# Review of Steady-State Electric Power Distribution System Datasets

^{1}

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

^{2}

^{*}

## Abstract

**:**

## 1. Introduction

#### 1.1. Related Literature and State of the Art

`pandapower`[21], include grid datasets in the respective format.

#### 1.2. Contribution of the Paper and Structure

## 2. Available Grid Datasets

## 3. Compilation Process of Grid Datasets

#### 3.1. Intended Use Case

#### 3.2. Region

#### 3.3. Grid Compilation Methodology

#### 3.3.1. Introduction of Common Grid Compilation Methodologies

- (I)
- (II)

#### 3.3.2. Comparison of Methodologies

- (i)
- What is the intended use case of the dataset?
- (ii)
- Which data base can be provided for the compilation process?
- (iii)
- May data from selected grids be published or must the data be kept confidential?

#### 3.4. Methodic Origin of Data

## 4. Terminology to Characterize Distribution Grid Datasets

#### 4.1. Review of Grid Term Nomenclature in Literature

#### 4.1.1. Synthetic Grids

#### 4.1.2. Example and Test Grids

#### 4.1.3. Benchmark Grids

#### 4.1.4. Representative Grids

#### 4.1.5. Generic Grids

#### 4.1.6. Typical Grids

#### 4.1.7. Reference Grids

#### 4.2. Recommended Terminology

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 1.**Grid selecting illustration of grid generation methods based on experts decisions (

**left**), using urbanization class assumptions (

**center**), without predefined grid classification (

**right**).

**Table 1.**Overview of grid data properties and possible analyses types of publicly available, widely used distribution grids (

**top**) and four exemplary transmission grids (

**bottom**).

Grid Datasets ${}^{\mathbf{a}}$ | Year Published | Voltage Levels ${}^{\mathbf{b}}$ | Number of Buses | Switch Models | Dynamic Models | OPF Analysis ${}^{\mathbf{c}}$ | Reliability Analysis | State Estimation | Unbalanced Power Flow | Short Circuit Calculation | GIS Data | Time Series Data |
---|---|---|---|---|---|---|---|---|---|---|---|---|

ICPSs [24,25,26,27] | 1968, 1974, 1981, 1982 | N/A | 11, 13, 43 | - | - | - | - | - | - | - | - | - |

IEEE Case 30 [28] | 1974 | HV | 30 | - | - | ✓ | - | - | - | - | - | - |

Cinvalar’s System [29] | 1988 | MV | 14 | (✓) | - | - | - | - | - | - | - | - |

Baran’s System [30] | 1989 | MV | 33 | (✓) | - | - | - | - | - | - | - | - |

IEEE DTFs [23,31,32,33] | 1991, 2002, 2010 | MV | 4–123 | - ,✓ | - | T | - | - | ✓ | - | - | - |

Salama’s System [34] | 1993 | MV | 34 | - | - | (L) | - | - | - | - | - | - |

Su’s TDG [35] | 2005 | MV | 84 | (✓) | - | - | - | - | - | - | - | - |

IEEE NEV [23,36,37] | 2008 | MV | 21 ${}^{\mathrm{d}}$ | - | - | T, L | - | - | ✓ | ✓ | - | - |

CIGRE Systems [38] | 2009 | LV, MV, EHV | 13–44 | (✓) | ✓ | G, EN, T, (L)-L | - | - | (✓) | (✓) | - | (✓) |

IEEE 8500 NTF [23,39] | 2010 | LV, MV | 8500 ${}^{\mathrm{d}}$ | - | - | T, L | - | - | ✓ | - | ✓ | - |

Kerber Grids [40] | 2011 | LV | 10–386 | - | - | V, T, L | - | - | - | - | - | (✓) |

UKGDSs [41,42] | 2011 | MV, HV | 52–413 | - | - | ✓ | - | - | - | - | - | - |

ATLANTIDE [43,44,45] | 2012 | MV | 97–103 | (✓) | ✓ | ✓ | ✓ | - | - | - | - | - |

Dickert’s LVDNs [46] | 2013 | LV | 1–150 | - | - | L | - | - | - | - | - | - |

IEEE LVNTS [23,47] | 2014 | LV, MV | 342 ${}^{\mathrm{d}}$ | - | - | T, (L) | - | - | ✓ | - | - | - |

