The steadily rising efficiency together with the accuracy of prediction in solar photovoltaic (PV) energy requires a deterministic reliability in the realistic PV characteristic’s prediction subject to climatic changes. This empirical-based research validates IEC 61853 and improves output power prediction of a solar PV module with considering nominal operating cell temperature (NOCT) using online infrared thermal camera at short range outside. The impact of NOCT consideration is investigated, in which the error can be as high as 10.4¿°C in comparison to non-NOCT. The objective is minimizing the power prediction error for the PV module, the significant parameters of the maximum power point tracking (MPPT) controller are used to evaluate the changes followed by the climatic-related parameters under partial shading condition. A set of non-parametric correlations are calculated using Spearman’s ¿ and Kendall t rank statistical methods to avoid experimental measurement difficulties and cost for an advanced output power prediction. Finally, the differences on the heat distribution of each cell, and its impact in the annual power prediction have been numerically and experimentally verified.

Peer Reviewed