INFORMATICA, 2016, Vol. 27, No. 3, 625-648
© Institute of Mathematics and Informatics,
Robust Optimization for Strategic Energy Planning
Stefano MORET1, Michel BIERLAIRE, François MARÉCHAL
Industrial Process and Energy Systems Engineering Group (IPESE) Transport and Mobility Laboratory École Polytechnique Fédérale de Lausanne 1015 Lausanne, Switzerland E-mail: firstname.lastname@example.org
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 characterization 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.
energy planning, robust optimization, uncertainty characterization, Mixed-Integer Linear Programming
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