This title appears in the Scientific Report : 2021 
COMANDO: A Next-Generation Open-Source Framework for Energy Systems Optimization
Langiu, Marco
Shu, David Yang / Baader, Florian / Hering, Dominik / Bau, Uwe / Xhonneux, André / Müller, Dirk / Bardow, André / Mitsos, Alexander / Dahmen, Manuel (Corresponding author)
Modellierung von Energiesystemen; IEK-10
2021
Preprint
Energie System 2050
Digitalisierung und Systemtechnik
OpenAccess
Please use the identifier: http://hdl.handle.net/2128/27422 in citations.


Existing open-source modeling frameworks dedicated to energy systems optimization typically utilize (mixed-integer) linear programming ((MI)LP) formulations, which lack modeling freedom for technical system design and operation. We present COMANDO, an open-source Python package for component-oriented modeling and optimization for nonlinear design and operation of integrated energy systems. COMANDO allows to assemble system models from component models including nonlinear, dynamic and discrete characteristics. Based on a single system model, different deterministic and stochastic problem formulations can be obtained by varying objective function and underlying data, and by applying automatic or manual reformulations. The flexible open-source implementation allows for the integration of customized routines required to solve challenging problems, e.g., initialization, problem decomposition, or sequential solution strategies. We demonstrate features of COMANDO via case studies, including automated linearization, dynamic optimization, stochastic programming, and the use of nonlinear artificial neural networks as surrogate models in a reduced-space formulation for deterministic global optimization.