Print Email Facebook Twitter GridPenguin: A District Heating Network Simulator Title GridPenguin: A District Heating Network Simulator Author Wu, J. (Flex Technologies) Everhardt, Rob (Flex Technologies) Stepanovic, K. (TU Delft Algorithmics) de Weerdt, M.M. (TU Delft Algorithmics) Contributor Gradwohl, Christopher (editor) Degold, Alexandra (editor) Kienberger, Thomas (editor) Date 2022 Abstract District heating system (DHS) optimization is becoming an increasingly important problem because of the unused potential in flexibility that could allow less energy being wasted and the integration of renewable energy. While new optimization methods are proposed every year to tackle this problem, the literature lacks a good way to benchmark newly proposed methods. To address this problem, we introduce GridPenguin, an open-source computational simulator for the physics of district heating networks. It provides flexibility in usage by providing building blocks with which the user can build any grid he wants. The detailed simulation of the physical world with a focus on the heat balance and average flow rate and temperature allows for fast and accurate simulation. By explaining the physical equations and computational model as well as the comparison to existing software, we lay a solid foundation for the performance of the simulator. We present GridPenguin as a metric to evaluate optimization methods as well as a tool for easy integration of advanced machine learning methods into DHS optimization. The source code of our project can be found on https://github.com/ftbv/grid-penguin. Subject District heating systemSimulationOptimizationHeat production planning To reference this document use: http://resolver.tudelft.nl/uuid:e04914e9-9345-45e7-acdf-2d59b64f5541 Publisher NEFI: New Energy for Industry ISBN 978-3-200-08856-6 Source Conference Proceedings New Energy for Industry 2022: 2nd Conference of the Innovation Network, October 13-14, 2022 in Linz, Austria Event New Energy for Industry 2022, 2022-10-13 → 2022-10-14, Linz, Austria Part of collection Institutional Repository Document type conference paper Rights © 2022 J. Wu, Rob Everhardt, K. Stepanovic, M.M. de Weerdt Files PDF NEFI_Conference_2022_Proc ... edings.pdf 644.94 KB PDF paper.pdf 1.76 MB Close viewer /islandora/object/uuid:e04914e9-9345-45e7-acdf-2d59b64f5541/datastream/OBJ1/view