Renewable energy sources are here to stay for a number of important reasons, including global warming and the depletion of fossil fuels. We explore in this paper how a thermal-dominated electric energy system can be transformed into a renewable-dominated one. This study relies on a stochastic programming model that allows representing the uncertain parameters plaguing such long-term planning exercise. Being the final year of our analysis 2050, we represent the transition from today to 2050 by allowing investment in both production and transmission facilities, with the target of achieving a renewable-dominated minimum-cost system. The methodology developed is illustrated using a realistic large-scale case study. Finally, policy conclusions are drawn.

Investment planning in generation facilities is necessarily a multi-stage exercise, especially in the near future, since most of the power to be built is expected to be from renewable units and their investment costs are still subject to high uncertainty. For this reason, in this paper we propose a multi-stage generation investment model where the demand growth and the investment costs of generating units are uncertain. To tackle this problem, we use a linear decision rule (LDR) approach, which allows us to consider several decision stages while achieving appropriate computing times. Using the proposed LDR methodology, we analyze the outcomes of a number of planning strategies, including achieving a 90% renewable generation mix, a non-carbon mix, and a non-nuclear mix. Additionally, we compare the results with those obtained using a two-stage stochastic programming model within a rolling window framework.