
This repository contains Python-based simulation tools and computational workflows for analysing solar thermal energy systems using Greenius. The code was created to support research activities related to the modelling, simulation, processing and evaluation of solar thermal system performance. The repository includes scripts for simulation management, input preparation, data processing, result extraction and analysis of key performance indicators. These tools enable the evaluation of system behaviour under different operating conditions and support the assessment of solar thermal technologies for renewable energy applications. The code is intended to improve reproducibility and transparency of the simulation methodology used in research studies. It can be adapted for further investigations involving solar thermal systems, performance optimisation, sensitivity analyses and integration studies.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
