The National Energy Technology Laboratory’s Institute for the Design of Advanced Energy Systems (IDAES) is a powerful and versatile computational platform offering next-generation engineering capabilities for optimizing the design and operation of innovative chemical process and energy systems beyond current constraints on complexity, uncertainty, and scales ranging from materials to process to market.
The IDAES Process Systems Energineering (PSE) framework was conceived in 2016 to specifically address the gaps between state-of-the-art simulation packages and algebraic modeling languages.
Major strengths of commercial simulation packages are their libraries of unit models and thermophysical properties. However, such simulation packages often have difficulty optimizing flowsheets and have limited support for incorporating models of non-standard, dynamic units, such as solids handling, and uncertainty quantification. On the other hand, AMLs are eminently flexible and readily support large-scale optimization, but considerable work is required to construct process models, which are often only useful for a one-time application.
The IDAES PSE framework represents an innovative approach for the design and optimization of chemical and energy processes by integrating an extensible, equation-oriented process model library with Pyomo (a Python-based AML). Built specifically to enable rigorous large-scale mathematical optimization, the framework includes capabilities for conceptual design, steady-state and dynamic optimization, multi-scale modeling, uncertainty quantification, and the automated development of thermodynamic, physical property, and kinetic sub-models from experimental data.
All IDAES Code is completely free and redistributable, the license is avaliable here. Users are free to modify and redistribute code, and community development is encouraged.
By using an equation-oriented platform, users gain access to a wide range of highly efficient, derivative-based numerical solvers for a wide range of problem types, including support for both linear and non-linear problems, ordinary and partial differential equations, and problems involving binary and integer variables.
Fully-Featured Programming Environment¶
By building off of Python, a fully-featured programming environment, users gain access to a wide range of libraries for tools such as data visualization and management.
The source code for all models and tools is fully-open and visible to the user. This allows users to both see and understand what is happening in each model, but also modify and extend models to suit their needs.
No single model form is best suited to all applications, thus the IDAES PSE framework is built to provide users with access to a range of different model forms. This allows users to easily pick-and-choose from the available model forms to find the one best suited to their particular application.
Access to Advanced Capabilities¶
IDAES aims to provide an integrated platform for development of not just process models but also tools for solving and analyzing these problems. The IDAES PSE framework supports conceptual design, parameter estimation, model predictive control, uncertainty quantification, and surrogate modeling.