Collaborative Research: In-field, GFM-enabled, Data-driven, and Stability-certified Tuning of Hybrid Diesel Generator/IBR Microgrids

This NSF project aims to reduce the cost of electricity in small, isolated grids by streamlining the integration of battery energy storage systems, thereby reducing reliance on diesel fuel consumption. Battery energy storage systems buffer fluctuations from variable distributed energy sources, allowing more efficient utilization of diesel generators. However, in many of these systems, the battery energy storage system and the diesel generators are co-located and are commensurate in size. These conditions can lead to adverse power interactions. The project will bring transformative change by developing a practical, data-driven way to detect and prevent these interactions on-site, without specialized studies and expertise that small utilities rarely have. This will be achieved by using the battery inverter itself to probe the grid and learn how each unit responds and then adjusting the battery controls accordingly to keep the system stable. The intellectual merit of the project includes new mathematical foundations and measurement methods for understanding and controlling how modern inverters and traditional generators interact when they are closely connected and similar in size. The broader impacts of the project include lower energy costs and greater resilience for rural and remote communities that face some of the nation's highest electricity prices. This project targets a core problem in small, isolated grids: when grid-forming (GFM) inverters (i.e., power electronic devices that impose the grid's voltage and frequency) run alongside comparably sized, electrically close diesel generators, the two can interact and produce sustained oscillations. Solutions designed to address this in large transmission systems, where such units are far apart and can be analyzed separately, fail in low-voltage community grids, where accurate generator models are also usually unavailable. To address these challenges, this project proposes a novel, data-driven approach that utilizes a grid-forming (GFM) inverter as an in-field probing source, and distributed monitoring through existing parallel controllers to determine the input-output (IO) transfer functions of microgrid components (e.g., legacy diesel generators). Moreover, analytical stability specifications on the IO transfer functions will be developed that account for low-impedance coupling and coupling between frequency and voltage dynamics. Active damping functions will be used to shape the aggregate dynamics of paralleled diesel generators/inverter-based resources through GFM inverters to achieve system stability without requiring complex interconnection studies. The proposed approach will be implemented in a 500kW-scale laboratory test bed including GFM inverters and diesel generators for data collection and experimental validation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.