def test_urdb_2():
urdb = str(Path(__file__).parent / "urdbv7.json")
with open(urdb, 'r') as file:
urdb_data = json.load(file)
urdb_data.pop("flatdemandmonths")
ur5 = tools.URDBv7_to_ElectricityRates(urdb_data)
ec_tou = [
1, 1, 100, 0, 0.070768997073173523, 0, 1, 2, 9.9999996802856925e+37, 0,
0.082948997616767883, 0, 2, 1, 100, 0, 0.056908998638391495, 0, 2, 2,
9.9999996802856925e+37, 0, 0.069078996777534485, 0
]
dc_tou = [
1, 1, 100, 19.538999557495117, 1, 2, 9.9999996802856925e+37,
13.093000411987305, 2, 1, 100, 8.0909996032714844, 2, 2,
9.9999996802856925e+37, 4.6760001182556152
]
ec_tou_tested = [
item for sublist in ur5['ur_ec_tou_mat'] for item in sublist
]
dc_tou_tested = [
item for sublist in ur5['ur_dc_tou_mat'] for item in sublist
]
assert (ec_tou_tested == ec_tou)
assert (dc_tou_tested == dc_tou)
def test_solar():
solar = str(
Path(__file__).parent /
"blythe_ca_33.617773_-114.588261_psmv3_60_tmy.csv")
data = tools.TMY_CSV_to_solar_data(solar)
assert (data['lat'] == 33.61)
assert (data['lon'] == -114.58)
assert (data['dn'][7] == 262)
assert (data['df'][7] == 16)
assert (data['gh'][7] == 27)
assert (data['tdry'][7] == pytest.approx(8.96, 0.1))
def test_wind():
wind = str(Path(__file__).parent / "AR Northwestern-Flat Lands.srw")
data = tools.SRW_to_wind_data(wind)
assert (data['fields'] == [1, 2, 4, 3, 1, 2, 4, 3, 1, 2, 4, 3, 1, 2, 4, 3])
assert (data['heights'] == [
50, 50, 50, 50, 80, 80, 80, 80, 110, 110, 110, 110, 140, 140, 140, 140
])
assert (data['data'][0] == [
9.587, 0.953420183, 173, 9.466, 10.247, 0.950086356, 174, 11.637,
10.627, 0.946649889, 175, 13.249, 10.997, 0.94340982, 175, 14.509
])
wind_model = wp.new()
wind_model.Resource.wind_resource_data = data
returned_data = wind_model.Resource.wind_resource_data['data'][0]
for i, d in enumerate(data['data'][0]):
assert (d == pytest.approx(returned_data[i], 1e-3))
def test_solar():
solar = str(
Path(__file__).parent /
"blythe_ca_33.617773_-114.588261_psmv3_60_tmy.csv")
data = tools.SAM_CSV_to_solar_data(solar)
assert (data['lat'] == 33.61)
assert (data['lon'] == -114.58)
assert (data['dn'][7] == 262)
assert (data['df'][7] == 16)
assert (data['gh'][7] == 27)
assert (data['tdry'][7] == pytest.approx(8.96, 0.1))
model = pv.default("PVwattsNone")
model.SolarResource.solar_resource_data = data
model.execute()
aep = model.Outputs.annual_energy
model.SolarResource.solar_resource_file = solar
model.execute()
assert (aep == pytest.approx(model.Outputs.annual_energy, 1))
Note
----
Please register for NREL_API_KEY at https://developer.nrel.gov/signup/, it's free.
