Stochastic-Predictive Energy Management System for Isolated Microgrids

Daniel E. Olivares, Jose D. Lara, Claudio A. Canizares, Mehrdad Kazerani

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

131 Citas (Scopus)

Resumen

This paper presents the mathematical formulation and control architecture of a stochastic-predictive energy management system for isolated microgrids. The proposed strategy addresses uncertainty using a two-stage decision process combined with a receding horizon approach. The first stage decision variables (unit commitment) are determined using a stochastic mixed-integer linear programming formulation, whereas the second stage variables (optimal power flow) are refined using a nonlinear programming formulation. This novel approach was tested on a modified CIGRE test system under different configurations comparing the results with respect to a deterministic approach. The results show the appropriateness of the method to account for uncertainty in the power forecast.

Idioma originalInglés
Número de artículo7265071
Páginas (desde-hasta)2681-2693
Número de páginas13
PublicaciónIEEE Transactions on Smart Grid
Volumen6
N.º6
DOI
EstadoPublicada - nov. 2015
Publicado de forma externa

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