The necessary transformation of the world’s energy matrices has led to a growth in developing technologies based on renewable sources. In this context, photovoltaic panels and their components count in Brazil with a production and commercialization chain that has accumulated a sustained growth of more than 100% of its generation capacities between the years 2018 and 2019, and that can fulfill or overcome this rate in 2019 to 2020. However, the conditions of a competitive market and the availability of a significant number of middle and small companies for the distribution and installation of photovoltaic technology may represent a scenario where multiple indicators must be considered. The purpose of this study is to apply a combined method to aid decision-making that corresponds to the supplier selection of the technology in the context of Northeast Brazil. The method is composed by the combination of a diffuse inference technique together with a multicriteria decision-making method, VIKOR, and the weight assignment to the indicators using the entropy method, according to the values of the decision matrix resulting from the diffuse inference technique that allows to develop the calculus. The results show that data collection from multiple sources and based on input variables can offer metrics about the suppliers for the selection criteria. Restrictions derived from data collection can be a barrier, and the method relies on an adapted script that facilitates application.

This paper presents a comprehensive methodology for the selection of power semiconductor devices in a standalone photovoltaic (PV)-battery system (SPBS) based on power loss analysis. The SPBS configuration is modeled analytically, and the waveforms for the system are obtained in a Hardware-In-the-Loop (HIL) and by simulation environment using Matlab. The study focuses on identifying the most cost-effective power semiconductor devices by assessing power loss at three distinct operating points. The algorithm evaluates losses in each component, facilitating the selection of optimal devices for enhanced system performance. The evaluation is performed for different operational modes, incorporating worst-case scenarios for current and voltage, providing a robust analysis of system behavior. By emphasizing the importance of power loss analysis in isolated PV systems, this research contributes to the advancement of energy efficiency in SPBS. The proposed methodology enables the identification of power semiconductor devices experiencing the highest losses, aiding in the selection of components that minimize overall losses and maximize energy utilization from PV panels and batteries.