# SimBench—A Benchmark Dataset of Electric Power Systems to Compare Innovative Solutions Based on Power Flow Analysis

^{1}

^{2}n), University Kassel, 34121 Kassel, Germany

^{2}

^{3}), TU Dortmund University, 44227 Dortmund, Germany

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

#### 1.1. Motivation

#### 1.2. Introducing SimBench

## 2. Methodology to Compile the SimBench Dataset

- a clear formulation of the objectives,
- a comprehensive view of the task and a literature review,
- a determination of use case requirements,
- an analysis of available data,
- the compilation of the grid dataset and
- the evaluation of the dataset.

#### 2.1. Voltage Level Dependent Methods to Generate the Grid Data

#### 2.1.1. Extra-High and High Voltage Level

#### 2.1.2. Medium Voltage Level

#### 2.1.3. Low Voltage Level

#### 2.2. Approach for Compiling Time Series

#### 2.2.1. Consumer Time Series

#### 2.2.2. Generation Time Series

#### 2.2.3. Storage Time Series

#### 2.2.4. Aggregated Grid Time Series

#### 2.2.5. Reactive Power Time Series

#### 2.3. Approach for Generating Future Scenarios

## 3. Overview of the SimBench Dataset

#### 3.1. Extra-High Voltage Grid

#### 3.2. High Voltage Grids

#### 3.3. Medium Voltage Grids

#### 3.4. Low Voltage Grids

- Transformers (${S}_{r}$): {160, 400, 630} $\mathrm{kVA}$
- Cables: NAYY 4 x {150, 240} ${\mathrm{mm}}^{2}$

#### 3.5. Load, Generation, Storage and Aggregated Grid Time Series

#### 3.6. Future Scenarios

## 4. Application Example of the SimBench Dataset

#### 4.1. Predefined Study Cases and Time Series

#### 4.2. Applied Algorithms and Grid Planning Use Case

- Implement a forecast scenario
- Power flow analysis
- Optimization of the transformer tap position
- Grid expansion
- Investment evaluation

- Generate new candidate solutions from the actual solution and (randomly) select one
- Evaluate an acceptance criterion, whether the new solution should replace the previous solution or be rejected

#### 4.3. Comparison of the Performance of the Applied Algorithms

^{2}), B2 does not require parallel lines. Usually, however, DSOs decide against the measures of B2 because of higher operational expenses of maintaining a second LV standard line type.

