{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Optimization of Surface Position\n", "\n", "Following we show a few examples on how to use the optimizer for the surface position in PVGIS." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", "- __Optimization of Surface Position__\n", "\n", " - Optimisation of Tilt, Orientation or both\n", " - Supported by optimizers implemented in SciPy\n", "\n", "- __Multiple examples__\n", "\n", " - Examples for a single day, single and multi-year timestamps\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Programmatic preamble" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from pvgisprototype import (\n", " TemperatureSeries,\n", " WindSpeedSeries,\n", " SpectralFactorSeries,\n", " LinkeTurbidityFactor,\n", " Longitude,\n", " Latitude,\n", " Elevation,\n", " SurfaceOrientation,\n", " SurfaceTilt,\n", ")\n", "from pvgisprototype.algorithms.huld.photovoltaic_module import PhotovoltaicModuleModel\n", "from pvgisprototype.api.datetime.datetimeindex import generate_datetime_series\n", "from zoneinfo import ZoneInfo\n", "from pvgisprototype.api.surface.graph_power_output import graph_power_output\n", "from pvgisprototype.api.surface.positioning import optimise_surface_position\n", "from pvgisprototype.api.surface.parameter_models import (\n", " SurfacePositionOptimizerMethod,\n", " SurfacePositionOptimizerMode,\n", ")\n", "import math\n", "from pvgisprototype.constants import DEGREES" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data preparation\n", "\n", "First, we define some basic parameters for a location, in which case it is a solar panel located behind the ESTI Lab, in the JRC, European Commission." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "latitude = Latitude(value=45.812, unit=DEGREES)\n", "longitude = Longitude(value=8.628, unit=DEGREES)\n", "elevation = 214\n", "timezone = ZoneInfo(\"UTC\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Optimization of Position" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Optimal Tilt for a Single Day\n", "\n", "For this first example, we will optimize the tilt of the panel on the 1st January 2010. We define the dates, the optimization mode as \"Tilt\", and the surface orientation of our panel" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "start_time = '2010-01-01'\n", "end_time = '2010-01-02'\n", "timestamps = generate_datetime_series(start_time=start_time, end_time=end_time, frequency=\"h\")\n", "mode = SurfacePositionOptimizerMode.Tilt\n", "surface_orientation = math.radians(180)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "from numpy import full\n", "photovoltaic_module = PhotovoltaicModuleModel.CIS_FREE_STANDING\n", "spectral_factor_series = SpectralFactorSeries(value=full(len(timestamps), 1, dtype='float32'))\n", "temperature_series = TemperatureSeries(value=full(len(timestamps), 12, dtype='float32'))\n", "wind_speed_series = WindSpeedSeries(value=full(len(timestamps), 2, dtype='float32'))\n", "linke_turbidity_factor_series = LinkeTurbidityFactor(value=full(len(timestamps), 1, dtype='float32'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we call the `optimise_surface_position()` function to calculate which is the optimal tilt for this case" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": true }, "outputs": [], "source": [ "result = optimise_surface_position(\n", " longitude=longitude.radians,\n", " latitude=latitude.radians,\n", " elevation=elevation, \n", " timestamps=timestamps,\n", " timezone=timezone,\n", " spectral_factor_series=spectral_factor_series,\n", " photovoltaic_module=photovoltaic_module,\n", " temperature_series=temperature_series,\n", " wind_speed_series=wind_speed_series,\n", " linke_turbidity_factor_series=linke_turbidity_factor_series,\n", " mode=mode,\n", " surface_orientation=surface_orientation\n", ")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
{\n",
       "    'Surface Orientation': SurfaceOrientation(\n",
       "        optimal=False,\n",
       "        optimiser=None,\n",
       "        min_degrees=0,\n",
       "        min_radians=0,\n",
       "        data_source=None,\n",
       "        equation=None,\n",
       "        algorithm=None,\n",
       "        unit='radians',\n",
       "        value=3.141592653589793,\n",
       "        symbol='⯐ ⎄',\n",
       "        description=None,\n",
       "        label='Surface Position',\n",
       "        title='Surface Position',\n",
       "        supertitle='Surface Position data',\n",
       "        shortname='Surface Position',\n",
       "        name='Surface Position',\n",
       "        max_radians=6.283185307179586,\n",
       "        max_degrees=360\n",
       "    ),\n",
       "    'Surface Tilt': SurfaceTilt(\n",
       "        optimal=True,\n",
       "        optimiser=None,\n",
       "        min_degrees=0,\n",
       "        min_radians=0,\n",
       "        data_source=None,\n",
       "        equation=None,\n",
       "        algorithm=None,\n",
       "        unit='radians',\n",
       "        value=1.3035176011540837,\n",
       "        symbol='⯐ ⎄',\n",
       "        description=None,\n",
       "        label='Surface Position',\n",
       "        title='Surface Position',\n",
