Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation
This paper presents the performance evaluation of a net load management (NLM) engine that balances load and generation in an isolated community to power a critical facility after a grid interruption event (e.g., the loss of a large generation unit). This NLM engine is particularly important for microgrid systems because it provides a high-speed, cost-optimal control solution to coordinate grid-forming inverters and to dispatch grid-following inverters and deferrable loads in microgrid systems to enhance grid resilience and reliability. The NLM algorithm cost-optimally dispatches the grid-following inverters and deferrable loads based on the demanded power and load priorities, and the grid-forming inverters use droop control to form system voltages and share active and reactive power. A controller-hardware-in-the-loop platform is developed to evaluate the control performance of the NLM algorithm with two sequential contingency events of lost generation units. The experimental results indicate that the NLM engine can maintain system stability, achieve the targeted system voltage and frequency, and balance load and generation to serve the critical facility with improved system resilience and reliability.
Citation Formats
TY - DATA
AB - This paper presents the performance evaluation of a net load management (NLM) engine that balances load and generation in an isolated community to power a critical facility after a grid interruption event (e.g., the loss of a large generation unit). This NLM engine is particularly important for microgrid systems because it provides a high-speed, cost-optimal control solution to coordinate grid-forming inverters and to dispatch grid-following inverters and deferrable loads in microgrid systems to enhance grid resilience and reliability. The NLM algorithm cost-optimally dispatches the grid-following inverters and deferrable loads based on the demanded power and load priorities, and the grid-forming inverters use droop control to form system voltages and share active and reactive power. A controller-hardware-in-the-loop platform is developed to evaluate the control performance of the NLM algorithm with two sequential contingency events of lost generation units. The experimental results indicate that the NLM engine can maintain system stability, achieve the targeted system voltage and frequency, and balance load and generation to serve the critical facility with improved system resilience and reliability.
AU - Wang, Jing
A2 - Chakraborty, Soham
A3 - Khatana, Vivek
A4 - Lundstrom, Blake
A5 - Saraswat, Govind
A6 - Salapaka, Murti
DB - C-MIX - Community Microgrid Information Exchange
DP - Open EI | National Laboratory of the Rockies
DO - 10.1109/ISGT50606.2022.9817515
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 - Case studies
KW - Performance
KW - Power plant controls
KW - SCADA
KW - Resilience
KW - Extreme weather
KW - Standards
KW - Interconnection
KW - Protection
LA - English
DA - 2022/01/01
PY - 2022
PB - NLR
T1 - Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation
UR - https://doi.org/10.1109/ISGT50606.2022.9817515
ER -
Wang, Jing, et al. Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation. NLR, 1 January, 2022, C-MIX - Community Microgrid Information Exchange. https://doi.org/10.1109/ISGT50606.2022.9817515.
Wang, J., Chakraborty, S., Khatana, V., Lundstrom, B., Saraswat, G., & Salapaka, M. (2022). Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation. [Data set]. C-MIX - Community Microgrid Information Exchange. NLR. https://doi.org/10.1109/ISGT50606.2022.9817515
Wang, Jing, Soham Chakraborty, Vivek Khatana, Blake Lundstrom, Govind Saraswat, and Murti Salapaka. Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation. NLR, January, 1, 2022. Distributed by C-MIX - Community Microgrid Information Exchange. https://doi.org/10.1109/ISGT50606.2022.9817515
@misc{CMIX_Dataset_94,
title = {Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation},
author = {Wang, Jing and Chakraborty, Soham and Khatana, Vivek and Lundstrom, Blake and Saraswat, Govind and Salapaka, Murti},
abstractNote = {This paper presents the performance evaluation of a net load management (NLM) engine that balances load and generation in an isolated community to power a critical facility after a grid interruption event (e.g., the loss of a large generation unit). This NLM engine is particularly important for microgrid systems because it provides a high-speed, cost-optimal control solution to coordinate grid-forming inverters and to dispatch grid-following inverters and deferrable loads in microgrid systems to enhance grid resilience and reliability. The NLM algorithm cost-optimally dispatches the grid-following inverters and deferrable loads based on the demanded power and load priorities, and the grid-forming inverters use droop control to form system voltages and share active and reactive power. A controller-hardware-in-the-loop platform is developed to evaluate the control performance of the NLM algorithm with two sequential contingency events of lost generation units. The experimental results indicate that the NLM engine can maintain system stability, achieve the targeted system voltage and frequency, and balance load and generation to serve the critical facility with improved system resilience and reliability.},
url = {https://cmix.openei.org/submissions/94},
year = {2022},
howpublished = {C-MIX - Community Microgrid Information Exchange, NLR, https://doi.org/10.1109/ISGT50606.2022.9817515},
note = {Accessed: 2026-08-06},
doi = {10.1109/ISGT50606.2022.9817515}
}
https://dx.doi.org/10.1109/ISGT50606.2022.9817515
Details
Data from Jan 1, 2022
Last updated Mar 30, 2026
Submitted Jun 2, 2026
Organization
NLR
Contact
Jing Wang

