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pypsa-eur/scripts/add_existing_baseyear.py

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Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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# coding: utf-8
import logging
logger = logging.getLogger(__name__)
import pandas as pd
idx = pd.IndexSlice
import numpy as np
import scipy as sp
import xarray as xr
import re, os
from six import iteritems, string_types
import pypsa
import yaml
import pytz
from vresutils.costdata import annuity
import prepare_cost function from prepare_sector_network
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from prepare_sector_network import prepare_costs
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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#First tell PyPSA that links can have multiple outputs by
#overriding the component_attrs. This can be done for
#as many buses as you need with format busi for i = 2,3,4,5,....
#See https://pypsa.org/doc/components.html#link-with-multiple-outputs-or-inputs
override_component_attrs = pypsa.descriptors.Dict({k : v.copy() for k,v in pypsa.components.component_attrs.items()})
override_component_attrs["Link"].loc["bus2"] = ["string",np.nan,np.nan,"2nd bus","Input (optional)"]
override_component_attrs["Link"].loc["bus3"] = ["string",np.nan,np.nan,"3rd bus","Input (optional)"]
override_component_attrs["Link"].loc["efficiency2"] = ["static or series","per unit",1.,"2nd bus efficiency","Input (optional)"]
override_component_attrs["Link"].loc["efficiency3"] = ["static or series","per unit",1.,"3rd bus efficiency","Input (optional)"]
override_component_attrs["Link"].loc["p2"] = ["series","MW",0.,"2nd bus output","Output"]
override_component_attrs["Link"].loc["p3"] = ["series","MW",0.,"3rd bus output","Output"]
Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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override_component_attrs["Link"].loc["build_year"] = ["integer","year",np.nan,"build year","Input (optional)"]
override_component_attrs["Link"].loc["lifetime"] = ["float","years",np.nan,"build year","Input (optional)"]
override_component_attrs["Generator"].loc["build_year"] = ["integer","year",np.nan,"build year","Input (optional)"]
override_component_attrs["Generator"].loc["lifetime"] = ["float","years",np.nan,"build year","Input (optional)"]
override_component_attrs["Store"].loc["build_year"] = ["integer","year",np.nan,"build year","Input (optional)"]
override_component_attrs["Store"].loc["lifetime"] = ["float","years",np.nan,"build year","Input (optional)"]
def add_power_capacities_installed_before_baseyear(n, grouping_years, costs):
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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"""
Parameters
----------
n : network
Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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grouping_years : intervals to group existing capacities
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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costs : to read lifetime to estimate YearDecomissioning
"""
print("adding power capacities installed before baseyear")
### add conventional capacities using 'powerplants.csv'
df_agg = pd.read_csv('../pypsa-eur/resources/powerplants.csv', index_col=0)
rename_fuel = {'Hard Coal':'coal',
'Lignite':'lignite',
'Nuclear':'nuclear',
'Oil':'oil',
'OCGT':'OCGT',
'CCGT':'CCGT',
'Natural Gas':'gas',}
fueltype_to_drop = ['Hydro',
'Wind',
'Solar',
'Geothermal',
'Bioenergy',
'Waste',
'Other',
'CCGT, Thermal']
technology_to_drop = ['Pv',
'Storage Technologies']
df_agg.drop(df_agg.index[df_agg.Fueltype.isin(fueltype_to_drop)],inplace=True)
df_agg.drop(df_agg.index[df_agg.Technology.isin(technology_to_drop)],inplace=True)
df_agg.Fueltype = df_agg.Fueltype.map(rename_fuel)
# add existing solar and wind capacities
# source: https://www.irena.org/Statistics/Download-Data
cc = pd.read_csv('data/Country_codes.csv', sep=',', index_col=-1)
name_to_2code = dict(zip(cc['Country'].tolist(),
cc['2 letter code (ISO-3166-2)'].tolist()))
for tech in ['solar', 'onwind', 'offwind']:
df = pd.read_csv('data/existing_infrastructure/{}_capacity_IRENA.csv'.format(tech),
sep=',', index_col=0)
df.rename(index={'Czechia':'Czech Republic',
'UK':'United Kingdom',
'Bosnia Herzg':'Bosnia Herzegovina',
'North Macedonia': 'Macedonia'}, inplace=True)
df.rename(index=lambda country : name_to_2code[country], inplace=True)
# calculate yearly differences
df.insert(loc=0, value=.0, column='1999')
df = df.diff(axis=1).drop('1999', axis=1)
