NETL, University Researchers Demonstrate the Power of IDAES to Advance Clean Energy Technology

A team of researchers from NETL and academia has demonstrated the unique dynamic analysis capabilities available through the Lab’s Institute for the Design of Advanced Energy Systems (IDAES) to advance clean energy technologies.

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IDAES is a next-generation multi-scale modeling and optimization framework designed to support the U.S. power industry. Researchers from NETL, other national labs, and universities across the nation use IDAES to accelerate the design and deployment of integrated power, hydrogen, and industrial processes to support broad decarbonization and emerging research and development priorities.

One area of clean energy technology optimization being explored using IDAES entails the use of solid oxide cell (SOC) systems. SOCs are a promising dual-mode technology to produce hydrogen through high-temperature water electrolysis or generate power through a fuel cell reaction that consumes natural gas or hydrogen. While SOCs hold great promise for near-zero-emissions energy production, there are known challenges associated with the technology. Fortunately, some of these challenges can be mitigated through what are known as advanced control strategies — ways of optimally regulating and maintaining a system.

Recently, NETL researchers and others supporting IDAES have published a series of papers that detail how IDAES software was implemented for the following SOC applications:

Demonstrating reinforcement learning control — the paper Development of algorithms for augmenting and replacing conventional process control using reinforcement learning, by NETL’s Douglas Allan and Stephen Zitney (retired), along with Daniel Beahr and Debangsu Bhattacharyya from West Virginia University (WVU), was published in the Computers and Chemical Engineering journal. The paper details how a machine learning approach called reinforcement learning control can be used to refine and improve conventional control for chemical and power systems.

Applying a nonlinear predictive control to an SOC — the paper Nonlinear model predictive control for mode-switching operation of reversible solid oxide cell systems, by Allan, Zitney, and Bhattacharyya, along with Nishant Giridhar from WVU and Mingrui Li, San Dinh, and Lorenz T. Biegler from Carnegie Mellon University, explained how the team applied advanced system controls to reduce temperature gradients for solid oxide cells during fast operational ramping, improving long-term cell life and thus reducing costs.

Optimizing solid oxide cell hydrogen production while including cell chemical degradation — the paper Optimal operation of solid-oxide electrolysis cells considering long-term chemical degradation, by Allan, Zitney, Bhattacharyya, Giridhar, Li, and Biegler, was published in the Energy & Conversion Management journal. The paper outlined how to optimize the performance of solid oxide electrolysis cells for long-term hydrogen production at high temperatures, reducing the hydrogen cost by over 9%.

NETL is a U.S. Department of Energy national laboratory that drives innovation and delivers solutions for an environmentally sustainable and prosperous energy future. By leveraging its world-class talent and research facilities, NETL is ensuring affordable, abundant, and reliable energy that drives a robust economy and national security, while developing technologies to manage carbon across the full life cycle, enabling environmental sustainability for all Americans.