A methodology to assess the impact of capacity remuneration mechanisms in a detailed power system model

Abstract

A methodology is proposed to implement a capacity constraint in an iterative investment algorithm, which can be applied to detailed power system models. An additional support for the investment in generation capacity is introduced, in order to fulfil given capacity requirements. The amount of the support is determined based on the generation capacity margin and the surplus of the most profitable power plant. Now, convergence of the algorithm is achieved when the income plus the support equals the long-run marginal cost for the investment assets. The estimated support represents the shadow-cost of the capacity requirement respectively the capacity price. The methodology is applied to a simplified model and a detailed Northern European power system model. In the first case the performance of the methodology is validated against an optimal solution. In the second case the performance is assessed in the case of a real-system analysis. The results report a rather well consistency between the iterative approach and the optimal solution from the simplified LP-model. Furthermore, when applying the methodology to the Northern European model, the capacity constraint can be fulfilled, while a value of the necessary support for generation capacity is estimated.