Optimizing individual renewable energies roadmaps: Criteria, methods, and end targets

•Minimization of the levelized cost of energy for roadmap design is put forward.•Analytical and simulation optimization for single energies with learning rates.•Cost minimization leads to delayed renewable energy deployments.•The social discount rate should be used to avoid overstating the roadmap cost.•Fast and high levels of renewable energies investment do not increase energy costs. The optimization of investment deployment roadmaps for single energy cases under significant learning rate effects is considered. An analytical solution for the minimization of the present value of total discounted cost is first considered. Then it is argued that a more appropriate criterion for roadmap design from the economic point of view would be the minimization of the levelized cost of energy and the analytical solution is also given. Solution methods for the optimization problem based on several kinds of simulations are presented and shown to work adequately. The first empirical result is that the cost minimization criterion leads to delayed investments; minimizing the levelized cost of energy on the contrary, is broadly compatible with accelerated investment deployments. It is also shown that increasing the end target values for capital investment and shortening the end roadmap horizon date, do not imply an increase in the levelized cost of energy, thereby lending support to the urgency required by the latest Intergovernmental Panel on Climate Change report to accelerate the carbon emissions reductions.