A Multiobjective Strategy for Generation Expansion Planning to Enable Increased Penetration of Variable Renewable Energy Sources

This work explores the generation expansion planning (GEP) problem from a multiobjective perspective, estimating the maximum capacity of non-controllable variable renewable energy (VRE) sources to be installed, when investments in flexible technologies are carried out. The problem is formulated as a multiobjective optimization model that seeks to maximize the capacity of VRE-based generation while simultaneously minimizing the investment costs in flexible technologies, system operation costs, and emission taxes. This model takes into account the uncertainty and variability in renewable power production and demand via a multi-period stochastic formulation. The problem solution provides a set of investment plans that allow the system planner to select the option that best satisfies economic, environmental and operational targets and, in addition, provides the necessary reserve capacity to accommodate the expected new VRE sources, addressing the intermittency and variability of renewable power production. Numerical results show that the proposed strategy reveals an interdependence between the VRE installed capacity and investment in flexible technologies to provide balancing services. Furthermore, the results indicate that the installed renewable capacity can increase by up to 44.12%, which correlates with an approximately 60% rise in investment costs for flexible technologies compared to the case where these investments are minimized.