the objective of this document is the determination of the maximum power point using the best suited algorithm on the environment Psim. The photovoltaic panel will be modelled by a diode and two resistances, the first on will be put in parallel, the second one will be put in series. The output of this model will be composed of the current, voltage, and the power. We added a DC-DC boost converter which will adapt the impedance in order to be always on the maximum power point, to track this maximum power point we added another block in which we implemented an algorithm to get to this point as fast as possible without needing lot of resources. And to get to that objective, we used an adapted version of the Kalman Filter.

The purpose of this paper is to present a performance comparison between two maximum power point tracking algorithms. These two algorithms are incremental conductance (INC) which is an improved version of the perturb and observe algorithm, and the second algorithm is the Kalman filter applied to a photovoltaic system. In this work, a photovoltaic panel is modeled in PSIM tool; a Boost converter controlled by the maximum power point tracker is put between the PV panel and the load. Then the two algorithms are implemented by using C language and C block provided by PSIM tool. Next, several tests under stable and variable environmental conditions are made for the two algorithms, and results show a better performance of the Kalman filter compared to the INC in terms of response time, efficiency and steady-state oscillations.