In [1]:
import os
from pathlib import Path


testfolder = str(Path().resolve().parent.parent / 'bifacial_radiance' / 'TEMP' / '1axis')

if not os.path.exists(testfolder):
    os.makedirs(testfolder)
    
print ("Your simulation will be stored in %s" % testfolder)

Your simulation will be stored in C:\Users\sayala\Documents\GitHub\bifacial_radiance\bifacial_radiance\TEMP\1axis
In [2]:
import bifacial_radiance as br
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
In [3]:
# This information helps with debugging and getting support :)
import sys, platform
print("Working on a ", platform.system(), platform.release())
print("Python version ", sys.version)
print("Pandas version ", pd.__version__)
print("bifacial_radiance version ", br.__version__)
print("pyplot ", plt.matplotlib.__version__)

Working on a  Windows 10
Python version  3.11.4 | packaged by Anaconda, Inc. | (main, Jul  5 2023, 13:38:37) [MSC v.1916 64 bit (AMD64)]
Pandas version  2.1.0
bifacial_radiance version  0.4.2+177.gd5001f6.dirty
pyplot  3.7.2
In [4]:
simulationname = '1axis-groundscan'

# Location
lat = 39.7555
lon = -105.2211

# Scene Parameters
azimuth_ang=90 # Facing south
tilt=30

# MakeModule Parameters
moduletype='PVmod'
numpanels=1
module_x = 2 # m
module_y = 1 # m. slope we will measure
sensorsy=2
sensorsground=5

# SceneDict Parameters
pitch = 6 # m
albedo = 0.2
clearance_height = 0.5 # m  
nMods = 4 
nRows = 3

sceneDict = {'tilt':10,'pitch':3,'clearance_height':0.2,'azimuth':180, 'nMods': 20, 'nRows': 7}
In [5]:
demo = br.RadianceObj(simulationname,path = testfolder)
demo.setGround(albedo)
epwfile = demo.getEPW(lat, lon)

path = C:\Users\sayala\Documents\GitHub\bifacial_radiance\bifacial_radiance\TEMP\1axis
Loading albedo, 1 value(s), 0.200 avg
1 nonzero albedo values.
Getting weather file: USA_CO_Golden-NREL.724666_TMY3.epw
 ... OK!
In [6]:
module=demo.makeModule(name=moduletype,x=module_x,y=module_y)

Module Name: PVmod
Module PVmod updated in module.json
Pre-existing .rad file objects\PVmod.rad will be overwritten
In [7]:
metdata = demo.readWeatherFile(epwfile, coerce_year=2021, starttime='2021-06-01', endtime='2021-06-30_23')

8760 line in WeatherFile. Assuming this is a standard hourly WeatherFile for the year for purposes of saving Gencumulativesky temporary weather files in EPW folder.
Coercing year to 2021
Filtering dates
Saving file EPWs\metdata_temp.csv, # points: 8760
Calculating Sun position for Metdata that is right-labeled  with a delta of -30 mins. i.e. 12 is 11:30 sunpos
In [8]:
hub_height = 1.5
pitch = 5.7
sazm = 180 # axis angle, N-S = 180
fixed_tilt_angle = None
gcr = 2 / pitch
cumulativesky = True

trakerParams = {
    'limit_angle': 50,
    'angledelta': 30,
    'backtrack': True,
    'gcr': gcr,
    'cumulativesky': cumulativesky,
    'azimuth': sazm,  # axis angle, N-S = 180
    'fixed_tilt_angle': fixed_tilt_angle
}
In [9]:
trackerdict = demo.set1axis(**trakerParams)

Saving file EPWs\1axis_-60.0.csv, # points: 90
Saving file EPWs\1axis_-30.0.csv, # points: 90
Saving file EPWs\1axis_-0.0.csv, # points: 90
Saving file EPWs\1axis_30.0.csv, # points: 90
Saving file EPWs\1axis_60.0.csv, # points: 90
In [10]:
if cumulativesky:
    demo.genCumSky1axis()
else:
    demo.gendaylit1axis()

message: There were 90 sun up hours in this climate file
Total Ibh/Lbh: 0.000000
Created skyfile skies\1axis_-60.0.rad
message: There were 89 sun up hours in this climate file
Total Ibh/Lbh: 0.000000
Created skyfile skies\1axis_-30.0.rad
message: There were 84 sun up hours in this climate file
Total Ibh/Lbh: 0.000000
Created skyfile skies\1axis_-0.0.rad
message: There were 86 sun up hours in this climate file
Total Ibh/Lbh: 0.000000
Created skyfile skies\1axis_30.0.rad
message: There were 86 sun up hours in this climate file
Total Ibh/Lbh: 0.000000
Created skyfile skies\1axis_60.0.rad
In [11]:
sceneDict = {
    'pitch': pitch,
    'hub_height': hub_height,
    'nMods': 5,
    'nRows': 2
}
In [12]:
trakerdict = demo.makeScene1axis(module=moduletype, sceneDict=sceneDict)
trakerdict = demo.makeOct1axis()

