Microgrid Controls

NREL develops and evaluates microgrid controls at multiple time scales. Our researchers evaluate in-house-developed controls and partner-developed microgrid components using software modeling and hardware-in-the-loop evaluation platforms.

NREL researchers work on controller- and power hardware-in-the-loop test setups to evaluate the performance of microgrid controllers.

A microgrid is a group of interconnected loads and distributed energy resources that acts as a single controllable entity with respect to the grid. It can connect and disconnect from the grid to operate in grid-connected or island mode.

Microgrids can include distributed energy resources such as generators, storage devices, and controllable loads. Microgrids generally must also include a control strategy to maintain, on an instantaneous basis, real and reactive power balance when the system is islanded and, over a longer time, to determine how to dispatch the resources. The control system must also identify when and how to connect/disconnect from the grid. 


  • Modeling and simulation of microgrid systems on timescales of electromagnetic transients and dynamic and steady-state behavior
  • Controller hardware-in-the-loop testing, where the physical controller interacts with a model of the microgrid and associated power devices
  • Expertise in distributed optimization and control of sustainable power systems that can be applied to microgrid distributed energy resources dispatch
  • Power hardware-in-the-loop testing of microgrid components with full range of emergency scenarios


With funding from the U.S. Department of Defense Environmental Security Technology Certification Program, NREL and industry partners are collaborating on a three-phase project to develop improved microgrids using large-scale energy storage solutions—advanced battery systems—for U.S. military bases. In Phase 1, multiple companies designed and modelled microgrids with large-scale energy storage to supplement or replace aging uninterruptable power supply systems. In Phase 2, NREL is hosting validations of the Phase 1 results with hardware-in-the-loop testing of microgrid controllers, controllable switchgear, advanced battery systems, and other distributed energy resource equipment at its Energy Systems Integration Facility and Flatirons Campus. Phase 3 will see further demonstration of one or two advanced battery and microgrid technologies at a larger scale at actual military bases.

NREL is collaborating with Los Alamos National Laboratory and Sandia National Laboratories and partners San Diego Gas & Electric and the National Rural Electric Cooperative Association to create a capability called resilient operation of networked microgrids, which can help utilities rapidly recover from extreme events using coordinated operation of microgrids. Lead by Los Alamos, the resilient operation of networked microgrids allows users to formally define their resilience goals and predicted threats, generate candidate microgrid designs integrated with the existing distribution infrastructure, and test, in simulation, recovery scenarios supported by networked coordination of the proposed microgrids. Using the digital real-time simulator capabilities within its Energy Systems Integration Facility, NREL is developing a hardware-in-the-loop test bed to simulate events and their impact on system stability and microgrid operation. The test bed will validate that the solutions from the resilient operation of networked microgrids tool result in feasible recovery schemes with data sets provided by investor-owned utility and electric cooperative utility partners. The finished capability will include a set of data import and editing tools to make the project results deployable to North American distribution utilities.

NREL partnered with the Electric Power Research Institute to validate the performance of a Spirae-developed advanced microgrid controller capable of managing 1–10 MW of aggregated generation capacity. The aim of the project was to develop a commercially viable and flexible microgrid controller that can easily adapt to end-user applications and electric grid characteristics.

The Electric Power Research Institute led a team that included Spirae, NREL, a microgrid system analytics consultant, 14 utilities, and three target communities. NREL's role was to validate and test the functions of the controller by connecting it to a virtual model of a microgrid embodied within a digital real-time simulator. In the digital real-time simulator, a modified version of the Buffalo Niagra Medical Campus was modeled. The controller was also connected to a utility-scale battery inverter, which interacts with the virtual model through an AC power amplifier and adjusts its output to the simulated electrical grid demand.

NREL is partnering with San Diego Gas & Electric to evaluate the performance of grid-forming inverters in a microgrid setting. The project team is developing an evaluation platform that will use power hardware-in-the-loop and controller hardware-in-the-loop techniques to evaluate the performance of the grid-forming inverter and an advanced microgrid controller for the Borrego Springs community microgrid that is projected to run on 100% renewable energy at times. This evaluation platform is an extension of the work done under the earlier San Diego Gas & Electric Borrego Springs microgrid project.

NREL is partnering with other national laboratories to develop a flexible, reproducible framework for evaluating the economic, resilience, and security impacts of a microgrid solution. The project team is applying and linking together their respective design, optimization, power flow, and simulation tools to evaluate potential co-benefits associated with a microgrid whose primary goal is to ensure resilience of loads that are associated with critical mission functions. The first instance of this joint capability is being demonstrated in partnership with Kirtland Air Force Base, which is interested in the potential affordability, sustainability, and resilience benefits of a microgrid that is strategically located and designed to maximize mission performance. However, the ultimate framework will be designed to be flexible so it can be applied to candidate sites throughout the United States.

