Distributed wind-hybrid microgrids with autonomous controls and forecasting
Distributed wind-hybrid microgrids have the potential to provide key resilience and economic benefits to both the customers they serve and the utility grids they are connected to. Such microgrids will likely be a key part of the grid of the future, whether connected to large utility grids or linked together in multi-microgrid systems. Through the hybridization of distributed wind and solar photovoltaics, autonomous device-level and system-level controls, battery energy storage systems with smart inverters, and forecasting, these microgrids could maintain local stability and provide grid services all with renewable power. In the literature, these elements have been considered individually. However, they have not been combined and demonstrated at a high fidelity, which is essential to prove the concept's operation before moving to hardware-in-the-loop and physical demonstrations. In this work, we develop a high-fidelity MATLAB-Simulink model of a real distributed wind-hybrid microgrid that includes all these elements. We demonstrate the microgrid maintaining stability and production in a variety of islanded, grid-connected, and transition scenarios. This includes riding through faults and grid transitions, handling resource variability, and providing grid services. The results demonstrate, at a high fidelity, how distributed wind-hybrid microgrids can operate in an economic and resilient fashion. Finally, we provide recommendations for future research to move advanced distributed wind-hybrid microgrids toward deployment.
Citation Formats
TY - DATA
AB - Distributed wind-hybrid microgrids have the potential to provide key resilience and economic benefits to both the customers they serve and the utility grids they are connected to. Such microgrids will likely be a key part of the grid of the future, whether connected to large utility grids or linked together in multi-microgrid systems. Through the hybridization of distributed wind and solar photovoltaics, autonomous device-level and system-level controls, battery energy storage systems with smart inverters, and forecasting, these microgrids could maintain local stability and provide grid services all with renewable power. In the literature, these elements have been considered individually. However, they have not been combined and demonstrated at a high fidelity, which is essential to prove the concept's operation before moving to hardware-in-the-loop and physical demonstrations. In this work, we develop a high-fidelity MATLAB-Simulink model of a real distributed wind-hybrid microgrid that includes all these elements. We demonstrate the microgrid maintaining stability and production in a variety of islanded, grid-connected, and transition scenarios. This includes riding through faults and grid transitions, handling resource variability, and providing grid services. The results demonstrate, at a high fidelity, how distributed wind-hybrid microgrids can operate in an economic and resilient fashion. Finally, we provide recommendations for future research to move advanced distributed wind-hybrid microgrids toward deployment.
AU - Anderson, Benjamin
A2 - Rane,
A3 - Jayaraj,
A4 - Khan, Rabia
DB - C-MIX - Community Microgrid Information Exchange
DP - Open EI | National Laboratory of the Rockies
DO -
KW - Wind energy
KW - Battery energy storage
KW - Solar
KW - Photovoltaics
KW - PV
KW - Diesel generators
KW - Other liquid-fuel generators
KW - Power plant controls
KW - SCADA
KW - Utility integration
KW - Bulk-system Integration
KW - Case studies
KW - Performance
LA - English
DA - 2023/03/01
PY - 2023
PB - NLR
T1 - Distributed wind-hybrid microgrids with autonomous controls and forecasting
UR - https://cmix.openei.org/submissions/395
ER -
Anderson, Benjamin, et al. Distributed wind-hybrid microgrids with autonomous controls and forecasting. NLR, 1 March, 2023, C-MIX - Community Microgrid Information Exchange. https://cmix.openei.org/submissions/395.
Anderson, B., Rane, ., Jayaraj, ., & Khan, R. (2023). Distributed wind-hybrid microgrids with autonomous controls and forecasting. [Data set]. C-MIX - Community Microgrid Information Exchange. NLR. https://cmix.openei.org/submissions/395
Anderson, Benjamin, Rane, Jayaraj, and Rabia Khan. Distributed wind-hybrid microgrids with autonomous controls and forecasting. NLR, March, 1, 2023. Distributed by C-MIX - Community Microgrid Information Exchange. https://cmix.openei.org/submissions/395
@misc{CMIX_Dataset_395,
title = {Distributed wind-hybrid microgrids with autonomous controls and forecasting},
author = {Anderson, Benjamin and Rane, and Jayaraj, and Khan, Rabia},
abstractNote = {Distributed wind-hybrid microgrids have the potential to provide key resilience and economic benefits to both the customers they serve and the utility grids they are connected to. Such microgrids will likely be a key part of the grid of the future, whether connected to large utility grids or linked together in multi-microgrid systems. Through the hybridization of distributed wind and solar photovoltaics, autonomous device-level and system-level controls, battery energy storage systems with smart inverters, and forecasting, these microgrids could maintain local stability and provide grid services all with renewable power. In the literature, these elements have been considered individually. However, they have not been combined and demonstrated at a high fidelity, which is essential to prove the concept's operation before moving to hardware-in-the-loop and physical demonstrations. In this work, we develop a high-fidelity MATLAB-Simulink model of a real distributed wind-hybrid microgrid that includes all these elements. We demonstrate the microgrid maintaining stability and production in a variety of islanded, grid-connected, and transition scenarios. This includes riding through faults and grid transitions, handling resource variability, and providing grid services. The results demonstrate, at a high fidelity, how distributed wind-hybrid microgrids can operate in an economic and resilient fashion. Finally, we provide recommendations for future research to move advanced distributed wind-hybrid microgrids toward deployment.},
url = {https://cmix.openei.org/submissions/395},
year = {2023},
howpublished = {C-MIX - Community Microgrid Information Exchange, NLR, https://cmix.openei.org/submissions/395},
note = {Accessed: 2026-10-14}
}
Details
Data from Mar 1, 2023
Last updated Jul 6, 2026
Submitted Jun 2, 2026
Organization
NLR
Contact
Benjamin Anderson

