def test_merge_asymmetric():
"""Test that merging nets properly handles bus IDs for asymmetric elements
"""
net1 = nw.ieee_european_lv_asymmetric()
net2 = nw.ieee_european_lv_asymmetric()
n_load_busses = len(net1.asymmetric_load.bus.unique())
n_sgen_busses = len(net1.asymmetric_sgen.bus.unique())
net3 = pp.merge_nets(net1, net2)
assert len(net3.asymmetric_load.bus.unique()) == 2 * n_load_busses
assert len(net3.asymmetric_sgen.bus.unique()) == 2 * n_sgen_busses
def simulate_network(scenario, installations_percent, cooperation_percent,
installation_buses, cooperating_buses, individual_buses):
scenario_name = get_scenario_name(scenario)
full_dir_path = "data/results/{}/03-simulation/{}_installations/{}_cooperative".format(
scenario_name, installations_percent, cooperation_percent)
if os.path.exists(full_dir_path) and SKIP_EXISTING:
if PRINT_SKIPPING_LINES:
print("[{}] [{}%] [{}%] Simulating network... [skipping]".format(
scenario_name, installations_percent, cooperation_percent))
return False
print("[{}] [{}%] [{}%] Simulating network...".format(
scenario_name, installations_percent, cooperation_percent))
net = ieee_european_lv_asymmetric('on_peak_566')
for index, _ in net.asymmetric_load.iterrows():
net.asymmetric_load.in_service.at[index] = False
pandapower.runpp(net)
for original_index, row in buses.iterrows():
load_index = pandapower.create_load(net, bus=row.bus, p_mw=0)
load_profile_raw = pandas.read_csv(
"data/source/load_profiles/Load_profile_{}.csv".format(
original_index + 1),
sep=",",
decimal=".")
load_profile_raw['mult'] = load_profile_raw['mult'].apply(
convertkWToMW).iloc[::10].reset_index(drop=True)
load_profile = frame_data.DFData(pandas.DataFrame(load_profile_raw))
load_controller = ConstControl(net,
element='load',
element_index=load_index,
variable='p_mw',
data_source=load_profile,
profile_name='mult',
recycle=False)
for original_index, row in installation_buses.iterrows():
if scenario.get('EV') == True:
ev_index = pandapower.create_load(net, bus=row.bus, p_mw=0)
ev_profile_raw = pandas.read_csv(
"data/source/ev_profiles/EV_home_profiles_{}.csv".format(
original_index + 1),
sep=";",
decimal=",")
ev_profile_raw['load'] = ev_profile_raw['load'].apply(
convert10minkWhTokW).apply(convertkWToMW)
ev_profile = frame_data.DFData(pandas.DataFrame(ev_profile_raw))
ev_controller = ConstControl(net,
element='load',
element_index=ev_index,
variable='p_mw',
data_source=ev_profile,
profile_name='load',
recycle=False)
if scenario.get('PV') == True:
sgen_index = pandapower.create_sgen(net,
bus=row.bus,
p_mw=0,
sn_mva=0,
type='PV')
pv_profile_raw = pandas.read_csv("data/source/PVProfile1440.csv",
sep=";",
decimal=".")
pv_profile_raw['pv_output_power_kw'] = pv_profile_raw[
'pv_output_power_kw'].apply(
convertkWToMW).iloc[::10].reset_index(drop=True)
pv_profile = frame_data.DFData(pandas.DataFrame(pv_profile_raw))
sgen_controller = ConstControl(net,
element='sgen',
element_index=sgen_index,
variable='p_mw',
data_source=pv_profile,
profile_name='pv_output_power_kw',
recycle=False)
for original_index, row in cooperating_buses.iterrows():
storage_index = pandapower.create_storage(
net,
bus=row.bus,
p_mw=0,
max_e_mwh=BATTERY_ENERGY_MAX / 1000.0,
soc_percent=(INITIAL_BATTERY_CHARGE / BATTERY_ENERGY_MAX) * 100.0,
max_p_mw=RATED_P / 1000.0,
min_p_mw=-RATED_P / 1000.0)
storage_profile_raw = pandas.read_csv(
"data/results/{}/02-collective/{}_installations/{}_cooperation/Storage_profile_{}.csv"
.format(scenario_name, installations_percent, cooperation_percent,
original_index + 1),
sep=",",
decimal=".")
