optihood provides a complete python-based framework to OPTImize the investment in alternative energy technologies (heat pump, solar thermal, PV, etc.) as well as the operation of available energy resources (natural gas, sun, grid electricity, etc.) at a neighbourHOOD-scale. It is designed to facilitate the researchers and energy planners in optimizing an energy neighbourhood in terms of cost and/or environmental criteria. It enables the users to perform both single-objective and multi-objective optimization and analysis. The energy model and it's associated parameters can be defined easily using an excel file. Additionally, a variety of plotting methods are defined for easy and fast result visualization.
The package was developed at the SPF - Institute for Solar Technology at the OST - Eastern Switzerland University of Applied Sciences and Haute Ecole d'Ingénierie et de Gestion du Canton Vaud.
guide/getting_started guide/energy_system_component_models guide/defining_an_energy_network guide/optimizing_the_energy_network guide/processing_results guide/advanced_under_development_features Code Reference <modules>
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- SPF Institute for Solar Technology, Rapperswil, Switzerland
- HEIG VD, Yverdon-les-Bains, Switzerland
This framework was created in 2021 and made open-source in 2022. We would like to thank the Swiss Federal Office Of Energy (SFOE) for the support and funding received in the projects OptimEase and SolHood which allowed us to spend efforts in developing and sharing the code and becoming a part of the open-source community.