Least-Cost Reserve Offer Deliverability in Day-Ahead Generation Scheduling Under Wind Uncertainty and Generation and Network Outages

Abstract

The relevant role played by the procurement of reserves becomes essential to hedge against the growing levels of penetration of intermittent wind-based generation. Within the context of unit-commitment-based day-ahead energy and reserve electricity markets, this paper proposes a novel approach for network-constrained energy and reserve scheduling based on adjustable robust optimization (ARO). Unlike previously reported generation scheduling models using ARO, offers for up- and down-spinning reserves and on/off generation statuses are explicitly considered in the problem formulation to jointly cope with uncertain nodal net injections and system component outages in a multiperiod setting. Moreover, the feasibility of the deployment of awarded reserve offers across the network is guaranteed at minimum offer cost. In other words, in contrast to current industry practice relying on deterministic models, the optimal scheduling of energy and reserve offers ensures power balance for all possible uncertainty realizations and credible contingencies. The proposed model is formulated as an instance of mixed-integer trilevel programming. The robust counterpart is effectively solved by a modified column-and-constraint generation algorithm featuring two novel acceleration strategies that improve the overall computational performance. Numerical simulations demonstrate the effectiveness of the proposed approach and its operational advantages over the conventional model relying on pre-specified reserve requirements.