## 5. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

- Project SimBench—Simulation Data Base for a Consistent Comparison of Innovative Solutions in the Field of Grid Analysis, Grid Planning and Grid Operation Management. Available online: www.simbench.net/en (accessed on 5 July 2018).
- Christie, R.D. Power Systems Test Case Archive; University Of Washington: Washington, DC, USA, 1999; Available online: http://www2.ee.washington.edu/research/pstca/ (accessed on 20 June 2018).
- Schneider, K.P.; Mather, B.A.; Pal, B.C.; Ten, C.; Shirek, G.J.; Zhu, H.; Fuller, J.C.; Pereira, J.L.R.; Ochoa, L.F.; de Araujo, L.R.; et al. Analytic Considerations and Design Basis for the IEEE Distribution Test Feeders. IEEE Trans. Power Syst.
**2018**, 33, 3181–3188. [Google Scholar] [CrossRef] - Strunz, K.; Hatziargyriou, N.; Andrieu, C. Benchmark systems for network integration of renewable and distributed energy resources. Cigre Task Force C
**2009**, 6, 78. [Google Scholar] - Meinecke, S.; Thurner, L.; Braun, M. Review and Classification of Published Electric Steady-State Power Distribution System Models. 2020. Available online: https://arxiv.org/abs/2005.06167 (accessed on 14 May 2020).
- Bialek, J.; Ciapessoni, E.; Cirio, D.; Cotilla-Sanchez, E.; Dent, C.; Dobson, I.; Henneaux, P.; Hines, P.; Jardim, J.; Miller, S.; et al. Benchmarking and validation of cascading failure analysis tools. IEEE Trans. Power Syst.
**2016**, 31, 4887–4900. [Google Scholar] [CrossRef][Green Version] - Mateo, C.; Prettico, G.; Gómez, T.; Cossent, R.; Gangale, F.; Frías, P.; Fulli, G. European representative electricity distribution networks. Electr. Power Energy Syst.
**2018**, 99, 273–280. [Google Scholar] [CrossRef] - Pilo, F.; Pisano, G.; Scalari, S.; Canto, D.D.; Testa, A.; Langella, R.; Caldon, R.; Turri, R. ATLANTIDE—Digital archive of the Italian electric distribution reference networks. In Proceedings of the CIRED 2012 Workshop: Integration of Renewables into the Distribution Grid, Lisbon, Portugal, 29–30 May 2012; pp. 1–4. [Google Scholar] [CrossRef]
- Celli, G.; Pilo, F.; Pisano, G.; Soma, G.G. Reference scenarios for Active Distribution System according to ATLANTIDE project planning models. In Proceedings of the 2014 IEEE International Energy Conference (ENERGYCON), Cavtat, Croatia, 13–16 May 2014; IEEE: Piscataway, NJ, USA, 2014; pp. 1190–1196. [Google Scholar]
- Bracale, A.; Caldon, R.; Celli, G.; Coppo, M.; Dal Canto, D.; Langella, R.; Petretto, G.; Pilo, F.; Pisano, G.; Proto, D.; et al. Analysis of the Italian distribution system evolution through reference networks. In Proceedings of the 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), Berlin, Germany, 14–17 October 2012; IEEE: Piscataway, NJ, USA, 2012; pp. 1–8. [Google Scholar]
- Subcommittee, P.M. IEEE Reliability Test System. IEEE Trans. Power Appar. Syst.
**1979**, PAS-98, 2047–2054. [Google Scholar] [CrossRef] - Grigg, C.; Wong, P.; Albrecht, P.; Allan, R.; Bhavaraju, M.; Billinton, R.; Chen, Q.; Fong, C.; Haddad, S.; Kuruganty, S.; et al. The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee. IEEE Trans. Power Syst.
**1999**, 14, 1010–1020. [Google Scholar] [CrossRef] - Josz, C.; Fliscounakis, S.; Maeght, J.; Panciatici, P. AC Power Flow Data in MATPOWER and QCQP Format: iTesla, RTE Snapshots, and PEGASE. 2016. Available online: https://arxiv.org/abs/1603.01533 (accessed on 12 May 2020).
- Fliscounakis, S.; Panciatici, P.; Capitanescu, F.; Wehenkel, L. Contingency Ranking With Respect to Overloads in Very Large Power Systems Taking Into Account Uncertainty, Preventive, and Corrective Actions. IEEE Trans. Power Syst.
**2013**, 28, 4909–4917. [Google Scholar] [CrossRef][Green Version] - Marten, F.; Löwer, L.; Töbermann, J.C.; Braun, M. Optimizing the reactive power balance between a distribution and transmission grid through iteratively updated grid equivalents. In Proceedings of the Power Systems Computation Conference (PSCC), Wrocław, Poland, 18–22 August 2014; pp. 1–7. [Google Scholar]
- Schäfer, F.; Menke, J.H.; Marten, F.; Braun, M. Time Series Based Power System Planning Including Storage Systems and Curtailment Strategies. In Proceedings of the CIRED 2019 25th International Conference on Electricity Distribution, Madrid, Spain, 3–6 June 2019; AIM: Madrid, Spain, 2019. [Google Scholar]
- Schäfer, F.; Menke, J.H.; Braun, M. Comparison of Meta-Heuristics for the Planning of Meshed Power Systems. 2020. Available online: https://arxiv.org/abs/2002.03619 (accessed on 12 May 2020).
- Larscheid, P.; Klettke, A.; van Leeuwen, T.; Meinecke, S.; Moser, A. Einfluss der Modellierungsgenauigkeit des Höchstspannungsnetzes auf die Simulation von Hochspannungsnetzen [Impact of the Extra High Voltage Grid Modeling Accuracy on the Simulation of High Voltage Grids]. 15. Symposium Energieinnovation. 2018. Available online: https://www.tugraz.at/fileadmin/user_upload/Events/Eninnov2018/files/lf/Session_D4/541_LF_Klettke1.pdf (accessed on 24 May 2020).
