Over the next two decades, hundreds of billions of dollars will be invested in new, 21st century energy systems and advanced manufacturing processes to meet the U.S. 2035 and 2050 decarbonization goals. These new processes and systems will be more dynamic and interconnected than ever before, offering unprecedented opportunities for innovation and the development of novel integrated systems. Such systems will extend significantly beyond current experience, incorporating advances in process intensification and advanced manufacturing. Thus, heuristic and evolutionary development approaches based on traditional systems will be insufficient to identify the most promising technologies, designs, and operating characteristics. Instead new approaches for the design and optimization of complex, interacting multiscale systems will be needed to ensure holistic understanding of the opportunity space and to accelerate development of the best technology options.
The U.S. Department of Energy’s Institute for the Design of Advanced Energy Systems (IDAES) is a next-generation, multi-scale, open-source PSE framework built to enable large-scale deterministic optimization. The framework is built on Pyomo, a Python based Algebraic Modeling Language (AML), with access to state-of-the-art optimization solvers and the Python foundation offers access to scientific computing, data analytics and visualization capabilities. The framework supports steady-state and dynamic optimization, conceptual design, parameter estimation, model predictive control, uncertainty quantification and generating surrogate models. These capabilities enable the design and optimization of complex integrated energy systems and smart manufacturing processes, accelerating their development and deployment to support rapid decarbonization of the energy and industrial sectors.