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The RAMP project is currently undergoing extensive further development, jointly led by TU Delft, the Reiner Lemoine Institut, VITO, the University of Liège, the Universidad Mayor de San Simón, and the Leibniz University Hannover.
These joint developments have been recently formalised in RAMP's publication in the Journal of Open Source Software, alongside a brand new version of the tool: more extensively documented, richer in visualisation options, and more easy to customise for different applications! We'll keep improving and expanding the tool, leveraging the diverse expertise of our multi-institution team.
Already done and available in the new v0.5.2 release of the code:
- inputs can be defined in tabular (.xslx) format
- outputs can be easily post-processed and plotted
- the code is a Python package installable via pip
- the documentation is expanded and released on readthedocs
- parallel processing is possible
- code is faster thanks to vectorising operations
- a new UseCase class allows grouping multiple Users and performing operations on those
- web-based graphical user interface for basic functionalities
- random-seed functionality to ensure reproducible results if needed
- more examples as Jupyter notebooks in the documentation
- new features to model productive uses, such as continuously operating machines
- expanded internal test coverage for higher code reliablity
Work-in-progress:
- bringing back together RAMP-mobility as a customisation option that builds on the same stochastic 'engine'
- further developing the 'heat' features
- application and possible new functionalities for non-energy loads, such as water demand
Do you have great ideas about further things to implement? Do you want to join the next-gen developmet? Then get in touch on our Gitter chat!