df = df.clip(lower=0)
df.replace(to_replace=0.0, value=np.nan, inplace=True)
for year in df.columns:
for country in df.index:
if df.notnull().loc[country,year]:
df_agg = df_agg.append({'Fueltype':tech,
'Country':country,
'Capacity':df.loc[country,year],
'YearCommissioned':int(year),
'YearDecommissioning':int(float(year)+costs.at[tech, 'lifetime'])},
ignore_index=True)
Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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nodes=set([node[0:2] for node in n.buses.index[n.buses.carrier == "AC"]])
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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#TODO: Check if we want to change YearCommisioned into YearRetrofited
for i,grouping_year in enumerate(grouping_years):
if i==0:
index = df_agg.YearCommissioned < int(grouping_year)
else:
index = (int(grouping_years[i-1]) < df_agg.YearCommissioned) & (df_agg.YearCommissioned < int(grouping_year))
df = df_agg[index].pivot_table(index='Country', columns='Fueltype',
values='Capacity', aggfunc='sum')
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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for node in nodes:
#if a country has more than one node, selects the first one
bus_selected=[bus for bus in n.buses.index[n.buses.carrier == "AC"] if bus[0:2]==node][0]
for generator,carrier in [("OCGT","gas"),
("CCGT", "gas"),
("coal", "coal"),
("oil","oil"),
("nuclear","uranium")]:
try:
if node in df.index and not np.isnan(df.loc[node, generator]):
n.add("Link",
bus_selected + " " + generator +"-" + grouping_year,
bus0="EU " + carrier,
bus1=bus_selected,
bus2="co2 atmosphere",
marginal_cost=costs.at[generator,'efficiency']*costs.at[generator,'VOM'], #NB: VOM is per MWel
capital_cost=costs.at[generator,'efficiency']*costs.at[generator,'fixed'], #NB: fixed cost is per MWel
p_nom=df.loc[node, generator],
efficiency=costs.at[generator,'efficiency'],
efficiency2=costs.at[carrier,'CO2 intensity'],
build_year=int(grouping_year),
lifetime=costs.at[generator,'lifetime'])
except:
print("No capacity installed around " + grouping_year + " of " + generator + " in node " + node)
for generator in ['solar', 'onwind', 'offwind']:
try:
if not np.isnan(df.loc[node, generator]):
if generator =='offwind':
p_max_pu=n.generators_t.p_max_pu[bus_selected + ' offwind-ac']
else:
p_max_pu=n.generators_t.p_max_pu[bus_selected + ' ' + generator]
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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n.add("Generator",
bus_selected + ' ' + generator +"-"+ grouping_year,
bus=bus_selected,
carrier=generator,
p_nom=df.loc[node, generator],
marginal_cost=costs.at[generator,'VOM'],
capital_cost=costs.at[generator,'fixed'],
efficiency=costs.at[generator, 'efficiency'],
p_max_pu=p_max_pu,
build_year=int(grouping_year),
lifetime=costs.at[generator,'lifetime'])
except:
print("No capacity installed around " + grouping_year + " of " + generator + " in node " + node)
# delete generators if their lifetime is over and p_nom=0
n.mremove("Generator", [index for index in n.generators.index.to_list() if grouping_year in index and n.generators.p_nom[index] < snakemake.config['existing_capacities']['threshold_capacity']])
n.mremove("Link", [index for index in n.links.index.to_list() if grouping_year in index and n.links.p_nom[index] < snakemake.config['existing_capacities']['threshold_capacity']])
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years, ashp_cop, gshp_cop, time_dep_hp_cop, costs, default_lifetime):
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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"""
Parameters
----------
n : network
Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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baseyear: last year covered in the existing capacities database
grouping_years : intervals to group existing capacities
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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linear decomissioning of heating capacities from 2020 to 2045 is
currently assumed
heating capacities split between residential and services proportional
to heating load in both
50% capacities in rural busess 50% in urban buses
"""
print("adding heating capacities installed before baseyear")
# Add existing heating capacities, data comes from the study
# "Mapping and analyses of the current and future (2020 - 2030)
# heating/cooling fuel deployment (fossil/renewables) "
# https://ec.europa.eu/energy/studies/mapping-and-analyses-current-and-future-2020-2030-heatingcooling-fuel-deployment_en?redir=1