OMNETRIC and partners developed a distributed intelligence platform that can support utility grid and microgrid operations. Power management during microgrid operation was enabled by the Siemens Microgrid Management System. NREL tested the microgrid management system on a microgrid test platform at its Energy Systems Integration Facility. The platform included a microgrid switch, PV inverter, wind power inverter, diesel generator, controllable loads, metering, and a grid simulator to emulate the point of common coupling.

NREL researchers have developed and tested advanced inverter control algorithms that “self-synchronize” when a utility voltage is not present. Under loss of utility power, a microgrid must regulate voltage and frequency within the grid, and therefore these controls would be well suited to microgrids. This research uses virtual oscillator control theory to implement voltage and frequency regulation. Virtual oscillator control refers to a grid-forming inverter control that allows the inverters to regulate their terminal voltage and frequency without external sources.

NREL was a member of the IEEE 2030.8 Working Group, which developed a standard for microgrid controller testing.

NREL piloted a dual-stage competitive procurement process in which Energy Systems Integration Facility engineers ran microgrid controllers from multiple vendors through challenging power system and cybersecurity performance evaluations. Following the rigorous 21-week program, NREL purchased a microgrid controller from Schweitzer Engineering Laboratories, resulting in a more comprehensive microgrid research platform. Controllers were evaluated against eight key performance parameters to measure a range of functions from power quality and reliability to the use of renewable versus fossil fuel generation.

NREL partnered with research engineers from Cummins Power Systems to evaluate the performance of an advanced energy storage microgrid controller. Using a complex microgrid built in the Energy Systems Integration Facility that consisted of a grid-parallel natural gas generator, a grid-forming bidirectional battery energy storage system, and multiple solar PV inverters, NREL worked with Cummins to complete its controller programming and validate the successful performance of the control algorithms.

The state of the art on microgrid operation typically considers a flat and static partition of the power system into microgrids that are coordinated via either centralized or distributed control algorithms. This approach works well on small- to medium-size systems under normal or static operating conditions. However, it becomes infeasible when the number of controllable distributed energy resources approaches millions. Moreover, the static partition into microgrids is inadequate from the resilience perspective. Indeed, a partition that is best for normal operation might be disastrous during major disruptions. And vice-versa: A partition that is best during disruptions might be suboptimal during normal operation. Moreover, even during normal operation, the optimal partition may change over time (e.g., because large numbers of electric vehicles dynamically change the loading conditions in the network). This calls for dynamic microgrid formation with a multiresolution control structure, laying the foundation for the vision of a fractal grid. 

In this framework, microgrids self-optimize when isolated from the main grid and participate in optimal operation when interconnected to the main grid using distributed control methods. We adaptively define the boundaries of microgrids in real time based on operating conditions. In particular, when a disruption is identified:

  1. A new partition within each layer of hierarchy is established via distributed communications and control algorithms while adhering to the priority of critical loads and availability of communication systems
  2. Distributed control algorithms are applied to prevent the system from collapse.

Once collapse is prevented and the disruption is cleared, the system will gradually return to normal operation by reconfiguring the microgrid partition to an optimal configuration and reconnecting the microgrids that disconnected during the disruption. 

This project will develop a new adaptive control framework to coordinate transmission and distribution assets for improved transmission-distribution system resilience. This project significantly extends transmission-distribution control approaches by providing these capabilities:

  • Joint transmission-distribution coordinated control
  • Adaptive, data-driven control robust to model inaccuracies
  • Full leverage of asynchronous data from different sensor streams (both transmission and distribution)
  • Distributed and decentralized control
  • Joint primary/secondary/tertiary control.


Open-Source Framework for Data Storage and Visualization of Real-Time Experiments, IEEE Kansas Power and Energy Conference (2020)

Remote Hardware-in-the-Loop Approach for Microgrid Controller Evaluation, NREL Technical Report (2020)

Research Roadmap on Grid-Forming Inverters, NREL Technical Report (2020)

Site-Specific Evaluation of Microgrid Controller Using Controller and Power-Hardware-in-the-Loop, 45th Annual Conference of the IEEE Industrial Electronics Society (2019)

Grid Interactive Microgrid Controller for Resilient Communities (Final Report), U.S. Department of Energy Office of Scientific and Technical Information Technical Report (2018)

Hardware-in-the-Loop Test Bed and Test Methodology for Microgrid Controller Evaluation, Transmission and Distribution Conference and Exposition (2018)

View all NREL publications about microgrid controllers.


Rishabh Jain

Lead Engineer, Distributed Energy Resource Integration