Long-term planning for energy systems is often based on deterministic economic optimization
and forecasts of fuel prices.When fuel price evolution is underestimated, the consequence
is a low penetration of renewables and more efficient technologies in favour of fossil alternatives.
This work aims at overcoming this issue by assessing the impact of uncertainty on energy planning
decisions.
A classification of uncertainty in energy systems decision-making is performed. Robust optimization
is then applied to a Mixed-Integer Linear Programming problem, representing the typical
trade-offs in energy planning. It is shown that in the uncertain domain investing in more efficient
and cleaner technologies can be economically optimal.
@Article{MoreBierMare15,
author = {Stefano Moret and Michel Bierlaire and Fran\c{c}ois Mar\'echal},
title = {Robust optimization for strategic energy planning},
journal = {Informatica},
year = {2016},
volume = {27},
number = {3},
pages = {625-648},
DOI = {10.15388/Informatica.2016.103},
note = {Accepted on Nov 25, 2015}}}