Strategies for investing in renewable energy projects present high risks associated with generation and price volatility and dynamics. Existing approaches for determining optimal strategies are based on real options theory, that often simplify the uncertainty process, or on stochastic programming approaches, that simplify the dynamic aspects. In this paper, we bridge the gap between these approaches by developing a multistage stochastic programming approach that includes real options such as postponing, hedging with fixed (forward) contracts and combination with other sources. The proposed model is solved by a procedure based on the Stochastic Dual Dynamic Programming (SDDP) method. The framework is extended to the risk averse setting. A specific case study in investment in hydro and wind projects in the Brazilian market is used to illustrate that the investment strategies generated by the proposed approach are efficient. 
Risk neutral and risk averse approaches to multistage renewable investment planning under uncertainty