A global maximum power point tracking algorithm including an artificial neural network and a hill climbing method is combined. The proposed solution is suitably designed for handling fast changing partial shading conditions in photovoltaic systems. Through only a limited number of preselected current measurements, the proposed algorithm is capable to automatically detect the global maximum power point of the photovoltaic array, also minimizing the time intervals required to identify the new optimal operating condition. The method does not require any information on the environmental operating conditions and it is cost-effective, with no additional hardware requirements. The analysis of different artificial neural network structures has pointed out that a simple network can be used when the not-uniform shading conditions change slowly. On the other hand, in the case of solar electric vehicles moving in a city it is necessary the use of more complex structures to reach satisfactory performance.
|Titolo:||Enhanced hybrid global MPPT algorithm for PV systems operating under fast-changing partial shading conditions|
RIZZO, SANTI AGATINO (Corresponding)
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||1.1 Articolo in rivista|