Real-Time Testing Optimal Power Flow in Smart-Transformer-Based Meshed Hybrid Microgrids: Design and Validation

Author:

Núñez-Rodríguez Rafael A.12ORCID,Unsihuay-Vila Clodomiro3ORCID,Posada Johnny4ORCID,Pinzón-Ardila Omar5,Aoki Alexandre Rasi3,Bueno-Otto Rodrigo6

Affiliation:

1. School of Engineering, Universidad Autónoma de Bucaramanga, Bucaramanga 680003, Colombia

2. School Electronic Engineering, Unidades Tecnológicas de Santander, Bucaramanga 680005, Colombia

3. Department of Electrical Engineering, Universidade Federal do Paraná, Curitiba 81531-980, Brazil

4. Department of Electronics Engineering, Universidad Autónoma de Occidente, Cali 760030, Colombia

5. School of Electronic Engineering, Universidad Pontificia Bolivariana, Floridablanca 681007, Colombia

6. R Bueno Otto Soluciones, Curitiba 81531-990, Brazil

Abstract

The smart transformer (ST) is a multiport and multi-stage converter that allows for the formation of meshed hybrid microgrids (MHMs) by enabling AC-DC ports in medium and low voltage. This type of microgrid has advantages over the performance of conventional hybrid AC-DC microgrids (HMGs); however, the number of degrees of freedom of the ST increases the complexity of the energy management systems (EMSs), which require adequate and accurate modeling of the power flow of the converters and the MG to find the feasible solution of optimal power flow (OPF) problems in the MHM. An ST’s equivalent power flow model is proposed for formulating the MHM OPF problem and developing low-frequency equivalent models integrated with a decoupled hierarchical control architecture under a real-time simulation approach to the ST-based MHM. A simulation model of the MHM in the Simulink® environment of Matlab® 9.12 is developed and implemented under a digital real-time simulation (DRTS) approach on the OPAL-RT® platform. This model allows for determining the accuracy of the developed equivalent models, both low-frequency and power flow, and determining the MHM performance based on optimal day-ahead scheduling. Simulation test results demonstrated the ST equivalent model’s accuracy and the MHM’s accuracy for OPF problems with an optimal day-ahead scheduling horizon based on the model-in-the-loop (MIL) and DRTS approach.

Funder

Science, Technology, and Innovation Fund of the General System of Royalties

Publisher

MDPI AG

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