The need to increase the share of electricity produced from renewable resources has pushed the installation of photovoltaic systems. Solar sources in recent years have experienced strong growth both in terms of investments and installations. In fact, in 2018, solar energy had a global generation capacity of 43% compared to all other power generation technologies. In the coming years, the use of solar energy will grow rapidly, especially for use in different applications. Therefore, studying the behavior of photovoltaic panels and having a model that accurately describes their behavior is essential for the design of the system. Furthermore, increasing the efficiency of the panel in anomalous conditions such as defects, breaks or partial shading is essential. As described, the doctoral thesis is focused on increasing the efficiency of the panels, on the modeling of photovoltaic panels and on the preliminary study of the causes of loss of efficiency and power produced by finding solutions through monitoring systems and applications for reconfigurable panels. After the introduction of the photovoltaic panels, the thesis is followed by a chapter dedicated to mathematical modeling using an equivalent electric model of a photovoltaic panel. This chapter allows to describe the behavior of a photovoltaic panel under normal operating conditions and variable environmental conditions. From a preliminary review of the methods in the literature for the estimations of the parameters, a new method for the extraction of the parameters is proposed. This method starts from the data provided by the manufacturer in the datasheet of the panel and estimates the five parameters. These parameters are needed to model a panel with a single diode equivalent circuit. The proposed method was compared with some works in the literature and the error concerning the data provided by the manufacturer was evaluated A chapter follows on the modeling and simulation of photovoltaic panels through the PSpice environment. In the literature, there are various more or less complex PV Spice models. Some Spice models do not take into account irradiation and temperature variation significant for the design of electronic circuits to be connected to the photovoltaic panels. This proposed model can simulate a photovoltaic panel with temperature and solar radiation variation. With the proposed Spice model as a block is possible to simulate photovoltaic plants both at low power and high power and force partial shading conditions to understand their behavior. After the description of models for photovoltaic panels, the study on possible anomalies present in photovoltaic systems due to defects on the panels or breakages was presented. Thanks to the combination of thermography and electrical measurements for the reconstruction of the IV characteristic of the individual panels, it was possible to understand the various anomalies. Indeed, it is possible to estimate thresholds that will serve to understand if a panel is still good or a replacement is necessary. For this reason, the comparison between thermography and electrical measurements and simulations is provided. Furthermore, this study has allowed us to understand and calculate the annual efficiency loss of the panels and the percentage of voltage variation concerning the temperature not supplied by the manufacturer. The next chapter describes the study and design of an electronic system for monitoring photovoltaic panels connected to a plant. The monitoring of the single panels allows the recognition of possible anomalies and to identify the panel that is the cause. Usually, monitoring is done at the inverter or string level, which however does not allow the faulty panel to be identified in the event of anomalies. The proposed parameter extraction methods and Spice model were used for the design of the monitoring board. Finally, the last activity developed concerns the increase in power lost during partial shading.
Energy efficiency of photovoltaic panel
MUTTILLO, MIRCO
2020
Abstract
The need to increase the share of electricity produced from renewable resources has pushed the installation of photovoltaic systems. Solar sources in recent years have experienced strong growth both in terms of investments and installations. In fact, in 2018, solar energy had a global generation capacity of 43% compared to all other power generation technologies. In the coming years, the use of solar energy will grow rapidly, especially for use in different applications. Therefore, studying the behavior of photovoltaic panels and having a model that accurately describes their behavior is essential for the design of the system. Furthermore, increasing the efficiency of the panel in anomalous conditions such as defects, breaks or partial shading is essential. As described, the doctoral thesis is focused on increasing the efficiency of the panels, on the modeling of photovoltaic panels and on the preliminary study of the causes of loss of efficiency and power produced by finding solutions through monitoring systems and applications for reconfigurable panels. After the introduction of the photovoltaic panels, the thesis is followed by a chapter dedicated to mathematical modeling using an equivalent electric model of a photovoltaic panel. This chapter allows to describe the behavior of a photovoltaic panel under normal operating conditions and variable environmental conditions. From a preliminary review of the methods in the literature for the estimations of the parameters, a new method for the extraction of the parameters is proposed. This method starts from the data provided by the manufacturer in the datasheet of the panel and estimates the five parameters. These parameters are needed to model a panel with a single diode equivalent circuit. The proposed method was compared with some works in the literature and the error concerning the data provided by the manufacturer was evaluated A chapter follows on the modeling and simulation of photovoltaic panels through the PSpice environment. In the literature, there are various more or less complex PV Spice models. Some Spice models do not take into account irradiation and temperature variation significant for the design of electronic circuits to be connected to the photovoltaic panels. This proposed model can simulate a photovoltaic panel with temperature and solar radiation variation. With the proposed Spice model as a block is possible to simulate photovoltaic plants both at low power and high power and force partial shading conditions to understand their behavior. After the description of models for photovoltaic panels, the study on possible anomalies present in photovoltaic systems due to defects on the panels or breakages was presented. Thanks to the combination of thermography and electrical measurements for the reconstruction of the IV characteristic of the individual panels, it was possible to understand the various anomalies. Indeed, it is possible to estimate thresholds that will serve to understand if a panel is still good or a replacement is necessary. For this reason, the comparison between thermography and electrical measurements and simulations is provided. Furthermore, this study has allowed us to understand and calculate the annual efficiency loss of the panels and the percentage of voltage variation concerning the temperature not supplied by the manufacturer. The next chapter describes the study and design of an electronic system for monitoring photovoltaic panels connected to a plant. The monitoring of the single panels allows the recognition of possible anomalies and to identify the panel that is the cause. Usually, monitoring is done at the inverter or string level, which however does not allow the faulty panel to be identified in the event of anomalies. The proposed parameter extraction methods and Spice model were used for the design of the monitoring board. Finally, the last activity developed concerns the increase in power lost during partial shading.I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/20.500.14242/93212
URN:NBN:IT:UNIVAQ-93212