Worst-case feasibility evaluation of bilateral transactions in electricity markets

The open access transmission regime has pushed toward an increase in the number of bilateral transactions and to a more intensive use of the transmission system. When the transaction can be accommodated with no line flow limits being violated for all possible values of the net load, the transaction is referred to as worst-case feasible. The ability to identify bilateral transactions that are feasible even under the worst-case assumed scenario, is of high importance to system operators since they can make better decisions about whether to schedule a set of bilateral transactions or not. In this study we propose an approach to evaluate the impacts of the uncertainties introduced by the network structure and the net load in the accommodation of bilateral transactions. To this end, we bound the net load uncertainty with a convex polytope and deploy a Markov chain model to represent the uncertainty in the network structure resulting from component outages. We condition on each network configuration and make use of the DC power flow to evaluate the uncertainty propagated from the net load to the line flows. We also apply a node-connection detection algorithm to avoid unnecessary computation of the line flow uncertainty. The proposed approach is applied to a benchmark 3-bus test system where the impacts of load and network uncertainty on the feasibility of a bilateral transaction are analyzed separately. The proposed methodology provides physically reasonable results and is applicable to large-scale networks.