minor changes

component_test_connectors/heat_pump_connection_read_data.py

@@ -0,0 +1,7 @@
+from heat_pump import HeatPump
+
+hp_master = HeatPump(device_name='hp_master', ip_address='10.0.0.10', port=502, excel_path="../modbus_registers/heat_pump_registers.xlsx")
+
+state = hp_master.get_state()
+
+print(state)

component_test_connectors/heat_pump_connection_sg_ready.py

@@ -0,0 +1,49 @@
+from pymodbus.client import ModbusTcpClient
+
+def switch_sg_ready_mode(ip, port, mode):
+    """
+    Register 300: 1=BUS 0= Hardware Kontakte
+    Register 301 & 302:
+        0-0= Kein Offset
+        0-1 Boiler und Heizung Offset
+        1-1 Boiler Offset + E-Einsatz Sollwert Erhöht
+        1-0 SG EVU Sperre
+    :param ip:
+    :param mode:
+    'mode1' = [True, False, False] => SG Ready deactivated
+    'mode2' = [True, False, True] => SG ready activated for heatpump only
+    'mode3' = [True, True, True] => SG ready activated for heatpump and heat rod
+    :return:
+    """
+    client = ModbusTcpClient(ip, port=port)
+    if not client.connect():
+        print("Verbindung zur Wärmepumpe fehlgeschlagen.")
+        return
+
+    mode_code = None
+    if mode == 'mode1':
+        mode_code = [True, False, False]
+    elif mode == 'mode2':
+        mode_code = [True, False, True]
+    elif mode == 'mode3':
+        mode_code = [True, True, True]
+    else:
+        print('Uncorrect or no string for mode!')
+
+    try:
+        response_300 = client.write_coil(300, mode_code[0])
+        response_301 = client.write_coil(301, mode_code[1])
+        response_302 = client.write_coil(302, mode_code[2])
+
+        # Optional: Rückmeldungen prüfen
+        for addr, resp in zip([300, 301, 302], [response_300, response_301, response_302]):
+            if resp.isError():
+                print(f"Fehler beim Schreiben von Coil {addr}: {resp}")
+            else:
+                print(f"Coil {addr} erfolgreich geschrieben.")
+
+    finally:
+        client.close()
+
+if '__name__' == '__main__':
+    switch_sg_ready_mode(ip='10.0.0.10', port=502, mode='mode2')

