The objective of this study was to develop an optimal evaluation system for collocating photovoltaic (PV) modules and power conditioners by using the extension engineering method. The matter-element model and correlation functions of the extension theory were adopted as the basis of the proposed extension evaluation system, which was then used to develop a multilevel evaluation model for PV modules and PV power conditioners. The extension evaluation system was used to evaluate and test numerous PV modules and power conditioner products that are commonly employed and commercially available in Taiwan. First, a PV module matter-element model was established based on price, power temperature, size, and weight, and a PV power conditioner matter-element model was established based on input voltage range, maximum power point tracking (MPPT) voltage range, number of MPPT units, minimum operating voltage, and maximum input current. Second, the weighting values of the various characteristics in the extension method were determined according to numerous consideration factors of the PV modules and power conditioners. Finally, the values of the degree of correlation between numerous user preferences and the various PV modules and power conditioner brands were calculated using correlation functions to determine the key components of PV power generation systems (PV-PGSs) that corresponded to user preferences. The test results confirmed that the proposed extension evaluation system can determine the optimal collocation for the key components of the PV-PGSs under different user preference settings.

This paper aims to present a smart, particle swarm optimization (PSO)-based, real time configuration strategy for a photovoltaic (PV) module array in the event of shadow cast on a PV module(s) and/or module failure as an effective approach to power generation efficiency elevation. At the first step, the respective maximum output power levels provided by a normal operating array at various levels of irradiation and module surface temperatures are measured and entered as references into a database. Subsequently, the maximum output power (MPP) level, tracked by a MPP tracker, is feedbacked for a comparison with an aforementioned reference as a way to tell whether there is either a shadow or a malfunction event on a PV module(s). Once an abnormal operation is detected, the presented smart configuration algorithm is performed to reconfigure the PV module array such that the array is operated at the global MPP as intended. Furthermore, by use of a PIC microcontroller that is a family of microcontrollers made by Microchip Technology for compact implementation, this study is experimentally validated as an effective approach to locating the global MPP at all events.