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  1. Research
  2. Sustainable Energy
  3. Electric Grid Modernization
  4. Grid Analytics
  5. AGM Program

Advanced Grid Modeling at PNNL

Better grid support with powerful predictive analytics and modeling tools

  • Emergency Response
  • Grid Analytics
    • AGM Program
    • Tools and Capabilities
  • Grid Architecture
  • Grid Cybersecurity
  • Grid Energy Storage
  • Grid Resilience and Decarbonization
  • Transmission
  • Distribution

About AGM at PNNL

As the electric power grid becomes more complex, dynamic, and uncertain, it is important to improve its reliability, resiliency, security, and flexibility. The industry and regulators need advanced tools to help them make better use of the vast amount of grid data to support their planning and decision making. This becomes particularly important under the uncertainty environment brought by renewable energy and advanced smart technologies applied to smart loads.

To address this need, the U.S Department of Energy’s Office of Electricity has provided leadership in the research area of Advanced Grid Modeling (AGM) for many years. PNNL is one of the main supporting organizations for the AGM program.

This program applies tools and techniques that include advanced computing, artificial intelligence (AI), machine learning, advanced modeling and control approaches, quantitative risk and uncertainty methods, and advanced visualization tools. Together, these tools form analytic solutions to evaluate the state of the power grid in real time, predict operational conditions and system status to determine corrective actions, and support system operations and planning.

Providing faster and better decision-support leads to a more reliable and efficient power grid. Specifically, the AGM program benefits the industry by giving grid operators wide-area, real-time visibility of grid conditions and by providing improved predictive capability. The program also provides governmental policy makers with analytical tools to guide regulatory policy.

The PNNL AGM research team is engaged in transforming the electric power grid analysis and tools using mathematical and computational methods. PNNL's primary areas of research under the AGM program include:

EIOC_west

Adaptive RAS/SPS system settings for improving grid reliability and asset utilization through predictive simulation and controls


EIOC Panorama

Coordination of transmission, distribution, and communication systems for prompt power system recovery after disasters


Photo of city showing possible interactions

Energy Management System 2.0: A Hybrid State Estimator for Multiscale Grid Resilience and Reliability


city highway at night

GridPACKtm: An open source framework for developing high performance computing simulations of the power grid


data on screen

Integrated State Estimation and Contingency Analysis


A city at night with lights in windows

Open source and high-fidelity aggregate composite load models of emerging load behaviors for large scale analysis


EIOC overview

Dynamic paradigm for grid operation


city at night

Stochastic Operations and Planning


picture

PowerDrone: Adaptive steering of power systems for resilient operation under adversarial conditions


Windmills at sunset in Turlock, United States.

Wide Area Oscillation Assessment and Trending Analysis


Researchers discuss the power grid in an electrical control room

Developing high performance computing platform to parallelize Dynamic Contingency Analysis Tool (DCAT) for Cascading Outage Analysis


Wind turbines on hill

New analytical approaches to ensure grid resiliency under high penetration of centralized and distributed inverter-based resources


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A machine learning framework for DCAT to assess power grid security for future grid planning


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Learning to adapt and control for complex power systems


hurricane in the atlantic

Restoration planning following a large-scale extreme event using DCAT


News

August 9, 2022
Strengthening Puerto Rico's Power Grid
November 16, 2021
Industry Collaboration Powers New Generation of Grid Emergency Control Technology
March 22, 2021
Tri-Cities Researchers Work to Protect Electric Grid From Mother Nature’s Fury
August 26, 2019
Tool Could Keep Solar Power From Going Off The Grid

Contact

Yousu Chen
Technical Lead in Grid Analytic Research and High-Performance Computing Applications
yousu.chen@pnnl.gov

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