New Sun Road delivers AI-powered performance optimization with EPRI and Incubatenergy Labs
New Sun Road collaborated with EPRI and Incubatenergy Labs to demonstrate how microgrids can provide services to the grid to mitigate capacity constraints on the local distribution system. Electrification of vehicles and buildings is increasing demands on utilities and our power grid. New Sun Road’s Stellar AI™ was deployed in EPRI’s simulation testbed to optimize DER performance while responding to a utility DERMS signal. After 16 weeks of collaboration, the results were presented at Demo Day 2023 hosted by Fortis BC in Vancouver, Canada.
New Sun Road’s Demo Day video (view on Youtube)
The demo was constructed to model a grid-connected, utility-owned, 250 kW / 760 kWh islandable microgrid for resilience and disaster relief on a capacity-constrained distribution system. High EV load on the system coincides with reduced solar generation at dusk. In a baseline scenario, this causes the distribution feeder to be overloaded, which would result in a service interruption. The demo shows how the microgrid’s energy storage can be recruited to meet this load and avoid a service interruption.
The utility/distribution system operator uses a DER management system (DERMS) to monitor the distribution feeder and issue “grid services requests” to the microgrid. The grid services requests signal the microgrid to supply power or reduce consumption to prevent overloading the feeder.
New Sun Road’s Stellar Edge™ site controller and Stellar Microgrid OS™ software coordinates and optimizes distributed energy resources (DERs) within the microgrid. It uses time-of-use electricity pricing, day-ahead forecasts of solar generation and load in an AI algorithm that controls batteries in the microgrid to minimize energy costs, maximize renewable energy generation, and respond to grid services requests.
EPRI’s SPIDER (Simulation Platform for Integration of Distributed Energy Resources) testbed facilitates hardware-in-the-loop testing for DER and microgrid controllers. It simulates DER operations and implements standard monitoring and control protocols such as IEEE 1547, DNP3, and SunSpec to support R&D, evaluate commercial control systems, and test systems before deployment. The testbed was used for this demonstration project to simulate the DERs and validate the Stellar AI controls in the test scenarios.
The project compared three scenarios: a “baseline” scenario without energy storage in the microgrid, a “controlled” scenario with energy storage and a grid services request, and a “cost-minimization” scenario that uses storage to minimize microgrid energy costs with time-of-use pricing and net-metering without a grid services request.
The first scenario is a baseline, shown above in the top two graphs. The left side shows the microgrid with the solar generation and local load shown in yellow and green shaded areas respectively. The microgrid’s net load is shown in blue. When it is below zero, it means the microgrid is exporting power to the main grid. The top right graph shows the power on an upstream power line. During the evening, the upstream power line is overloaded by EV charging outside the microgrid. In the controlled scenario, New Sun Road receives a grid service request ahead of time, directing the microgrid to supply power between 6 PM and midnight. The AI system forecasts solar generation and load, and decides how much to pre-charge the microgrid’s battery so it can supply power back to the grid during the designated time. This action is shown in the bottom left, where the microgrid net load is reduced by the request and the microgrid provides power back to the grid. In total, this prevents the upstream line from being overloaded, allowing the utility to supply power to all customers on the grid without interruption.
Learn more about Stellar AI™
EPRI defined performance metrics for response to the grid services request, renewable generation, and energy costs. In the controlled scenario, the microgrid met the request, staying within the limits with no violation penalties on a five minute timescale. Renewable generation was equal in all scenarios. In the baseline scenario, the microgrid nets $188 over the day from exporting energy. This increased to $229 in the controlled scenario because the grid-services request commands the microgrid to export power during peak pricing. New Sun Road controls increased this further to $249 in the cost-minimization scenario by exporting additional power during peak pricing.
Robin Milshtein (Director of Business Development, New Sun Road), Jonathan Lee (Director of Research, New Sun Road), and Manisha Rauniyar (Engineer / Scientist, EPRI) presenting at Demo Day hosted by Fortis BC in Vancouver, Canada
Microgrids with advanced controls and sufficient energy storage can be leveraged to support the grid.
Performance results show that with control by New Sun Road’s Stellar AI™ and a utility DERMS, the microgrid can support the grid during peak load and remove line overloading. The test system included a battery sized to serve the microgrid load autonomously for 18 hours. While this is typical for a resilience microgrid, a system with a smaller battery may not have sufficient capacity to perform grid services.
A trusted DER simulator accelerates R&D and validates controls.
EPRI’s SPIDER testbed allowed New Sun Road to test our control algorithm running in real-time with real-world communications. This allowed New Sun Road to rapidly prototype, identify, and fix issues before field deployment. Standardized performance metrics allow utilities to compare and evaluate different controllers.
Interoperable communications protocols accelerate integration.
The microgrid controller used DNP3 and Sunspec to communicate with simulated DERs. This streamlined integration, however, the basic Sunspec model needed to be expanded to control battery charging.
Robin Milshtein (Director of Business Development, New Sun Road), Adi Mahan (Engineer / Scientist, EPRI), Jonathan Lee (Director of Research, New Sun Road), and Jerry Ligrani (Incubatenergy Labs Program Lead, EPRI), and Ben York (Applications Manager – Integrated Grid and Energy Systems, EPRI) presenting at Demo Day hosted by Fortis BC in Vancouver, Canada
“This IEL project allowed EPRI to evaluate the performance of a commercially available microgrid controller, as well as validate the DER emulation capabilities of the Simulation Platform for the Integration of DER (SPIDER) testbed. Device interoperability and dispatching of microgrid controller services during grid-connected operations will be a key part of effectively leveraging microgrid controllers for grid operations as installations grow.” – Jacqueline Baum, Technical Leader at EPRI, one of the subject matter experts managing the demonstration effort.
To learn more about EPRI’s Incubatenergy Labs program visit: https://labs.incubatenergy.org