In the current scenario of increasing energy demand and encouraging sustainable development in countries, the energy sector’s planning has become more complex, involving multiple factors, such as technical, economic, environmental, social, and political. The decision process plays a vital role in structuring and evaluating complex decision situations related to the sector, considering various criteria and objectives, encouraging adopting policies to promote energy efficiency actions by increasing research on renewable energy sources and strategic energy decisions. The high number of multi-criteria decision support methods (MCDM) available and their efficiency in solving highly complex problems results in an impasse with their selection and application in specific decision situations. Thus, the scientific community requires methodological approaches that help the decision-maker select the method consistent with his problem. Accordingly, this paper conducts a Systematic Literature Review (SLR) of renewable energy problems associated with MCDM methods based on a final set of 163 articles. We identified five categories of problems solved by MCDM techniques: Source selection, location, sustainability, project performance, and technological performance. We separate the MCDM process into five evaluation steps (alternative selection, criteria selection, criteria weighting, evaluation of alternatives, and post-assessment analyzes), and we extract the methods used in each MCDM step from papers. This paper’s main contribution is identifying the most common MCDM methods in the renewable energy area and the energy problem they solve. Accordingly, this manuscript helps energy decision-makers, entrepreneurs, investors, and policy-makers to improve their ability to choose the proper MCDM methods to solve energy problems.

Photovoltaic (PV) power generation is embedded in a globally competitive environment. This characteristic forces PV power plants to perform most processes relevant for their competitiveness with maximum efficiency. From managers’ point of view, the evaluation of solar energy performance from installed plants is justified to indicate their level of organizational competitiveness, which supports the decision-making process. This manuscript purposes a computational tool that graphically presents the level of competitiveness of PV power plants units based on performance indicators. This tool was developed by using the Key Performance Indicators (KPIs) concept, which represents a set of measures focusing on the most critical aspects for the success of the organizations. The KPIs encompass four Fundamental Viewpoints (FV): Strategic Alliances, Solar Energy Monitoring, Management and Strategic Processes, and Power Generation Innovations. These four FVs were deployed on 26 Critical Success Factors (CSFs) and 39 KPIs. Sequentially, the tool was applied in four solar generation plants, where three presented an organizational competitiveness global level “potentially competitive”. The proposed computational tool allows managers to assess the degree of organization competitiveness as well as aid in prospecting of future scenarios and decision-making.

The implementation of energy-efficient systems in homes is of interest to many people, especially regarding the use of solar photovoltaic (PV) energy systems. Solar PV generation is essential worldwide because it is a significant source of renewable energy, wherein electricity can be stored for future use, and a cost-effective path for residential consumers. In contrast, considering the number of people who invest in PV systems versus those who do not, adherence is significantly unequal throughout society. Accordingly, predominant factors exist that increase the likelihood of residential PV solar power generation system adoption, which are seen as opportunities to increase energy efficiency. Furthermore, the literature is still insufficient regarding the exploration of variables that determine decisions around the purchase of green power generation systems. From this perspective, the current research aims to identify the socio-psychological profile of photovoltaic energy investors by applying four questionnaires, namely, psychological values, the human–nature relationship, motivation analyses, and household characteristics. The research results define the profile and motivations of green energy investors. The attitudes of potential investors are also predicted, and this research contributes to the development of the photovoltaic energy industry production chain by providing relevant information for better photovoltaic policy design and more targeted marketing strategies for companies.