       "        supertitle='Surface Position data',\n",
       "        shortname='Surface Position',\n",
       "        name='Surface Position',\n",
       "        max_radians=3.141592653589793,\n",
       "        max_degrees=180\n",
       "    ),\n",
       "    'Mean PV Power': np.float32(232.95676),\n",
       "    'Unit': 'radians',\n",
       "    'Timing': 'Milne1921'\n",
       "}\n",
       "
\n" ], "text/plain": [ "\u001b[1m{\u001b[0m\n", " \u001b[32m'Surface Orientation'\u001b[0m: \u001b[1;35mSurfaceOrientation\u001b[0m\u001b[1m(\u001b[0m\n", " \u001b[33moptimal\u001b[0m=\u001b[3;91mFalse\u001b[0m,\n", " \u001b[33moptimiser\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33mmin_degrees\u001b[0m=\u001b[1;36m0\u001b[0m,\n", " \u001b[33mmin_radians\u001b[0m=\u001b[1;36m0\u001b[0m,\n", " \u001b[33mdata_source\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33mequation\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33malgorithm\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33munit\u001b[0m=\u001b[32m'radians'\u001b[0m,\n", " \u001b[33mvalue\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.141592653589793\u001b[0m,\n", " \u001b[33msymbol\u001b[0m=\u001b[32m'⯐ ⎄'\u001b[0m,\n", " \u001b[33mdescription\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33mlabel\u001b[0m=\u001b[32m'Surface Position'\u001b[0m,\n", " \u001b[33mtitle\u001b[0m=\u001b[32m'Surface Position'\u001b[0m,\n", " \u001b[33msupertitle\u001b[0m=\u001b[32m'Surface Position data'\u001b[0m,\n", " \u001b[33mshortname\u001b[0m=\u001b[32m'Surface Position'\u001b[0m,\n", " \u001b[33mname\u001b[0m=\u001b[32m'Surface Position'\u001b[0m,\n", " \u001b[33mmax_radians\u001b[0m=\u001b[1;36m6\u001b[0m\u001b[1;36m.283185307179586\u001b[0m,\n", " \u001b[33mmax_degrees\u001b[0m=\u001b[1;36m360\u001b[0m\n", " \u001b[1m)\u001b[0m,\n", " \u001b[32m'Surface Tilt'\u001b[0m: \u001b[1;35mSurfaceTilt\u001b[0m\u001b[1m(\u001b[0m\n", " \u001b[33moptimal\u001b[0m=\u001b[3;92mTrue\u001b[0m,\n", " \u001b[33moptimiser\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33mmin_degrees\u001b[0m=\u001b[1;36m0\u001b[0m,\n", " \u001b[33mmin_radians\u001b[0m=\u001b[1;36m0\u001b[0m,\n", " \u001b[33mdata_source\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33mequation\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33malgorithm\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33munit\u001b[0m=\u001b[32m'radians'\u001b[0m,\n", " \u001b[33mvalue\u001b[0m=\u001b[1;36m1\u001b[0m\u001b[1;36m.3035176011540837\u001b[0m,\n", " \u001b[33msymbol\u001b[0m=\u001b[32m'⯐ ⎄'\u001b[0m,\n", " \u001b[33mdescription\u001b[0m=\u001b[3;35mNone\u001b[0m,\n", " \u001b[33mlabel\u001b[0m=\u001b[32m'Surface Position'\u001b[0m,\n", " \u001b[33mtitle\u001b[0m=\u001b[32m'Surface Position'\u001b[0m,\n", " \u001b[33msupertitle\u001b[0m=\u001b[32m'Surface Position data'\u001b[0m,\n", " \u001b[33mshortname\u001b[0m=\u001b[32m'Surface Position'\u001b[0m,\n", " \u001b[33mname\u001b[0m=\u001b[32m'Surface Position'\u001b[0m,\n", " \u001b[33mmax_radians\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.141592653589793\u001b[0m,\n", " \u001b[33mmax_degrees\u001b[0m=\u001b[1;36m180\u001b[0m\n", " \u001b[1m)\u001b[0m,\n", " \u001b[32m'Mean PV Power'\u001b[0m: \u001b[1;35mnp.float32\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m232.95676\u001b[0m\u001b[1m)\u001b[0m,\n", " \u001b[32m'Unit'\u001b[0m: \u001b[32m'radians'\u001b[0m,\n", " \u001b[32m'Timing'\u001b[0m: \u001b[32m'Milne1921'\u001b[0m\n", "\u001b[1m}\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from rich import print\n", "print(result)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the photovoltaic power output against the surface tilt angle along with the point of maximum output" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "ename": "IndexError", "evalue": "boolean index did not match indexed array along axis 0; size of axis is 0 but size of corresponding boolean axis is 25", "output_type": "error", "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mIndexError\u001b[39m Traceback (most recent call last)", "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[8]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m 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mode, surface_orientation, surface_tilt, min_surface_orientation, max_surface_orientation, min_surface_tilt, max_surface_tilt, optimal_surface_tilt, optimal_surface_orientation, optimal_pv_power)\u001b[39m\n\u001b[32m 59\u001b[39m surface_tilt_values = numpy.linspace(min_surface_tilt, max_surface_tilt, num=\u001b[32m50\u001b[39m)\n\u001b[32m 61\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m surface_tilt_value \u001b[38;5;129;01min\u001b[39;00m surface_tilt_values:\n\u001b[32m---> \u001b[39m\u001b[32m62\u001b[39m mean_power_output = \u001b[43mcalculate_photovoltaic_power_output_series\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlongitude\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mlongitude\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m 63\u001b[39m \u001b[43m \u001b[49m\u001b[43mlatitude\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mlatitude\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m 64\u001b[39m \u001b[43m \u001b[49m\u001b[43melevation\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43melevation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimestamps\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimestamps\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m 65\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimezone\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimezone\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mspectral_factor_series\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mspectral_factor_series\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m 66\u001b[39m \u001b[43m \u001b[49m\u001b[43mphotovoltaic_module\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mphotovoltaic_module\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m 67\u001b[39m \u001b[43m \u001b[49m\u001b[43mtemperature_series\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemperature_series\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 68\u001b[39m \u001b[43m \u001b[49m\u001b[43mwind_speed_series\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mwind_speed_series\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m 69\u001b[39m \u001b[43m \u001b[49m\u001b[43mlinke_turbidity_factor_series\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mlinke_turbidity_factor_series\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m 70\u001b[39m \u001b[43m \u001b[49m\u001b[43msurface_orientation\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43msurface_orientation\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m 71\u001b[39m \u001b[43m \u001b[49m\u001b[43msurface_tilt\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43msurface_tilt_value\u001b[49m\n\u001b[32m 72\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m.value.mean()\n\u001b[32m 73\u001b[39m mean_power_output_values.append(mean_power_output)\n\u001b[32m 74\u001b[39m surface_tilt_values_degrees = numpy.linspace(math.degrees(min_surface_tilt), math.degrees(max_surface_tilt), num=\u001b[32m50\u001b[39m)\n", "\u001b[36mFile \u001b[39m\u001b[32m/spacetime/pvgis/pvgis-prototype-public/pvgisprototype/log.py:429\u001b[39m, in \u001b[36mlog_function_call..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 424\u001b[39m parent_frame = inspect.stack()[\u001b[32m1\u001b[39m]\n\u001b[32m 425\u001b[39m logger.debug(\n\u001b[32m 426\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m> Call : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunction.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() from \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.function\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() in \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.filename\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m:\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.lineno\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m, Requested : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_type\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m,\n\u001b[32m 427\u001b[39m alt=\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m> Call \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunction.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() from [reverse]\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.function\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m()[/reverse] in \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.filename\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m:\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.lineno\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m, Requested : [reverse]\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_type\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m[/reverse]\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 428\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m429\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunction\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "\u001b[36mFile \u001b[39m\u001b[32m/spacetime/pvgis/pvgis-prototype-public/pvgisprototype/api/power/broadband.py:210\u001b[39m, in \u001b[36mcalculate_photovoltaic_power_output_series\u001b[39m\u001b[34m(longitude, latitude, elevation, surface_orientation, surface_tilt, timestamps, timezone, global_horizontal_irradiance, direct_horizontal_irradiance, spectral_factor_series, temperature_series, wind_speed_series, linke_turbidity_factor_series, adjust_for_atmospheric_refraction, albedo, apply_reflectivity_factor, solar_position_model, sun_horizon_position, solar_incidence_model, zero_negative_solar_incidence_angle, horizon_profile, shading_model, shading_states, solar_time_model, solar_constant, eccentricity_phase_offset, eccentricity_amplitude, photovoltaic_module_type, bifaciality_factor, photovoltaic_module, peak_power, system_efficiency, power_model, radiation_cutoff_threshold, temperature_model, efficiency, dtype, array_backend, validate_output, verbose, log, fingerprint, profile)\u001b[39m\n\u001b[32m 205\u001b[39m pr.enable()\n\u001b[32m 207\u001b[39m \u001b[38;5;66;03m# In-Plane Irradiance After Reflectivity Loss\u001b[39;00m\n\u001b[32m 208\u001b[39m \u001b[38;5;66;03m# [ also referred to as inlined irradiance ]\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m210\u001b[39m