Merge branch 'dev_all_publication' into 'main'

Setting up documents for publication of code

See merge request ineed-dc/ineed-dc-framework!5

.github/workflows/draft-pdf.yml

+on: [push]
+
+jobs:
+  paper:
+    runs-on: ubuntu-latest
+    name: Paper Draft
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+      - name: Open Journals PDF Generator
+        uses: openjournals/openjournals-draft-action@v.1.0
+        with:
+          journal: joss
+          # This should be the path to the paper within your repo.
+          paper-path: paper.md
+      - name: Upload
+        uses: actions/upload-artifact@v1
+        with:
+          name: paper
+          # This is the output path where Pandoc will write the compiled
+          # PDF. Note, this should be the same directory as the input
+          # paper.md
+          path: paper.pdf
\ No newline at end of file

publication/information about paper contents.txt

+https://joss.readthedocs.io/en/latest/submitting.html#what-should-my-paper-contain
\ No newline at end of file

publication/paper.bib

+@misc{demandlib,
+author={{Oemof Developing Group}},
+title={Demandlib Documentation},
+year={2016},
+howpublished={Read the Docs},
+url={https://demandlib.readthedocs.io},
+urldate={2021-03-14}
+}
+
+@article{Mavrotas.2009,
+ author = {Mavrotas, George},
+ year = {2009},
+ title = {Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems},
+ keywords = {GAMS;Multi-Objective Programming;ε-Constraint method},
+ pages = {455--465},
+ volume = {213},
+ number = {2},
+ issn = {00963003},
+ journal = {Applied Mathematics and Computation},
+ doi = {10.1016/j.amc.2009.03.037}
+}
+
+@article{pyomo,
+ author = {Hart, William E. and Watson, Jean-Paul and Woodruff, David L.},
+ year = {2011},
+ title = {Pyomo: modeling and solving mathematical programs in Python},
+ url = {https://www.researchgate.net/publication/229032361_Pyomo_Modeling_and_solving_mathematical_programs_in_Python},
+ pages = {219--260},
+ volume = {3},
+ number = {3},
+ issn = {1867-2949},
+ journal = {Mathematical Programming Computation},
+ doi = {10.1007/s12532-011-0026-8}
+}
+
+@article{Riffonneau.2011,
+ abstract = {This paper presents an optimal power management mechanism for grid connected photovoltaic (PV) systems with storage. The objective is to help intensive penetration of PV production into the grid by proposing peak shaving service at the lowest cost. The structure of a power supervisor based on an optimal predictive power scheduling algorithm is proposed. Optimization is performed using Dynamic Programming and is compared with a simple ruled-based management. The particularity of this study remains first in the consideration of batteries ageing into the optimization process and second in the ``day-ahead'' approach of power management. Simulations and real conditions application are carried out over one exemplary day. In simulation, it points out that peak shaving is realized with the minimal cost, but especially that power fluctuations on the grid are reduced which matches with the initial objective of helping PV penetration into the grid. In real conditions, efficiency of the predictive schedule depends on accuracy of the forecasts, which leads to future works about optimal reactive power management.},
+ author = {Riffonneau, Y. and Bacha, S. and Barruel, F. and Ploix, S.},
+ year = {2011},
+ title = {Optimal Power Flow Management for Grid Connected PV Systems With Batteries},
+ pages = {309--320},
+ volume = {2},
+ number = {3},
+ issn = {1949-3037},
+ journal = {IEEE Transactions on Sustainable Energy},
+ doi = {10.1109/TSTE.2011.2114901},
+ file = {9f117b4b-135b-4a25-85ee-ba01f26cc811:C\:\\Users\\Acer\\AppData\\Local\\Swiss Academic Software\\Citavi 6\\ProjectCache\\fdkc0101zwa7pqlcw8slfbvllf602j27ov4o7q0nqy\\Citavi Attachments\\9f117b4b-135b-4a25-85ee-ba01f26cc811.pdf:pdf}
+}
+
+@article{Sauer,
+  year = {1996},
+  month = aug,
+  publisher = {Deutsche Gesellschaft f\"ur Sonnenenergie e.V. - International Solar Energy Society - German Section},
+  volume = {21},
+  number = {4},
+  pages = {43-47},
+  author = {H. Schmidt and D. U. Sauer},
+  title = {Wechselrichter-Wirkungsgrade - Praxisgerechte Modellierung und Abschätzung},
+  journal = {Sonnenenergie},
+ issn = {01723278},
+url={https://www.dgs.de/fileadmin/sonnenenergie/SE-4-1996-ganz/Wechselrichter-Wirkungsgrade.PDF}
+}
\ No newline at end of file

