User:RobbieIanMorrison/sandbox/work in progress aeK7ic

Project	Demod
Host	EPFL
Status	active
Scope/type	domestic demand
Code license	GPLv3+
Language	Python
Repository	github.com/epfl-herus/demod
Documentation	demod.readthedocs.io
Python package	pypi.org/project/demod

Project	RAMP
Host	TU Delft
Status	active
Scope/type	synthetic demand profiles
Code license	EUPL-1.2
Language	Python
Website	rampdemand.org
Repository	github.com/RAMP-project/RAMP
Documentation	rampdemand.readthedocs.io
Python package	pypi.org/project/rampdemand/
Chat	Gitter/RAMP-project/community

Development for material for Open energy system models#Specialist models

forum.openmod.org/t/demod-a-new-python-lybrary-for-domestic-energy-demand-modeling/2875

Open energy system models#RAMP

Open energy system models • Work‑in‑progress

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RAMP

D E P L O Y E D

RAMP is an open-source software suite for the stochastic simulation of user‑driven energy demand time series based on few simple inputs. For example, a minimal definition of a user type — for instance, a certain category of household — requires only information about which energy-consuming devices they own, when they tend to use them on any typical day, and for how long in total. The software then leverages stochasticity to make up for the absence of more detailed information and to represent the unpredictability of human behavior.

The RAMP software can then generate synthetic data wherever metered data does not exist, such as when designing systems in remote areas ^[1] or when looking forward to future electric-vehicle fleets.^[2] Moreover, the limited data requirements allow for a greater flexibility in scenario choice and development than similar but more data-intensive characterizations.^[3]

RAMP has been used in scientific research across diverse use cases, including generating electricity demand profiles for remote or residential communities, domestic hot water usage, cooking practices, and electric mobility. With geographic scales ranging from the level of districts to continents.

RAMP has several dozen users globally. In the early‑2020s, the software became part of a multi-institution software development effort, supported by TU Delft, VITO, Reiner Lemoine Institute, University of Liège, Leibniz University Hannover, and Universidad Mayor de San Simón.^[3]

RAMP runs on Python and requires inputs in tabular format. Graphical user interfaces (GUI) are available that allow the software to be run from a web browser.^[4]

Demod

The Demod or Domestic Energy Demand Modelling Library is a Python library for assembling bottom‑up domestic energy demand models.^[5]

References

^ Lombardi, Francesco; Balderrama, Sergio; Quoilin, Sylvain; Colombo, Emanuela (15 June 2019). "Generating high-resolution multi-energy load profiles for remote areas with an open-source stochastic model". Energy. 177: 433–444. doi:10.1016/j.energy.2019.04.097. Retrieved 2024-06-19.
^ Mangipinto, Andrea; Lombardi, Francesco; Sanvito, Francesco Davide; Pavičević, Matija; Quoilin, Sylvain; Colombo, Emanuela (15 April 2022). "Impact of mass-scale deployment of electric vehicles and benefits of smart charging across all European countries". Applied Energy. 312: 118676. doi:10.1016/j.apenergy.2022.118676. Retrieved 2024-06-19.
^ ^a ^b Lombardi, Francesco; Duc, Pierre-François; Tahavori, Mohammad Amin; Sanchez-Solis, Claudia; Eckhoff, Sarah; Hart, Maria CG; Sanvito, Francesco; Ireland, Gregory; Balderrama, Sergio; Kraft, Johann; Dhungel, Gokarna; Quoilin, Sylvain (12 June 2024). "RAMP: stochastic simulation of user-driven energy demand time series". Journal of Open Source Software. 9 (98): 6418. doi:10.21105/joss.06418. ISSN 2475-9066. Retrieved 2024-06-18.
^ "RAMP: NESSI web interface". NESSI:RAMP. Retrieved 2024-06-19.
^ Barsanti, Matteo; Schwarz, Jan Sören; Gérard Constantin, Lionel Guy; Kasturi, Pranay; Binder, Claudia R; Lehnhoff, Sebastian (13 September 2021). "Socio-technical modeling of smart energy systems: a co-simulation design for domestic energy demand" (PDF). Energy Informatics. 4 (3): 12. ISSN 2520-8942. Retrieved 2021-11-30.

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[lombardi-etal-2019-1] Lombardi, Francesco; Balderrama, Sergio; Quoilin, Sylvain; Colombo, Emanuela (15 June 2019). "Generating high-resolution multi-energy load profiles for remote areas with an open-source stochastic model". Energy. 177: 433–444. doi:10.1016/j.energy.2019.04.097. Retrieved 2024-06-19.

[mangipinto-etal-2022-2] Mangipinto, Andrea; Lombardi, Francesco; Sanvito, Francesco Davide; Pavičević, Matija; Quoilin, Sylvain; Colombo, Emanuela (15 April 2022). "Impact of mass-scale deployment of electric vehicles and benefits of smart charging across all European countries". Applied Energy. 312: 118676. doi:10.1016/j.apenergy.2022.118676. Retrieved 2024-06-19.

[lombardi-etal-2024-3] Lombardi, Francesco; Duc, Pierre-François; Tahavori, Mohammad Amin; Sanchez-Solis, Claudia; Eckhoff, Sarah; Hart, Maria CG; Sanvito, Francesco; Ireland, Gregory; Balderrama, Sergio; Kraft, Johann; Dhungel, Gokarna; Quoilin, Sylvain (12 June 2024). "RAMP: stochastic simulation of user-driven energy demand time series". Journal of Open Source Software. 9 (98): 6418. doi:10.21105/joss.06418. ISSN 2475-9066. Retrieved 2024-06-18.

[ramp-web-interface-4] "RAMP: NESSI web interface". NESSI:RAMP. Retrieved 2024-06-19.

[barsanti-etal-2021-5] Barsanti, Matteo; Schwarz, Jan Sören; Gérard Constantin, Lionel Guy; Kasturi, Pranay; Binder, Claudia R; Lehnhoff, Sebastian (13 September 2021). "Socio-technical modeling of smart energy systems: a co-simulation design for domestic energy demand" (PDF). Energy Informatics. 4 (3): 12. ISSN 2520-8942. Retrieved 2021-11-30.

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