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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A stochastic programming model for the optimal operation of unbalanced three-phase islanded microgrids

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Author(s):
Vergara, Pedro P. [1, 2] ; Lopez, Juan Camilo [1] ; Rider, Marcos J. [1] ; Shaker, Hamid R. [2] ; da Silva, Luiz C. P. [1] ; Jorgensen, Bo N. [2]
Total Authors: 6
Affiliation:
[1] Univ Estadual Campinas, Sch Elect & Comp Engn, Dept Syst & Energy, UNICAMP, BR-13083852 Campinas, SP - Brazil
[2] Univ Southern Denmark, Ctr Energy Informat, Maersk Mc Kinney Moller Inst, SDU, DK-5230 Odense - Denmark
Total Affiliations: 2
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS; v. 115, FEB 2020.
Web of Science Citations: 0
Abstract

This paper presents a stochastic mixed-integer nonlinear programming (MINLP) model for the optimal operation of islanded microgrids in the presence of stochastic demands and renewable resources. In the proposed formulation, the microgrid is modeled as an unbalanced three-phase electrical distribution system comprising distributed generation (DG) units with droop control, battery systems (BSs) and wind turbines (WTs). The stochastic nature of the consumption and the renewable generation is considered through a scenario-based approach, which determines the optimal values of the decision variables that minimize the average operational cost of the microgrid. A set of efficient linearizations are used to transform the proposed MINLP model into an approximated convex model that can be solved via commercial solvers. In order to assess the effectiveness of the obtained solution, Monte Carlo simulations (MCS) are carried out. Results show that the proposed model considers the uncertainty while reducing the average operational costs and load curtailments, when compared with a deterministic model. (AU)

FAPESP's process: 15/09136-8 - Fault tolerant portfolio optimization in Smart Grid
Grantee:Pedro Pablo Vergara Barrios
Support Opportunities: Scholarships in Brazil - Doctorate