Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation

Jing Wang, Soham Chakraborty, Vivek Khatana, Blake Lundstrom, Govind Saraswat, Murti Salapaka

Research output: NRELPresentation


This presentation discusses 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.
Original languageAmerican English
Number of pages5
StatePublished - 2022

Publication series

NamePresented at the IEEE PES Innovative Smart Grid Technologies Conference (ISGT NA), 24-28 April 2022, New Orleans, Louisiana

NREL Publication Number

  • NREL/PR-5D00-82912


  • droop control
  • grid-following inverter
  • grid-forming inverter
  • net load management


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