  Nowadays, the transition from a conventional generation system to a renewable
generation system is one of the most difficult challenges for system operators
and companies. There are several reasons: the long-standing impact of
investment decisions, the proper integration of renewable sources into the
system, the present and future uncertainties, and the convenience to consider
an integrated year-by-year representation of both uncertainties and investment
decisions. However, recent breakthroughs in Dynamic Transmission Network
Expansion Planning (DTNEP) have demonstrated that the use of robust
optimization might render this problem computationally tractable for real
systems. This paper intends to consider not only the capacity expansion of
lines, but the construction and/or dismantling of renewable and conventional
generation facilities as well. The Dynamic Transmission Network and Renewable
Generation Expansion Planning (DTNRGEP) problem is formulated as an adaptive
robust optimization problem with three levels. First level minimizes the
investment costs of transmission network and generation expansion planning, the
second level maximizes system operational costs with respect to uncertain
parameters, while the third level minimizes those operational costs with
respect to operational decisions. The method is tested for two cases: i) an
illustrative example based on Garver IEEE system and ii) a case study using the
IEEE 118-bus system. Numerical results from these examples demonstrate that the
proposed model allows making optimal decisions towards reaching a sustainable
power system, while overcoming problem size limitations and computational
intractability for realistic cases.
