IESopt: A Modular Framework for High-Performance Energy System Optimization

urrent climatic, political, and societal challenges pose increasingly complex questions, which in turn require comprehensive models of the real world, with rapidly growing complexity, to support decision makers with sound and reliable
quantitative analyses. The energy system optimization framework IESopt may constitute one piece in filling this gap, by offering a modular and adaptable tool for modelers, that does not compromise on performance while still being user-friendly. This is enabled by reducing energy system assets to abstract building
blocks, that are supported by specialized implementation, and can be combined into complex systems without the need of a detailed understanding of mathematical modeling or proficiency in any coding-language. IESopt’s architecture and functionalities are laid out here, and demonstrated by the means of an illustrative example