Abstract:
This study proposes a decentralized hybrid energy system consisting of solar photovoltaics
(PV) and wind turbines (WT) connected with the local power grid for a small Najran, Saudi Arabia
community. The goal is to provide the selected community with sustainable energy to cover a partial
load of the residential buildings and the power requirements for irrigation. For this, a dynamic
model was constructed to estimate the hourly energy demand for residential buildings consisting of
20 apartments with a total floor area of 4640 m2, and the energy requirements for irrigation to supply
a farm of 10,000 m2 with water. Subsequently, HOMER software was used to optimize the proposed
hybrid energy system. Even considering the hourly fluctuations of renewable energies, the artificial
neural network (ANN) successfully estimated PV and wind energy. Based on the mathematical
calculations, the final R-square values were 0.928 and 0.993 for PV and wind energy, respectively.
According to the findings, the cost of energy (COE) for the optimized hybrid energy system is
$0.1053/kWh with a renewable energy penetration of 65%. In addition, the proposed system will
save 233 tons of greenhouse gases annually.
