The significant integration of renewable energy sources to electricity grids poses
unprecedented challenges to power systems planning. Each of these challenges is
implied by a particular circumstance faced by the system planner when devising the
expansion plan, which should be tailored to address the needs and objectives of the
system under consideration. Within this context, this thesis is dedicated to propose
methodologies to address three timely situations that may arise when planning the
expansion of the grid.
In the first situation, we consider the case in which the system planner must meet
established renewable penetration targets while complying with multiple deterministic
security criteria. Renewable targets have been largely adopted as an important
mechanism to foster the decarbonization of power systems. Hence, we propose a
methodology that simultaneously identifies the optimal subset of candidate assets
as well as renewable sites to be developed, while introducing the concept of compound
GT n-K security criteria.
In the second situation, we aim to minimize the regret of the system planner under
generation expansion uncertainty. In many cases, e.g. the United Kingdom, the
decision on the transmission expansion plan is taken by a market player that does
not determine the future generation expansion. Within this context, we propose a
5-level MILP formulation to represent the minimization of the regret of the system
planner in light of a set of credible scenarios of generation expansion while enforcing
n-1 security criterion.
Finally, in the third situation, the objective is to inform the optimal transmission
expansion plan under ambiguity in the probability distribution of RES generation
output. To do so, we present a methodology capable of determining the transmission
plan under deterministic security criterion while accommodating a set of different
probability distributions for RES output in order to integrate ambiguity aversion.