LAUSR

In deregulated electricity markets, available transfer capability (ATC) provides valuable information for market participants, because ATC indicates the remaining amount of power that can be transferred between different areas over already committed capacity. Under the paradigm of renewable power with uncertainty, it is reasonable to apply probabilistic ATC evaluation. However, the probabilistic distribution of uncertainty is not always readily available. In this paper, an interval optimization-based model is proposed for ATC evaluation that only requires the bounds of uncertainty without the precise data of wind power probabilistic distribution. The purpose of introducing interval optimization is to determine the possible ATC range considering wind power uncertainty. In the proposed method, the original interval-based model is first decomposed into a lower boundary (optimistic) model and an upper boundary (pessimistic) model. Then, strong duality theory and a big-M algorithm are applied to convert the combinatorial max-min problem in the pessimistic model to a single level maximization problem for efficient calculations. The proposed methodology is implemented on the PJM 5-bus and IEEE 118-bus systems. Simulation results validate its effectiveness.