- Liu, Z.; Wende-von Berg, S.; Banerjee, G.; Bornhorst, N.; Kerber, T.; Maurus, A.; Braun, M. Adaptives Statisches Netzäquivalent Mit künstlichen Neuronalen Netzen [Adaptive Static Network Equivalent with artificial Neuronal Networks]. 16. Symposium Energieinnovation. 2020. Available online: https://www.tugraz.at/events/eninnov2020/nachlese/download-beitraege/stream-d/#c279406 (accessed on 24 May 2020).
- Meinecke, S.; Bornhorst, N.; Braun, M. Power System Benchmark Generation Methodology. In Proceedings of the NEIS-Conference, Hamburg, Germany, 20 September 2018. [Google Scholar]
- Meinecke, S.; Drauz, S.; Klettke, A.; Sarajlic, D.; Sprey, J.; Spalthoff, C.; Kittl, C.; Braun, M.; Moser, A.; Rehtanz, C. SimBench Documentation—Electric Power System Benchmark Models; Technical Report EN-1.0.0; University of Kassel, Fraunhofer IEE, RWTH Aachen University, TU Dortmund University: Kassel, Germany, 2020. [Google Scholar]
- Thurner, L.; Scheidler, A.; Schäfer, F.; Menke, J.; Dollichon, J.; Meier, F.; Meinecke, S.; Braun, M. Pandapower—An Open-Source Python Tool for Convenient Modeling, Analysis, and Optimization of Electric Power Systems. IEEE Trans. Power Syst.
**2018**, 33, 6510–6521. [Google Scholar] [CrossRef][Green Version] - DIgSILENT GmbH. DIgSILENT PowerFactory. Version 2017. Available online: https://www.digsilent.de/en/news.html (accessed on 20 January 2020).
- FGH GmbH. INTEGRAL. Available online: https://www.fgh-ma.de/de/ueber-uns/fgh-organisation/fgh-gmbh (accessed on 20 January 2020).
- OpenStreetMap. About Openstreetmap—Openstreetmap Wiki. Available online: https://wiki.openstreetmap.org/wiki/Main_Page (accessed on 1 July 2018).
- Reiners, D. Flosm Powergrid. Available online: http://www.flosm.de/en/powergrid.html (accessed on 1 July 2018).
- Matke, C.; Medjroubi, W.; Kleinhans, D. SciGRID—An Open Source Reference Model for the European Transmission Network (v0.2). 2016. Available online: http://www.scigrid.de (accessed on 12 May 2018).
- Bundesnetzagentur. Marktstammdatenregister [Market Data Register]. Available online: https://www.marktstammdatenregister.de/MaStR/Einheit/Einheiten/OeffentlicheEinheitenuebersicht (accessed on 31 May 2019).
- DESTATIS—Statistisches Bundesamt [German Federal Statistical Office]. Available online: https://www.destatis.de/EN/Home/_node.html (accessed on 1 July 2018).
- Meinecke, S.; Klettke, A.; Sarajlic, D.; Dickert, J.; Hable, M.; Fischer, F.; Braun, M.; Moser, A.; Rehtanz, C. General Planning and Operational Principles in German Distribution Systems Used for SimBench. In Proceedings of the CIRED 25th International Conference on Electricity Distribution, Madrid, Spain, 3–6 June 2019. [Google Scholar]
- Klettke, A.; van Leeuwen, T.; Flörkemeier, S.; Moser, A. Generierung von Benchmark—Modellnetzen in der Hochspannungsebene auf Basis öffentlich verfügbarer Daten [Generation of high Voltage Benchmark Grids Based on Publicly Accessible Data]. 10. Internationale Energiewirtschaftstagung an der TU Wien. 2017. Available online: https://simbench.de/wp-content/uploads/2019/02/IEWT2017_lf_Klettke.pdf (accessed on 24 May 2020).
- Kittl, C.; Sarajlić, D.; Rehtanz, C. k-means based identification of common supply tasks for low voltage grids. In Proceedings of the 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Sarajevo, Bosnia and Herzegovina, 21–25 October 2018; pp. 1–5. [Google Scholar] [CrossRef]
- Kays, J.; Seack, A.; Smirek, T.; Westkamp, F.; Rehtanz, C. The Generation of Distribution Grid Models on the Basis of Public Available Data. IEEE Trans. Power Syst.
**2017**, 32, 2346–2353. [Google Scholar] [CrossRef] - Sarajlić, D.; Rehtanz, C. Low Voltage Benchmark Distribution Network Models Based on Publicly Available Data. In Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Bucharest, Romania, 29 September–2 October 2019; pp. 1–5. [Google Scholar] [CrossRef]
- Spalthoff, C.; Sarajlić, D.; Kittl, C.; Drauz, S.; Kneiske, T.; Rehtanz, C.; Braun, M. SimBench: Open source time series of power load, storage and generation for the simulation of electrical distribution grids. In Proceedings of the International ETG Congress, Esslingen, Germany, 28–29 November 2019. [Google Scholar]
- Tjaden, T.; Bergner, J.; Weniger, J.; Quaschning, V. Repräsentative elektrische Lastprofile für Wohngebäude in Deutschland auf 1-sekündiger Datenbasis [Representative Electrical Load Profiles for Residential Buildings in Germany Based on 1-Second Data]. 2015. Available online: https://doi.org/10.13140/RG.2.1.5112.0080 (accessed on 18 July 2018).
- Drauz, S. Synthesis of A Heat and Electrical Load Profile for Single and Multi-Family Houses Used for Subsequent Performance Tests of A Multi-Component Energy System. Master’s Thesis, RWTH Aachen University, Aachen, Germany, 2016. [Google Scholar]
- Follmer, R.; Gruschwitz, D.; Jesske, B.; Quandt, S.; Lenz, B.; Nobis, C.; Köhler, K.; Mehlin, M. Mobilität in Deutschland 2008 [Mobility in Germany]; Technical report; infas Institut für angewandte Sozialwissenschaft GmbH; Deutsches Zentrum für Luft- und Raumfahrt e.V: Cologne, Germany, 2010. [Google Scholar]
