-
Notifications
You must be signed in to change notification settings - Fork 2
/
config.yml
96 lines (78 loc) · 3.54 KB
/
config.yml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
### ------------------------------------------- ###
### ###
### CONFIGURATION FILE ###
### ###
### ------------------------------------------- ###
# The main.py script reads this file to extract the parameters
# inputed by the final user to excute the characteristics extraction
# algorithm
# 1. Folders and common parameters
# The geojson contains geolocalized polygons of arrays. Currently, the supported coordinates system are
# ESPG:4623 (i.e. WGS84 or GPS coordinate system)
data_dir: "data" # The name of the folder where the source data is located
source-data: 'input.geojson' # The name of the source data. It corresponds to the .geojson file with all the polygons to proceed.
output-name: "charateristics" # The name of the output file
# 2. Parameterization
# These parameters specify whether the users has either a database with PV panels characteristics
# or if he has DEM rasters.
has-data: True
has-dem: False
# 2.1. Table formatting
# If the user has a table, he should specify the name of some columns
# as the table is reformatted later in the script.
data-directory: "data" # The location of the auxiliary data file with the PV panels characteristics
data-name: "filtered_characteristics.csv" # The name of the table with the minimal information
# Name of the columns.
# Edit the name of the columns as they are named in the data_name file.
latitude_var: "latitude"
longitude_var: "longitude"
ic_var: "kWp"
surface_var: "surface"
tilt_var: 'tilt'
# 2.2. DEM preparation
# If the user has DEM rasters, the path to the rasters should be specified
# The indicated folder should contain all necessary rasters
# The supported format is geotiff.
# the conversion specifies the in proj and out proj
# epsg codes are expected and should be separated by a comma (,) and no spaces
# after the comma
# otherwise it is a None
raster-folder: 'hands-on'
conversion: "epsg:4326,epsg:2154"
# 2. Methods
# The following parameters define the methods chosen to infer the characteristics
### SURFACE COMPUTATION ###
# No parameter necessary.
### TILT ESTIMATION ###
# Methods : {theil-sen, lut, constant}
tilt-method: "theil-sen"
### AZIMUTH ESTIMATION ###
# Methods : {theil-sen, bounding-box}
azimuth-method: "theil-sen"
# Parameters for the Theil-Sen (TS) regression
# These parameters are common for the tilt and azimuth computation
M: None # Number of iterations for the TS regressor
N: None # Number of points for the samples for the TS regressor
seed: 42 # Random seed for the TS regressor
offset: 25 # offset with respect to the polygon boundaries for the computation of the masks and DSM
# Parameters for the look-up-table
# The number of slices (in both latitude and longitude) desired
# for the computation of the LUT.
# Given a surface slice, the LUT will be an array of shape (lut-steps, lut-steps)
lut-steps: 25
# Parameters for the constant tilt imputation
# Should be passed in degrees
constant-tilt : 30
### INSTALLED CAPACITY ESTIMATION ###
# Regression type : {clustered, linear, constant}
# The regression type can be either clustered, linear or constant.
regression-type: "clustered"
# Regression clusters:
# If the user choses a clustered linear regression (`clustered`), then
# he also needs to specify the number of clusters
regression-clusters: 4
# Default coefficient:
# If the user choses a constant computation of the installed capacity,
# then the coefficient should be passed as input.
# this is expressed in [kWp / m2]
default-coefficient: 0.167