Received 1 September 2014 Received in revised form 31 March 2015 Accepted 20 April 2015 Available online 3 July 2015 Keywords: Photovoltaic systems Maximum power production Dynamical reconfiguration 1. Introduction The efficiency of a photovoltaic (PV) panel is actually about 15%, but in real applications this figure is even lower because of many reasons. One of the reasons occurring especially in urban context is the mismatched operating conditions at which the panels forming a PV plant work [10]. As some panels are connected in series in order to reach a voltage level that fits with the input specifications of the commercial inverters, the presence of a partial shadowing affecting some cells or other inhomogeneity among the parameters of the cells, e.g., due to aging, failures or manufactur- ing tolerances, might cause a significant drop in the power production [24]. Producers usually install bypass diodes in the panels for mitigating the power loss in case of mismatching, but these diodes greatly change the voltage vs. current ðV IÞ char- acteristic of the PV array. When the diodes enter into conduction for compensating a current mismatching among the cells of the string, the voltage vs. power (V P) characteristic of the array shows more than one Maximum Power Point (MPP). To obtain the MPP, the inverter control system is usually equipped with a Maximum Power Point Tracking (MPPT) algorithm and many methods have been proposed in the literature with the aim to find the MPP, including Fuzzy Logic and Neural Networks n Corresponding author. E-mail addresses: pcarotenuto@unisa.it (P.L. Carotenuto), adellacioppa@unisa.it (A. Della Cioppa), amarcelli@unisa.it (A. Marcelli), gspagnuolo@unisa.it (G. Spagnuolo). http://dx.doi.org/10.1016/j.neucom.2015.04.094 0925-2312/& 2015 Elsevier B.V. All rights reserved. abstract The dynamical reconfiguration of photovoltaic panels is a useful approach for fighting the detrimental effects of mismatching on their power production. The practical implementation of the method has been recently optimized by means of efficient and reliable relays. However, two problems remain still open. The first is to determine the optimal electrical connection among the panels that ensures the maximum power produced at the actual irradiance conditions, while the latter is to constrain the computation time of such optimal configuration to fit the need of real time applications. We present an evolutionary approach to the first problem. It is designed for allowing a straightforward porting to an embedded system and it is aimed at reconfiguring photovoltaic panels, thus not modules like some other approaches do in literature. Simulation results confirm the reliability and convergence capabilities of the proposed method and encourage further work for the adoption of the algorithm in real time applications. The problem of minimizing the computation time is also addressed.

An Evolutionary Approach to the Dynamical Reconfiguration of PhotoVoltaic Panels

SPAGNUOLO, Giovanni;DELLA CIOPPA, Antonio;MARCELLI, Angelo;CAROTENUTO, PIETRO LUIGI
2015

Abstract

Received 1 September 2014 Received in revised form 31 March 2015 Accepted 20 April 2015 Available online 3 July 2015 Keywords: Photovoltaic systems Maximum power production Dynamical reconfiguration 1. Introduction The efficiency of a photovoltaic (PV) panel is actually about 15%, but in real applications this figure is even lower because of many reasons. One of the reasons occurring especially in urban context is the mismatched operating conditions at which the panels forming a PV plant work [10]. As some panels are connected in series in order to reach a voltage level that fits with the input specifications of the commercial inverters, the presence of a partial shadowing affecting some cells or other inhomogeneity among the parameters of the cells, e.g., due to aging, failures or manufactur- ing tolerances, might cause a significant drop in the power production [24]. Producers usually install bypass diodes in the panels for mitigating the power loss in case of mismatching, but these diodes greatly change the voltage vs. current ðV IÞ char- acteristic of the PV array. When the diodes enter into conduction for compensating a current mismatching among the cells of the string, the voltage vs. power (V P) characteristic of the array shows more than one Maximum Power Point (MPP). To obtain the MPP, the inverter control system is usually equipped with a Maximum Power Point Tracking (MPPT) algorithm and many methods have been proposed in the literature with the aim to find the MPP, including Fuzzy Logic and Neural Networks n Corresponding author. E-mail addresses: pcarotenuto@unisa.it (P.L. Carotenuto), adellacioppa@unisa.it (A. Della Cioppa), amarcelli@unisa.it (A. Marcelli), gspagnuolo@unisa.it (G. Spagnuolo). http://dx.doi.org/10.1016/j.neucom.2015.04.094 0925-2312/& 2015 Elsevier B.V. All rights reserved. abstract The dynamical reconfiguration of photovoltaic panels is a useful approach for fighting the detrimental effects of mismatching on their power production. The practical implementation of the method has been recently optimized by means of efficient and reliable relays. However, two problems remain still open. The first is to determine the optimal electrical connection among the panels that ensures the maximum power produced at the actual irradiance conditions, while the latter is to constrain the computation time of such optimal configuration to fit the need of real time applications. We present an evolutionary approach to the first problem. It is designed for allowing a straightforward porting to an embedded system and it is aimed at reconfiguring photovoltaic panels, thus not modules like some other approaches do in literature. Simulation results confirm the reliability and convergence capabilities of the proposed method and encourage further work for the adoption of the algorithm in real time applications. The problem of minimizing the computation time is also addressed.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4648999
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