Theoretical background ¶

eTraGo’s theoretical Background ¶

Learn more about eTraGo’s theoretical background of methods and assumptions here.

eDisGo’s theoretical Background ¶

Learn more about eDisGo’s theoretical background of methods and assumptions here.

To reduce computational complexity, eGo applies a k-means clustering algorithm to the MV grids. The algorithm selects a specified number of representative MV grids and assigns a weighting to each representative grid.

The available clustering attributes are determined by the get_cluster_attributes function and include:

PV capacity,
onshore wind capacity,
power-to-heat (PtH) capacity, and
maximum load from electric vehicles in the case of uncoordinated charging.

The attributes are available both as absolute values in MW and as area-specific values in MW/km². The function also provides expansion values relative to the status quo.

Economic calculation ¶

The tool eGo unites the extra high (ehv) and high voltage (hv) models with the medium (mv) and low voltage (lv) models to ascertain the costs per selected measure and scenario. This results in a cross-grid-level economic result of the electrical grid and storage optimization.

Overnight costs ¶

The overnight costs represents the investment costs of the components or construction project without any interest, as if the project was completed “overnight”. The overnight costs ( $C_{\text{Overnight}}$ ) of the grid measures (lines and transformers) are calculated as:

$C_{Line~extension} = S_{Extension}~[MVA] * C_{assumtion}~[\frac{EUR}{MVA}] * L_{Line~length}~[km]$

$C_{Transformer~extension} = S_{Extension}~[MVA] * C_{assumtion}~[\frac{EUR}{MVA}]$

The total overnight grid extension costs are given by:

$C_{overnight} = \sum C_{Line~extension} + \sum C_{Transformer~extension}$

The conversion of the given annuity costs of eTraGo is done in etrago_convert_overnight_cost().

Annuity costs ¶

The annuity costs represents project investment costs with an interest as present value of an annuity. The investment years T and the interest rate p are defined as default in eGo with an interest rate ( $p$ ) of 0.05 and a number of investment years ( $T$ ) of 40 years. The values are based on the [StromNEV_A1] for the grid investment regulation in Germany.

The present value of an annuity (PVA) is calculated as:

$PVA = \frac{1}{p}- \frac{1}{\left ( p*\left (1 + p \right )^T \right )}$

In order to calculate the $C_{annuity}$ of a given period less than a year the annuity costs are factorized by the hours of the $t_{year}=8760$ and the defined calculation period.

$t_{period} = t_{\text{end\_snapshot}} - t_{\text{start\_snapshot}} ~[h]$

The annuity costs ( $C_{annuity}$ ) is calculated as:

$C_{annuity} = C_{\text{overnight}} * PVA * \left ( \frac{t_{year}}{\left ( t_{\text{period}}+ 1 \right )} \right )$

Investment cost modeling ¶

Within the eGo workflow, investment costs are considered through the underlying optimization models. Investment decisions for transmission grid expansion, storage technologies and flexibility options are optimized at the eHV/HV level using eTraGo . The resulting expansion requirements are subsequently transferred to eDisGo , where the required expansion of the underlying MV/LV grids is determined. A detailed description of the optimization methodology is provided by [Buettner2025].

References ¶

[StromNEV_A1]

Stromnetzentgeltverordnung - StromNEV Anlage 1 (2018). Verordnung über die Entgelte für den Zugang zu Elektrizitätsversorgungsnetzen (Stromnetzentgeltverordnung - StromNEV) Anlage 1 (zu § 6 Abs. 5 Satz 1) Betriebsgewöhnliche Nutzungsdauern. (https://www.gesetze-im-internet.de/stromnev/anlage_1.html)

[Buettner2025] (1,2)

Büttner, C., Esterl, K., Schachler, B., and Cußmann, I. (2025). Challenges of top-down flexibility deployment for grid expansion across all voltage levels. Environmental Research: Energy, 2, 045017. (https://doi.org/10.1088/2753-3751/ae2686)

[Cussmann2024]

Cußmann, I., Schachler, B., Büttner, C., Tetens, H.-P., Esterl, K., Amme, J., Helfenbein, K., Held, M., Nadal, A., Günther, S., and Epia Realpe, C. A. (2024). Projektabschlussbericht: Ein offenes netzebenen- und sektorenübergreifendes Planungsinstrument zur Bestimmung des optimalen Einsatzes und Ausbaus von Flexibilitätsoptionen in Deutschland. Technical Report. (https://ego-n.org/papers/Endbericht_egon_v2.pdf)