data_base_operations/transform_old_db_to_new.py

@@ -0,0 +1,213 @@
+import os, re, math, time
+from datetime import datetime, timezone, timedelta
+
+import pandas as pd
+from influxdb_client import InfluxDBClient, Point, WritePrecision
+from influxdb_client.client.write_api import SYNCHRONOUS
+from influxdb_client.rest import ApiException
+
+
+# -----------------------
+# CONFIG
+# -----------------------
+INFLUX_URL = "http://192.168.1.146:8086"
+INFLUX_ORG = "allmende"
+INFLUX_TOKEN = os.environ.get("INFLUX_TOKEN", "Cw_naEZyvJ3isiAh1P4Eq3TsjcHmzzDFS7SlbKDsS6ZWL04fMEYixWqtNxGThDdG27S9aW5g7FP9eiq5z1rsGA==")
+
+SOURCE_BUCKET = "allmende_db"
+TARGET_BUCKET = "allmende_db_v2"
+
+MEASUREMENTS = [
+    "hp_master", "hp_slave", "pv_forecast", "sg_ready",
+    "solaredge_master", "solaredge_meter", "solaredge_slave", "wohnung_2_6"
+]
+
+START_DT = datetime(2025, 6, 1, tzinfo=timezone.utc)
+STOP_DT = datetime.now(timezone.utc)
+WINDOW = timedelta(days=1)
+
+EXCEL_PATH = "../modbus_registers/heat_pump_registers.xlsx"
+EXCEL_SHEET = "Register_Map"
+
+BATCH_SIZE = 1000
+MAX_RETRIES = 8
+
+
+# -----------------------
+# Helpers
+# -----------------------
+def normalize(s) -> str:
+    s = "" if s is None else str(s).strip()
+    return re.sub(r"\s+", " ", s)
+
+def is_invalid_sentinel(v: float) -> bool:
+    return v in (-999.9, -999.0, 30000.0, 32767.0, 65535.0)
+
+def ensure_bucket(client: InfluxDBClient, name: str):
+    bapi = client.buckets_api()
+    if bapi.find_bucket_by_name(name):
+        return
+    bapi.create_bucket(bucket_name=name, org=INFLUX_ORG, retention_rules=None)
+
+def build_field_type_map_from_excel(path: str) -> dict[str, str]:
+    df = pd.read_excel(path, sheet_name=EXCEL_SHEET)
+    df = df[df["Register_Type"].astype(str).str.upper() == "IR"].copy()
+    df["Address"] = df["Address"].astype(int)
+    df["Description"] = df["Description"].fillna("").astype(str)
+    df["Tag_Name"] = df["Tag_Name"].fillna("").astype(str)
+    df["Data_Type"] = df["Data_Type"].fillna("").astype(str)
+
+    m: dict[str, str] = {}
+    for _, r in df.iterrows():
+        addr = int(r["Address"])
+        desc = normalize(r["Description"])
+        tag  = normalize(r["Tag_Name"])
+        dtp  = normalize(r["Data_Type"]).upper()
+        if tag:
+            m[tag] = dtp
+        old_key = normalize(f"{addr} - {desc}".strip(" -"))
+        if old_key:
+            m[old_key] = dtp
+    return m
+
+def coerce_value_to_dtype(v, dtype: str):
+    if v is None:
+        return None
+    dtp = (dtype or "").upper()
+
+    if isinstance(v, (int, float)):
+        fv = float(v)
+        if math.isnan(fv) or math.isinf(fv):
+            return None
+
+    if dtp in ("BOOL", "BOOLEAN"):
+        if isinstance(v, bool): return v
+        if isinstance(v, (int, float)): return bool(int(v))
+        return None
+
+    if dtp.startswith("INT") or dtp.startswith("UINT"):
+        if isinstance(v, bool): return int(v)
+        if isinstance(v, (int, float)): return int(float(v))
+        return None
+
+    if dtp.startswith("FLOAT") or dtp in ("DOUBLE",):
+        if isinstance(v, bool): return float(int(v))
+        if isinstance(v, (int, float)): return float(v)
+        return None
+
+    return None
+
+def write_with_retry(write_api, batch):
+    delay = 1.0
+    last_msg = ""
+    for _ in range(MAX_RETRIES):
+        try:
+            write_api.write(bucket=TARGET_BUCKET, org=INFLUX_ORG, record=batch)
+            return
+        except ApiException as e:
+            last_msg = getattr(e, "body", "") or str(e)
+            status = getattr(e, "status", None)
+            if "timeout" in last_msg.lower() or status in (429, 500, 502, 503, 504):
