Olivares, Daniel E.Lara, Jose D.Canizares, Claudio A.Kazerani, Mehrdad2025-08-062025-08-062015-09-141949-30531949-3061https://doi.org/10.1109/TSG.2015.2469631https://hdl.handle.net/10012/22107(© 2015 IEEE) Olivares, D. E., Lara, J. D., Canizares, C. A., & Kazerani, M. (2015). Stochastic-predictive energy management system for isolated microgrids. IEEE Transactions on Smart Grid, 6(6), 2681–2693. https://doi.org/10.1109/tsg.2015.2469631This 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.enOPFmicrogridstochastic programmingenergy management systemmodel predictive controloptimal dispatchArticle10.1109/tsg.2015.2469631