publication/publication.md

+---
+title: 'FEN Framework: A Bottom-up Urban Energy Systems Modeling Framework'
+tags:
+  - Python
+  - energy
+  - optimization
+  - prosumer
+authors: # order pending
+  - name: Mauricio Celi Cortés
+    orcid: 0000-0002-2624-9598
+    equal-contrib: # do we need this?
+    corresponding: true
+    affiliation: "1, 2, 3, 6" #
+  - name: Jingyu Gong
+    orcid:
+    affiliation: "1, 2, 3, 6"
+  - name: Jonas van Ouwerkerk
+    orcid:
+    affiliation: "1, 2, 3, 6"
+  - name: Felix Wege
+    orcid:
+    affiliation: "4, 6"
+  - name: Yi Nie
+    orcid:
+    affiliation: "5, 6"
+  - name: Jonas Brucksch
+    orcid:
+    affiliation: "1, 2, 3, 6"
+affiliations:
+  - name: Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Campus-Boulevard 89, 52074 Aachen, Germany
+    index: 1
+  - name: Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustraße 10, 52074 Aachen, Germany
+    index: 2
+  - name: Jülich Aachen Research Alliance, JARA-Energy
+    index: 3
+  - name: Institute for Automation of Complex Power Systems, E.ON ERC, RWTH Aachen University, Mathieustraße 10, 52074 Aachen, Germany
+    index: 4
+  - name: Institute for Energy Efficient Buildings and Indoor Climate, E.ON ERC, RWTH Aachen University, Mathieustraße 10, 52074 Aachen, Germany
+    index: 5
+  - name: Research Campus Flexible Electrical Grids (FEN), RWTH Aachen University, Campus-Boulevard 79, 52074 Aachen, Germany
+    index: 6
+date: 4 August 2022
+bibliography: paper.bib
+---
+
+# Summary
+
+[The current idea is to do some light cleaning up of the code and libraries to push our project as open source by the end
+of August 2022. From there on, we will link this public repository in all our publications. Eventually the repository will be
+in a development state where we can submit it together with this paper to the Journal of Open Source Software (JOSS).
+For this we need full features, i.e Community (and maybe also City) fully functional, we need to trim out scripts we do not need (likely found in Tooling), 
+we need better documentation, we need to write tests for all scripts, we need an examples directory (instead of runme's everywhere). 
+Submodules GUI and Database will remain private and are not originally thought for submission although if properly 
+developed and publicly available (no accounts necessary!) they can be included. Submission to be made public will include 
+the InEEd-DC Framework repository and the Model_Library and Tooling submodules. Submission requirements: 
+https://joss.readthedocs.io/en/latest/submitting.html#the-review-process]
+
+[In theory City can be submitted as a separate JOSS publication since they also review significant contributions made to existing packages]
+
+FEN Framework [change name] is a software framework for the flexible and dynamic 
+formulation of optimization problems with a focus on multi energy sector coupling. 
+To broaden the view of multi energy systems, traditional energy carriers including alternating current, 
+natural gas, cooling and heat grids, are extended by energy carriers such as electrochemical storages, 
+direct current and hydrogen.
+
+The resulting optimization framework is implemented as three individual stages. At the first 
+stage individual prosumer models are created as interconnected compositions of technological 
+components from the energy sectors of interest. In addition to components that produce or 
+transform energy, such as photovoltaic panels, power electronic converters and heat pumps, the framework includes energy based models for 
+electrical, thermal as well as hydrogen storages. This variety of different storage technologies, 
+which allow long-term storage as well as flexible withdrawal, enables studies 
+of various use cases in the multi energy sector domain.
+
+The model building process of individual prosumers is is illustrated in Figure [Simplified workflow of the prosumer framework]. In order to 
+generate the mathematical optimization model, a Prosumer class is instantiated with 
+certain configuration inputs, such as the prosumer topology, a 
+set of time series including weather data and energy price information, as well as the 
+optimization strategy and additional regulatory settings. The Prosumer 
+then distributes the input data between the EMS class, representing an energy management 
+system, and the required Component classes which implement the required component models, 
+before orchestrating them to build the actual optimization model consisting of optimization 
+variables, constraints and one or more objective functions. Depending on the received inputs, 
+different types of optimization programs can be generated in this way. Two possible use cases 
+are the optimization of prosumer operation and the optimization of component sizes in the 
+context of an economic feasibility study. The framework’s ability to generate 
+multi-objective optimization problems, i.e. optimization problems with more than one 
+optimization goal, is especially useful in the second use case as it can provide decision 
+makers with a powerful tool to evaluate different criteria before deciding on specific 
+investment plans.
+[since the JOSS publication will include at least the community stage (not sure if city stage will be in the scope) maybe we should use the space to present the community briefly 