ELVTF [23,48] | 2015 | LV | 906 | - | - | T | - | - | ✓ | - | ✓ | ✓ |

EREDNs [49] | 2016 | LV, MV | 13–6921 | - | - | V, T, L | - | - | - | - | - ${}^{\mathrm{e}}$ | - |

SimBench [50] | 2019 | LV, MV, HV, EHV | 15–380 | ✓ | - | V, G, T, L | - | ✓ | - | - | (✓), ✓ | ✓ |

IEEE RTS [51] | 1979 | HV, EHV | 24 | - | - | C, G, T, L | ✓ | - | - | - | - | ✓ |

IEEE Case 9 [52] | 1980 | EHV | 9 | - | ✓ | G | - | - | - | - | - | - |

IEEJs [53] | 2000 | HV EHV | 236–933 47–115 | ✓ - | - ✓ | T, L G, (L) | ✓ - | - | - | - ✓ | - | - (✓) |

PEGASE Cases [54,55] | 2015 | HV, EHV | 89–13,659 | - | - | ✓ | - | - | - | - | - ${}^{\mathrm{e}}$ | - |

RTE Cases [54] | 2016 | MV-EHV | 1888–6515 | - | - | ✓ | - | - | - | - | - ${}^{\mathrm{e}}$ | - |

Grid Datasets | Intended Use Cases | Region ${}^{\mathbf{a}}$ | Information on Methodology | Methodic Origin of Data |
---|---|---|---|---|

ICPSs [24,25,26,27] | ill-conditioned sample systems for power flow methods | N/A | N/A | synthetic ${}^{\mathrm{a}}$ |

IEEE Case 30 [28] | test case for optimal load flow with steady-state security | N/A | adaption of existing test case | N/A |

Cinvalar’s System [29] | illustrating the problem of switch positioning for minimum distribution grid losses | North America | N/A | synthetic ${}^{\mathrm{a}}$ |

Baran’s System [30] | test system for loss reduction and load balancing via network reconfiguration | North America | N/A | N/A |

IEEE DTFs [23,31,32,33] | testing of new power flow solution methods for unbalanced systems | North America | N/A | N/A |

Salama’s System [34] | application example for the VAr control problem | North America | N/A | N/A |

Su’s TDG [35] | example grid for network reconfiguration | Taiwan | N/A | real |

IEEE NEV [23,36,37] | examining the voltage rise on the neutral conductor | North America | N/A | N/A |

CIGRE Systems [38] | benchmark system for issues of grid operation, planning, power quality, protection, stability | North America & Europe | use case driven approach based on experts decisions | derived from real grids |

IEEE 8500 NTF [23,39] | representative of full-size distribution system with suitable complexity | North America | N/A | derived from real grid |

Kerber Grids [40] | estimation of photovoltaic hosting capacity in low voltage grids | Germany | predefined classification method | synthetic |

UKGDSs [41,42] | representative distribution grids to test and evaluate new concepts | United Kingdom | N/A | N/A |

ATLANTIDE [43,44,45] | representative distribution grids to develop and simulate predictive scenarios | Italy | clustering method | real |

Dickert’s LVDNs [46] | low voltage benchmark grids representative of German feeders | Germany | principal component analysis and clustering method | synthetic |

IEEE LVNTS [23,47] | testing of solvers in highly meshed low voltage systems | North America | N/A | N/A |

ELVTF [23,48] | typical test feeders | Europe | N/A | N/A |

EREDNs [49] | large-scale distribution grids representative of European grids | Europe | greenfield reference network model | synthetic |

SimBench [12,50] | benchmark dataset with multiple voltage levels and data of time series and study cases to compare innovative solutions of multiple use cases based on power flow analysis | Germany | use case driven approach deriving grids from avail- able data with validating against real grids [62] | synthetic |

IEEE RTS [51] | test or compare methods for reliability analysis | North America | N/A | N/A |

IEEE Case 9 [52] | small test system for stability studies | North America | N/A | synthetic ${}^{\mathrm{a}}$ |

IEEJs [53] | testing of power supply restoration planning and reliability analysis algorithms bulk power systems for load flow and stability studies | Japan | N/A | N/A |

PEGASE Cases [54,55] | development of new tools for control and operational planning of the pan-European transmission network | France Europe | N/A N/A | derived from real grids synthetic |

RTE Cases [54] | validation of mathematical methods and tools | France | snapshots from SCADAs | real |

