@article{35597, author = {Alexandre Moreira and Alexandre Street and José M Arroyo}, title = {Energy and reserve scheduling under correlated nodal demand uncertainty: An adjustable robust optimization approach}, 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.

}, year = {2015}, journal = {International Journal of Electrical Power & Energy Systems}, volume = {72}, pages = {91 - 98}, month = {03/2015}, issn = {01420615}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0142061515000988}, doi = {10.1016/j.ijepes.2015.02.015}, language = {eng}, }