Experimental Analysis of Hill-Climbing MPPT Algorithms under Low Irradiance Levels

Adaptive hill-climbing MPPT algorithms have superior performance as opposed to their conventional counterparts under medium-high irradiance. However, the performance of these hill-climbing algorithms remains mostly unknown under low irradiance condition. The low irradiance conditions are prominent in tropical countries during rainy seasons and niche PV applications. Additionally, several thin-film photovoltaic (PV) technologies have better efficiency under low irradiance conditions. Hence, the optimum operation of MPPT algorithms under low irradiance conditions is vital. In the real-time implementation, MPPT algorithms can fail to detect the incremental changes in voltage and current under low irradiance conditions. Hence, analog to digital converter (ADC) resolution becomes a critical constraint that governs the performance of hill-climbing (HC) MPPT algorithms. This work entails a detailed calculation to determine the perturbation step-sizes of the MPPT algorithms under a wide range of irradiance. Two distinct perturbation step-sizes are determined corresponding to the minimum and optimum change in voltage and current due to perturbation, that is sensed by the ADC. The authors also defined a general expression to determine the optimum digitized step-size for duty-based perturb and observe algorithm under low irradiance condition. This expression is formulated by considering the resolution of the ADC and the desirability of keeping the power oscillations at an acceptable level. Finally, the performance of eight hill-climbing algorithms for two distinct step-sizes is analyzed on a small-scale experimental prototype under both uniform and sudden changes in low values of irradiance. The statistical analysis validates that the adaptive HC drift-free MPPT algorithm outperforms other HC algorithms when implemented with the optimum perturbation step-size under low irradiance conditions.