A novel auto‐tuned adaptive frequency and adaptive step‐size incremental conductance MPPT algorithm for photovoltaic system

Summary This paper presents an auto‐tuned Incremental Conductance (Inc) maximum power point tracking (MPPT) algorithm for a photovoltaic (PV) system. Proposed MPPT algorithm is adaptive in nature in terms of both MPPT perturbation frequency and step‐size based on the change in PV voltage. To verify the functionality of the proposed adaptive frequency adaptive step‐size Inc MPPT method, a boost converter based PV setup is developed and the algorithm is implemented in Arduino Mega‐2560 micro‐controller. An extensive comparative result analysis of the proposed technique is done with the conventional fixed frequency variable step‐size Inc MPPT algorithms which are based on power‐voltage slope and change in power. The proposed change in PV voltage based adaptive frequency adaptive step‐size algorithm improves both steady‐state and dynamic performance compared to the conventional fixed frequency variable step‐size Inc algorithm. The steady‐state oscillation is low with a faster tracking response. The classical and proposed Inc MPPT algorithm is verified in a 200 W developed laboratory solar PV setup. All the algorithms are tested through 10‐bit Arduino Mega‐2560 micro‐controller which makes field implementation simple and less costly. The selection of variable step‐size and perturbation frequency is discussed in detail. The proposed approach customizes the tuning of PV voltage based MPPT perturbation step‐size and frequency. A detailed experimental comparative results are presented for fixed step‐size (FSS), fixed frequency variable step‐size (FFVS) with proposed adaptive frequency adaptive step‐size (AFAS) Inc algorithm. The performance of the proposed one is better in terms of tracking speed and efficiency. The effectiveness of the algorithm is also tested during load change which confirms the robustness of the system.