Machine Learning for Natural Gas to Electric Power System Design

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Richland, Washington
Project Term:
03/26/2020 - 11/30/2022

Critical Need:

The DIFFERENTIATE program seeks to leverage the emerging artificial intelligence (AI) revolution to help resolve the energy and environmental challenges of our time. The program aims to speed energy innovation by incorporating machine learning (ML) into the energy technology development process. A core part of AI, ML is the study of computer algorithms that improve automatically through experience. This approach is expected to facilitate a rapid transition to lower-carbon-footprint energy sources and systems. To organize the proposed efforts, the program uses a simplified engineering design process framework to conceptualize several ML tools that could help engineers execute and solve these problems in a manner that dramatically accelerates the pace of energy innovation.

Project Innovation + Advantages:

Pacific Northwest National Laboratory (PNNL) will apply multiple machine learning tools to develop next-generation natural gas to electric power conversion system designs. The project leverages a physics-informed machine learning tool for automated reduced order model (ROM) construction. This will significantly reduce prediction errors compared to traditional approaches. Machine learning will also leverage a superstructure-based mathematical optimization tools combined with reinforcement learning and graph network methods to explore and optimize component connections in fuel to electric power conversion systems.

Potential Impact:

DIFFERENTIATE aims to enhance the productivity of energy engineers in helping them to develop next-generation energy technologies. If successful, DIFFERENTIATE will yield the following benefits in ARPA-E mission areas:


Seek U.S. technological competitive advantage by leading the development of machine-learning enhanced engineering design tools.


Use these tools to solve our most challenging energy and environmental problems by facilitating an economically-attractive transition to lower carbon-footprint energy sources and systems.


Reap the economic productivity benefits associated with the commercial adoption of the resulting higher-value energy technologies and associated products.


ARPA-E Program Director:
Dr. David Tew
Project Contact:
Dr. Jie Bao
Press and General Inquiries Email:
Project Contact Email:


National Energy Technology Laboratory
University of Washington

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