Statistical modeling of DSP-based hill-climbing MPPT algorithms in noisy environments

The effect of measurement noise on DSP-based maximum power point tracking (MPPT) algorithms is investigated in this paper. Based on the probabilistic characteristics of noise signals, a statistical model is constructed that allows quantitative analysis of the behavior of such algorithms both during transients and in steady-state. This model is then used to classify tracking problems into those presented by noise, and others resulting from other non-idealities such as measurement bias. It is then used to inspect different noise fighting techniques in order to predict their validity, and to suggest more relevant techniques. The results arrived at are then experimentally verified and confirm the predictions of the statistical model.