- Prior, J. Testverfahren zur Bestimmung des Elektrischen Verhaltens von Batteriesystemen in Elektrofahrzeugen [Test Method to Determine the Electric Behaviour of Battery Systems in Electric Vehicles]. Ph.D. Thesis, University Kassel, Kassel, Germany, 2017. [Google Scholar]
- Statista. Neuzulassungen von Elektroautos nach Marke/Modellreihe bis 2018 [New Registrations of Electric Vehicles by Brand/model Line Until 2018]. Available online: https://de.statista.com/statistik/daten/studie/224041/umfrage/neuzulassungen-von-elektroautos-nach-marke-modellreihe/ (accessed on 14 April 2020).
- Kays, J.; Rehtanz, C. Planning process for distribution grids based on flexibly generated time series considering RES, DSM and storages. IET Gener. Transm. Distrib.
**2016**, 10, 3405–3412. [Google Scholar] [CrossRef] - Kays, J.; Seack, A.; Häger, U. The potential of using generated time series in the distribution grid planning process. In Proceedings of the CIRED 23rd International Conference on Electricity Distribution, Lyon, France, 15–18 June 2015. [Google Scholar]
- ENTSO-E. Historical data (until December 2015)—Consumption Data: Hourly Load Values 2006–2015. 2015. Available online: https://www.entsoe.eu/data/data-portal/ (accessed on 8 August 2019).
- Fraunhofer IEE. Sektorübergreifende Einsatz- und Ausbauoptimiertung für die Analysen des Zukünftigen Energieversorgungssystems [Multi-Sectors Deployment and Expansion Optimization for the Analyses of the Future Energy Supply System]. Available online: https://www.iee.fraunhofer.de/content/dam/iee/energiesystemtechnik/de/Dokumente/Broschueren/2018_F_SCOPE_Einzelseiten.pdf (accessed on 17 April 2020).
- Scholz, Y. Renewable Energy Based Electricity Supply at Low Costs. Ph.D. Thesis, University Stuttgart, Stuttgart, Germany, 2012. [Google Scholar]
- Regionalversammlung Mittelhessen. Anhang 2—Steckbriefe der im Teilregionalplanentwurf Ausgewiesenen Vorranggebiete zur Nutzung der Windenergie (VRG WE) [Appendix 2 —Briefings of Priority Areas for the Use of Wind Energy (VRG WE) Identified in the Sub-Regional Plan Draft]; Technical Report; Regierungspräsidium Gießen, Dezernat 31: Gießen, Germany, 2012. [Google Scholar]
- van den Busch, U.; Gauler, A.; Müller, H.; Frings, K.; Petkova, G. Energiewende in Hessen—Monitoringbericht 2016 [Energy Transition in Hesse—Monitoring Report 2016]; Technical Report; Hessisches Ministerium für Wirtschaft, Energie, Verkehr und Landesentwicklung: Wiesbaden, Germany, 2016.
- Scheidler, A.; Bolgaryn, R.; Ulffers, J.; Dasenbrock, J.; Horst, D.; Gauglitz, P.; Pape, C.; Becker, H.; Braun, M. DER Integration study for the German state of hesse—Methodology and key results. In Proceedings of the CIRED 25th International Conference on Electricity Distribution, Madrid, Spain, 3–6 June 2019. [Google Scholar]
- Braun, M.; Krybus, I.; Becker, H.; Bolgaryn, R.; Dasenbrock, J.; Gauglitz, P.; Horst, D.; Pape, C.; Scheidler, A.; Ulffers, J. Veteilnetzstudie Hessen 2024-2034 [Der Integration Study for The German State of Hesse]; Technical Report; BearingPoint GmbH and Fraunhofer IEE: Frankfurt am Main, Germany, 2018. [Google Scholar]
- 50Hertz Transmission GmbH and Amprion GmbH and TenneT TSO GmbH and TransnetBW GmbH. In Netzentwicklungsplan Strom 2030, Version 2019 [Network Development Plan of Electricity 2030, Version 2019]; Technical Report; CB.e Clausecker | Bingel AG: Berlin, Germany, 2019.
- Zimmerman, R.D.; Murillo-Sánchez, C.E.; Thomas, R.J. MATPOWER: Steady-state operations, planning, and analysis tools for power systems research and education. IEEE Trans. Power Syst.
**2011**, 26, 12–19. [Google Scholar] [CrossRef][Green Version] - Bundesnetzagentur. Monitoringbericht 2017 [Monitoring Report 2017]. Available online: https://www.bundesnetzagentur.de/SharedDocs/Mediathek/Monitoringberichte/Monitoringbericht2017.pdf?_blob=publicationFile&v=4 (accessed on 14 April 2020).
- Wagner, C.; Kittl, C.; Kippelt, S.; Rehtanz, C. A Heuristic Process for an Automated Evaluation of Distribution Grid Expansion Planning Approaches. In Proceedings of the International ETG Congress, Bonn, Germany, 28–29 November 2017; pp. 1–6. [Google Scholar]
- Scheidler, A.; Thurner, L.; Braun, M. Heuristic optimisation for automated distribution system planning in network integration studies. IET Renew. Power Gener.
**2018**, 12, 530–538. [Google Scholar] [CrossRef][Green Version] - Thurner, L. Structural Optimizations in Strategic Medium Voltage Power System Planning. Ph.D. Thesis, University Kassel, Kassel, Germany, 2018. [Google Scholar]
- Klaus Faber AG. Technical Data—NAYY-J 01X400RM BK. Available online: https://shop.faberkabel.de/en/Power-cables-1-up-to-30-kV/Low-voltage-cables/Power-cable-NAYY-J-O/090225.html (accessed on 15 March 2020).
- Rehtanz, C.; Greve, M.; Häger, U.; Hagemann, Z.; Kippelt, S.; Kittl, C.; Kloubert, M.L.; Pohl, O.; Rewald, F.; Wagner, C. Verteilnetzstudie für das Land Baden-Württemberg; Technical Report; Ruhr GmbH: Dortmund, Germany, 2017. [Google Scholar]

