With the increasing demand for electrical energy, the design of electrical networks is becoming more and more complex to operate according to standards. The choice of devices for the installation of an electrical network would lead to many consequences such as loss of power, deterioration of the line due to overvoltages, etc. As a result, there are several methods of solving difficult problems, including metaheuristic methods. These methods, which appeared in the 1980s, are inspired by natural systems such as the particle swarm (PSO), the ant colony (ACO) and the genetic algorithm method (AG). The latter is a global research and optimization technique that is based on the mechanisms of natural selection and genetics, which can simultaneouly search for several possible solutions. In this work, it is a question of proposing a progam based on a metaheuristic method which will make it possible to optimally choose the elements of an electrical network. To do this, we first used the parameters of the Cameroonian North Interconnected Network (RIN) the proposed a program based on a genetic algorithm that we simulated with the characteristics of the latter using the MATLAB software in order to choose the best devices (conductors, insulators, pylons) for its implementation.

This work relates to a method of flow control for a unit of ultrafiltration membrane water powered by photovoltaic energy over the Sun in order to better master the sealing time and avoid damage to the filtration module. The complete system modeled and simulated on Matlab/Simulink includes a photovoltaic generator and a floor of adaptation converter-inverter, a single phase Electromagnetic induction motor coupled to a centrifugal pump, constituting the membrane ultrafiltration unit. The chopper booster switch IGBT is controlled by a MPPT controller - P & O that regularly adjusts the duty cycle taking its values in a range restricted to stabilize the voltage at the output of the chopper, and at the same time the flow of the pump.