Improved Incremental Conductance Algorithm with NMPC Controller for Tracking GMPPT under Partial Shading Conditions in Photovoltaic Arrays

This work presents a methodology for tracking the maximum power point in a photovoltaic (PV) panel through the setup of a converter and battery; in this context, the search for the Maximum Power Point Tracking (MPPT) is carried out by integrating an improved Incremental Conductance (INC) algorithm with a Nonlinear Model Predictive Controller (NMPC). This approach uses voltage and current data to adjust system behavior under partial shading conditions, improving accuracy in Global Maximum Power Point Tracking (GMPPT). The methodology is implemented on a DC/DC boost converter connected to a battery and tested under five irradiance scenarios. The INC algorithm is enhanced by a random exploration strategy to escape local maxima and a moving average filter to stabilize voltage tracking. The NMPC controller optimizes the control signals in real time, enabling precise adjustment despite nonlinear behavior. The proposed system achieves over 99% accuracy and response times under 0.05 seconds. The results indicate better performance than traditional algorithms, especially under dynamic irradiance conditions, validating the suitability of this control strategy for real-world PV applications.