Transmission expansion calculation

[Felix Delgado Elizundia]

Hello! I hope you are well

I wanted to ask a quick question regarding the expansion of transmission lines and links. and particularly s_nom and s_nom_opt.

I have done the exercise as is shown in the tutorial, where to calculate the expansion of the lines you substract n.lines.s_nom_opt minus n.lines.s_nom. However this results in minimal differences (1e-13) and only in some cases and noticed that the sum of n.lines.s_nom_opt is the same as the sum n.lines.s_nom. Implying no real change

I wanted to understand, especially because while using the plotting function, I could see the some lines where expanded  heavily. 

I noticed that in the plot_network.py script s_nom_opt is plotted against s_nom_min. And indeed by checking, as seen in the image below, s_nom_min is lower than both s_nom_opt and s_nom.

In this sense I wanted to ask the following questions.

• How is it that s_nom_min can be lower than s_nom (in some cases 0) and the same as s_nom_opt? I understand that lines can only be expanded and that s_nom_min was set at the value of s_nom. Could the optimization be overwriting the s_nom value?
• To calculate line expansion during the optimization, should I use s_nom_min instead?

Would love to hear if you have any insights or clarity on my questions and thank you in advance. have a great evening!

[Fabian Neumann]

Hi Felix,

you're analysis is quite correct.

In PyPSA-Eur, you should take s_nom_opt - s_nom_min for the calculation
of line expansion.

The reason is that indeed s_nom gets new values when calling the
function n.ilopf(), which iteratively solves lopf while adjusting line
impedances to line expansion. This is intended.

Best wishes,

Fabian N

On 10.08.22 19:09, Felix Delgado Elizundia wrote:
> Hello! I hope you are well
>
> I wanted to ask a quick question regarding the expansion of transmission
> lines and links. and particularly s_nom and s_nom_opt.
>
> I have done the exercise as is shown in the tutorial, where to calculate

> the expansion of the lines you substract *n.lines.s_nom_opt* minus
> *n.lines.s_nom. *However this results in minimal differences (1e-13) and
> only in some cases and noticed that the sum of *n.lines.s_nom_opt* is
> the same as the sum *n.lines.s_nom. Implying no real change*

>
> I wanted to understand, especially because while using the plotting
> function, I could see the some lines where expanded  heavily.

> I noticed that in the plot_network.py script *s_nom_opt* is plotted
> against *s_nom_min*. And indeed by checking, as seen in the image below,
> *s_nom_min* is lower than both *s_nom_op*t and*s_nom.*

>
> In this sense I wanted to ask the following questions.
>

> * How is it that *s_nom_min* can be lower than *s_nom *(in some cases

> 0) and the same as s_nom_opt? I understand that lines can only be
> expanded and that s_nom_min was set at the value of s_nom. Could the
> optimization be overwriting the s_nom value?

> * To calculate line expansion during the optimization, should I use
> *s_nom_min* instead?

>
> Would love to hear if you have any insights or clarity on my questions
> and thank you in advance. have a great evening!
>
>

> Screenshot 2022-08-10 185714.png
>
> Screenshot 2022-08-10 190809.png
>
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--
Dr.-Ing.
Fabian Neumann (he/him)
Postdoctoral Researcher

Department of Digital Transformation in Energy Systems
Institute of Energy Technology
Technische Universität Berlin

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