+                time.sleep(delay)
+                delay = min(delay * 2, 30)
+                continue
+            raise
+    raise RuntimeError(f"Write failed after {MAX_RETRIES} retries: {last_msg}")
+
+def window_already_migrated(query_api, measurement: str, start: datetime, stop: datetime) -> bool:
+    # Prüft: gibt es im Zielbucket im Fenster mindestens 1 Punkt?
+    flux = f'''
+from(bucket: "{TARGET_BUCKET}")
+  |> range(start: time(v: "{start.isoformat()}"), stop: time(v: "{stop.isoformat()}"))
+  |> filter(fn: (r) => r._measurement == "{measurement}")
+  |> limit(n: 1)
+'''
+    tables = query_api.query(flux, org=INFLUX_ORG)
+    for t in tables:
+        if t.records:
+            return True
+    return False
+
+def migrate_window(query_api, write_api, measurement: str,
+                   start: datetime, stop: datetime,
+                   type_map: dict[str, str],
+                   do_type_cast: bool) -> int:
+    flux = f'''
+from(bucket: "{SOURCE_BUCKET}")
+  |> range(start: time(v: "{start.isoformat()}"), stop: time(v: "{stop.isoformat()}"))
+  |> filter(fn: (r) => r._measurement == "{measurement}")
+  |> keep(columns: ["_time","_measurement","_field","_value"])
+'''
+    tables = query_api.query(flux, org=INFLUX_ORG)
+
+    batch, written = [], 0
+    for table in tables:
+        for rec in table.records:
+            t = rec.get_time()
+            field = normalize(rec.get_field())
+            value = rec.get_value()
+            if value is None:
+                continue
+
+            if do_type_cast:
+                dtp = type_map.get(field)
+                if dtp:
+                    cv = coerce_value_to_dtype(value, dtp)
+                    if cv is None:
+                        continue
+                    if isinstance(cv, (int, float)) and is_invalid_sentinel(float(cv)):
+                        continue
+                    value = cv
+                # kein Mapping -> unverändert schreiben
+
+            batch.append(Point(measurement).field(field, value).time(t, WritePrecision.NS))
+
+            if len(batch) >= BATCH_SIZE:
+                write_with_retry(write_api, batch)
+                written += len(batch)
+                batch = []
+
+    if batch:
+        write_with_retry(write_api, batch)
+        written += len(batch)
+
+    return written
+
+
+# -----------------------
+# Main
+# -----------------------
+def main():
+    if not INFLUX_TOKEN:
+        raise RuntimeError("INFLUX_TOKEN fehlt (Env-Var INFLUX_TOKEN setzen).")
+
+    with InfluxDBClient(url=INFLUX_URL, token=INFLUX_TOKEN, org=INFLUX_ORG, timeout=900_000) as client:
+        ensure_bucket(client, TARGET_BUCKET)
+
+        type_map = build_field_type_map_from_excel(EXCEL_PATH)
+        query_api = client.query_api()
+        write_api = client.write_api(write_options=SYNCHRONOUS)
+
+        for meas in MEASUREMENTS:
+            do_cast = meas in ("hp_master", "hp_slave")
+            cur, total = START_DT, 0
+            print(f"\n== {meas}  (cast={'ON' if do_cast else 'OFF'}) ==")
+
+            while cur < STOP_DT:
+                nxt = min(cur + WINDOW, STOP_DT)
+
+                if window_already_migrated(query_api, meas, cur, nxt):
+                    print(f"{cur.isoformat()} -> {nxt.isoformat()} : SKIP (existiert schon)")
+                    cur = nxt
+                    continue
+
+                n = migrate_window(query_api, write_api, meas, cur, nxt, type_map, do_cast)
+                total += n
+                print(f"{cur.isoformat()} -> {nxt.isoformat()} : {n} (gesamt {total})")
+                cur = nxt
+
+            print(f"== Fertig {meas}: {total} Punkte ==")
+
+
+if __name__ == "__main__":
+    main()

