Optimisation of fuzzy controller for tracking the maximum power point in PV systems

In recent years the development of photovoltaic cells has increased due to the high demand for clean and green energy. Used around the world for energy production, the power production of these cells must be maximized in all weather conditions, therefor systems for tracking the Maximum Power Point became necessary, the most widely used being Perturb & Observe. Fuzzy Logic (Type 1 & 2) was introduced due to inconveniences in the use of the P&O method. FL furthers development and allows the system to better handle uncertainty. This method proves to be both efficient and robust, and is combined with an evolutionary algorithm to further enhance it. This work focuses on the tracking of MPP using IT2FL in combination with genetic algorithms and Particle Swarm Optimization Algorithms.