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

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.
- State University of Campinas Brazil
- University of Southern Denmark Denmark
- Technical University Eindhoven Netherlands
- Technical University Eindhoven Netherlands
- Technical University Eindhoven TU Eindhoven Research Portal Netherlands
Droop control, Islanded mode, Stochastic optimization, Energy Engineering and Power Technology, SDG 7 - Affordable and Clean Energy, Microgrids, Electrical and Electronic Engineering, SDG 7 – Betaalbare en schone energie, Optimal power flow
Droop control, Islanded mode, Stochastic optimization, Energy Engineering and Power Technology, SDG 7 - Affordable and Clean Energy, Microgrids, Electrical and Electronic Engineering, SDG 7 – Betaalbare en schone energie, Optimal power flow
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).33 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
