results from each scenario in a Jupytor Notebook

[gplssm]

#	Größe	Einheit	Plot/Tabelle	Kommentar	Done?
1	LCOE (Electricity, Heat)	divers	table	TODO #35	x
2	CO2 Emissionen	divers	table	1) absolute, 2) year X compared to SQ, 3) compared to 1990	1) x
3	Required Area	divers	Geoplots	absolute, relative	x
4	Autarky (balance)	%	Bar plot	rel suppy/demand,	x
5	Autarky (time)	hours, %	Bar plot	hours a month/year	x
6	energymix	MWh	Barplot, areaplot (+ table)	generatio per technology	x
7	CO2 emissions per technology (elec. + heat)	tCO2	stacked bar plot (elec/heat)	full year, 2 bars, technology stacked	x
8	rel use of flexibility options		bar plot / boxplots	Ausgespeicherte Energie (Speicher), Durchgelaufene Energie (DSM)
9	line loadings	%	bar plot	Ein Wert je Leitung
10	line loadings	%	box plot	Median, whisker(min/max), full year
11		%	Gridmap	(optional), Einfärbung nach Auslastung, pandapower
12	LCOE+LCOE	€/Mwh	stacked bar plot jeweils für LCOE und LCOH	Anteilig für je Technologie. Daten in results_scns[scn_id]['results_t']["LCOE"] zu finden	x

[nesnoj]

@nailend I've added some plotting functions in draw.py incl. plotting geodata, you may want to make use of parts...

[nesnoj]

@nailend Feel free to create a new branch from feature/#18-highlevel-results for your tasks, cf. #26

[nailend]

nr. 1:

• shall this be accumulated values or specific for every district?
• no costs for LCOE available yet... TODO
• rel CO2 emission to SQ: where do I get the SQ emissions from? isn't it a different scenario?
• total area required or for each technology? == highlevel-results

[nesnoj]

• shall this be accumulated values or specific for every district?

Aggregated values for ABW should be fine. Land use (Flächenbedarf) should be given per mun but this is part of #31. You may skip this for now.

• no costs for LCOE available yet... TODO

?

• rel CO2 emission to SQ: where do I get the SQ emissions from? isn't it a different scenario?

They result from the SQ analysis which should be done before. To allow for multiple scenarios, see #39.

• total area required or for each technology? == highlevel-results

Not sure what you mean here, I guess the land use again (see above, #31)

[nesnoj]

As we will update the table above successively, I added a column "Done?" to the table above to track your progress..

[nesnoj]

The params and numbers of abs.+rel. areas required by wind+pv will change when #57 is merged, the notebook need to be adjusted. I'll come back to you with some ideas+comments on what needs to be done @nailend .

[nesnoj]

Ok, some updates:

RES Landuse: 1 scenario

• geoplots: absolute available areas per mun and technology in ha (for pv_roof_small, pv_roof_large, pv_ground, wind)
• barplot: relative area use of pv_roof for entire region (highlevel) in %
  • total
  • small
  • large
• barplot: relative area use of pv_ground for entire region (highlevel) in %
  • All 7 'Area required rel. PV ground XXX'
• barplot: relative area use of wind for entire region (highlevel) in %
  • All 5 'Area required rel. wind XXX'

If the 3 barplots above fit smoothly into a single plot, go for it.

I saw that I didn't update the units dict in #57, I'll fix this.

RES Landuse: Scenario comparison (I'll add this to the list in #64)

Other Furthermore, I think it'd be good to have more general information on the scenario setting, e.g. visualization of the spatial mismatch between supply and demand, so 2 plots just prior to the reqd. areas

• installed RE capacity per mun and technology (geoplots for pv_roof, pv_ground, wind, bio, hydro, rest) similar to this one.
• cumulative demand per mun and sector (geoplots for res, rca, ind)

Does this make sense to you?