vpplib/test_pv.py at dev · Pyosch/vpplib · GitHub

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# -*- coding: utf-8 -*-
"""
Info
----
In this testfile the basic functionalities of the Photovoltaic class are tested.
Run each time you make changes on an existing function.
Adjust if a new function is added or
parameters in an existing function are changed.

"""

import matplotlib.pyplot as plt

from vpplib.environment import Environment
from vpplib.photovoltaic import Photovoltaic
import datetime # for Mosmix test

latitude = 50.933954264541924
longitude = 6.988538343769104
identifier = "Cologne"
timestamp_int = 48

"""
Read weather data from .csv file - Use this to avoid DWD API issues:

timestamp_str = "2015-11-09 12:00:00"
environment = Environment(start="2015-01-01 00:00:00", end="2015-12-31 23:45:00")
environment.get_pv_data(file="./input/pv/dwd_pv_data_2015.csv")
"""

"""
Using dwd observation (weather recording) database for weather data - Commented out due to wetterdienst breaking changes
use_timezone_aware_time_index has to be set to True because there is a timezone shift within the queried time period. Otherwise the dataframe's time index would be non monotonic.
"""
timestamp_now = datetime.datetime.now(datetime.timezone.utc)
# Round down to the last 15 minute value
minute = (timestamp_now.minute // 15) * 15
timestamp_now = timestamp_now.replace(minute=minute, second=0, microsecond=0)
timestamp_str = (timestamp_now + datetime.timedelta(days=-2)).strftime("%Y-%m-%d %H:%M:%S")
environment = Environment(
    start = (timestamp_now + datetime.timedelta(days=-5)).strftime("%Y-%m-%d %H:%M:%S"),
    end = (timestamp_now + datetime.timedelta(days=-1)).strftime("%Y-%m-%d %H:%M:%S"),
    use_timezone_aware_time_index = True,
    surpress_output_globally = False)
environment.get_dwd_pv_data(lat=latitude, lon=longitude)


"""MOSMIX
Using dwd mosmix (weather forecast) database for weather data.
The forecast is queried for the next 10 days automatically.
force_end_time is set to True to get a resulting dataframe from the start time
to the end time even if there is no forecast data for the last hours of the time
period --> Missing data is filled with NaN values.
"""
time_now = Environment().get_time_from_dwd()
mosmix_timestamp_str = str((time_now + datetime.timedelta(days = 5)).replace(minute = 0, second = 0))
mosmix_environment = Environment(
    start = time_now,
    end = time_now + datetime.timedelta(hours = 240),
    force_end_time = True,
    use_timezone_aware_time_index = True,
    surpress_output_globally = False)
mosmix_environment.get_dwd_pv_data(lat=latitude, lon=longitude, min_quality_per_parameter=10)

pv = Photovoltaic(
    unit="kW",
    latitude=latitude,
    longitude=longitude,
    identifier=identifier,
    environment=environment,
    module_lib="SandiaMod",
    module="Canadian_Solar_CS5P_220M___2009_",
    inverter_lib="cecinverter",
    inverter="ABB__MICRO_0_25_I_OUTD_US_208__208V_",
    surface_tilt=20,
    surface_azimuth=200,
    modules_per_string=2,
    strings_per_inverter=2,
    temp_lib='sapm',
    temp_model='open_rack_glass_glass'
)


def test_prepare_time_series(pv):

    pv.prepare_time_series()
    print("prepare_time_series:")
    print(pv.timeseries.head())
    pv.timeseries.plot(figsize=(16, 9))
    plt.show()


def test_value_for_timestamp(pv, timestamp):

    timestepvalue = pv.value_for_timestamp(timestamp)
    print("\nvalue_for_timestamp:\n", timestepvalue)


def observations_for_timestamp(pv, timestamp):

    print("observations_for_timestamp:")
    observation = pv.observations_for_timestamp(timestamp)
    print(observation, "\n")


test_prepare_time_series(pv)
test_value_for_timestamp(pv, timestamp_int)
test_value_for_timestamp(pv, timestamp_str)

observations_for_timestamp(pv, timestamp_int)
observations_for_timestamp(pv, timestamp_str)


# MOSMIX PV test
print("\n" + "="*60)
print("MOSMIX PV Test")
print("="*60)
mosmix_pv = Photovoltaic(
    unit="kW",
    latitude=latitude,
    longitude=longitude,
    identifier=identifier + "_mosmix",
    environment=mosmix_environment,
    module_lib="SandiaMod",
    module="Canadian_Solar_CS5P_220M___2009_",
    inverter_lib="cecinverter",
    inverter="ABB__MICRO_0_25_I_OUTD_US_208__208V_",
    surface_tilt=20,
    surface_azimuth=200,
    modules_per_string=2,
    strings_per_inverter=2,
    temp_lib='sapm',
    temp_model='open_rack_glass_glass'
)
test_prepare_time_series(mosmix_pv)
test_value_for_timestamp(mosmix_pv, 48)
observations_for_timestamp(mosmix_pv, 48)