**Figure 2.**Geographical distribution of generation (

**left**) and line loadings in a highly utilized state (

**right**) of the EHV grid.

**Figure 3.**Distribution of installed generation capacities and loads in the mixed (

**left**) and the urban (

**right**) HV grid.

**Figure 6.**Statistical comparison of parameters of real MV grids (boxplots) and SimBench MV grids; The horizontal axis are only introduced to avoid overlaps.

**Figure 8.**Overview of selected SimBench load and generation time series [35].

**Figure 9.**Heat map highlighting the line/transformer loadings and the under-/overvoltages of both future scearios of a rural LV grid: “1-LV-rural3--1-sw” in “lPV” study case (

**left**) and “1-LV-rural3--2-sw” in “hL” study case (

**right**).

**Figure 10.**Voltages and loadings of the “1-LV-semiurb4--2-sw” grid at the low load, high generation, extra-high PV generation (lPV,

**top**) and the high load, low generation (hL,

**bottom**) study cases.

Acro-nym | SimBench Code | Urbanization Characteristic | Rated Voltage [kV] | No. of Supply Points | Transformer Types | Generation Unit Types | Geo-References ${}^{\phantom{\rule{4.pt}{0ex}}1}$ |
---|---|---|---|---|---|---|---|

EHV1 | 1-EHV-mixed--0-sw | mixed | 380, 220 | 390 | 209 × 600 MVA | Nuclear, Coal, Gas | √ |

HV1 | 1-HV-mixed--0-sw | mixed | 110 | 58 | 2 × 300 MVA, 4 × 350 MVA | Wind | √ |

