Crafting an investment portfolio is an intricate process, steeped in an environment laden with uncertainties. Within this context, this study introduces the concept of a hypothetical investment fund, with a primary focus on energy infrastructure. The fund specifically targets renewable energy generation assets, such as solar and wind farms, strategically situated in the Northeast region of Brazil. The fund’s investment strategy is rooted in a risk-averse stochastic optimization model, aiming to maximize the Conditional Value at Risk (CVaR) of the revenue stream generated by the energy generation assets. This model accounts for fluctuations in energy production and spot market prices, with the overarching goal of optimizing the fund s return against a specified risk. The data employed for analysis and modeling were drawn from real-world generation records of solar and wind farms in the Northeast, spanning the period from July 2019 to July 2021. This dataset offers a comprehensive perspective on energy production variations and enables precise modeling of the fund s asset performance. Through this study, we were able to pinpoint the optimal portfolio composition for the fund to maximize the CVaR of the revenue stream. However, it s crucial to underscore that the optimal portfolio composition can shift depending on market conditions and the unique characteristics of the energy generation assets. As such, the portfolio composition should undergo regular review and adjustment to ensure that the fund maintains the desired balance between risk and return.