global_inclined_irradiance_series = \u001b[43mcalculate_global_inclined_irradiance\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 211\u001b[39m \u001b[43m \u001b[49m\u001b[43mlongitude\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlongitude\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 212\u001b[39m \u001b[43m \u001b[49m\u001b[43mlatitude\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlatitude\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 213\u001b[39m \u001b[43m \u001b[49m\u001b[43melevation\u001b[49m\u001b[43m=\u001b[49m\u001b[43melevation\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 214\u001b[39m \u001b[43m \u001b[49m\u001b[43msurface_orientation\u001b[49m\u001b[43m=\u001b[49m\u001b[43msurface_orientation\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 215\u001b[39m \u001b[43m \u001b[49m\u001b[43msurface_tilt\u001b[49m\u001b[43m=\u001b[49m\u001b[43msurface_tilt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 216\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimestamps\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimestamps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 217\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimezone\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimezone\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 218\u001b[39m \u001b[43m \u001b[49m\u001b[43mglobal_horizontal_irradiance\u001b[49m\u001b[43m=\u001b[49m\u001b[43mglobal_horizontal_irradiance\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# time series optional\u001b[39;49;00m\n\u001b[32m 219\u001b[39m \u001b[43m \u001b[49m\u001b[43mdirect_horizontal_irradiance\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdirect_horizontal_irradiance\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# time series, optional\u001b[39;49;00m\n\u001b[32m 220\u001b[39m \u001b[43m \u001b[49m\u001b[43mlinke_turbidity_factor_series\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlinke_turbidity_factor_series\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 221\u001b[39m \u001b[43m \u001b[49m\u001b[43madjust_for_atmospheric_refraction\u001b[49m\u001b[43m=\u001b[49m\u001b[43madjust_for_atmospheric_refraction\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 222\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# unrefracted_solar_zenith=unrefracted_solar_zenith,\u001b[39;49;00m\n\u001b[32m 223\u001b[39m \u001b[43m \u001b[49m\u001b[43mapply_reflectivity_factor\u001b[49m\u001b[43m=\u001b[49m\u001b[43mapply_reflectivity_factor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 224\u001b[39m \u001b[43m \u001b[49m\u001b[43msolar_position_model\u001b[49m\u001b[43m=\u001b[49m\u001b[43msolar_position_model\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 225\u001b[39m \u001b[43m \u001b[49m\u001b[43msun_horizon_position\u001b[49m\u001b[43m=\u001b[49m\u001b[43msun_horizon_position\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 226\u001b[39m \u001b[43m \u001b[49m\u001b[43msolar_incidence_model\u001b[49m\u001b[43m=\u001b[49m\u001b[43msolar_incidence_model\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 227\u001b[39m \u001b[43m \u001b[49m\u001b[43mzero_negative_solar_incidence_angle\u001b[49m\u001b[43m=\u001b[49m\u001b[43mzero_negative_solar_incidence_angle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 228\u001b[39m \u001b[43m \u001b[49m\u001b[43mhorizon_profile\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhorizon_profile\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 229\u001b[39m \u001b[43m \u001b[49m\u001b[43mshading_model\u001b[49m\u001b[43m=\u001b[49m\u001b[43mshading_model\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 230\u001b[39m \u001b[43m \u001b[49m\u001b[43mshading_states\u001b[49m\u001b[43m=\u001b[49m\u001b[43mshading_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 231\u001b[39m \u001b[43m \u001b[49m\u001b[43msolar_time_model\u001b[49m\u001b[43m=\u001b[49m\u001b[43msolar_time_model\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 232\u001b[39m \u001b[43m \u001b[49m\u001b[43msolar_constant\u001b[49m\u001b[43m=\u001b[49m\u001b[43msolar_constant\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 233\u001b[39m \u001b[43m \u001b[49m\u001b[43meccentricity_phase_offset\u001b[49m\u001b[43m=\u001b[49m\u001b[43meccentricity_phase_offset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 234\u001b[39m \u001b[43m \u001b[49m\u001b[43meccentricity_amplitude\u001b[49m\u001b[43m=\u001b[49m\u001b[43meccentricity_amplitude\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 235\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# angle_output_units=angle_output_units,\u001b[39;49;00m\n\u001b[32m 236\u001b[39m \u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 237\u001b[39m \u001b[43m \u001b[49m\u001b[43marray_backend\u001b[49m\u001b[43m=\u001b[49m\u001b[43marray_backend\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 238\u001b[39m \u001b[43m \u001b[49m\u001b[43mvalidate_output\u001b[49m\u001b[43m=\u001b[49m\u001b[43mvalidate_output\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 239\u001b[39m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m=\u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 240\u001b[39m \u001b[43m \u001b[49m\u001b[43mlog\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlog\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 241\u001b[39m \u001b[43m \u001b[49m\u001b[43mfingerprint\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfingerprint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 242\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 243\u001b[39m rear_side_global_inclined_irradiance_series = \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;66;03m# to avoid the \"unbound error\"\u001b[39;00m\n\u001b[32m 244\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m photovoltaic_module_type == PhotovoltaicModuleType.Bifacial:\n\u001b[32m 245\u001b[39m \n\u001b[32m 246\u001b[39m \u001b[38;5;66;03m# Redesign Me : Maybe rethink the logic to get the rear side angles ?\u001b[39;00m\n", "\u001b[36mFile \u001b[39m\u001b[32m/spacetime/pvgis/pvgis-prototype-public/pvgisprototype/log.py:429\u001b[39m, in \u001b[36mlog_function_call..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 424\u001b[39m parent_frame = inspect.stack()[\u001b[32m1\u001b[39m]\n\u001b[32m 425\u001b[39m logger.debug(\n\u001b[32m 426\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m> Call : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunction.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() from \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.function\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() in \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.filename\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m:\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.lineno\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m, Requested : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_type\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m,\n\u001b[32m 427\u001b[39m alt=\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m> Call \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunction.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() from [reverse]\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.function\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m()[/reverse] in \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.filename\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m:\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.lineno\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m, Requested : [reverse]\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_type\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m[/reverse]\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 428\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m429\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunction\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "\u001b[36mFile \u001b[39m\u001b[32m/spacetime/pvgis/pvgis-prototype-public/pvgisprototype/api/irradiance/shortwave/inclined.py:306\u001b[39m, in \u001b[36mcalculate_global_inclined_irradiance\u001b[39m\u001b[34m(longitude, latitude, elevation, surface_orientation, surface_tilt, surface_tilt_horizontally_flat_panel_threshold, timestamps, timezone, global_horizontal_irradiance, direct_horizontal_irradiance, linke_turbidity_factor_series, adjust_for_atmospheric_refraction, albedo, apply_reflectivity_factor, solar_position_model, sun_horizon_position, solar_incidence_model, zero_negative_solar_incidence_angle, horizon_profile, shading_model, shading_states, solar_time_model, solar_constant, eccentricity_phase_offset, eccentricity_amplitude, dtype, array_backend, validate_output, verbose, log, fingerprint)\u001b[39m\n\u001b[32m 273\u001b[39m global_inclined_irradiance_series = calculate_global_inclined_irradiance_hofierka(\n\u001b[32m 274\u001b[39m longitude=longitude,\n\u001b[32m 275\u001b[39m latitude=latitude,\n\u001b[32m (...)\u001b[39m\u001b[32m 303\u001b[39m fingerprint=fingerprint,\n\u001b[32m 304\u001b[39m )\n\u001b[32m 305\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m306\u001b[39m global_inclined_irradiance_series = \u001b[43mcalculate_clear_sky_global_inclined_irradiance_hofierka\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 307\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mlocation_arguments\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 308\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43msurface_position\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 309\u001b[39m \u001b[43m \u001b[49m\u001b[43msurface_tilt_horizontally_flat_panel_threshold\u001b[49m\u001b[43m=\u001b[49m\u001b[43msurface_tilt_horizontally_flat_panel_threshold\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 310\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mtime\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 311\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mhorizontal_irradiance\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 312\u001b[39m \u001b[43m \u001b[49m\u001b[43mlinke_turbidity_factor_series\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlinke_turbidity_factor_series\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 313\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# unrefracted_solar_zenith=unrefracted_solar_zenith,\u001b[39;49;00m\n\u001b[32m 314\u001b[39m \u001b[43m \u001b[49m\u001b[43malbedo\u001b[49m\u001b[43m=\u001b[49m\u001b[43malbedo\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 315\u001b[39m \u001b[43m \u001b[49m\u001b[43mapply_reflectivity_factor\u001b[49m\u001b[43m=\u001b[49m\u001b[43mapply_reflectivity_factor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 316\u001b[39m \u001b[43m \u001b[49m\u001b[43msolar_incidence_series\u001b[49m\u001b[43m=\u001b[49m\u001b[43msolar_incidence_series\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 317\u001b[39m \u001b[43m \u001b[49m\u001b[43msolar_altitude_series\u001b[49m\u001b[43m=\u001b[49m\u001b[43msolar_altitude_series\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 318\u001b[39m \u001b[43m \u001b[49m\u001b[43msolar_azimuth_series\u001b[49m\u001b[43m=\u001b[49m\u001b[43msolar_azimuth_series\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 319\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43msolar_positioning\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 320\u001b[39m \u001b[43m \u001b[49m\u001b[43msun_horizon_position\u001b[49m\u001b[43m=\u001b[49m\u001b[43msun_horizon_position\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 321\u001b[39m \u001b[43m \u001b[49m\u001b[43msurface_in_shade_series\u001b[49m\u001b[43m=\u001b[49m\u001b[43msurface_in_shade_series\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 322\u001b[39m \u001b[43m \u001b[49m\u001b[43mshading_states\u001b[49m\u001b[43m=\u001b[49m\u001b[43mshading_states\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 323\u001b[39m \u001b[43m \u001b[49m\u001b[43msolar_constant\u001b[49m\u001b[43m=\u001b[49m\u001b[43msolar_constant\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 324\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mearth_orbit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 325\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43marray_parameters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 326\u001b[39m \u001b[43m \u001b[49m\u001b[43mvalidate_output\u001b[49m\u001b[43m=\u001b[49m\u001b[43mvalidate_output\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 327\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43moutput_parameters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 328\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# angle_output_units=angle_output_units,\u001b[39;49;00m\n\u001b[32m 329\u001b[39m \u001b[43m \u001b[49m\u001b[43mfingerprint\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfingerprint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 330\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 332\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m verbose > DEBUG_AFTER_THIS_VERBOSITY_LEVEL:\n\u001b[32m 333\u001b[39m debug(\u001b[38;5;28mlocals\u001b[39m())\n", "\u001b[36mFile \u001b[39m\u001b[32m/spacetime/pvgis/pvgis-prototype-public/pvgisprototype/log.py:429\u001b[39m, in \u001b[36mlog_function_call..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 424\u001b[39m parent_frame = inspect.stack()[\u001b[32m1\u001b[39m]\n\u001b[32m 425\u001b[39m logger.debug(\n\u001b[32m 426\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m> Call : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunction.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() from \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.function\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() in \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.filename\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m:\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.lineno\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m, Requested : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_type\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m,\n\u001b[32m 427\u001b[39m alt=\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m> Call \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfunction.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m() from [reverse]\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.function\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m()[/reverse] in \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.filename\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m:\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparent_frame.lineno\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m, Requested : [reverse]\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_type\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m[/reverse]\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 428\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m429\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunction\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "\u001b[36mFile \u001b[39m\u001b[32m/spacetime/pvgis/pvgis-prototype-public/pvgisprototype/core/caching.py:215\u001b[39m, in \u001b[36mcustom_cached..