# file: "WP2_DataAnnex_1_BuildingTechs_ForPublication_201603.xls" -> "existing_heating_raw.csv".
# retrieve existing heating capacities
techs = ['gas boiler',
'oil boiler',
'resistive heater',
'air heat pump',
'ground heat pump']
df = pd.read_csv('data/existing_infrastructure/existing_heating_raw.csv',
index_col=0,
header=0)
# data for Albania, Montenegro and Macedonia not included in database
df.loc['Albania']=np.nan
df.loc['Montenegro']=np.nan
df.loc['Macedonia']=np.nan
df.fillna(0, inplace=True)
df *= 1e3 # GW to MW
cc = pd.read_csv('data/Country_codes.csv', sep=',', index_col=-1)
name_to_2code = dict(zip(cc['Country'].tolist(),
cc['2 letter code (ISO-3166-2)'].tolist()))
df.rename(index=lambda country : name_to_2code[country], inplace=True)
# coal and oil boilers are assimilated to oil boilers
df['oil boiler'] =df['oil boiler'] + df['coal boiler']
df.drop(['coal boiler'], axis=1, inplace=True)
# rename countries with network buses names
nodes_elec=[node for node in n.buses.index[n.buses.carrier == "AC"]]
name_to_busname={ index : [node for node in nodes_elec if index in node][0] for index in df.index}
df.rename(index=lambda country : name_to_busname[country], inplace=True)
# split existing capacities between residential and services
# proportional to energy demand
ratio_residential=pd.Series([(n.loads_t.p_set.sum()['{} residential rural heat'.format(node)] /
(n.loads_t.p_set.sum()['{} residential rural heat'.format(node)] +
n.loads_t.p_set.sum()['{} services rural heat'.format(node)] ))
for node in df.index], index=df.index)
for tech in techs:
df['residential ' + tech] = df[tech]*ratio_residential
df['services ' + tech] = df[tech]*(1-ratio_residential)
nodes={}
p_nom={}
for name in ["residential rural",
"services rural",
"residential urban decentral",
"services urban decentral",
"urban central"]:
name_type = "central" if name == "urban central" else "decentral"
nodes[name] = pd.Index([index[0:5] for index in n.buses.index[n.buses.index.str.contains(name) & n.buses.index.str.contains('heat')]])
heat_pump_type = "air" if "urban" in name else "ground"
heat_type= "residential" if "residential" in name else "services"
if name == "urban central":
p_nom[name]=df['air heat pump'][nodes[name]]
else:
p_nom[name] = df['{} {} heat pump'.format(heat_type, heat_pump_type)][nodes[name]]
# Add heat pumps
costs_name = "{} {}-sourced heat pump".format("decentral", heat_pump_type)
cop = {"air" : ashp_cop, "ground" : gshp_cop}
efficiency = cop[heat_pump_type][nodes[name]] if time_dep_hp_cop else costs.at[costs_name,'efficiency']
Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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for i,grouping_year in enumerate(grouping_years):
if int(grouping_year) + default_lifetime <= int(baseyear):
ratio=0
else:
#installation is assumed to be linear for the past 25 years (default lifetime)
ratio = (int(grouping_year)-int(grouping_years[i-1]))/default_lifetime
print(grouping_year + ' ratio ' + str(ratio))
n.madd("Link",
nodes[name],
suffix=" {} {} heat pump-{}".format(name,heat_pump_type, grouping_year),
bus0=nodes[name],
bus1=nodes[name] + " " + name + " heat",
carrier="{} {} heat pump".format(name,heat_pump_type),
efficiency=efficiency,
capital_cost=costs.at[costs_name,'efficiency']*costs.at[costs_name,'fixed'],
p_nom=p_nom[name]*ratio,
build_year=int(grouping_year),
lifetime=costs.at[costs_name,'lifetime'])
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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# add resistive heater, gas boilers and oil boilers
# (50% capacities to rural buses, 50% to urban buses)
n.madd("Link",
nodes[name],
suffix= " " + name + " resistive heater-{}".format(grouping_year),
bus0=nodes[name],
bus1=nodes[name] + " " + name + " heat",
carrier=name + " resistive heater",
efficiency=costs.at[name_type + ' resistive heater','efficiency'],
capital_cost=costs.at[name_type + ' resistive heater','efficiency']*costs.at[name_type + ' resistive heater','fixed'],
p_nom=0.5*df['{} resistive heater'.format(heat_type)][nodes[name]]*ratio,
build_year=int(grouping_year),
lifetime=costs.at[costs_name,'lifetime'])
n.madd("Link",
nodes[name],
suffix= " " + name + " gas boiler-{}".format(grouping_year),
bus0=["EU gas"]*len(nodes[name]),
bus1=nodes[name] + " " + name + " heat",
bus2="co2 atmosphere",
carrier=name + " gas boiler",
efficiency=costs.at[name_type + ' gas boiler','efficiency'],
efficiency2=costs.at['gas','CO2 intensity'],
capital_cost=costs.at[name_type + ' gas boiler','efficiency']*costs.at[name_type + ' gas boiler','fixed'],
p_nom=0.5*df['{} gas boiler'.format(heat_type)][nodes[name]]*ratio,
build_year=int(grouping_year),
lifetime=costs.at[name_type + ' gas boiler','lifetime'])
n.madd("Link",
nodes[name],
suffix=" " + name + " oil boiler-{}".format(grouping_year),
bus0=["EU oil"]*len(nodes[name]),
bus1=nodes[name] + " " + name + " heat",
bus2="co2 atmosphere",
carrier=name + " oil boiler",
efficiency=costs.at['decentral oil boiler','efficiency'],
