GridPenguin: A District Heating Network Simulator

Conference Paper (2022)
Author(s)

J. Wu (Flex Technologies)

Rob Everhardt (Flex Technologies)

K. Stepanovic (TU Delft - Electrical Engineering, Mathematics and Computer Science)

M.M. de Weerdt (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Algorithmics
URL related publication
https://www.nefi.at/files/media/Bilder/News/NEFI%20Konferenz%202022/NEFI2022%20Conference%20Proceedings/NEFI_Conference_2022_Proceedings.pdf Final published version
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Publication Year
2022
Language
English
Research Group
Algorithmics
Pages (from-to)
132-141
ISBN (electronic)
978-3-200-08856-6
Event
New Energy for Industry 2022 (2022-10-13 - 2022-10-14), Linz, Austria
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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.