Making .rad files for cumulativesky 1-axis workflow
5 Radfiles created in /objects/

Making 5 octfiles in root directory.
Created 1axis_-60.0.oct
Created 1axis_-30.0.oct
Created 1axis_-0.0.oct
Created 1axis_30.0.oct
Created 1axis_60.0.oct
In [13]:
sensorsgroundvalues = np.array([2, 30, 100, 150])
angles = np.array([-0.0, -30.0, -60.0, 30.0, 60.0])
In [15]:
trakerdict = demo.analysis1axis(sensorsy=4)

Linescan in process: 1axis_-60.0_Row1_Module3_Front
Linescan in process: 1axis_-60.0_Row1_Module3_Back
Saved: results\irr_1axis_-60.0_Row1_Module3.csv
Index: -60.0. Wm2Front: 54915.925. Wm2Back: 5775.628500000001
Linescan in process: 1axis_-30.0_Row1_Module3_Front
Linescan in process: 1axis_-30.0_Row1_Module3_Back
Saved: results\irr_1axis_-30.0_Row1_Module3.csv
Index: -30.0. Wm2Front: 49277.3025. Wm2Back: 6292.562499999999
Linescan in process: 1axis_-0.0_Row1_Module3_Front
Linescan in process: 1axis_-0.0_Row1_Module3_Back
Saved: results\irr_1axis_-0.0_Row1_Module3.csv
Index: -0.0. Wm2Front: 42478.545. Wm2Back: 6379.288500000001
Linescan in process: 1axis_30.0_Row1_Module3_Front
Linescan in process: 1axis_30.0_Row1_Module3_Back
Saved: results\irr_1axis_30.0_Row1_Module3.csv
Index: 30.0. Wm2Front: 42481.815. Wm2Back: 5922.213500000001
Linescan in process: 1axis_60.0_Row1_Module3_Front
Linescan in process: 1axis_60.0_Row1_Module3_Back
Saved: results\irr_1axis_60.0_Row1_Module3.csv
Index: 60.0. Wm2Front: 39707.3. Wm2Back: 5650.172
In [ ]:
resultsdict = {}

for i, sensorsground in enumerate(sensorsgroundvalues):
    print("Doing sensor", i)
    print(f"sensorsground: {sensorsground}")
    trakerdict = demo.analysis1axisground(customname='1-axis_groundscan_' + str(sensorsground), 
                                          sensorsground=sensorsground)
In [ ]:
for i, sensorsground in enumerate(sensorsgroundvalues): 
    for i, angle in enumerate(angles):
        for i, x in enumerate(trakerdict[angle]['Results'][0]['AnalysisObj'].x):
            if x >= 1 and x <= pitch-1:
                if (sensorsground, angle) in resultsdict:
                    resultsdict[(sensorsground, angle)] += trakerdict[angle]['Results'][0]['AnalysisObj'].Wm2Front
                else:
                    resultsdict[(sensorsground, angle)] = trakerdict[angle]['Results'][0]['AnalysisObj'].Wm2Front
In [ ]:
trakerdict
In [ ]:
resulsbyangle = {}

for i, angle in enumerate(angles):
    results = []
    for i, sensorsground in enumerate(sensorsgroundvalues):
        if (sensorsground, angle) in resultsdict:
            results.append(np.mean(resultsdict[(sensorsground, angle)]))
        else:
            results.append(0)
    
    resulsbyangle[angle] = results
In [ ]:
resulsbyangle
In [ ]:
for i, angle in enumerate(angles):
    df = pd.DataFrame({
        'groundscan': sensorsgroundvalues,
        'average': resulsbyangle[angle]
    })

    df.plot(x='groundscan', y='average', marker='o', color='blue')
    plt.xticks(np.arange(0, 501, 50))
    plt.title(f'Irradiance at different groundscan for 1-axis {angle}')
    plt.show()
In [ ]:
# one graph for all angles
resultsbysensor = {}

for i, sensorsground in enumerate(sensorsgroundvalues):
    resultsarr = []
    for i, angle in enumerate(angles):
        if (sensorsground, angle) in resultsdict:
            resultsarr.append(np.mean(resultsdict[(sensorsground, angle)]))
                          
    resultsbysensor[sensorsground] = np.mean(resultsarr)
In [ ]:
resultsbysensor
In [ ]:
df1 = pd.DataFrame({
    'groundscan': sensorsgroundvalues,
    'average': resultsbysensor.values()
})

df1.plot(x='groundscan', y='average', marker='o', color='blue')
plt.xticks(np.arange(0, 501, 50))
plt.title('Cummulative irradiance at different groundscan for 1-axis')
plt.show()
In [ ]: