Abstract
Many Generation Expansion Problems (GEP) models have been proposed in the literature based on agent-based equilibria or cost-minimization, integrated in bilevel or single-level models. In the simplest (and unrealistic)single-level cost minimization GEP with only the balance constraint, it can be proved that optimal generation investments are recovered through the system marginal cost, meaning that the Net Present Value (NPV) is 0. However, in more complex representations with additional constraints(such as technical or minimum capacity system constraints) non-profitable investments might occur, i.e., their NPV can go below 0.The aim of this work is to provide insights on how introducing complexity into GEP models affects the investments with and without imposing positive NPV as new constraints. The non-linearities in the NPV formulation are solved with a novel iterative algorithm. The main conclusion from the case studies is that the cost minimization GEP model forcing positive NPV can help to better represent the behavior of energy market players and simulate oligopolistic energy markets without explicitly representing profit maximization.
