The work presented in this paper focuses on the introduction of multiobjective programming methods into a large-scale energy systems planning model. We first review several multiobjective techniques, ranging from simple methods aiming at exploring the set of efficient solutions, to complex interactive algorithms providing best compromise solutions. We also review and apply an algorithm which implements a decentralized hierarchical decision process with multiple objectives. All methods are applied to versions of an existing large-scale linear programming model of the energy system. We evaluate these methods on a practical basis, concerning mainly the computational effort needed to implement the algorithms and the quality of the interaction with a decision-maker.
