Distributed predictive secondary control with soft constraints for optimal dispatch in hybrid AC/DC microgrids

Navas-Fonseca, Alex; Burgos-Mellado, Claudio; Gómez, Juan S.; Espina, Enrique; Llanos, Jacqueline; Śaez, Doris; Sumner, Mark; Olivares, Daniel E.

Abstract

Hybrid AC/DC microgrids (H-MGs) are a prominent solution for integrating distributed generation and modern AC and DC loads. However, controlling these systems is challenging as multiple electrical variables need to be controlled and coordinated. To provide flexibility to the control system, these variables can be regulated to specific values or within secure bands. This paper proposes a set of distributed model predictive control schemes for the secondary control level to control certain variables to specific values and other variables within secure pre-defined bands into H-MGs. Specifically, optimal dispatch of active and reactive power is achieved while frequency and voltages are regulated within secure bands in H-MGs. Dynamic models of AC generators, DC generators and interlinking converters along with their novel multi-objective cost functions are developed in constrained distributed predictive optimisation problems to simultaneously achieve the aforementioned objectives via information sharing. Extensive simulation work validates the performance of this proposal.

Citation

Navas-Fonseca, A., Burgos-Mellado, C., Gómez, J. S., Espina, E., Llanos, J., Śaez, D., …Olivares, D. E. (2023). Distributed predictive secondary control with soft constraints for optimal dispatch in hybrid AC/DC microgrids. IEEE Transactions on Smart Grid, 14(6), 4204-4218. https://doi.org/10.1109/tsg.2023.3261569

• Journal Article Type: Article
• Acceptance Date: Mar 15, 2023
• Online Publication Date: Mar 24, 2023
• Publication Date: 2023-11
• Deposit Date: May 2, 2024
• Publicly Available Date: May 2, 2024
• Journal: IEEE Transactions on Smart Grid
• Print ISSN: 1949-3053
• Electronic ISSN: 1949-3061
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 6
• Pages: 4204-4218
• DOI: https://doi.org/10.1109/tsg.2023.3261569
• Keywords: General Computer Science
• Public URL: https://nottingham-repository.worktribe.com/output/19010022
• Publisher URL: https://ieeexplore.ieee.org/document/10081021