# Evaluation of Investments in Wind Energy Projects, under Uncertainty. State of the Art Review
## 6 Conclusions  
This article provides a review of models or approaches used in the evaluation of investment in wind systems, under uncertainty. In total, 97 publications were analyzed, finding that this type of research has been increasing. The real options approach is the one most used by researchers, applied in 31 publications, representing 32%. Twenty-eight sources of uncertainty were identified, which were grouped into nine categories: 1. Power generation, 2. Environmental conditions, 3. Energy price, 4. Costs, 5. Income, 6. Energy policies regulation, 7. Market, 8. Wind conditions, and 9. Technological progress. The price of electricity is the source of uncertainty that generates the most interest in the researchers, considered in 20 publications. Random and non-random techniques or models are applied, both to value real options and in uncertainty modeling. There are a series of barriers to investment in wind power generation projects, within these are public opposition-NIMBY \"Not in my backyard\", but no studies were found under the real options approach that would develop this theme, which justifies the possibility of exploring what the management of flexibility may be in this case. Given the importance of investment projects in renewable energy, including wind energy, flexibility is a key factor in the business decision-making process, both in the planning and operating phases. The organizations that have some level of managerial flexibility (administrative and operational) are able to adjust their current decisions to the changes and conditions generated in the future, as caused by the existence of uncertainty. Thus, flexibility becomes an alternative to face uncertainty, because it represents rights and opportunities that any organization can execute when the underlying conditions of a respective project are either favorable or unfavorable. When the value of flexibility is positive, it increases the value of investment cash flows, generating greater social welfare. The effective use of renewable energy sources, including wind energy, is the best strategy to contribute to meeting the objectives of the 2030 Agenda and the Paris agreement, aimed at reducing CO2 emissions. For this reason, it is necessary to intensify in the future the level of research on investment in renewable energy projects, under the approach of real options, which allows further assessment of the uncertainty of the projects to establish flexible strategies and establish efficient controls on high risk of the project investment. According to the findings observed in this analysis, the following lines of future research identified others:  
1. Within a framework of Real Options, investigate the decision of communities to invest in wind energy [72]. 2. Delve into how the application of the real options approach has the potential to increase the expected value of the investment in wind energy, by addressing the impact of uncertainty in the evaluation of the wind resource and contemplating the flexibility within the design and in the project planning [113]. 3. Deepen the impact of the uncertainty caused in the future development of regulatory policies for the generation of renewable energy [114]. 4. Investigate the impact of additional, sequential, or staged investment options at the optimal investment time and size. Future investigations related to public opposition:  
1. Develop studies that consider the real options approach to evaluate the impact of public opposition on investment in renewable energy projects. 2. Study on how to create institutional capital for wind energy and other renewable resources. This implies that more participatory planning practices and inclusive politics of the communities are needed [153]. 3. Research aimed at establishing the determinants for indigenous and Afro-descendant communities within their uses and custom to accept the location of renewable energy projects [155]. Conceptualization, A.H.; methodology, B.M., L.G. and A.H.; validation, A.H. and L.G. ; formal analysis, B.M. ; investigation, B.M.