Term | Recommended Usage |
---|---|

Synthetic Grid | Grid that either do not model a real grid or that is not obtained by simplifying or modifying models of a real grid. |

Example and Test Grid | Grid that is simply created and used for basic testing, validation, or demonstration of only one issue. Transferring quantitative conclusions from this type of grid to conditions in real grids is doubtful. |

Benchmark Grid | Grid that is used to compare the efficiency or validity of algorithms. When using a benchmark grid, the object of investigation is the algorithm rather than the grid itself. |

Representative Grid | Grid that is created or selected to be considered instead of a number of grids. Since one grid can hardly be representative for all grids, there are usually multiple representative grids to cover different clusters of similar grids. |

Generic Grid | Grid with variable parameters that allow to synthesize different grids through parametrization. While representative grids use multiple grids with fixed parameters to represent different states of grids, generic grids cover multiple states through parameter variation of one grid. |

Typical Grid | Grid with common parameters. While representative grids intend to represent a wide range of possible grids, a typical grid claim solely to cover a common or normal grid type, so that outliers and extreme cases have little or no influence on a typical grid. |

Reference Grid | Grid that is optimal with regard to a specific criterion, such as cost-optimality. |

**Table 4.**Application of the recommended terminology to the well-known grids: well-suited terms (✓), partially fitting terms ( (✓) ), inappropriate terms (-), missing information (N/A).

Grids | Synthetic | Example/Test | Benchmark | Representative | Generic | Typical | Reference |
---|---|---|---|---|---|---|---|

ICPSs [24,25,26,27] | ${\u2713}^{\mathrm{a}}$ | ✓ | - | - | - | - | - |

IEEE Case 30 [28] | - | - | ✓ | - | - | - | - |

Cinvalar’s System [29] | ${\u2713}^{\mathrm{a}}$ | ✓ | - | - | - | - | - |

Baran’s System [30] | N/A | ✓ | - | - | - | - | - |

IEEE DTFs [23,31,32,33] | N/A | (✓) | ✓ | - | - | - | - |

Salama’s System [34] | N/A | ✓ | - | - | - | - | - |

Su’s TDG [35] | - | (✓) | ✓ | - | - | - | - |

IEEE NEV [23,36,37] | N/A | - | ✓ | - | - | - | - |

CIGRE Systems [38] | - | - | ✓ | - | - | (✓) | - |

IEEE 8500 NTF [23,39] | - | - | ✓ | - | - | - | - |

Kerber Grids [40] | - | ✓ | - | ✓ | - | - | |

UKGDSs [41,42] | N/A | - | ✓ | (✓) | - | - | - |

ATLANTIDE [43,44,45] | - | - | (✓) | ✓ | - | - | - |

Dickert’s LVDNs [46] | (✓) | - | ✓ | ✓ | (✓) | - | - |

IEEE LVNTS [23,47] | N/A | - | ✓ | - | - | - | - |

ELVTF [23,48] | N/A | - | ✓ | - | - | (✓) | - |

EREDNs [49] | ✓ | - | - | (✓) | - | (✓) | ✓ |

SimBench [50] | (✓) | - | ✓ | (✓) | - | - | - |

IEEE RTS [51] | N/A | - | ✓ | - | - | - | - |

IEEE Case 9 [52] | ${\u2713}^{\mathrm{a}}$ | ✓ | - | - | - | - | - |

IEEJs [53] | N/A | - | ✓ | - | - | - | - |

PEGASE Cases [54,55] | - | - | ✓ | - | - | - | - |

RTE Cases [54] | - | - | ✓ | - | - | - | - |

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**MDPI and ACS Style**

Meinecke, S.; Thurner, L.; Braun, M.
Review of Steady-State Electric Power Distribution System Datasets. *Energies* **2020**, *13*, 4826.
https://doi.org/10.3390/en13184826

**AMA Style**

Meinecke S, Thurner L, Braun M.
Review of Steady-State Electric Power Distribution System Datasets. *Energies*. 2020; 13(18):4826.
https://doi.org/10.3390/en13184826

**Chicago/Turabian Style**

Meinecke, Steffen, Leon Thurner, and Martin Braun.
2020. "Review of Steady-State Electric Power Distribution System Datasets" *Energies* 13, no. 18: 4826.
https://doi.org/10.3390/en13184826