Sizing Renewable Energy by Using Genetic Algorithm

In this study, the levelized cost of energy (LCOE) is used as an objective function that will be minimized using the genetic algorithm (GA). The main objective is to assess the techno-economic viability of renewable energy (RE) systems less than 20 KW based on solar and wind energy and produce at least an annual output of 5000 KWh per year in 12 Moroccan locations that have a good potential of solar and wind energy. Moreover, this work discusses two scenarios. In the first scenario, the energy excess is not injected into the grid, whereas in the second scenario, all the energy excess is injected into the grid. The obtained results have demonstrated that a hybrid RE system consisting of both, wind and solar energy sources, is the most favorable type of system for the majority of the studied cities, with nine hybrid systems and three single-energy systems identified by the GA. The lowest LCOE value of 0.11 $/KWh was achieved in Dakhla using a single RE system based on wind with a nominal capacity of 8.7 KW. These findings indicate that the hybrid RE system design is a viable and cost-effective option for powering the cities in Morocco with RE, which can lead to significant environmental and economic benefits.