Hi Paul,
Your post seems very helpful. However, I am trying to develop something similar to the NSRDB data download and processing for wind from WindToolkit but my model doesn't seem to work. As a new user of PySAM, I seek for your help. Below is my code. Can you please help me to find out what really the issue is?
import pandas as pdimport numpy as npimport sys, osfrom IPython.display import displaylat, lon, year = 33.2164, -97.1292, 2010 # You must request an NSRDB api key from the link aboveapi_key = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX'# Set the attributes to extract (e.g.,windspeed, winddirection, etc.), separated by commas.attributes = 'pressure_100m,windspeed_100m,winddirection_100m,temperature_100m'# Choose year of datayear = '2010'# Set leap year to true or false. True will return leap day data if present, false will not.leap_year = 'false'# Set time interval in minutes, i.e., '30' is half hour intervals. Valid intervals are 5, 15, 30, 45 & 60.interval = '5'# Specify Coordinated Universal Time (UTC), 'true' will use UTC, 'false' will use the local time zone of the data.# NOTE: In order to use the WindToolkit data in SAM, you must specify UTC as 'false'. SAM requires the data to be in the# local time zone.utc = 'false'# Your full name, use '+' instead of spaces.your_name = 'X+X'# Your reason for using the NSRDB.reason_for_use = 'example'# Your affiliationyour_affiliation = 'NREL'# Your email addressyour_email = 'X@X.com'# Please join our mailing list so we can keep you up-to-date on new developments.mailing_list = 'true'# Declare url stringurl = '
developer.nrel.gov/api/wind-toolkit/v2/wind/wtk-download.csv?wkt=POINT({lon}%20{lat})&names={year}&leap_day={leap}&interval={interval}&utc={utc}&full_name={name}&email={email}&affiliation={affiliation}&mailing_list={mailing_list}&reason={reason}&api_key={api}&attributes={attr}'.format( year=year, lat=lat, lon=lon, leap=leap_year, interval=interval, utc=utc, name=your_name, email=your_email, mailing_list=mailing_list, affiliation=your_affiliation, reason=reason_for_use, api=api_key, attr=attributes)# Return just the first 1 line to get metadata:info = pd.read_csv(url, nrows=1)# See metadata for specified properties, e.g., timezone timezone= info# Return all but first 1 line of csv to get data:df = pd.read_csv( '
developer.nrel.gov/api/wind-toolkit/v2/wind/wtk-download.csv?wkt=POINT({lon}%20{lat})&names={year}&leap_day={leap}&interval={interval}&utc={utc}&full_name={name}&email={email}&affiliation={affiliation}&mailing_list={mailing_list}&reason={reason}&api_key={api}&attributes={attr}'.format( year=year, lat=lat, lon=lon, leap=leap_year, interval=interval, utc=utc, name=your_name, email=your_email, mailing_list=mailing_list, affiliation=your_affiliation, reason=reason_for_use, api=api_key, attr=attributes), skiprows=1)# Set the time index in the pandas dataframe:df = df.set_index(pd.date_range('1/1/{yr}'.format(yr=year), freq=interval+'Min', periods=525600/int(interval)))# take a lookprint ('shape:',df.shape)df.head()print (df.columns.values)################################################################################################################## My Doubt is in this section mostly ####import site# Use site.addsitedir() to set the path to the SAM SDK API. Set path to the python directory.site.addsitedir('/Applications/sam-sdk-2015-6-30-r3/languages/python/')import sscapissc = sscapi.PySSC()# Resource inputs for SAM model:wfd = ssc.data_create()ssc.data_set_number(wfd, 'lat', lat)ssc.data_set_number(wfd, 'lon', lon)#ssc.data_set_number(wfd, 'tz', timezone)#ssc.data_set_number(wfd, 'elev', elevation)ssc.data_set_array(wfd, 'year', df.index.year)ssc.data_set_array(wfd, 'month', df.index.month)ssc.data_set_array(wfd, 'day', df.index.day)ssc.data_set_array(wfd, 'hour', df.index.hour)ssc.data_set_array(wfd, 'minute', df.index.minute)wind_turbine_powercurve_windspeeds = [ 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3, 3.25, 3.5, 3.75, 4, 4.25, 4.5, 4.75, 5, 5.25, 5.5, 5.75, 6, 6.25, 6.5, 6.75, 7, 7.25, 7.5, 7.75, 8, 8.25, 8.5, 8.75, 9, 9.25, 9.5, 9.75, 10, 10.25, 10.5, 10.75, 11, 11.25, 11.5, 11.75, 12, 12.25, 12.5, 12.75, 13, 13.25, 13.5, 13.75, 14, 14.25, 14.5, 14.75, 15, 15.25, 15.5, 15.75, 16, 16.25, 16.5, 16.75, 17, 17.25, 17.5, 17.75, 18, 18.25, 18.5, 18.75, 19, 19.25, 19.5, 19.75, 20, 20.25, 20.5, 20.75, 21, 21.25, 21.5, 21.75, 22, 22.25, 22.5, 22.75, 23, 23.25, 23.5, 23.75, 24, 24.25, 24.5, 24.75, 25, 25.25, 25.5, 25.75, 26, 26.25, 26.5, 26.75, 27, 27.25, 27.5, 27.75, 28, 28.25, 28.5, 28.75, 29, 29.25, 29.5, 29.75, 30, 30.25, 30.5, 30.75, 31, 31.25, 31.5, 31.75, 32, 32.25, 32.5, 32.75, 33, 33.25, 33.5, 33.75, 34, 34.25, 34.5, 34.75, 35, 35.25, 35.5, 35.75, 36, 36.25, 36.5, 36.75, 37, 37.25, 37.5, 37.75, 38, 38.25, 38.5, 38.75, 39, 39.25, 39.5, 39.75, 40 ]wind_turbine_powercurve_powerout = [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 21.32, 33.51, 45.69, 65.21, 79.83, 104.25, 128.66, 157.97, 187.27, 216.58, 250.78, 292.32, 333.85, 375.4, 426.72, 475.6, 534.27, 597.81, 656.49, 724.94, 798.29, 871.63, 940.08, 1010, 1060, 1130, 1190, 1240, 1290, 1330, 1370, 1390, 1410, 1430, 1440, 1460, 1470, 1475, 1480, 1485, 1490, 1495, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 1500, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]ssc.data_set_array(wfd,'wind_turbine_powercurve_windspeeds',wind_turbine_powercurve_windspeeds)ssc.data_set_array(wfd,'wind_turbine_powercurve_powerout',wind_turbine_powercurve_powerout)#####ssc.data_set_array(wfd, 'wind_speed', df)ssc.data_set_array(wfd, 'wind_direction', df)# Create SAM compliant object dat = ssc.data_create()ssc.data_set_table(dat, 'wind_resource_data', wfd)ssc.data_free(wfd)# Specify the system Configurationwind_resource_model_choice=0ssc.data_set_number(dat, 'wind_resource_model_choice', wind_resource_model_choice)# Set system capacity in MWsystem_capacity = 2 # will change for different sitesssc.data_set_number(dat, 'system_capacity', system_capacity)# Setting the hub height in meter of wind turbinewind_turbine_hub_ht=100ssc.data_set_number(dat, 'wind_turbine_hub_ht', wind_turbine_hub_ht)# Set rotor diameter in meterwind_turbine_rotor_diameter=95ssc.data_set_number(dat, 'wind_turbine_rotor_diameter',wind_turbine_rotor_diameter)# Set the shearwind_resource_shear=0.14ssc.data_set_number(dat, 'wind_resource_shear', wind_resource_shear)# execute and put generation results back into dataframemod = ssc.module_create('WindPowerSingleOwner')ssc.module_exec(mod, dat)df = np.array(ssc.data_get_array(dat, 'gen'))# free the memoryssc.data_free(dat)ssc.module_free(mod)############################################## Divide sum of generation by the number of periods times the system sizedf.sum() / (525600/int(interval) * system_capacity)# Total Energy:df.sum()