+instead of talking about the software structure in detail. A figure will be sufficient to illustrate the information flows]
+
+After creation, the optimization model is passed to one of many compatible solvers chosen by 
+the user, rendering results such as time series, optimal component sizes, investment plans and
+Pareto-Set approximations in the case of multi-objective optimization scenarios.
+
+As the structural approach of the framework allows to feed the results from any the stages 
+into the next higher one, the prosumer models can not only be used to perform independent 
+optimization studies on a prosumer level, but the results can also be used as the basic blocks 
+for the second stage. One of the main tasks when modeling city quarters is to establish 
+appropriate models for central supply and storage units such as converters, stationary batteries, 
+hydrogen storage, and large generation units. A further focus is on the distribution of the 
+generated or stored energy by means of DC power grids, as well as thermal and gas network, 
+in order to connect the individual prosumers as efficiently as possible. An optimization model 
+is being developed for optimal operations on the city-quarter-level with aims to use synergy 
+effects of the prosumers efficiently. [@jbr we have to talk a bit more about communities] The connections between city quarters forms interconnected 
+urban areas, which is the third stage of the three-stage optimization model. The power exchange 
+towards higher grid levels is investigated for networked urban areas with respect to DC power
+grid topologies as a possible alternative to gas grids and AC power grids. The optimization
+model targets on addressing the issue of providing energy and power reserves, taking into 
+account the balancing mechanisms among the city quarters. [as far as I know we haven't done anything about city yet(?) are there students working on this? could this be a topic for @jbr?]
+
+In parallel to the actual development of the underlying models, complexity reduction 
+techniques like temporal aggregation of the input time series are studied and integrated
+at the framework level continuously during the project timeline. This allows ensuring feasible 
+execution times for the optimization of large scale scenarios. [how far has this been implemented?]
+
+With that, the framework is a highly flexible modeling tool, capable of generating optimization 
+models dynamically enabling holistic studies of intelligent integration approaches of available 
+energy sectors and storage technologies within a single prosumer, a city quarter or a coupled 
+district. The combination of a modular topology configuration and the flexible 
+definition of an optimization strategy offers the possibility of modeling both technical 
+relationships and political regulations.
+
+[Cite literature where models are taken from, cite demandlib, cite pyomo, cite pareto optimization mavrotas]
+[expandable framework with new component models]
+# Statement of need
+
+Sustainable decarbonization of the energy sector may be achieved through the use of 
+novel technologies and approaches for an integrated coupling of available energy carriers, 
+the upgrade of energy conversion, and the involvement of individual prosumers. The arising 
+decentralized power system is complex, its operation is challenging, and the economic 
+efficiency of technologies depends on their interconnection and applications. This evokes 
+the need for special tools for holistic observations of this new energy system to support 
+business decisions, identify boundary conditions for urban planning, as well as discover 
+entirely new possiblities and approaches.
+[The need to flexibly model prosumers to model communities and cities]
+
+# Citations
+
+Citations to entries in paper.bib should be in
+[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html)
+format.
+
+If you want to cite a software repository URL (e.g. something on GitHub without a preferred
+citation) then you can do it with the example BibTeX entry below for @fidgit.
+
+For a quick reference, the following citation commands can be used:
+- `@author:2001`  ->  "Author et al. (2001)"
+- `[@author:2001]` -> "(Author et al., 2001)"
+- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)"
+
+# Figures
+
+Figures can be included like this:
+![Caption for example figure.\label{fig:example}](figures/3-Stufen-Framework.png){ width=20% }
+and referenced from text using \autoref{fig:example}.
+
+Figure sizes can be customized by adding an optional second parameter:
+![Caption for example figure.](figure.png){ width=20% }
+
+# Acknowledgements
+
+We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong
+Oh, and support from Kathryn Johnston during the genesis of this project.
+
+# References
\ No newline at end of file

runme.py

 """
 The FEN-Tool is an optimization tool for prosumer, district, and interconnected city models.
 
-Copyright (C) 2022. Mauricio Celi Cortés, Jingyu Gong, Jonas van Ouwerkerk, Felix Wege, Nie Yi, Jonas Brucksch
+Copyright (C) 2022. Mauricio Celi Cortés, Jingyu Gong, Jonas van Ouwerkerk, Felix Wege, Yi Nie, Jonas Brucksch
 
 This program is free software; you can redistribute it and/or
 modify it under the terms of the GNU Lesser General Public License