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 212\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m cache_memory[key]\n\u001b[32m 214\u001b[39m \u001b[38;5;66;03m# Cache miss: call function and store result\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m215\u001b[39m result = \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 216\u001b[39m cache_memory[key] = result\n\u001b[32m 218\u001b[39m request_id = \u001b[38;5;28mgetattr\u001b[39m(_thread_local_storage, \u001b[33m'\u001b[39m\u001b[33mrequest_id\u001b[39m\u001b[33m'\u001b[39m, \u001b[33m'\u001b[39m\u001b[33munknown\u001b[39m\u001b[33m'\u001b[39m)\n", "\u001b[36mFile \u001b[39m\u001b[32m/spacetime/pvgis/pvgis-prototype-public/pvgisprototype/algorithms/hofierka/irradiance/shortwave/clear_sky/inclined.py:376\u001b[39m, in \u001b[36mcalculate_clear_sky_global_inclined_irradiance_hofierka\u001b[39m\u001b[34m(longitude, latitude, elevation, surface_orientation, surface_tilt, surface_tilt_horizontally_flat_panel_threshold, timestamps, timezone, global_horizontal_irradiance, direct_horizontal_irradiance, linke_turbidity_factor_series, adjust_for_atmospheric_refraction, albedo, apply_reflectivity_factor, solar_altitude_series, solar_azimuth_series, solar_incidence_series, solar_position_model, surface_in_shade_series, sun_horizon_position, shading_states, solar_time_model, solar_constant, eccentricity_phase_offset, eccentricity_amplitude, dtype, array_backend, validate_output, verbose, log, fingerprint)\u001b[39m\n\u001b[32m 368\u001b[39m logger.info(\n\u001b[32m 369\u001b[39m \u001b[33m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mi [bold]Calculating[/bold] the [magenta]global inclined irradiance[/magenta] ..\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 370\u001b[39m )\n\u001b[32m 371\u001b[39m global_inclined_irradiance_series[mask_above_horizon_not_in_shade] += (\n\u001b[32m 372\u001b[39m direct_inclined_irradiance_series.value[mask_above_horizon_not_in_shade]\n\u001b[32m 373\u001b[39m )\n\u001b[32m 374\u001b[39m global_inclined_irradiance_series[mask_above_horizon] += (\n\u001b[32m 375\u001b[39m + diffuse_inclined_irradiance_series.value[mask_above_horizon]\n\u001b[32m--> \u001b[39m\u001b[32m376\u001b[39m + \u001b[43mground_reflected_inclined_irradiance_series\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m[\u001b[49m\u001b[43mmask_above_horizon\u001b[49m\u001b[43m]\u001b[49m\n\u001b[32m 377\u001b[39m )\n\u001b[32m 378\u001b[39m global_inclined_reflectivity_series = (\n\u001b[32m 379\u001b[39m direct_inclined_irradiance_series.reflected\n\u001b[32m 380\u001b[39m + diffuse_inclined_irradiance_series.reflected\n\u001b[32m 381\u001b[39m + ground_reflected_inclined_irradiance_series.reflected\n\u001b[32m 382\u001b[39m )\n\u001b[32m 383\u001b[39m global_inclined_irradiance_before_reflectivity_series = (\n\u001b[32m 384\u001b[39m direct_inclined_irradiance_series.value_before_reflectivity\n\u001b[32m 385\u001b[39m + diffuse_inclined_irradiance_series.value_before_reflectivity\n\u001b[32m 386\u001b[39m + ground_reflected_inclined_irradiance_series.value_before_reflectivity\n\u001b[32m 387\u001b[39m )\n", "\u001b[31mIndexError\u001b[39m: boolean index did not match indexed array along axis 0; size of axis is 0 but size of corresponding boolean axis is 25" ] } ], "source": [ "graph_power_output(longitude = longitude,\n", " latitude = latitude,\n", " elevation = elevation, \n", " timestamps = timestamps,\n", " timezone = timezone,\n", " spectral_factor_series = spectral_factor_series,\n", " photovoltaic_module = photovoltaic_module,\n", " temperature_series = temperature_series,\n", " wind_speed_series = wind_speed_series,\n", " linke_turbidity_factor_series = linke_turbidity_factor_series,\n", " mode = mode,\n", " surface_orientation = SurfaceOrientation(value=(surface_orientation), unit='radians'),\n", " optimal_surface_tilt = result['Surface Tilt'].value,\n", " optimal_pv_power = result['Mean PV Power'] \n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Optimal Tilt over a year \n", "\n", "In this example, we optimize the tilt of the panel for the year 2010, considering the same panel orientation as before. First we need to define the new timestamps." ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [], "source": [ "start_time = '2010-01-01'\n", "end_time = '2010-12-31'\n", "timestamps = generate_datetime_series(start_time=start_time, end_time=end_time, frequency=\"h\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We run the optimizer" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'optimize_angles' is not defined", "output_type": "error", "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mNameError\u001b[39m Traceback (most recent call last)", "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[78]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m result = \u001b[43moptimize_angles\u001b[49m(longitude = longitude,\n\u001b[32m 2\u001b[39m latitude = latitude,\n\u001b[32m 3\u001b[39m elevation = elevation, \n\u001b[32m 4\u001b[39m timestamps = timestamps,\n\u001b[32m 5\u001b[39m timezone = timezone,\n\u001b[32m 6\u001b[39m spectral_factor_series = spectral_factor_series,\n\u001b[32m 7\u001b[39m photovoltaic_module = photovoltaic_module,\n\u001b[32m 8\u001b[39m temperature_series = temperature_series,\n\u001b[32m 9\u001b[39m wind_speed_series = wind_speed_series,\n\u001b[32m 10\u001b[39m linke_turbidity_factor_series = linke_turbidity_factor_series,\n\u001b[32m 11\u001b[39m mode = mode,\n\u001b[32m 12\u001b[39m surface_orientation = surface_orientation\n\u001b[32m 13\u001b[39m )\n\u001b[32m 14\u001b[39m \u001b[38;5;28mprint\u001b[39m(result)\n", "\u001b[31mNameError\u001b[39m: name 'optimize_angles' is not defined" ] } ], "source": [ "result = optimize_angles(longitude = longitude,\n", " latitude = latitude,\n", " elevation = elevation, \n", " timestamps = timestamps,\n", " timezone = timezone,\n", " spectral_factor_series = spectral_factor_series,\n", " photovoltaic_module = photovoltaic_module,\n", " temperature_series = temperature_series,\n", " wind_speed_series = wind_speed_series,\n", " linke_turbidity_factor_series = linke_turbidity_factor_series,\n", " mode = mode,\n", " surface_orientation = surface_orientation\n", " )\n", "print(result)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And now we plot the PV Power" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "ename": "KeyError", "evalue": "'surface_tilt'", "output_type": "error", "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mKeyError\u001b[39m Traceback (most recent call last)", "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[79]\u001b[39m\u001b[32m, line 13\u001b[39m\n\u001b[32m 1\u001b[39m graph_power_output(longitude = longitude,\n\u001b[32m 2\u001b[39m latitude = latitude,\n\u001b[32m 3\u001b[39m elevation = elevation, \n\u001b[32m 4\u001b[39m timestamps = timestamps,\n\u001b[32m 5\u001b[39m timezone = timezone,\n\u001b[32m 6\u001b[39m spectral_factor_series = spectral_factor_series,\n\u001b[32m 7\u001b[39m photovoltaic_module = photovoltaic_module,\n\u001b[32m 8\u001b[39m temperature_series = temperature_series,\n\u001b[32m 9\u001b[39m wind_speed_series = wind_speed_series,\n\u001b[32m 10\u001b[39m linke_turbidity_factor_series = linke_turbidity_factor_series,\n\u001b[32m 11\u001b[39m mode = mode,\n\u001b[32m 12\u001b[39m surface_orientation = SurfaceOrientation(value=(surface_orientation), unit=\u001b[33m'\u001b[39m\u001b[33mradians\u001b[39m\u001b[33m'\u001b[39m),\n\u001b[32m---> \u001b[39m\u001b[32m13\u001b[39m optimal_surface_tilt = \u001b[43mresult\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43msurface_tilt\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m]\u001b[49m.value,\n\u001b[32m 14\u001b[39m optimal_pv_power = result[\u001b[33m'\u001b[39m\u001b[33mmean_power_output\u001b[39m\u001b[33m'\u001b[39m] \n\u001b[32m 15\u001b[39m )\n", "\u001b[31mKeyError\u001b[39m: 'surface_tilt'" ] } ], "source": [ "graph_power_output(longitude = longitude,\n", " latitude = latitude,\n", " elevation = elevation, \n", " timestamps = timestamps,\n", " timezone = timezone,\n", " spectral_factor_series = spectral_factor_series,\n", " photovoltaic_module = photovoltaic_module,\n", " temperature_series = temperature_series,\n", " wind_speed_series = wind_speed_series,\n", " linke_turbidity_factor_series = linke_turbidity_factor_series,\n", " mode = mode,\n", " surface_orientation = SurfaceOrientation(value=(surface_orientation), unit='radians'),\n", " optimal_surface_tilt = result['surface_tilt'].value,\n", " optimal_pv_power = result['mean_power_output'] \n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Optimal Tilt & Orientation angles over 15 years\n", "\n", "In this last example, we will optimize the tilt and orientation of the panel from 2005 to 2010. Let's define the new timestamps, and change our mode to \"Tilt and Orientation\"" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "start_time = '2005-01-01'\n", "end_time = '2020-01-01'\n", "timestamps = generate_datetime_series(start_time=start_time, end_time=end_time, frequency=\"h\")\n", "mode = SurfacePositionOptimizerMode.Tilt_and_Orientation" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'surface_orientation': SurfaceOrientation(value=3.141592653589793, unit='radians', min_radians=0, max_radians=6.283185307179586, min_degrees=0, max_degrees=360, optimal=True, optimizer='SHGO'), 'surface_tilt': SurfaceTilt(value=0.7853981633974483, unit='radians', min_radians=0, max_radians=1.5707963267948966, min_degrees=0, max_degrees=90, optimal=True, optimizer='SHGO'), 'mean_power_output': 263.25497}\n" ] } ], "source": [ "result = optimize_angles(longitude = longitude,\n", " latitude = latitude,\n", " elevation = elevation, \n", " timestamps = timestamps,\n", " timezone = timezone,\n", " spectral_factor_series = spectral_factor_series,\n", " photovoltaic_module = photovoltaic_module,\n", " temperature_series = temperature_series,\n", " wind_speed_series = wind_speed_series,\n", " linke_turbidity_factor_series = linke_turbidity_factor_series,\n", " mode = mode,\n", " )\n", "\n", "print(result)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "graph_power_output(longitude = longitude,\n", " latitude = latitude,\n", " elevation = elevation, \n", " timestamps = timestamps,\n", " timezone = timezone,\n", " spectral_factor_series = spectral_factor_series,\n", " photovoltaic_module = photovoltaic_module,\n", " temperature_series = temperature_series,\n", " wind_speed_series = wind_speed_series,\n", " linke_turbidity_factor_series = linke_turbidity_factor_series,\n", " mode = mode,\n", " optimal_surface_tilt = result['surface_tilt'].value,\n", " optimal_surface_orientation= result['surface_orientation'].value,\n", " optimal_pv_power = result['mean_power_output'] \n", " )" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.10" } }, "nbformat": 4, "nbformat_minor": 4 }