Add new daemons and debug scripts for Sigenergy and Oracle functionalities

- Implement `sigen_daemon.py` to poll Sigenergy plant metrics and store snapshots. - Create `web_daemon.py` for serving a web interface with various endpoints. - Add debug scripts: - `debug_duplicates.py` to find duplicate target times in forecast data. - `debug_energy_forecast.py` to print baseline energy forecast curves. - `debug_oracle_evaluations.py` to run the oracle evaluator. - `debug_sigen.py` to inspect stored Sigenergy plant snapshots. - `debug_weather.py` to trace resolved truth data. - `modbus_test.py` for exploring Sigenergy plants or inverters over Modbus TCP. - Introduce `oracle_evaluator.py` for evaluating stored oracle predictions against actuals. - Add TCN training scripts in `tcn` directory for training usage sequence models.
2026-04-28 08:14:00 +02:00
parent ff0c65a794
commit c8e3016fd6
55 changed files with 6385 additions and 633 deletions
@@ -0,0 +1,60 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from os import environ
+
+
+@dataclass(frozen=True)
+class EnergyForecastConfig:
+    horizon_hours: int = 24
+    oracle_step_minutes: int = 15
+    fallback_solar_peak_w: float = 10000
+    solar_peak_headroom: float = 1.05
+    solar_scale: float = 1.0
+    solar_training_days: int = 30
+    solar_min_training_samples: int = 24
+    solar_ridge_lambda: float = 0.1
+    load_lookback_minutes: int = 30
+    load_profile_days: int = 30
+    load_profile_bucket_minutes: int = 15
+    load_profile_min_samples: int = 5
+    load_recent_blend: float = 0.35
+    local_timezone: str = "Europe/Stockholm"
+
+    @classmethod
+    def from_env(cls) -> "EnergyForecastConfig":
+        return cls(
+            horizon_hours=int(environ.get("ASTRAPE_ENERGY_FORECAST_HOURS", "24")),
+            oracle_step_minutes=int(environ.get("ASTRAPE_ORACLE_STEP_MINUTES", "15")),
+            fallback_solar_peak_w=float(
+                environ.get("ASTRAPE_SOLAR_PEAK_W", "10000")
+            ),
+            solar_peak_headroom=float(
+                environ.get("ASTRAPE_SOLAR_PEAK_HEADROOM", "1.05")
+            ),
+            solar_scale=float(environ.get("ASTRAPE_SOLAR_FORECAST_SCALE", "1.0")),
+            solar_training_days=int(
+                environ.get("ASTRAPE_SOLAR_TRAINING_DAYS", "30")
+            ),
+            solar_min_training_samples=int(
+                environ.get("ASTRAPE_SOLAR_MIN_TRAINING_SAMPLES", "24")
+            ),
+            solar_ridge_lambda=float(
+                environ.get("ASTRAPE_SOLAR_RIDGE_LAMBDA", "0.1")
+            ),
+            load_lookback_minutes=int(
+                environ.get("ASTRAPE_LOAD_LOOKBACK_MINUTES", "30")
+            ),
+            load_profile_days=int(environ.get("ASTRAPE_LOAD_PROFILE_DAYS", "30")),
+            load_profile_bucket_minutes=int(
+                environ.get("ASTRAPE_LOAD_PROFILE_BUCKET_MINUTES", "15")
+            ),
+            load_profile_min_samples=int(
+                environ.get("ASTRAPE_LOAD_PROFILE_MIN_SAMPLES", "5")
+            ),
+            load_recent_blend=float(environ.get("ASTRAPE_LOAD_RECENT_BLEND", "0.35")),
+            local_timezone=environ.get(
+                "ASTRAPE_LOCAL_TIMEZONE",
+                environ.get("TZ", "Europe/Stockholm"),
+            ),
+        )