Stochastic Distributed Control for Arbitrarily Connected Microgrid Clusters

Maryam Khanbaghi and Aleksandar Zecevic
Additional contact information
Maryam Khanbaghi: Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA 95053, USA
Aleksandar Zecevic: Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA 95053, USA

Energies, 2022, vol. 15, issue 14, 1-17

Abstract: Due to the success of single microgrids, the coming years are likely to see a transformation of the current electric power system to a multiple microgrid network. Despite its obvious promise, however, this paradigm still faces many challenges, particularly when it comes to the control and coordination of energy exchanges between subsystems. In view of that, in this paper we propose an optimal stochastic control strategy in which microgrids are modeled as stochastic hybrid dynamic systems. The optimal control is based on the jump linear theory and is used as a means to maximize energy storage and the utilization of renewable energy sources in islanded microgrid clusters. Once the gain matrices are obtained, the concept of ε -suboptimality is applied to determine appropriate levels of power exchange between microgrids for any given interconnection pattern. It is shown that this approach can be efficiently applied to large-scale systems and guarantees their connective stability. Simulation results for a three microgrid cluster are provided as proof of concept.

Keywords: microgrid clusters; stochastic control; distributed control; jump linear theory; large-scale systems; energy management (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/14/5163/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/14/5163/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:14:p:5163-:d:864117

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().