风光功率预测与电力交易气象数据

import os
import requests
import pandas as pd

params = {
    "latitude": 41.15,
    "longitude": 114.70,
    "elevation": 1450,  # 场站海拔（m）
    "hourly": "wind_speed_100m,wind_direction_100m,wind_gusts_10m,"
              "temperature_2m,surface_pressure,relative_humidity_2m",
    "models": "ecmwf_ifs",
    "temporal_resolution": "minutely_15",
    "forecast_days": 3,
    "timezone": "Asia/Shanghai",
    "apikey": os.environ["MIRROR_EARTH_API_KEY"],
}
res = requests.get("https://api.mirror-earth.com/v1/forecast", params=params, timeout=60)
res.raise_for_status()
df = pd.DataFrame(res.json()["hourly"])  # 15 分钟一行，北京时间
print(df.head())

import os
import requests
import pandas as pd

params = {
    "latitude": 36.40,
    "longitude": 94.90,
    "hourly": "global_tilted_irradiance,shortwave_radiation,"
              "direct_normal_irradiance,diffuse_radiation,"
              "cloud_cover_low,temperature_2m,wind_speed_10m",
    "tilt": 35,     # 组件倾角
    "azimuth": 0,   # 0 正南，-90 正东，90 正西
    "models": "ecmwf_ifs",
    "temporal_resolution": "minutely_15",
    "forecast_days": 3,
    "timezone": "Asia/Shanghai",
    "apikey": os.environ["MIRROR_EARTH_API_KEY"],
}
res = requests.get("https://api.mirror-earth.com/v1/forecast", params=params, timeout=60)
res.raise_for_status()
df = pd.DataFrame(res.json()["hourly"])
print(df[["time", "global_tilted_irradiance"]].head())

import os
import time
from datetime import date, timedelta
import requests

BASE_URL = "https://api.mirror-earth.com"
headers = {"X-API-Key": os.environ["MIRROR_EARTH_API_KEY"]}
today = date.today()

payload = {
    "domain": "ecmwf_ifs",
    "hourly": ["temperature_2m", "apparent_temperature", "relative_humidity_2m",
               "wind_speed_100m", "shortwave_radiation", "precipitation"],
    "daily": [],
    "monthly": [],
    "time_range": {
        "type": "date_range",
        "start": str(today),
        "end": str(today + timedelta(days=3)),
    },
    "area": {"type": "point", "adcodes": ["370000", "320000"]},  # 山东、江苏
    "area_average": True,   # 省域面平均，不是省会点值
    "time_resolution": "minutely_15",
    "timezone": "Asia/Shanghai",
}

est = requests.post(f"{BASE_URL}/api/tasks/estimate", json=payload, headers=headers).json()["data"]
if est.get("error") or not est.get("estimate_id"):
    raise RuntimeError(est.get("error_msg") or "预估失败")
payload["estimate_id"] = est["estimate_id"]

res = requests.post(f"{BASE_URL}/api/tasks/export", json=payload, headers=headers)
res.raise_for_status()
task_id = res.json()["data"]["task_id"]

while True:
    status = requests.get(f"{BASE_URL}/api/tasks/{task_id}/status", headers=headers).json()["data"]
    if status["status"] == "completed":
        print(status["output_file"])  # 下载：GET /user_downloads/<output_file>
        break
    if status["status"] in ("failed", "cancelled"):
        raise RuntimeError(status["status"])
    time.sleep(10)

import os
import requests
import pandas as pd

params = {
    "latitude": 41.15,
    "longitude": 114.70,
    "hourly": "wind_speed_100m,shortwave_radiation,temperature_2m",
    "start_date": "2015-01-01",
    "end_date": "2024-12-31",
    "models": "era5",
    "timezone": "Asia/Shanghai",
    "apikey": os.environ["MIRROR_EARTH_API_KEY"],
}
res = requests.get("https://api.mirror-earth.com/v1/archive", params=params, timeout=300)
res.raise_for_status()
df = pd.DataFrame(res.json()["hourly"])
df["time"] = pd.to_datetime(df["time"])

monthly = df.set_index("time").resample("MS").agg({
    "wind_speed_100m": "mean",                               # 月平均风速 m/s
    "shortwave_radiation": lambda x: x.sum() * 3600 / 1e6,   # 月辐射量 MJ/m²
    "temperature_2m": "mean",
})
print(monthly.groupby(monthly.index.month).mean())  # 10 年逐月气候态