DEEE0011375
Cooperative Agreement
Overview
Grant Description
The goal of this project is to develop the Grid Operator Analytics and Assessment Tools for Inverter-Based Resources Dominated Grid (GOAAT-IBR).
The project aims to develop a cloud-based grid health assessment and risk assessment tool to improve the situational awareness of large-scale transmission interconnected inverter based resources (IBRs).
As IBR deployments increase, utilities will need new tools that can detect and be used to mitigate system impacts.
GOAAT-IBR is a suite of tools and applications designed to run on a commercially available, state-of-the-art time series data analytics platform for electric utilities.
Specifically, we will:
1. Configure the cloud-based time series data and analytics platform to ingest both streaming and historical data archives from different sources such as the Supervisory Control and Data Acquisition (SCADA) system, Phasor Measurement Units (PMUs), Intelligent Electronic Devices (IEDs), devices capable of streaming Point-on-Wave (POW) data, Power Quality Meters (PQM), Digital Fault Recorders (DFR), PI Historian, and weather forecast services.
GOAAT-IBR will provide the analytical foundation and secure environment in which the GOAAT-IBR applications will run.
2. Research and develop data analytic techniques tailored for enhancing data-driven situational awareness of IBR-dominated power systems.
Three target use cases are 1) real-time effective inertia estimation, 2) grid strength (short circuit level) estimation, and 3) IBR control-driven sub-synchronous oscillation (SSO) detection and source location.
3. Design and develop advanced visualization tools to seamlessly convey actionable and interpretable information indicating system health and risk to operators.
4. Develop data analytics applications to support disturbance data spatial-temporal correlations, automated event analysis, and automatic report generation (not only for system events but even for hardware sensor health monitoring).
5. Develop decision support system (DSS) application to deliver actionable recommendations to operators to mitigate IBR abnormal behaviors and oscillations.
6. Set up RTDS hardware-in-the-loop (HIL) simulation to prototype and validate all developed applications.
As a field demonstration, GOAAT-IBR will be demonstrated with the utility with field sensor streams.
7. Develop a commercialization and implementation roadmap for GOAAT-IBR.
The project aims to develop a cloud-based grid health assessment and risk assessment tool to improve the situational awareness of large-scale transmission interconnected inverter based resources (IBRs).
As IBR deployments increase, utilities will need new tools that can detect and be used to mitigate system impacts.
GOAAT-IBR is a suite of tools and applications designed to run on a commercially available, state-of-the-art time series data analytics platform for electric utilities.
Specifically, we will:
1. Configure the cloud-based time series data and analytics platform to ingest both streaming and historical data archives from different sources such as the Supervisory Control and Data Acquisition (SCADA) system, Phasor Measurement Units (PMUs), Intelligent Electronic Devices (IEDs), devices capable of streaming Point-on-Wave (POW) data, Power Quality Meters (PQM), Digital Fault Recorders (DFR), PI Historian, and weather forecast services.
GOAAT-IBR will provide the analytical foundation and secure environment in which the GOAAT-IBR applications will run.
2. Research and develop data analytic techniques tailored for enhancing data-driven situational awareness of IBR-dominated power systems.
Three target use cases are 1) real-time effective inertia estimation, 2) grid strength (short circuit level) estimation, and 3) IBR control-driven sub-synchronous oscillation (SSO) detection and source location.
3. Design and develop advanced visualization tools to seamlessly convey actionable and interpretable information indicating system health and risk to operators.
4. Develop data analytics applications to support disturbance data spatial-temporal correlations, automated event analysis, and automatic report generation (not only for system events but even for hardware sensor health monitoring).
5. Develop decision support system (DSS) application to deliver actionable recommendations to operators to mitigate IBR abnormal behaviors and oscillations.
6. Set up RTDS hardware-in-the-loop (HIL) simulation to prototype and validate all developed applications.
As a field demonstration, GOAAT-IBR will be demonstrated with the utility with field sensor streams.
7. Develop a commercialization and implementation roadmap for GOAAT-IBR.
Awardee
Funding Goals
THIS FOA WILL FUND RESEARCH IN THREE (3) TOPICS AREAS THAT DEVELOP TECHNOLOGIES TO ADDRESS EMERGING CHALLENGES AND ENHANCE THE BENEFITS OF VRE, IBR, AND DER, INCLUDING LONG-TERM PLANNING ACTIVITIES AND THE DAILY OPERATION OF THE GRID. THE NEW STATE-OF-THE-ART PLANNING AND OPERATIONS TOOLS WILL ENABLE SOLAR ENERGY TO BE MORE OPTIMALLY UTILIZED OVER TIME AND ALLOW IT TO BE UTILIZED IN PLACE OF TRADITIONAL GENERATION, PROVIDING AMERICANS WITH MORE CHEAP AND SECURE SOURCES OF CLEAN ENERGY.
Grant Program (CFDA)
Awarding Agency
Place of Performance
Raleigh,
North Carolina
27607-3960
United States
Geographic Scope
Single Zip Code
Quanta Technology was awarded
Grid Operator Analytics for IBR-Dominated Grid
Cooperative Agreement DEEE0011375
worth $3,161,341
from the Office of Energy Efficiency and Renewable Energy in October 2024 with work to be completed primarily in Raleigh North Carolina United States.
The grant
has a duration of 1 year 5 months and
was awarded through assistance program 81.087 Renewable Energy Research and Development.
$1,453,843 (32.0%) of this Cooperative Agreement was funded by non-federal sources.
The Cooperative Agreement was awarded through grant opportunity Operation and Planning Tools for Inverter-based Resource Management and Availability for future power systems (OPTIMA), DE-FOA-0003034.
Status
(Ongoing)
Last Modified 7/1/25
Period of Performance
10/1/24
Start Date
3/31/26
End Date
Funding Split
$3.2M
Federal Obligation
$1.5M
Non-Federal Obligation
$4.6M
Total Obligated
Activity Timeline
Transaction History
Modifications to DEEE0011375
Additional Detail
Award ID FAIN
DEEE0011375
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
For-Profit Organization (Other Than Small Business)
Awarding Office
892434 GOLDEN FIELD OFFICE
Funding Office
892403 ENERGY EFFICIENCYRENEWABLE ENERGY
Awardee UEI
SY2KSD7B7M31
Awardee CAGE
516Y9
Performance District
NC-02
Senators
Thom Tillis
Ted Budd
Ted Budd
Modified: 7/1/25