heat_pump.py

@@ -1,64 +1,173 @@
 from pymodbus.client import ModbusTcpClient
 import pandas as pd
 import time
+import struct
+import math
+
 
 class HeatPump:
-    def __init__(self, device_name: str, ip_address: str, port: int=502):
+    def __init__(self, device_name: str, ip_address: str, port: int = 502,
+                 excel_path: str = "modbus_registers/heat_pump_registers.xlsx",
+                 sheet_name: str = "Register_Map"):
         self.device_name = device_name
         self.ip = ip_address
         self.port = port
-        self.client = None
+        self.client = ModbusTcpClient(self.ip, port=self.port)
-        self.connect_to_modbus()
-        self.registers = None
-        self.get_registers()
 
-    def connect_to_modbus(self):
+        self.excel_path = excel_path
-        port = self.port
+        self.sheet_name = sheet_name
-        self.client = ModbusTcpClient(self.ip, port=port)
+        self.registers = self.get_registers()
-        try:
+
-            if not self.client.connect():
+    # -------------
+    # Connection
+    # -------------
+    def connect(self) -> bool:
+        ok = self.client.connect()
+        if not ok:
             print("Verbindung zur Wärmepumpe fehlgeschlagen.")
-                exit(1)
+        return ok
-            print("Verbindung zur Wärmepumpe erfolgreich.")
+
-        except KeyboardInterrupt:
+    def close(self):
-            print("Beendet durch Benutzer (Ctrl+C).")
+        try:
-        finally:
             self.client.close()
+        except Exception:
+            pass
 
-    def get_registers(self):
+    # -------------
-        # Excel-Datei mit den Input-Registerinformationen
+    # Excel parsing
-        excel_path = "modbus_registers/heat_pump_registers.xlsx"
+    # -------------
-        xls = pd.ExcelFile(excel_path)
+    def get_registers(self) -> dict:
-        df_input_registers = xls.parse('04 Input Register')
+        df = pd.read_excel(self.excel_path, sheet_name=self.sheet_name)
+        df = df[df["Register_Type"].astype(str).str.upper() == "IR"].copy()
 
-        # Relevante Spalten bereinigen
+        df["Address"] = df["Address"].astype(int)
-        df_clean = df_input_registers[['MB Adresse', 'Variable', 'Beschreibung', 'Variabel Typ']].dropna()
+        df["Length"] = df["Length"].astype(int)
-        df_clean['MB Adresse'] = df_clean['MB Adresse'].astype(int)
+        df["Data_Type"] = df["Data_Type"].astype(str).str.upper()
+        df["Byteorder"] = df["Byteorder"].astype(str).str.upper()
 
-        # Dictionary aus Excel erzeugen
+        df["Scaling"] = df.get("Scaling", 1.0)
-        self.registers = {
+        df["Scaling"] = df["Scaling"].fillna(1.0).astype(float)
-            row['MB Adresse']: {
+
-                'desc': row['Beschreibung'],
+        df["Offset"] = df.get("Offset", 0.0)
-                'type': 'REAL' if row['Variabel Typ'] == 'REAL' else 'INT'
+        df["Offset"] = df["Offset"].fillna(0.0).astype(float)
-            }
+
-            for _, row in df_clean.iterrows()
+        regs = {}
+        for _, row in df.iterrows():
+            regs[int(row["Address"])] = {
+                "length": int(row["Length"]),
+                "data_type": row["Data_Type"],
+                "byteorder": row["Byteorder"],
+                "scaling": float(row["Scaling"]),
+                "offset": float(row["Offset"]),
+                "tag": str(row.get("Tag_Name", "")).strip(),
+                "desc": "" if pd.isna(row.get("Description")) else str(row.get("Description")).strip(),
             }
+        return regs
 
