAL ENERGY SOLUTION IN ETHIOPIA (IN CASE: KULUMSA VILLAGE)

Electrical energy is a key factor for socio-economic development, improved health care and living standards of human being. Moreover, the benefit is highly exceled if the electricity is generated with Renewable Energy sources (RES). However, RES such as solar PV system have low conversion efficiencies, but have high fabrication cost and are not reliable due to their intermittent nature. Thus, an appropriate control system and a management strategy is required to generate power at optimum efficiency and supply the loads. This thesis work presents the intelligent based PV-Wind hybrid power generation system (IHPGS) with battery energy storage system (ESS) in selected sites of rural areas. A power management algorithms based on Artificial Intelligent Techniques (AITs) is proposed. To enhance efficiency and ensure optimum power from RES, Adaptive Neural-Fuzzy Inference System (ANFIS) based Maximum Power Point Tracking (MPPT) algorithm is employed for PV generation system (PGS) and Fuzzy logic Controller (FLC) based MPPT for wind power generation system (WGS). Moreover, this thesis work describes the implementation of Fuzzy controlled power management system (FPMS) to manage the power flow to the system