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[BUG]: modelchain fills nan with 0

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难度
2/5
预计耗时
1-3 小时
新手友好度
54/100
Issue 类型
缺陷
描述清晰度
基本清楚
活跃度
活跃
技术栈
pandas, python
领域
data

调研方向

Start in pvlib/modelchain.py at the two fillna(0) calls linked in the issue (around lines 668 and 769), then read the related tests to understand their intended behavior. Reproduce the reported case and check whether those calls replace NaNs in the AC results; done means NaNs are preserved without breaking existing ModelChain tests.

由索引模型根据 Issue 内容生成。

描述

Describe the bug

We fillna(0) twice in modelchain.py
https://github.com/pvlib/pvlib-python/blob/9a0ad5504d821a81ec2a4531b40034794c6c42bd/pvlib/modelchain.py#L769
https://github.com/pvlib/pvlib-python/blob/9a0ad5504d821a81ec2a4531b40034794c6c42bd/pvlib/modelchain.py#L668

I can open a PR deleting these lines, which would make more sense to me, unless there was a specific reason to do so ?

To Reproduce

def calculate_pv_system_production(
    pv_system: SimplifiedPVSystem, solar_inputs: SolarInputs
) -> np.ndarray:
    """
    Returns AC power output in kW using the PVWatts model.
    """
    # 1. Location
    location = pvlib.location.Location(
        latitude=pv_system.coordinates.latitude,
        longitude=pv_system.coordinates.longitude,
        tz=str(pv_system.timezone),
        altitude=pv_system.coordinates.altitude,
    )

    # 2. System
    system = pvlib.pvsystem.PVSystem(  # todo review all of these parameters with dict
        surface_tilt=pv_system.surface_tilt,
        surface_azimuth=pv_system.surface_azimuth,
        module_parameters={
            "pdc0": pv_system.solar_power_kwp * 1000,  # W peak DC
            "gamma_pdc": pv_system.temp_coefficient,
        },
        inverter_parameters={
            "pdc0": pv_system.solar_power_kwp * 1000,
            "eta_inv_nom": pv_system.inverter_efficiency,
        },
        temperature_model_parameters=pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS[
            "sapm"
        ]["open_rack_glass_glass"],
    )

    # 3. ModelChain
    mc = pvlib.modelchain.ModelChain(
        system,
        location,
        dc_model="pvwatts",
        ac_model="pvwatts",
        aoi_model="physical",
        spectral_model="no_loss",
        losses_model="pvwatts",
    )

    # 4. Run model — pvlib computes sun position internally from location + times
    weather_data = {
        "dni": solar_inputs.dni_wm2,
        "dhi": solar_inputs.dhi_wm2,
        "ghi": solar_inputs.ghi_wm2,
    }
    if solar_inputs.outdoor_air_temp_c is not None:
        weather_data["temp_air"] = solar_inputs.outdoor_air_temp_c

    solar_inputs_pvlib_format = pd.DataFrame(
        index=solar_inputs.ts,
        data=weather_data,
    )

    mc.run_model(solar_inputs_pvlib_format)

    # 5. Return AC power in kW
    return (mc.results.ac / 1000).to_numpy()

Expected behavior
Don't fill NaNs with 0, keep NaNs

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Versions:

  • pvlib.__version__: 0.15.2
  • pandas.__version__:
  • python: 3.10
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Python
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  3. Fork 仓库，在一个分支上完成修改。
  4. 提交 Pull Request，并在描述里引用这个 Issue 编号。

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