Coordinated hybrid approach based on firefly algorithm and particle swarm optimization for distributed secondary control and stability analysis of direct current microgrids

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dc.contributor.authorLasabi, Olanrewaju
dc.contributor.authorSwanson, Andrew
dc.contributor.authorJarvis, Leigh
dc.contributor.authorAluko, Anuoluwapo
dc.contributor.authorGoudarzi, Arman
dc.date.accessioned2024-10-10T17:23:12Z
dc.date.available2024-10-10T17:23:12Z
dc.date.issued2024
dc.description.abstractStandalone DC microgrids can potentially influence intelligent energy systems in the future. They accomplish this by employing droop control to smoothly integrate various renewable energy sources (RESs) to satisfy energy demands. This method ensures equitable allocation of load current among RESs, promoting efficiency and smooth operation. Utilizing droop control typically leads to a reduction in the voltage of the DC bus. Hence, to uniformly distribute current among several RESs while simultaneously regulating the DC bus voltage, this research proposes a distributed secondary control technique. The proposed technique ensures fair distribution of current and eliminates bus voltage variations by integrating both current and voltage errors within the designed control loop. An innovative hybrid firefly and particle swarm optimization algorithm (FFA–PSO) is introduced to aid in parameter selection for the distributed control approach, facilitating the attainment of the intended control objectives. A DC microgrid state-space model was developed, which incorporates eigenvalue observation analysis to evaluate the impacts of the optimized secondary distributed control on the stability of the microgrid. A real-time testing setup is built using MATLAB/Simulink® R2022b software. and implemented on a Speedgoat™ real-time machine to verify the practical performance of the proposed approach in real-world applications. The results showcase the robustness of the proposed control technique in achieving voltage stabilization and even current allocation within the DC microgrid. This is evidenced by minimal oscillations and undershoots/overshoots and swift response times.
dc.description.reviewstatusReviewed
dc.description.scholarlevelFaculty
dc.identifier.citationLasabi, O., Swanson, A., Jarvis, L., Aluko, A., & Goudarzi, A. (2024). Coordinated hybrid approach based on firefly algorithm and particle swarm optimization for distributed secondary control and stability analysis of direct current microgrids. Sustainability, 16(3), Article 3. https://doi.org/10.3390/su16031204
dc.identifier.urihttps://doi.org/10.3390/su16031204
dc.identifier.urihttps://hdl.handle.net/1828/20563
dc.language.isoen
dc.publisherSustainability
dc.rightsAttribution CC BY
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectcurrent sharing
dc.subjectDC microgrid
dc.subjectdistributed secondary control
dc.subjectFFA
dc.subjectoptimization
dc.subjectPSO
dc.subjectstability analysis
dc.subjectvoltage restoration
dc.titleCoordinated hybrid approach based on firefly algorithm and particle swarm optimization for distributed secondary control and stability analysis of direct current microgrids
dc.typeArticle

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