[en] ENERGY AND RESERVE SCHEDULING UNDER CORRELATED NODAL DEMAND UNCERTAINTY: AN ADJUSTABLE ROBUST OPTIMIZATION APPROACH

[pt] ALEXANDRE STREET DE AGUIAR

[pt] ALEXANDRE MOREIRA DA SILVA

[pt] JOSE MANUEL ARROYO

[en] LINEARIZATION

[en] DECOMPOSITION

[en] OPTIMIZATION

[en] 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 model the worst-case load variation under a given user-defined uncertainty set. This paper generalizes 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 optimization problem and solved by means of Benders decomposition. Preliminary empirical results suggest that the incorporation of nodal correlations can be captured by the robust scheduling model.

2013-02-01

[pt] TEXTO

application/pdf

INGLÊS

https://www.maxwell.vrac.puc-rio.br/colecao.php?strSecao=resultado&nrSeq=21087@2