1 research outputs found
GridPenguin: A District Heating Network Simulator
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