efficiency2=costs.at['oil','CO2 intensity'],
capital_cost=costs.at['decentral oil boiler','efficiency']*costs.at['decentral oil boiler','fixed'],
p_nom=0.5*df['{} oil boiler'.format(heat_type)][nodes[name]]*ratio,
build_year=int(grouping_year),
lifetime=costs.at[name_type + ' gas boiler','lifetime'])
# delete links with p_nom=nan corresponding to extra nodes in country
n.mremove("Link", [index for index in n.links.index.to_list() if grouping_year in index and np.isnan(n.links.p_nom[index])])
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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# delete links if their lifetime is over and p_nom=0
n.mremove("Link", [index for index in n.links.index.to_list() if grouping_year in index and n.links.p_nom[index]<snakemake.config['existing_capacities']['threshold_capacity']])
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
2020-07-18 09:22:30 +00:00
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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if __name__ == "__main__":
# Detect running outside of snakemake and mock snakemake for testing
if 'snakemake' not in globals():
from vresutils.snakemake import MockSnakemake
snakemake = MockSnakemake(
wildcards=dict(network='elec', simpl='', clusters='37', lv='1.0',
Remove generators, stores and links whose installationYear + lifetime < year. Correct commented lines to YearDecomissioning > year
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sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
co2_budget_name='go',
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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planning_horizons='2020'),
Remove generators, stores and links whose installationYear + lifetime < year. Correct commented lines to YearDecomissioning > year
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input=dict(network='pypsa-eur-sec/results/test/prenetworks/{network}_s{simpl}_{clusters}_lv{lv}__{sector_opts}_{co2_budget_name}_{planning_horizons}.nc',
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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costs='pypsa-eur-sec/data/costs/costs_{planning_horizons}.csv',
cop_air_total="pypsa-eur-sec/resources/cop_air_total_{network}_s{simpl}_{clusters}.nc",
cop_soil_total="pypsa-eur-sec/resources/cop_soil_total_{network}_s{simpl}_{clusters}.nc"),
Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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output=['pypsa-eur-sec/results/test/prenetworks_brownfield/{network}_s{simpl}_{clusters}_lv{lv}__{sector_opts}_{planning_horizons}.nc'],
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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)
import yaml
with open('config.yaml') as f:
snakemake.config = yaml.load(f)
logging.basicConfig(level=snakemake.config['logging_level'])
options = snakemake.config["sector"]
opts = snakemake.wildcards.sector_opts.split('-')
baseyear= snakemake.config['scenario']["planning_horizons"][0]
n = pypsa.Network(snakemake.input.network,
override_component_attrs=override_component_attrs)
Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Nyears = n.snapshot_weightings.sum()/8760.
import prepare_cost function from prepare_sector_network
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costs = prepare_costs(snakemake.input.costs,
snakemake.config['costs']['USD2013_to_EUR2013'],
snakemake.config['costs']['discountrate'],
Nyears)
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
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grouping_years=snakemake.config['existing_capacities']['grouping_years']
add_power_capacities_installed_before_baseyear(n, grouping_years, costs)
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
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if "H" in opts:
time_dep_hp_cop = options["time_dep_hp_cop"]
ashp_cop = xr.open_dataarray(snakemake.input.cop_air_total).T.to_pandas().reindex(index=n.snapshots)
gshp_cop = xr.open_dataarray(snakemake.input.cop_soil_total).T.to_pandas().reindex(index=n.snapshots)
Remove generators, stores and links whose installationYear + lifetime < year. Correct commented lines to YearDecomissioning > year
2020-07-08 14:28:08 +00:00
default_lifetime = snakemake.config['costs']['lifetime']
Group the generators existing before base year into categories and add them to the network as e.g. solar-2005, solar-2010, solar-2015
2020-07-18 09:22:30 +00:00
add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years, ashp_cop, gshp_cop, time_dep_hp_cop, costs, default_lifetime)
Add scripts to (a) include existing power and heating capacities installed before the base year, and (b) add to year n, capacities optimized in year n-1. Existing onwind and offwind capacity are now read from IRENA database, similarly to solar capacities. Previously we were using thewindpower.net database which is not open.
2020-07-07 16:20:51 +00:00
n.export_to_netcdf(snakemake.output[0])
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