Dynamic Robust Transmission Network Expansion Planning in Renewable Dominated Power Systems Considering Inter-Temporal and Non-Convex Operational Constraints

This paper addresses the two-stage transmission network expansion planning problem considering a dynamic robust approach, in which investment decisions can be made in different years of the planning horizon. In contrast to previous multi-year approaches, we focus on modeling the non-convex and inter-temporal operation of technologies such as storage facilities, whose performance promotes the incorporation of renewable generating units into power systems. An adaptive robust optimization approach is considered to model the uncertainty in, for instance, the maximum power consumption of loads. Furthermore, representative days are used to model the operational variability of electrical demand and the production of climate-based renewable generating units. We propose combining acceleration techniques with the nested column-and-constraint generation algorithm to tackle the resulting problem. Numerical results show that the use of the proposed model leads to reductions in the total worst-case cost of up to 5% in comparison with a static approach.