-    def get_state(self):
+    # -------------
-        data = {}
+    # Byteorder handling
-        data['Zeit'] = time.strftime('%Y-%m-%d %H:%M:%S')
+    # -------------
-        for address, info in self.registers.items():
+    @staticmethod
-            reg_type = info['type']
+    def _registers_to_bytes(registers: list[int], byteorder_code: str) -> bytes:
-            result = self.client.read_input_registers(address, count=2 if reg_type == 'REAL' else 1)
+        """
+        registers: Liste von uint16 (0..65535), wie pymodbus sie liefert.
+        byteorder_code: AB, ABCD, CDAB, BADC, DCBA (gemäß Template)
+        Rückgabe: bytes in der Reihenfolge, wie sie für struct.unpack benötigt werden.
+        """
+        code = (byteorder_code or "ABCD").upper()
+
+        # Pro Register: 16-bit => zwei Bytes (MSB, LSB)
+        words = [struct.pack(">H", r & 0xFFFF) for r in registers]  # big endian pro Wort
+
+        if len(words) == 1:
+            w = words[0]  # b'\xAA\xBB'
+            if code in ("AB", "ABCD", "CDAB"):
+                return w
+            if code == "BADC":  # byte swap
+                return w[::-1]
+            if code == "DCBA":  # byte swap (bei 16-bit identisch zu BADC)
+                return w[::-1]
+            return w
+
+        # 32-bit (2 words) oder 64-bit (4 words): Word/Byte swaps abbilden
+        # words[0] = high word bytes, words[1] = low word bytes (in Modbus-Reihenfolge gelesen)
+        if code == "ABCD":
+            ordered = words
+        elif code == "CDAB":
+            # word swap
+            ordered = words[1:] + words[:1]
+        elif code == "BADC":
+            # byte swap innerhalb jedes Words
+            ordered = [w[::-1] for w in words]
+        elif code == "DCBA":
+            # word + byte swap
+            ordered = [w[::-1] for w in (words[1:] + words[:1])]
+        else:
+            ordered = words
+
+        return b"".join(ordered)
+
+    @staticmethod
+    def _decode_by_type(raw_bytes: bytes, data_type: str):
+        dt = (data_type or "").upper()
+
+        # struct: > = big endian, < = little endian
+        # Wir liefern raw_bytes bereits in der richtigen Reihenfolge; daher nutzen wir ">" konsistent.
+        if dt == "UINT16":
+            return struct.unpack(">H", raw_bytes[:2])[0]
+        if dt == "INT16":
+            return struct.unpack(">h", raw_bytes[:2])[0]
+        if dt == "UINT32":
+            return struct.unpack(">I", raw_bytes[:4])[0]
+        if dt == "INT32":
+            return struct.unpack(">i", raw_bytes[:4])[0]
+        if dt == "FLOAT32":
+            return struct.unpack(">f", raw_bytes[:4])[0]
+        if dt == "FLOAT64":
+            return struct.unpack(">d", raw_bytes[:8])[0]
+
+        raise ValueError(f"Unbekannter Data_Type: {dt}")
+
+    def _decode_value(self, registers: list[int], meta: dict):
+        raw = self._registers_to_bytes(registers, meta["byteorder"])
+        val = self._decode_by_type(raw, meta["data_type"])
+        return (val * meta["scaling"]) + meta["offset"]
+
+    # -------------
+    # Reading
+    # -------------
+    def get_state(self) -> dict:
+        data = {"Zeit": time.strftime("%Y-%m-%d %H:%M:%S")}
+
+        if not self.connect():
+            data["error"] = "connect_failed"
+            return data
+
+        try:
+            for address, meta in self.registers.items():
+                count = int(meta["length"])
+                result = self.client.read_input_registers(address, count=count)
                 if result.isError():
                     print(f"Fehler beim Lesen von Adresse {address}: {result}")
                     continue
 
-            if reg_type == 'REAL':
+                try:
-                value = result.registers[0] / 10.0
+                    value = self._decode_value(result.registers, meta)
-            else:
+                except Exception as e:
-                value = result.registers[0]
+                    print(f"Decode-Fehler an Adresse {address} ({meta.get('tag','')}): {e}")
+                    continue
+
+                # Optional filter
+                # if self._is_invalid_sentinel(value):
+                #     continue
+                value = float(value)
+                desc = meta.get("desc") or ""
+                field_name = f"{address} - {desc}".strip(" -")
+                data[field_name] = float(value)
+
+                print(f"Adresse {address} - {desc}: {value}")
+
+        finally:
+            self.close()
 
