test_wake_losses.py

"""
SPDX-FileCopyrightText: 2019 oemof developer group <contact@oemof.org>
SPDX-License-Identifier: MIT
"""

import pandas as pd
import numpy as np
import pytest
from pandas.util.testing import assert_series_equal

from windpowerlib.wake_losses import (
    reduce_wind_speed,
    get_wind_efficiency_curve,
)


class TestWakeLosses:
    def test_reduce_wind_speed(self):
        parameters = {
            "wind_speed": pd.Series(np.arange(0, 26, 1.0)),
            "wind_efficiency_curve_name": "dena_mean",
        }
        wind_speed_exp = pd.Series(
            [
                0.0,
                0.9949534234119396,
                1.9897327884892086,
                2.9843374545454546,
                3.807636264984227,
                4.714931284760845,
                5.642507531914893,
                6.607021108049704,
                7.592423167192429,
                8.59498170212766,
                9.606135658475111,
                10.619828799086758,
                11.641291957894737,
                12.674012890137966,
                13.709490666666666,
                14.742508260567297,
                15.773293013157893,
                16.794615009724474,
                17.817683032858028,
                18.85294996704484,
                19.86509539493748,
                20.858807854510186,
                21.854369681134507,
                22.850700350710902,
                23.85962037735849,
                24.958125,
            ]
        )
        assert_series_equal(reduce_wind_speed(**parameters), wind_speed_exp)

        # Raise ValueError - misspelling
        with pytest.raises(ValueError):
            parameters["wind_efficiency_curve_name"] = "misspelled"
            reduce_wind_speed(**parameters)
        with pytest.raises(ValueError):
            parameters["wind_efficiency_curve_name"] = "dena_misspelled"
            reduce_wind_speed(**parameters)

    def test_get_wind_efficiency_curve_one(self):
        """Test get_wind_efficiency_curve() for one curve."""
        wec = get_wind_efficiency_curve("dena_mean").sum()
        wec_exp = pd.Series(
            {"efficiency": 162.45047, "wind_speed": 1915.23620}
        )
        assert_series_equal(wec.sort_index(), wec_exp.sort_index())

    def test_get_wind_efficiency_curve_all(self):
        """Test get_wind_efficiency_curve() for all curves."""
        wec_all_sum = int(get_wind_efficiency_curve("all").sum().round().sum())
        assert wec_all_sum == 12145

    def test_get_wind_efficiency_curve_list(self):
        """Test get_wind_efficiency_curve() for all curves."""
        wec_all_sum = int(
            get_wind_efficiency_curve(["dena_mean", "knorr_mean"])
            .sum()
            .round()
            .sum()
        )
        assert wec_all_sum == 3568