Abstract Future district heating systems and technologies—also known as fourth-generation heating—have a potentially important role to play in the green transition of societies. The implementation involves adjustments demand side allow for low temperature supply. In order facilitate such changes, supply companies have recent years introduced tariffs with penalties high return temperatures benef...

The district heating (DH) industry is facing an important transformation towards more efficient networks that utilise significantly lower water temperatures to distribute the heat. This change requires taking advantage of new technologies, and Machine Learning (ML) a popular direction. In last decade, we have witnessed extreme growth in number published research papers focus on applying ML tech...

DiGriPy is a newly developed Python tool for the simulation of district heating networks published as open-source software in GitHub and offered package on PyPI. It enables user to easily build network model, run large-scale demand time series, automatically compare different temperature-control conditions. In this paper, implementation details usage instructions are given. Tests showing result...