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The U.S. Department of Energy’s (DOE’s) Institute for the Design of Advanced Energy Systems (IDAES) is the winner of a prestigious 2020 R&D100 award, which recognizes the developers of the 100 most technologically significant products introduced into the marketplace in the last year. IDAES, which won in the category of software/services, develops next-generation computational tools for process systems engineering (PSE) of advanced energy systems, enabling their rapid design and optimization.
Led by NETL Senior Fellow, David C. Miller, IDAES is a collaboration with Sandia National Laboratories, Lawrence Berkeley National Laboratory, West Virginia University, Carnegie Mellon University and the University of Notre Dame in partnership with a broad range of stakeholders, which have been intimately involved in IDAES since its inception, reviewing progress, testing early releases, and developing end-use cases. The Stakeholder Advisory Board includes representatives from a wide range of organizations, skills, experience and end-use applications. Over 200 end-users have been trained in using the IDAES Computational Framework through multiple tutorial sessions. In addition, over 2200 users have installed IDAES using PyPI (the official third-party software repository for Python).
“I am immensely proud of the entire IDAES Technical Team. Their spirit of teamwork, collaboration, and innovation have enabled us to create and deploy the IDAES Integrated Platform to optimize the design and operation of complex, interacting technologies and systems,” said David Miller after hearing the announcement. “I am deeply thankful for our industry stakeholders and the support of the Simulation-Based Engineering Program of DOE’s Office of Fossil Energy for giving us the opportunity to develop and deploy these unique modeling capabilities to increase efficiency, lower costs, increase revenue and improve sustainability.”
“I am excited to see IDAES selected as an R&D100 award winner. The new capabilities that we are building are unique, groundbreaking, and eminently useful for a broad range of applications,” said Daniel Gunter, who heads the LBNL’s Computational Research Division’s Integrated Data Frameworks Group and IDAES team member. “The project team includes a number of top experts across the domain, and even more impressively the team collaborates deeply and well – better than any team this size I have ever been part of. I feel privileged to be part of this very successful example of the power of team science.”
By providing rigorous modeling capabilities, the IDAES Modeling & Optimization Platform helps energy and process companies, technology developers, academic researchers, and the U.S. Department of Energy to design, develop, scale-up and analyze new and potential PSE technologies and processes to accelerate advances and apply them to address the nation’s energy needs. The IDAES platform is also a key component in the “National Alliance for Water Innovation,” a $100M 5-year DOE project led by Berkeley Lab
, which will examine the critical technical barriers and research needed to radically lower the cost and energy of desalination.
IDAES provides revolutionary new capabilities for Process Systems Engineering that exceed existing tools and approaches. After years of development, IDAES has established an extensive modeling library integrated with a suite of advanced machine learning, uncertainty quantification and optimization techniques that enable process optimization, parameter estimation, advanced process control and multi-scale analysis across various levels of implementation. With its equation-oriented modeling approach, IDAES uniquely supports the process modeling lifecycle, from conceptual design to dynamic optimization and control. IDAES has cultivated an active, growing user community from multiple industries. This open-source Integrated Platform is available from Github.
The R&D 100 Awards competition received entries from 19 countries and regions for the 2020 competition. A full list of the 2020 winners is available at the R&D World website.
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