nesnoj

## regions.csv

          
            region_id
            RegioStaR7
            bev_mini
            bev_medium
            bev_luxury
            phev_mini
            phev_medium
            phev_luxury

            
              71
              SR_Metro
              1690
              3844
              1235
              1047
              2382
              765

            
              72
              SR_Gross
              1750
              3676
              1045
              1084
              2278
              647

            
              73
              SR_Mitte
              3548
              7776
              2421
              2197
              4818
              1499

            
              74
              SR_Klein
              880
              1958
              574
              545
              1213
              355

            
              75
              LR_Zentr
              816
              1760
              511
              506
              1090
              317

            
              76
              LR_Mitte
              2050
              4625
              1331
              1269
              2866
              824

            
              77
              LR_Klein
              2250
              5230
              1487
              1394
              3241
              921

## edges.csv

          
            node1
            node2

            
              Source
              1

            
              2
              3

            
              1
              2

            
              3
              10

            
              10
              Target

            
              1
              4

            
              4
              5

            
              5
              Target

            
              1
              6

## write_db_table_comments_to_jsons.py
#
# Read all table comments from a database and write to json files
# * Tables without comment are skipped
# * Output format: <schema>.<table>.json
#

import json
import os
from sqlalchemy import create_engine, inspect, MetaData, Table

## dirtree.txt
./output/
├── constituency.gpkg
├── country.gpkg
├── district.gpkg
├── municipality.gpkg
├── state.gpkg
├── datapackage
│   └── datapackage.json
├── LOD
│   ├── 1

## meta_stemp_abw.json
{"id":25,"meta_data":{"name": "", "title": "Zeitreihen elektrisch Haushalte, GHD und Landwirtschaft", "review": {"path": "none", "badge": "none"}, "context": {"contact": "https://github.com/nesnoj", "grantNo": "03SFK4E1", "homepage": "https://reiner-lemoine-institut.de/kopernikus-projekt-enavi/", "sourceCode": "https://github.com/rl-institut/WAM_APP_stemp_abw", "documentation": "https://github.com/rl-institut/WAM_APP_stemp_abw"}, "sources": [{"path": "https://openenergy-platform.org/dataedit/view/demand/ego_dp_loadarea", "title": " eGo dataprocessing - Loadarea", "license": "Open Data Commons Open Database License 1.0 (ODbL-1.0) ", "copyright": "© Reiner Lemoine Institut", "description": "Below is the data that is contained in the table you selected. Only a limited amout of data is fetched at one time. You can browse different chuncks of data using the data view interface."}, {"path": "https://www.uni-flensburg.de/fileadmin/content/abteilungen/industrial/dokumente/downloads/veroeffentlichungen/forschungsergeb

## line_invest_min_example.py
# original example: https://github.com/oemof/oemof-examples/blob/master/oemof_examples/oemof.solph/v0.3.x/electrical/transshipment.py

import pandas as pd

# solph imports
from oemof.solph import (EnergySystem, Model, Bus, Flow, Source, Sink,
                         custom, Investment)
from oemof.outputlib import processing, views
from oemof.graph import create_nx_graph

## ashp_test_system.ipynb

      
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                nesnoj
                / ashp_test_system.ipynb
            
            
              Last active
              February 28, 2020 12:35
            
              
                Testing COPs of ASHP and GSHP using oemof thermal
              
          
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## powerplants2db.py
import pandas as pd
import geopandas as gpd
from geoalchemy2 import Geometry, WKTElement
from shapely import wkt
from sqlalchemy import create_engine
from sqlalchemy.types import BIGINT
import getpass
import logging

filename = 'reegis_pp_ABW.h5'

## feedin_test.py
import pandas as pd
from windpowerlib import ModelChain
from windpowerlib.wind_turbine import WindTurbine

weather_df = pd.read_csv('weather.csv', index_col=0, header=[0, 1])
# change type of index to datetime and set time zone
weather_df.index = pd.to_datetime(weather_df.index).tz_localize(
    'UTC').tz_convert('Europe/Berlin')
# change type of height from str to int by resetting columns
weather_df.columns = [weather_df.axes[1].levels[0][

## README.md

      
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                nesnoj
                / README.md
            
            
              Last active
              November 5, 2018 15:01
            
              
                Jupyter Notebook aus der DINGO-Session auf des open_eGo-Abschlussworkshops vom 30.10.18
              
          
    Jupyter Notebook aus der DINGO-Session des open_eGo-Abschlussworkshops vom 30.10.18
Siehe auch https://openegoproject.wordpress.com/ergebnisse/
region_id	RegioStaR7	bev_mini	bev_medium	bev_luxury	phev_mini	phev_medium	phev_luxury
71	SR_Metro	1690	3844	1235	1047	2382	765
72	SR_Gross	1750	3676	1045	1084	2278	647
73	SR_Mitte	3548	7776	2421	2197	4818	1499
74	SR_Klein	880	1958	574	545	1213	355
75	LR_Zentr	816	1760	511	506	1090	317
76	LR_Mitte	2050	4625	1331	1269	2866	824
77	LR_Klein	2250	5230	1487	1394	3241	921
	#
	# Read all table comments from a database and write to json files
	# * Tables without comment are skipped
	# * Output format: <schema>.<table>.json
	#

	import json
	import os
	from sqlalchemy import create_engine, inspect, MetaData, Table
	./output/
	├── constituency.gpkg
	├── country.gpkg
	├── district.gpkg
	├── municipality.gpkg
	├── state.gpkg
	├── datapackage
	│ └── datapackage.json
	├── LOD
	│ ├── 1
	# original example: https://github.com/oemof/oemof-examples/blob/master/oemof_examples/oemof.solph/v0.3.x/electrical/transshipment.py

	import pandas as pd

	# solph imports
	from oemof.solph import (EnergySystem, Model, Bus, Flow, Source, Sink,
	custom, Investment)
	from oemof.outputlib import processing, views
	from oemof.graph import create_nx_graph
	import pandas as pd
	import geopandas as gpd
	from geoalchemy2 import Geometry, WKTElement
	from shapely import wkt
	from sqlalchemy import create_engine
	from sqlalchemy.types import BIGINT
	import getpass
	import logging

	filename = 'reegis_pp_ABW.h5'
	import pandas as pd
	from windpowerlib import ModelChain
	from windpowerlib.wind_turbine import WindTurbine

	weather_df = pd.read_csv('weather.csv', index_col=0, header=[0, 1])
	# change type of index to datetime and set time zone
	weather_df.index = pd.to_datetime(weather_df.index).tz_localize(
	'UTC').tz_convert('Europe/Berlin')
	# change type of height from str to int by resetting columns
	weather_df.columns = [weather_df.axes[1].levels[0][