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

Pedro P. Vergara, Juan Camilo López, Marcos J. Rider, Hamid R. Shaker, Luiz C.P. da Silva, Bo N. Jørgensen

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)

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.

Original languageEnglish
Article number105446
JournalInternational Journal of Electrical Power and Energy Systems
Volume115
DOIs
Publication statusPublished - 2020
Externally publishedYes

Keywords

  • Droop control
  • Islanded mode
  • Microgrids
  • Optimal power flow
  • Stochastic optimization

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