| dc.description.abstract | Brazil has a world different energy matrix, where the most part of the electricity generation is by renewable resources. However, the expectation of increase load demand, the problems caused by the burning of fossil fuels and the environmental impacts of large hydropowers are factors that imply the need to increase the installed capacity of other renewable sources. This increase in capacity requires investments in renewable generation, and this decision is affected by different aspects such as variability in generation, uncertainties in the energy market and investor risk aversion, the company’s current portfolio, among others. The paper presents a stochastic decision support model for investments in renewable energy that considers these factors and maximizes the expected return for a given level of risk aversion. To represent the uncertainties of the problem is used the Conditional Value-at-Risk (CVaR), that model the portfolio risk in relation to the most unfavorable future revenue scenarios. The scenarios are generated based on past generation and the output data from NEWAVE, the medium-term planning model of the operation system. The simulations show how the current portfolio and the investment option are related in terms of energy complementation. It is also possible to realize that risk for intermittent source entails to company by means of the evaluation of CVaR. In this way, current company portfolio can be a hedge for the investment, thus reducing the risk of the project. The results show that the diversification of the company’s assets and the complementary composition of the generating sources reduce the financial risks of the investor’s portfolio. The risk aversion level of the decision maker also influences the market position that the company must adopt, such that the model tends towards more conservative solutions when the risk aversion is higher. Thus, confirming the literature, the existence of a trade-off between risk aversion and expected return. | en |
