Energy and reserve scheduling under correlated nodal demand uncertainty: An adjustable robust optimization approach. (November 2015)

• Record Type: Journal Article
• Authors: Moreira, Alexandre; Street, Alexandre; Arroyo, José M.
• Is Part Of: International journal of electrical power & energy systems. Volume 72(2015:Nov.)
• Page Start: 91
• Page End: 98
• Publication Date: 2015-11
• Subjects: Adjustable robust optimization -- Benders decomposition -- Binary expansion -- Correlated nodal demand uncertainty -- Generation scheduling; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2015.02.015
• Languages: English
• ISSNs: 0142-0615

Abstract

Abstract: This paper presents a nonparametric approach based on adjustable robust optimization to consider correlated nodal demand uncertainty in a joint energy and reserve scheduling model with security constraints. In this model, up- and down-spinning reserves provided by generators are endogenously defined as a result of the optimization problem. Adjustable robust optimization is used to characterize the worst-case load variation under a given user-defined uncertainty set. This paper differs from recent previous work in two respects: (i) nonparametric correlations between nodal demands are accounted for in the uncertainty set and (ii) based on the binary expansion linearization approach, a mixed-integer linear model is provided for the optimization related to the worst-case demand. The resulting problem is formulated as a trilevel program and solved by means of Benders decomposition. Empirical results suggest that the effect of nodal correlations can be effectively captured by the robust scheduling model.