storage_profile_raw['power_kW'] = storage_profile_raw[
'power_kW'].apply(convertkWToMW).apply(convertStorage)
storage_profile = frame_data.DFData(
pandas.DataFrame(storage_profile_raw))
storage_controller = ConstControl(net,
element='storage',
element_index=storage_index,
variable='p_mw',
data_source=storage_profile,
profile_name='power_kW',
recycle=False)
for original_index, row in individual_buses.iterrows():
storage_index = pandapower.create_storage(
net,
bus=row.bus,
p_mw=0,
max_e_mwh=BATTERY_ENERGY_MAX / 1000.0,
soc_percent=(INITIAL_BATTERY_CHARGE / BATTERY_ENERGY_MAX) * 100.0,
max_p_mw=RATED_P / 1000.0,
min_p_mw=-RATED_P / 1000.0)
storage_profile_raw = pandas.read_csv(
"data/results/{}/01-individual/storage-profiles/Storage_profile_{}.csv"
.format(scenario_name, original_index + 1),
sep=",",
decimal=".")
storage_profile_raw['power_kW'] = storage_profile_raw[
'power_kW'].apply(convertkWToMW).apply(convertStorage)
storage_profile = frame_data.DFData(
pandas.DataFrame(storage_profile_raw))
storage_controller = ConstControl(net,
element='storage',
element_index=storage_index,
variable='p_mw',
data_source=storage_profile,
profile_name='power_kW',
recycle=False)
time_steps = range(0, T)
ow = OutputWriter(net,
output_path=full_dir_path,
output_file_type=".csv",
log_variables=[])
ow.log_variable("load", "p_mw")
ow.log_variable("res_bus", "vm_pu", index=buses_nodes)
ow.log_variable("res_line", "p_to_mw", index=line_nodes)
ow.log_variable("res_trafo", "vm_lv_pu")
ow.log_variable("res_trafo", "p_lv_mw")
if scenario.get('PV') == True:
ow.log_variable("sgen", "p_mw")
if cooperating_buses.size > 0 or individual_buses.size > 0:
ow.log_variable("storage", "p_mw")
run_timeseries(net, time_steps, continue_on_divergence=True, verbose=False)
return True
# SKIP_EXISTING = False
# PRINT_SKIPPING_LINES = False
# DER_INSTALLATIONS_PERCENT_STEP = 50
# DER_COOPERATION_PERCENT_STEP = 50
# BUS_LIMIT = 5
T = 144
INTERVAL_LENGTH = 1.0 / 6.0 # hours (1/6 hour = 10 minutes)
BATTERY_ENERGY_MAX = 7.7 # kWh
RATED_P = 3.0 # kW
INITIAL_BATTERY_CHARGE = 3.85 # kWh
CHARGE_EFFICIENCY = 0.92
DISCHARGE_EFFICIENCY = 0.92
net_structure = ieee_european_lv_asymmetric('on_peak_566')
buses = pandas.read_csv('data/source/buses.csv', sep=";",
decimal=',')[:BUS_LIMIT]
buses_nodes = buses['bus'].tolist()
line_nodes = []
print("Obtaining line indices...")
for _, bus in buses.iterrows():
for line_index, line in net_structure.line.iterrows():
if bus.bus == line.to_bus:
line_nodes.append(line_index)
import pandas as pd
import pandapower as pp
import pandapower.timeseries.data_sources.frame_data as fd
from pandapower.control import ConstControl
from pandapower.networks import ieee_european_lv_asymmetric
from pandapower.timeseries.run_time_series import run_timeseries
from pandapower.timeseries import OutputWriter
import matplotlib.pyplot as plt
import pandapower.control.basic_controller as basic_controller
import numpy
# initialize a network
net = ieee_european_lv_asymmetric('on_peak_566')
# turn off asymmetric loads
for index, _ in net.asymmetric_load.iterrows():
net.asymmetric_load.in_service.at[index] = False
# power flow run
pp.runpp(net)
# load consumer bus indices
consumer_bus_indices = pd.read_csv('buses.csv', sep=";")
# function of kW to MW convertation