Selection Map for PV Module Installation Based on Shading Tolerability and Temperature Coefficient

Abstract

Photovoltaic (PV) systems have provided the world with a renewable and environment friendly energy solution. However, PV systems face various loss mechanisms at the module level as well as power electronics level which need to be addressed for further growth of the technology. Power generation from PV modules suffer from heat losses that are a function of the temperature coefficient of maximum power (γ) of the PV module. Another loss mechanism is the shading of PV module where the power output of a module and ultimately the system can be severely compromised. Although various approaches such as bypass diodes and module level power electronics have been employed to minimize the effects of shading on a PV module, so far, the performance of a PV module under shading had only been addressed vaguely and was generally described qualitatively. Therefore, a parameter called Shading Tolerability (ST) was recently developed to quantify the behavior of PV modules under all kinds of shade. However, the observations pertaining to Shading Tolerability were only carried out under Standard Test Conditions (STC). Hence, this thesis aims to investigate whether ST is an innate property of a PV module by formulating a correlation, if there’s any, between ST and ambient temperature, classify various PV technologies based on ST and γ and develop a selection map so that an optimal selection of PV modules can be made for the design of PV systems simply by knowing the specifications of the module along with the meteorological conditions of the installation location. Furthermore, different interpolation techniques were evaluated to achieve a comprehensive picture of the meteorological conditions of The Netherlands to determine the most optimal PV technology for The Netherlands using the PV selection map. Finally, Performance Ratios of various existing PV systems were calculated using suitable irradiation decomposition and transposition models as a proof for the validity of the selection map. The obtained results showed that PV systems using CIGS technologies exhibited higher performance ratios on average as was suggested by the selection map.