Distributed Coordination of Networked Microgrids for Voltage Support in Bulk Power Grids

Gray, Nathan; Sadnan, Rabayet; Bose, Anjan; Dubey, Anamika; Vu, Thanh Long; Xie, Jing; Marinovici, Laurentiu D.; Schneider, Kevin P.; Klauber, Cecilia; Trinh, Wei

doi:10.1109/tia.2024.3429288

Distributed Coordination of Networked Microgrids for Voltage Support in Bulk Power Grids

Journal Article · Tue Jul 16 00:00:00 EDT 2024 · IEEE Transactions on Industry Applications

DOI:https://doi.org/10.1109/tia.2024.3429288· OSTI ID:2432430

Gray, Nathan ^[1]; Sadnan, Rabayet ^[2]; Bose, Anjan ^[1]; Dubey, Anamika ^[1]; Vu, Thanh Long ^[2]; Xie, Jing ^[2]; Marinovici, Laurentiu D. ^[2]; Schneider, Kevin P. ^[2]; Klauber, Cecilia ^[3]; Trinh, Wei ^[3]

Washington State Univ., Pullman, WA (United States)
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

The increasing deployment of distributed energy resources (DERs) and microgrids (MGs) in power distribution systems has enabled the adjustment of reactive power consumption as seen at the substation, which can be used to provide voltage support for the bulk power system (BPS). Leveraging this new capability will provide greater resiliency to the power system as a whole. Here, the goal of this paper is to develop and compare three different algorithms, namely distributed optimal power flow, distributed consensus algorithm, and fully decentralized collaborative autonomy for unbalanced distribution systems for microgrid coordination. These algorithms use networked MGs to support the BPS voltage when a contingency at the bulk grid results in abnormally low voltages, which may be a precursor to voltage collapse. Our comparative analysis includes both qualitative and quantitative assessments of the three algorithms and a discussion of the trade-offs between the decentralized and distributed methods in normal and disrupted conditions. Each algorithm was evaluated on the modified IEEE 13-bus system and a real power distribution system at Chattanooga, Tennessee, that encompasses more than 4500 buses. Each algorithms excels differently and may be suited for different scenarios depending on the condition, operations, and priorities of the power and communication systems.

View Accepted Manuscript (DOE)

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-76RL01830; AC52-07NA27344

OSTI ID:: 2432430

Report Number(s):: PNNL-SA--198482

Journal Information:: IEEE Transactions on Industry Applications, Journal Name: IEEE Transactions on Industry Applications Journal Issue: 6 Vol. 60; ISSN 0093-9994

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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