Browsing by Author "Gomez, Juan S."

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Distributed Model-Based Predictive Secondary Control for Hybrid AC/DC Microgrids
    (2023) Rute-Luengo, Erwin; Navas-Fonseca, Alex; Gomez, Juan S.; Espina, Enrique; Burgos-Mellado, Claudio; Saez, Doris; Sumner, Mark; Munoz-Carpintero, Diego
    This article presents a novel scheme based on distributed model-based predictive control for the secondary level control of hybrid ac/dc microgrids (MGs). Prediction models based on droop control and power-transfer equations are proposed to characterize the generators in both the ac and dc sub-MGs, whereas power balance constraints are used to predict the behavior of interlinking converters. The operational constraints (such as powers and control action limits) are included in all the formulations. Experimental results validate the proposed scheme for the following cases: 1) load changes, working within operating constraints; 2) managing frequency regulation in the ac sub-MG, voltage regulation in the dc sub-MG, and global power consensus in the whole hybrid MG; and 3) maintaining the MG performance in the presence of communication malfunction while ensuring that plug-and-play capability is preserved.
  • No Thumbnail Available
    Item
    Distributed Predictive Secondary Control for Imbalance Sharing in AC Microgrids
    (2022) Navas-Fonseca, Alex; Burgos-Mellado, Claudio; Gomez, Juan S.; Donoso, Felipe; Tarisciotti, Luca; Saez, Doris; Cardenas, Roberto; Sumner, Mark
    This paper proposes a distributed predictive secondary control strategy to share imbalance in three-phase, three-wire isolated AC Microgrids. The control is based on a novel approach where the imbalance sharing among distributed generators is controlled through the control of single-phase reactive power. The main characteristic of the proposed methodology is the inclusion of an objective function and dynamic models as constraints in the formulation. The controller relies on local measurements and information from neighboring distributed generators, and it performs the desired control action based on a constrained cost function minimization. The proposed distributed model predictive control scheme has several advantages over solutions based on virtual impedance loops or based on the inclusion of extra power converters for managing single-phase reactive power among distributed generators. In fact, with the proposed technique the sharing of imbalance is performed directly in terms of single-phase reactive power and without the need for adding extra power converters into the microgrid. Contrary to almost all reported works in this area, the proposed approach enables the control of various microgrid parameters within predefined bands, providing a more flexible control system. Extensive simulation and Hardware in the Loop studies verify the performance of the proposed control scheme. Moreover, the controller's scalability and a comparison study, in terms of performance, with the virtual impedance approach were carried out.