Particle Swarm Optimization Of a Hybrid Wind/Tidal/PV/Battery Energy System. Application To a Remote Area In Bretagne, France

A new method proposed in this work to optimize the power generated by a hybrid renewable energy system which consists of Wind turbine/Tidal turbine/PV module/Batteries. This system has been designed to satisfy a stand-alone area in Brittany, France, as an example of load demand. The Particle Swarm Optimization technique (PSO) was proposed and developed to minimize the cost of energy. Where the ability of this algorithm was developed to reach the best results in double speeds, at a time rate better than 80% of conventional technology time and less than 20 repetitions only. The problem is defined as an economic problem, taking into consideration the optimal sizing of the system, high reliability, planning expansion for future development, the state of charge of the battery. The total net present cost (TNPSC) is introduced as the objective function, taking into consideration the minimum fitness values in the particle swarm process. The (PSO) algorithm developed has several characteristics and advantages over other traditional techniques and algorithms. In fact, it allows to achieve the optimal solution and to reduce the overall cost with high speed and accuracy. The PSO algorithm program was developed using MATLAB software.