Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation
This paper presents the performance evaluation of a peer-to-peer microgrids coordination algorithm for sub-transmission systems. As distributed energy resources (DERs) in distribution system start to show negative impact to the bulk power system, a paradigm shift is needed for transmission planning and operation. Because distribution substations are located far from the sub-transmission system, and it is hard to use traditional centralized control for real-time control and coordination. Thus, distributed control is a natural choice because it requires less communication and central computation. In this paper, each distribution substation is treated as a microgrid, and the peer-to-peer distributed microgrids control is formulated as a real-time optimal power flow problem to reduce the negative impact in sub-transmission systems. A distributed primal-dual optimization algorithm is adopted to solve the problem. Validation of the peer-to-peer algorithm is performed through the simulation of a real-world sub-transmission system composing of many distribution systems with high renewable penetration. Simulation results show that the peer-to-peer algorithm can achieve satisfactory voltage regulation performance in sub-transmission system by coordinating and controlling DERs in distribution systems.
Citation Formats
TY - DATA
AB - This paper presents the performance evaluation of a peer-to-peer microgrids coordination algorithm for sub-transmission systems. As distributed energy resources (DERs) in distribution system start to show negative impact to the bulk power system, a paradigm shift is needed for transmission planning and operation. Because distribution substations are located far from the sub-transmission system, and it is hard to use traditional centralized control for real-time control and coordination. Thus, distributed control is a natural choice because it requires less communication and central computation. In this paper, each distribution substation is treated as a microgrid, and the peer-to-peer distributed microgrids control is formulated as a real-time optimal power flow problem to reduce the negative impact in sub-transmission systems. A distributed primal-dual optimization algorithm is adopted to solve the problem. Validation of the peer-to-peer algorithm is performed through the simulation of a real-world sub-transmission system composing of many distribution systems with high renewable penetration. Simulation results show that the peer-to-peer algorithm can achieve satisfactory voltage regulation performance in sub-transmission system by coordinating and controlling DERs in distribution systems.
AU - Gan, Houchao
A2 - Wang, Jing
A3 - Lin, Yashen
A4 - Bhela, Siddharth
A5 - Bilby, Chris
DB - C-MIX - Community Microgrid Information Exchange
DP - Open EI | National Laboratory of the Rockies
DO - 10.1109/PESGM48719.2022.9916762
KW - Power electronics and inverters
KW - Power electronics
KW - Inverters
KW - Battery energy storage
KW - Solar
KW - Photovoltaics
KW - PV
KW - Diesel generators
KW - Other liquid-fuel generators
KW - Utility integration
KW - Bulk-system Integration
KW - Case studies
KW - Performance
KW - Power plant controls
KW - SCADA
KW - Policy and regulation
KW - Policy
KW - Regulation
LA - English
DA - 2022/01/01
PY - 2022
PB - NLR
T1 - Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation
UR - https://doi.org/10.1109/PESGM48719.2022.9916762
ER -
Gan, Houchao, et al. Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation. NLR, 1 January, 2022, C-MIX - Community Microgrid Information Exchange. https://doi.org/10.1109/PESGM48719.2022.9916762.
Gan, H., Wang, J., Lin, Y., Bhela, S., & Bilby, C. (2022). Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation. [Data set]. C-MIX - Community Microgrid Information Exchange. NLR. https://doi.org/10.1109/PESGM48719.2022.9916762
Gan, Houchao, Jing Wang, Yashen Lin, Siddharth Bhela, and Chris Bilby. Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation. NLR, January, 1, 2022. Distributed by C-MIX - Community Microgrid Information Exchange. https://doi.org/10.1109/PESGM48719.2022.9916762
@misc{CMIX_Dataset_70,
title = {Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation},
author = {Gan, Houchao and Wang, Jing and Lin, Yashen and Bhela, Siddharth and Bilby, Chris},
abstractNote = {This paper presents the performance evaluation of a peer-to-peer microgrids coordination algorithm for sub-transmission systems. As distributed energy resources (DERs) in distribution system start to show negative impact to the bulk power system, a paradigm shift is needed for transmission planning and operation. Because distribution substations are located far from the sub-transmission system, and it is hard to use traditional centralized control for real-time control and coordination. Thus, distributed control is a natural choice because it requires less communication and central computation. In this paper, each distribution substation is treated as a microgrid, and the peer-to-peer distributed microgrids control is formulated as a real-time optimal power flow problem to reduce the negative impact in sub-transmission systems. A distributed primal-dual optimization algorithm is adopted to solve the problem. Validation of the peer-to-peer algorithm is performed through the simulation of a real-world sub-transmission system composing of many distribution systems with high renewable penetration. Simulation results show that the peer-to-peer algorithm can achieve satisfactory voltage regulation performance in sub-transmission system by coordinating and controlling DERs in distribution systems.},
url = {https://cmix.openei.org/submissions/70},
year = {2022},
howpublished = {C-MIX - Community Microgrid Information Exchange, NLR, https://doi.org/10.1109/PESGM48719.2022.9916762},
note = {Accessed: 2026-06-17},
doi = {10.1109/PESGM48719.2022.9916762}
}
https://dx.doi.org/10.1109/PESGM48719.2022.9916762
Details
Data from Jan 1, 2022
Last updated Mar 30, 2026
Submitted Jun 2, 2026
Organization
NLR
Contact
Jing Wang

