Portal de Periódicos da CAPES

COMANDO: A Next-Generation Open-Source Framework for Energy Systems Optimization

2021; Elsevier BV; Volume: 152; Linguagem: Inglês

10.1016/j.compchemeng.2021.107366

1873-4375

Marco Langiu, David Yang Shu, Florian Joseph Baader, Dominik Hering, Uwe Bau, André Xhonneux, Dirk Müller, André Bardow, Alexander Mitsos, Manuel Dahmen,

Building Energy and Comfort Optimization

Existing open-source modeling frameworks dedicated to energy systems optimization typically utilize (mixed-integer) linear programming ((MI)LP) formulations, which lack granularity 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 (ANNs) as surrogate models in a reduced-space formulation for deterministic global optimization.