In this paper an equipment aimed to help researchers and engineers in developing new techniques for the effective usage of photovoltaic panels is presented. Basically, the proposed equipment is a fully programmable DC-DC converter, with the capability to produce in output either a lower or an upper voltage, with respect to that delivered by the photovoltaic panel. An advanced microcomputer board inside it provides easy and wide connectivity as well as extensive programming and measurement functionalities. An example of use case for this equipment is the development of maximum power point tracking (MPPT) algorithms, but also photovoltaic (PV) panels characterization, by means of their characteristic curves, is possible. A fast prototyping of a battery charger employing a neural network MPPT algorithm is described.
Gaiotto, S., Laudani, A., RIGANTI FULGINEI, F., Salvini, A., Cardelli, E., Faba, A. (2016). An equipment for photovoltaic panels characterization based on a fully programmable DC-DC converter. In EEEIC 2016 - International Conference on Environment and Electrical Engineering (pp.1-6). Institute of Electrical and Electronics Engineers Inc. [10.1109/EEEIC.2016.7555563].
An equipment for photovoltaic panels characterization based on a fully programmable DC-DC converter
LAUDANI, ANTONINO;RIGANTI FULGINEI, Francesco;SALVINI, Alessandro;
2016-01-01
Abstract
In this paper an equipment aimed to help researchers and engineers in developing new techniques for the effective usage of photovoltaic panels is presented. Basically, the proposed equipment is a fully programmable DC-DC converter, with the capability to produce in output either a lower or an upper voltage, with respect to that delivered by the photovoltaic panel. An advanced microcomputer board inside it provides easy and wide connectivity as well as extensive programming and measurement functionalities. An example of use case for this equipment is the development of maximum power point tracking (MPPT) algorithms, but also photovoltaic (PV) panels characterization, by means of their characteristic curves, is possible. A fast prototyping of a battery charger employing a neural network MPPT algorithm is described.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