HV2 | 1-HV-urban--0-sw | urban | 110 | 79 | 3 × 300 MVA | Wind | √ |

MV1 | 1-MV-rural--0-sw | rural | 20 | 92 | 2 × 25 MVA | Wind, PV, BM, Hydro | (√) |

MV2 | 1-MV-semiurb--0-sw | semi-urban | 20 | 112 | 2 × 40 MVA | Wind, PV, BM, Hydro | (√) |

MV3 | 1-MV-urban--0-sw | urban | 10 | 134 | 2 × 63 MVA | Wind, PV, Hydro | (√) |

MV4 | 1-MV-comm--0-sw | commercial | 20 | 98 | 2 × 40 MVA | Wind, PV, BM, Hydro | (√) |

LV1 | 1-LV-rural1--0-sw | rural | 0.4 | 13 | 1 × 160 kVA | PV | (√) |

LV2 | 1-LV-rural2--0-sw | rural | 0.4 | 93 | 1 × 250 kVA | PV | (√) |

LV3 | 1-LV-rural3--0-sw | rural | 0.4 | 118 | 1 × 400 kVA | PV | (√) |

LV4 | 1-LV-semiurb4--0-sw | semi-urban | 0.4 | 39 | 1 × 400 kVA | PV | (√) |

LV5 | 1-LV-semiurb5--0-sw | semi-urban | 0.4 | 104 | 1 × 630 kVA | PV | (√) |

LV6 | 1-LV-urban6--0-sw | urban | 0.4 | 53 | 1 × 630 kVA | PV | (√) |

Available Measures | Measure Costs | A | B1 | B2 | B3 |
---|---|---|---|---|---|

Transformer reinforcement by 630 kVA | 12,000€ | √ | √ | √ | √ |

Transformer tap position change | 0€ | √ | √ | √ | √ |

Reinforce lines by 240 mm^{2} | 70,000€/km | √ | √ | √ | √ |

Reinforce lines by 400 mm^{2} ${}^{\phantom{\rule{0.277778em}{0ex}}\mathrm{a}}$ | 75,000€/km | √ | |||

Add parallel lines to 240 mm^{2} lines | 10,000€/km | √ | √ | √ | √ |

^{−1}, ${x}^{\prime}=0.086\mathsf{\Omega}/\mathrm{k}\mathrm{m}$

^{−1}, ${c}^{\prime}=840\mathrm{n}\mathrm{F}/\mathrm{k}\mathrm{m}$

^{−1}, ${i}_{\mathrm{max}}^{\prime}=78\mathrm{A}$ [56].

Measures of the (Best) Solution | A | B1 | B2 | B3 |
---|---|---|---|---|

Transformer reinforcement | √ | - | - | - |

Transformer tap position change | - | - | - | - ${}^{1}$ |

Reinforced lines by 240 mm^{2} | 5–32, 32–36 | 5–26, 5–32 | 5–26, 5–32 | 32–36, 36–37 |

36–37, 37–38 | 32–36, 36–37 | |||

Reinforced lines by 400 mm^{2} | - | - | 32–36, 36–37 | - |

Added parallel lines | 32–36, 36–37 | 32–36, 36–37 | - | |

Overall costs | 21,724€ | 8256€ | 7816€ | 6160€ |

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Meinecke, S.; Sarajlić, D.; Drauz, S.R.; Klettke, A.; Lauven, L.-P.; Rehtanz, C.; Moser, A.; Braun, M. SimBench—A Benchmark Dataset of Electric Power Systems to Compare Innovative Solutions Based on Power Flow Analysis. *Energies* **2020**, *13*, 3290.
https://doi.org/10.3390/en13123290

**AMA Style**

Meinecke S, Sarajlić D, Drauz SR, Klettke A, Lauven L-P, Rehtanz C, Moser A, Braun M. SimBench—A Benchmark Dataset of Electric Power Systems to Compare Innovative Solutions Based on Power Flow Analysis. *Energies*. 2020; 13(12):3290.
https://doi.org/10.3390/en13123290

**Chicago/Turabian Style**

Meinecke, Steffen, Džanan Sarajlić, Simon Ruben Drauz, Annika Klettke, Lars-Peter Lauven, Christian Rehtanz, Albert Moser, and Martin Braun. 2020. "SimBench—A Benchmark Dataset of Electric Power Systems to Compare Innovative Solutions Based on Power Flow Analysis" *Energies* 13, no. 12: 3290.
https://doi.org/10.3390/en13123290