@author: skoeb
"""
import PySAM.ResourceTools as tools
import PySAM.Windpower as wp
import PySAM.Singleowner as so
# --- Initialize Wind Fetcher ---
wtkfetcher = tools.FetchResourceFiles(
tech='wind',
workers=1, #thread workers if fetching multiple files
nrel_api_key=<NREL_API_KEY>,
nrel_api_email=<NREL_API_EMAIL>)
# --- Pass a list of (lon, lat) tuples or Shapely points to fetch the nearest resource data ---
lon_lats = [(-105.1800775, 39.7383155)] # golden CO
wtkfetcher.fetch(lon_lats)
# --- Get resource data file path ---
wtk_path_dict = wtkfetcher.resource_file_paths_dict
wtk_fp = wtk_path_dict[lon_lats[0]]
# --- Initialize Generator ---
generator = wp.default('WindPowerSingleOwner')
generator.Resource.assign({'wind_resource_model_choice': 0})
generator.Resource.assign({'wind_resource_filename': wtk_fp}) #pass path to resource file
def test_resourcefilefetcher():
# please get your own API key from here https://developer.nrel.gov/signup/
NREL_API_KEY = 'HIiOQJN8C4dcWoJ5cxJ6Cl9LdEOQeo7c2bL67WqA'
NREL_API_EMAIL = '*****@*****.**'
lon_lats = [(-105.1800775, 39.7383155)] # golden CO
resource_dir = str(Path(__file__).parent / "tmp")
# --- fetch solar tmy file from psm3-tmy using default parameters ---
solarfetcher = tools.FetchResourceFiles(tech='solar',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir)
solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
solar_path_dict = solarfetcher.resource_file_paths_dict
solar_fp = solar_path_dict[lon_lats[0]]
solar_csv = pd.read_csv(solar_fp)
num_timesteps = 8760
assert solar_csv.shape[0] == num_timesteps + 2
# --- test legacy 'pv' instead of 'solar'---
solarfetcher = tools.FetchResourceFiles(tech='pv',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir)
solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
solar_path_dict = solarfetcher.resource_file_paths_dict
solar_fp = solar_path_dict[lon_lats[0]]
solar_csv = pd.read_csv(solar_fp)
num_timesteps = 8760
assert solar_csv.shape[0] == num_timesteps + 2
# --- fetch solar single-year 30-min file from psm3 ---
solarfetcher = tools.FetchResourceFiles(tech='solar',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir,
resource_type='psm3',
resource_year='2018',
resource_interval_min=30)
solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
solar_path_dict = solarfetcher.resource_file_paths_dict
solar_fp = solar_path_dict[lon_lats[0]]
solar_csv = pd.read_csv(solar_fp)
num_timesteps = 17520
assert solar_csv.shape[0] == num_timesteps + 2
# --- fetch solar tgy for 2018 from psm3-tmy ---
solarfetcher = tools.FetchResourceFiles(tech='solar',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir,
resource_type='psm3-tmy',
resource_year='tgy-2018')
solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
solar_path_dict = solarfetcher.resource_file_paths_dict
solar_fp = solar_path_dict[lon_lats[0]]
solar_csv = pd.read_csv(solar_fp)
num_timesteps = 8760
assert solar_csv.shape[0] == num_timesteps + 2
# --- fetch 5-minute data for 2018 from psm3-5min ---
# this NSRDB API endpoint not working properly as of 8/21/2020
#solarfetcher = tools.FetchResourceFiles(
# tech='solar',
# nrel_api_key=NREL_API_KEY,
# nrel_api_email=NREL_API_EMAIL,
# resource_dir=resource_dir,
# resource_type='psm3-5min',
# resource_interval_min=5,
# resource_year='2018')
#solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
#solar_path_dict = solarfetcher.resource_file_paths_dict
#solar_fp = solar_path_dict[lon_lats[0]]
#solar_csv = pd.read_csv(solar_fp)
#num_timesteps = 175200
#assert solar_csv.shape[0] == num_timesteps+2
# --- fetch wind ---
wtkfetcher = tools.FetchResourceFiles(tech='wind',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir)
wtkfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
wtk_path_dict = wtkfetcher.resource_file_paths_dict
wtk_fp = wtk_path_dict[lon_lats[0]]
wtk_csv = pd.read_csv(wtk_fp)
assert wtk_csv.shape == (8764, 10)
shutil.rmtree(resource_dir)
geocode = False
if geocode:
# See https://geocoder.readthedocs.io/ for different geocoding services
g = geocoder.bing('golden, co', key=geocode_api_key)
lon = g.latlng[1]
lat = g.latlng[0]