-            print(f"Adresse {address} - {info['desc']}: {value}")
-            data[f"{address} - {info['desc']}"] = value
         return data

main.py

@@ -1,19 +1,12 @@
 import time
 from datetime import datetime
 from data_base_influx import DataBaseInflux
-from forecaster.weather_forecaster import WeatherForecaster
 from heat_pump import HeatPump
 from pv_inverter import PvInverter
-from simulators.pv_plant_simulator import PvWattsSubarrayConfig, PvWattsPlant
 from solaredge_meter import SolaredgeMeter
 from shelly_pro_3m import ShellyPro3m
 from energysystem import EnergySystem
 from sg_ready_controller import SgReadyController
-from pvlib.location import Location
-import datetime as dt
-
-# For dev-System run in terminal: ssh -N -L 127.0.0.1:8111:10.0.0.10:502 pi@192.168.1.146
-# For productive-System change IP-adress in heatpump to '10.0.0.10' and port to 502
 
 interval_seconds = 10
 
@@ -23,7 +16,7 @@ db = DataBaseInflux(
     url="http://192.168.1.146:8086",
     token="Cw_naEZyvJ3isiAh1P4Eq3TsjcHmzzDFS7SlbKDsS6ZWL04fMEYixWqtNxGThDdG27S9aW5g7FP9eiq5z1rsGA==",
     org="allmende",
-    bucket="allmende_db"
+    bucket="allmende_db_v3"
 )
 
 hp_master = HeatPump(device_name='hp_master', ip_address='10.0.0.10', port=502)
@@ -35,24 +28,7 @@ meter = SolaredgeMeter(device_name='solaredge_meter', ip_address='192.168.1.112'
 es.add_components(hp_master, hp_slave, shelly, wr, meter)
 controller = SgReadyController(es)
 
-# FORECASTING
-latitude = 48.041
-longitude = 7.862
-TZ = "Europe/Berlin"
-HORIZON_DAYS = 2
-weather_forecaster = WeatherForecaster(latitude=latitude, longitude=longitude)
-site = Location(latitude=latitude, longitude=longitude, altitude=35, tz=TZ, name="Gundelfingen")
-
-p_module = 435
-upper_roof_north = PvWattsSubarrayConfig(name="north", pdc0_w=(29+29+21)*p_module, tilt_deg=10, azimuth_deg=20, dc_loss=0.02, ac_loss=0.01)
-upper_roof_south = PvWattsSubarrayConfig(name="south", pdc0_w=(29+21+20)*p_module, tilt_deg=10, azimuth_deg=200, dc_loss=0.02, ac_loss=0.01)
-upper_roof_east = PvWattsSubarrayConfig(name="east", pdc0_w=7*p_module, tilt_deg=10, azimuth_deg=110, dc_loss=0.02, ac_loss=0.01)
-upper_roof_west = PvWattsSubarrayConfig(name="west", pdc0_w=7*p_module, tilt_deg=10, azimuth_deg=290, dc_loss=0.02, ac_loss=0.01)
-cfgs = [upper_roof_north, upper_roof_south, upper_roof_east, upper_roof_west]
-pv_plant = PvWattsPlant(site, cfgs)
-
 now = datetime.now()
-next_forecast_at = (now + dt.timedelta(hours=1)).replace(minute=0, second=0, microsecond=0)
 while True:
     now = datetime.now()
     if now.second % interval_seconds == 0 and now.microsecond < 100_000:
@@ -65,18 +41,5 @@ while True:
             mode_as_binary = 1
         db.store_data('sg_ready', {'mode': mode_as_binary})
 
-    if now >= next_forecast_at:
-        # Start der Prognose: ab der kommenden vollen Stunde
-        start_hour_local = (now + dt.timedelta(hours=1)).replace(minute=0, second=0, microsecond=0)
-        weather = weather_forecaster.get_hourly_forecast(start_hour_local, HORIZON_DAYS)
-        total = pv_plant.get_power(weather)
-        db.store_forecasts('pv_forecast', total)
-
-        # Nächste geplante Ausführung definieren (immer volle Stunde)
-        # Falls wir durch Delay mehrere Stunden verpasst haben, hole auf:
-        while next_forecast_at <= now:
-            next_forecast_at = (next_forecast_at + dt.timedelta(hours=1)).replace(minute=0, second=0, microsecond=0)
-
-
     time.sleep(0.1)