Implementation of a neural MPPT algorithm on a low-cost 8-bit microcontroller

This work proposes a maximum power point tracking algorithm based on neural networks embedded in a low-cost 8-bit microcontroller. The obtained device can correctly track the maximum power point even under abrupt changes in solar irradiance and improves the dynamic performance of the power converter that connects photovoltaic power plants into the ac grid. Indeed, traditional maximum power point tracking algorithms such as “perturb & observe” and “incremental conductance” are able to track the point of maximum power in most cases but they can fail under rapidity changing atmospheric conditions. The use of a microcontroller allows for easy updates and enhancement by simply adding code libraries. Furthermore, it can be interfaced via standard communication means to other control devices, integrated into control schemes and remote-controlled through its embedded web server. The proposed approach has been validated through experimental and simulated results.