Deep Analysis on Sizing a Renewable Energy System at 12 Locations in Morocco Using Particle Swarm Optimization

Abstract

This study provides an in-depth analysis of the optimal sizing of a renewable energy system, consisting of both photovoltaic (PV) and wind energy, for twelve cities located throughout the Kingdom of Morocco. The objective of the study is to determine the most appropriate combination of wind and PV-based renewable energy systems with a capacity under 20 kWp that can achieve an annual output greater than 5000 kWh/year in each of the twelve cities. To attain this objective, the study employs the particle swarm optimization algorithm and the levelized cost of energy (LCOE) as the objective function to be minimized. The LCOE is calculated as the average cost of generating each kilowatt-hour of energy over the lifetime of the system, taking into account the initial capital cost, maintenance costs, operating costs, annual output, discount rate, and degradation rate. Three different scenarios were considered in this study. As a matter of fact, the first scenario includes the case where no excess energy is sent to the grid. In the second scenario, only 10% of excess energy is sent to the grid. In the last scenario, any excess energy available is sent to the grid. The results of the analysis show that integrating excess energy into the grid has a positive impact on the LCOE, with the lowest value (0.08$/kWh) achieved in Laayoune and Dakhla in the third scenario where all the excess of energy is sent to the grid.