Operation of the Egyptian Power Grid with Maximum Penetration Level of Renewable Energies Using Corona Virus Optimization Algorithm

Countries around the world are looking forward to fully sustainable energy by the middle of the century to meet Paris climate agreement goals. This paper presents a novel algorithm to optimally operate the Egyptian grid with maximum renewable power generation, minimum voltage deviation and minimum power losses. The optimal operation is performed using Corona Virus Algorithm (CVO). The proposed CVO is compared to the Teaching and Learning-Based Optimization (TLBO) algorithm in terms of voltage deviation, power losses and share of renewable energies. The real demand, solar irradiance and wind speed in typical winter and summer days are considered. The 2020 Egyptian grid model is developed, simulated, and optimized using DIgSILENT software application. The results have proved the effectiveness of the proposed CVO, compared to the TLBO, to operate the grid with the highest share possible of renewables. The paper is a step forward to achieve Egyptian government targets to reach 20% and 42% penetration level of renewable energies by 2022 and 2035, respectively.

Automated summary

This paper presents a novel algorithm, called the Corona Virus Algorithm (CVO), to optimally operate the Egyptian grid with maximum renewable power generation. The effectiveness of the proposed algorithm is compared to the Teaching and Learning-Based Optimization (TLBO) algorithm in terms of voltage deviation, power losses, and share of renewable energies. The results demonstrate that the CVO algorithm outperforms the TLBO algorithm in maximizing the use of renewable energies in the grid. This research is significant for the Egyptian government in achieving their targets for renewable energy penetration.