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 original | Inglés |
---|---|
Número de artículo | 7265071 |
Páginas (desde-hasta) | 2681-2693 |
Número de páginas | 13 |
Publicación | IEEE Transactions on Smart Grid |
Volumen | 6 |
N.º | 6 |
DOI | |
Estado | Publicada - nov. 2015 |
Publicado de forma externa | Sí |