energy calculation including shading effects
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Utilities/Optimisers.py
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Utilities/Optimisers.py
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@ -12,13 +12,14 @@ from Utilities.Processes import (
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logger = logging.getLogger(__name__)
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def get_location(c):
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location = pvlib.location.Location(
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latitude=c["environment"]["location"]["latitude"],
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longitude=c["environment"]["location"]["longitude"],
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tz=c["simulation_date_time"]["tz"],
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)
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return location
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@ -85,9 +86,7 @@ def define_grid_layout(c):
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for i in range(int(max__panels_per_row)):
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if counter < no_of_panels:
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x.append(i * c["panel"]["dimensions"]["width"])
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y.append(
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j * pitch
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)
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y.append(j * pitch)
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z.append(0)
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counter += 1
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else:
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@ -121,10 +120,111 @@ def get_solar_data(c):
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# Get solar position data using PVLib
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solar_positions = location.get_solarposition(times)
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clearsky_data = location.get_clearsky(times)
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# filter solar positions to only include times when the sun is above the horizon
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solar_positions = solar_positions[solar_positions["apparent_elevation"] > 0]
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# get datetime range from solar_positions
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day_times = solar_positions.index
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clearsky_data = location.get_clearsky(day_times)
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return solar_positions, clearsky_data
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def calculate_shading(c, coordinates, solar_positions):
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def calculate_shading(c):
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panel_coordinates, no_of_panels = define_grid_layout(c)
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solar_positions, clearsky_data = get_solar_data(c)
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# split the solar positions data into morning and afternoon, using solar azimuth of
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# 180 degrees as the threshold
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morning_solar_positions = solar_positions[solar_positions["azimuth"] <= 180]
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afternoon_solar_positions = solar_positions[solar_positions["azimuth"] > 180]
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# the first row is always not shaded so exclude
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no_of_rows = np.unique(panel_coordinates["y"]).shape[0]
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no_of_shaded_rows = no_of_rows - 1
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collector_width = c["panel"]["dimensions"]["length"]
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# calculate delta between unique y coordinates of panels to get pitch
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pitch = np.unique(panel_coordinates["y"])[1] - np.unique(panel_coordinates["y"])[0]
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surface_to_axis_offset = 0
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shaded_row_rotation = c["array"]["tilt"]
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shading_row_rotation = c["array"]["tilt"]
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axis_tilt = 0
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axis_azimuth = c["array"]["front_face_azimuth"]
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morning_shaded_fraction = pvlib.shading.shaded_fraction1d(
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solar_zenith=morning_solar_positions["zenith"],
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solar_azimuth=morning_solar_positions["azimuth"],
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axis_azimuth=axis_azimuth,
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shaded_row_rotation=shaded_row_rotation,
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shading_row_rotation=shading_row_rotation,
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collector_width=collector_width,
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pitch=pitch,
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surface_to_axis_offset=surface_to_axis_offset,
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axis_tilt=axis_tilt,
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)
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morning_shaded_fraction = morning_shaded_fraction * no_of_shaded_rows / no_of_rows
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afternoon_shaded_fraction = pvlib.shading.shaded_fraction1d(
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solar_zenith=afternoon_solar_positions["zenith"],
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solar_azimuth=afternoon_solar_positions["azimuth"],
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axis_azimuth=axis_azimuth + 180,
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shaded_row_rotation=shaded_row_rotation,
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shading_row_rotation=shading_row_rotation,
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collector_width=collector_width,
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pitch=pitch,
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surface_to_axis_offset=surface_to_axis_offset,
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axis_tilt=axis_tilt,
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)
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afternoon_shaded_fraction = (
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afternoon_shaded_fraction * no_of_shaded_rows / no_of_rows
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)
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logger.info(
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f"Shaded fraction calculated for morning and afternoon solar positions."
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)
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# calculate irradiance on plane of array
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poa_front = pvlib.irradiance.get_total_irradiance(
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surface_tilt=c["array"]["tilt"],
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surface_azimuth=c["array"]["front_face_azimuth"],
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solar_zenith=morning_solar_positions["zenith"],
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solar_azimuth=morning_solar_positions["azimuth"],
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dni=clearsky_data["dni"],
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ghi=clearsky_data["ghi"],
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dhi=clearsky_data["dhi"],
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)
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# drop rows with poa_global NaN values
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poa_front = poa_front.dropna(subset=["poa_global"])
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poa_rear = pvlib.irradiance.get_total_irradiance(
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surface_tilt=180 - c["array"]["tilt"],
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surface_azimuth=c["array"]["front_face_azimuth"] + 180,
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solar_zenith=afternoon_solar_positions["zenith"],
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solar_azimuth=afternoon_solar_positions["azimuth"],
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dni=clearsky_data["dni"],
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ghi=clearsky_data["ghi"],
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dhi=clearsky_data["dhi"],
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)
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# drop rows with poa_global NaN values
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poa_rear = poa_rear.dropna(subset=["poa_global"])
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effective_front = (
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poa_front["poa_global"]
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* (1 - morning_shaded_fraction)
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* c["panel"]["efficiency"]
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)
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effective_rear = (
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poa_rear["poa_global"]
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* (1 - afternoon_shaded_fraction)
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* c["panel"]["bifaciality"]
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* c["panel"]["efficiency"]
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)
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energy_front = effective_front * 15 / 60 / 1e3
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energy_rear = effective_rear * 15 / 60 / 1e3
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energy_total = energy_front.sum() + energy_rear.sum()
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logger.info(f"Energy yield calculated: {energy_total} kWh/m2")
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panel_area = c["panel"]["dimensions"]["length"] * c["panel"]["dimensions"]["width"]
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total_area = panel_area * no_of_panels
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total_energy = energy_total * total_area
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logger.info(f"Total energy yield calculated: {total_energy} kWh")
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@ -1,6 +1,6 @@
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array:
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system_size: 100 # in kWp
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spacing: 1.5 # spacing between adjacent panel rows in m
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system_size: 400 # in kWp
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spacing: 0.5 # spacing between adjacent panel rows in m
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edge_setback: 1.8 # distance from the edge of the roof to the array
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front_face_azimuth: 90 # 90=east, 180=south, 270=west
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tilt: 90 # just 0 and 90 are supported for now
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@ -24,6 +24,7 @@ environment:
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panel:
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peak_power: 710 # in Wp
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efficiency: 0.229 # max efficiency of the front face
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bifaciality: 0.85 # rear face efficiency relative to front face
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# dimensions all in m
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dimensions:
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4
main.py
4
main.py
@ -1,7 +1,7 @@
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# %%
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import yaml
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import logging
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from Utilities.Shading import define_grid_layout
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from Utilities.Shading import calculate_shading
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logging.basicConfig(
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level=logging.INFO,
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@ -24,7 +24,7 @@ with open(config_path, "r") as file:
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logger.info("Configuration loaded successfully.")
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logger.debug(f"Configuration: {c}")
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shading = define_grid_layout(c)
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shading = calculate_shading(c)
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logger.info("Shading calculation completed successfully.")
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# %%
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