else:
lon = -105.22
lat = 39.75
# --- Wind Example ---
# --- Initialize Wind Resource Fetcher using minimum parameters---
# See function documentation for full parameter list
wtkfetcher = tools.FetchResourceFiles(tech='wind',
nrel_api_key=sam_api_key,
nrel_api_email=sam_email)
# --- List of (lon, lat) tuples or Shapely points ---
lon_lats = [(lon, lat)]
wtkfetcher.fetch(lon_lats)
# --- Get resource data file path ---
wtk_path_dict = wtkfetcher.resource_file_paths_dict
wtk_fp = wtk_path_dict[lon_lats[0]]
# --- Initialize generator ---
if wtk_fp is not None:
generator = wp.default('WindPowerSingleOwner')
generator.Resource.assign({'wind_resource_model_choice': 0})
generator.Resource.assign({'wind_resource_filename': wtk_fp})
def test_resourcefilefetcher():
load_dotenv()
# please get your own API key from here https://developer.nrel.gov/signup/
NREL_API_KEY = os.environ.get('NREL_API_KEY')
NREL_API_EMAIL = os.environ.get('NREL_API_EMAIL')
lon_lats = [(-105.1800775, 39.7383155)] # golden CO
resource_dir = str(Path(__file__).parent / "tmp")
# --- fetch solar tmy file from psm3-tmy using default parameters ---
solarfetcher = tools.FetchResourceFiles(tech='solar',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir)
solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
solar_path_dict = solarfetcher.resource_file_paths_dict
solar_fp = solar_path_dict[lon_lats[0]]
with open(solar_fp, mode='r') as f:
reader = csv.DictReader(f)
list(reader)
num_timesteps = 8760
assert reader.line_num == num_timesteps + 3
# --- test legacy 'pv' instead of 'solar'---
solarfetcher = tools.FetchResourceFiles(tech='pv',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir)
solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
solar_path_dict = solarfetcher.resource_file_paths_dict
solar_fp = solar_path_dict[lon_lats[0]]
with open(solar_fp, mode='r') as f:
solar_csv = csv.DictReader(f)
list(solar_csv)
num_timesteps = 8760
assert solar_csv.line_num == num_timesteps + 3
# --- fetch solar single-year 30-min file from psm3 ---
solarfetcher = tools.FetchResourceFiles(tech='solar',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir,
resource_type='psm3',
resource_year='2018',
resource_interval_min=30)
solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
solar_path_dict = solarfetcher.resource_file_paths_dict
solar_fp = solar_path_dict[lon_lats[0]]
with open(solar_fp, mode='r') as f:
solar_csv = csv.DictReader(f)
list(solar_csv)
num_timesteps = 17520
assert solar_csv.line_num == num_timesteps + 3
# --- fetch solar tgy for 2018 from psm3-tmy ---
solarfetcher = tools.FetchResourceFiles(tech='solar',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir,
resource_type='psm3-tmy',
resource_year='tgy-2018')
solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
solar_path_dict = solarfetcher.resource_file_paths_dict
solar_fp = solar_path_dict[lon_lats[0]]
with open(solar_fp, mode='r') as f:
solar_csv = csv.DictReader(f)
list(solar_csv)
num_timesteps = 8760
assert solar_csv.line_num == num_timesteps + 3
# --- fetch 5-minute data for 2018 from psm3-5min ---
# this NSRDB API endpoint not working properly as of 8/21/2020
#solarfetcher = tools.FetchResourceFiles(
# tech='solar',
# nrel_api_key=NREL_API_KEY,
# nrel_api_email=NREL_API_EMAIL,
# resource_dir=resource_dir,
# resource_type='psm3-5min',
# resource_interval_min=5,
# resource_year='2018')
#solarfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
#solar_path_dict = solarfetcher.resource_file_paths_dict
#solar_fp = solar_path_dict[lon_lats[0]]
#solar_csv = pd.read_csv(solar_fp)
#num_timesteps = 175200
#assert solar_csv.shape[0] == num_timesteps+2
# --- fetch wind ---
wtkfetcher = tools.FetchResourceFiles(tech='wind',
nrel_api_key=NREL_API_KEY,
nrel_api_email=NREL_API_EMAIL,
resource_dir=resource_dir)
wtkfetcher.fetch(lon_lats)
# --- read csv and confirm dimensions ---
wtk_path_dict = wtkfetcher.resource_file_paths_dict
wtk_fp = wtk_path_dict[lon_lats[0]]
with open(wtk_fp, mode='r') as f:
wtk_csv = csv.DictReader(f)
list(wtk_csv)
assert wtk_csv.line_num == 8764 + 1
shutil.rmtree(resource_dir)
