Transparency, reproducibility, and quality of energy system analyses – A process to improve scientific work

Hülk, Ludwig; Müller, Berit; Glauer, Martin; Förster, Elisa; Schachler, Birgit

doi:10.1016/j.esr.2018.08.014

Cited by 22 publications

(10 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Documentation to associate with versioned open-source code helps in understanding the tool, as well as tutorials and beginner examples, in addition to execution environments. Hülk et al [63] also offer factsheets to present frameworks, models, and scenarios in a clear, concise, and understandable way. Means of synchronous or asynchronous socialisation (e.g., forums), if used by a sufficiently broad community, make it possible to capture and disseminate both explicit and tacit knowledge [64].…”

Section: User Friendliness and Accessibilitymentioning

confidence: 99%

OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale

et al. 2021

View full text Add to dashboard Cite

Energy modelling is key in order to face the challenges of energy transition. There is a wide variety of modelling tools, depending on their purpose or study phase. This article summarises their main characteristics and highlights ones that are relevant when it comes to the preliminary design of energy studies at district scale. It introduces OMEGAlpes, a multi-carrier energy modelling tool to support stakeholders in the preliminary design of district-scale energy systems. OMEGAlpes is a Mixed-Integer Linear Programming (MILP) model generation tool for optimisation. It aims at making energy models accessible and understandable through its open-source development and the integration of energy stakeholders and their areas of responsibility into the models. A library of use cases developed with OMEGAlpes is presented and enables the presentation of past, current, and future development with the tool, opening the way for future developments and collaborations.

show abstract

Section: User Friendliness and Accessibilitymentioning

confidence: 99%

OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Self-assessment is particularly recommended to qualify and improve the openness of studies: Cao et al (2016) propose a transparency checklist, focusing on both models and study results comprehensibility, at least by experts. Hülk et al (2018) apply this method and propose fact sheets for the framework, models and scenarios of the studies, in order to provide a publicly available, clear and concise representation of these, since well documented open source projects can still cause information overload issues. Finally, open digital platforms making energy data and models available can help to meet the challenges of transparency and reproducibility (Pfenninger et al 2018).…”

Section: Open Energy Modellingmentioning

confidence: 99%

Open and Reproducible Use Cases for Energy (ORUCE) methodology in systems design and operation: a dwelling photovoltaic self-consumption example.

Hodencq¹,

Delinchant²,

Würtz³

2021

Building Simulation Conference Proceedings

View full text Add to dashboard Cite

“…To this type of input-output system we can now apply (data-driven) systemtheoretic model reduction methods, which preserve the input-to-output mapping S, but explicitly not the internal state p q . Lastly, we note that based on [65], we added a model fact sheet in the Appendix.…”

Section: Input-output Modelmentioning

confidence: 99%

Model Order Reduction for Gas and Energy Networks

Himpe,

Grundel,

Benner

2020

Preprint

View full text Add to dashboard Cite

To counter the volatile nature of renewable energy sources, gas networks take a vital role. But, to ensure fulfillment of contracts under these new circumstances, a vast number of possible scenarios, incorporating uncertain supply and demand, has to be simulated ahead of time. This many-query task can be accelerated by model order reduction, yet, large-scale, nonlinear, parametric, hyperbolic partial differential(-algebraic) equation systems, modeling gas transport, are a challenging application for model reduction algorithms. For this industrial application, we bring together the scientific computing topics of: mathematical modeling of gas transport networks, numerical simulation of hyperbolic partial differential equation, and model order reduction for nonlinear parametric systems. This research resulted in the morgen (Model Order Reduction for Gas and Energy Networks) software platform, which enables modular testing of various combinations of models, solvers, and model reduction methods. In this work we present the theoretical background on systemic modeling and structured, data-driven, system-theoretic model reduction for gas networks, as well as the implementation of morgen and associated numerical experiments testing model reduction adapted to gas network models.

show abstract

Transparency, reproducibility, and quality of energy system analyses – A process to improve scientific work

Cited by 22 publications

References 4 publications

OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale

OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale

Open and Reproducible Use Cases for Energy (ORUCE) methodology in systems design and operation: a dwelling photovoltaic self-consumption example.

Model Order Reduction for Gas and Energy Networks

Contact Info

Product

Resources

About