Energy Flow Management in a Smart Microgrid Based on Photovoltaic Energy Supplying Multiple Loads

Decentralized electricity production solutions based on renewable energies are increasingly used in Africa to promote the social inclusion of the population in rural areas. In these areas not served by the electricity network, there are more and more network infrastructures installed by mobile network operators that are powered by genset. These energy sources only serve to provide electricity to the site elements while the local population lives without electricity. The use of microgrid based on renewable energies, particularly solar energy, on these operator sites can contribute to achieving goals 7 and 9c of the Sustainable Development Goals. Indeed, intelligent management of these microgrids can ensure a continuous supply of electricity to the mobile network operators' sites and the use of excess production to offer electricity to the local population. To achieve this convergence between universal access to telecommunications and energy, based on these microgrids, the use of an optimization algorithm for better planning and operating efficiency of these microgrids is essential. To this end, the Particle Swarm Optimization algorithm was used for optimal power flow management in a multi-source and multi-load system to test the ability of microgrids to achieve this new objective. The obtained results showed that an optimal management of these microgrids guarantees a Loss of Power Supply Probability of 0.18 %, a Levelized Cost of Electricity of US$ 0.0187, and a Maximum Renewable Factor of 98%. Low cost of electricity obtained shows that this solution is a real opportunity for increasing universal access to electricity for low-income populations in rural areas. Similarly, the Maximum Renewable Factor value obtained shows a reduction in the running time of the genset, with the consequence of significantly reducing operating costs and greenhouse gas emissions.