Energy Management of PV-Wind hybrid System (Case Study Washuy Village in South Gonder Zone)

Abstract

In places where there isn't a consistent power supply, providing consistent and dependable service can be a major challenge. To address this issue, renewable energies are often considered the most suitable and practical supply options for sustainable and clean electricity production in isolated rural areas. In this thesis, an Energy Management System (EMS) based on an ANFIS (Adaptive Neuron Fuzzy Inference System) is presented for a hybrid configuration of Wind Turbine (WT), Photo Voltaic (PV) and Battery for the critical Washuy village sites. The design, simulation, and evaluation of this system are carried out using MATLAB software. A power flow control scheme is designed to control the flow of electricity from renewable energy sources like wind and solar and to manage the battery charging and discharging level. Different modes of operation are selected automatically dependent on the battery's State of Charge (SOC), solar isolation, and the wind's available velocity. To modify the range of DC voltage for the solar PV system, a Single Ended Primary Inductance Converter (SEPIC) DC-DC converter and a low-pass filter are created and modeled. The ANFIS controller is made for Maximum Power Point Tracking (MPPT), which takes into account changes in voltage and power from both solar and wind energy. The batteries' charge and discharge are controlled by a Proportional Integral (PI)controller. The total load of Washuy village is 206.945KW with a daily energy consumption of 843.22 KWh, for this load designed 1212 panels with a peak power of 301.443kW polycrystalline silicon photovoltaic, 40kW of wind power and 6000Ah of batteries are connected integrally.