3 Commits

16 changed files with 234 additions and 558 deletions

View File

@@ -1,7 +0,0 @@
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)

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@@ -1,49 +0,0 @@
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')

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@@ -1,213 +0,0 @@
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()

View File

@@ -1,173 +1,64 @@
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,
excel_path: str = "modbus_registers/heat_pump_registers.xlsx",
sheet_name: str = "Register_Map"):
def __init__(self, device_name: str, ip_address: str, port: int=502):
self.device_name = device_name
self.ip = ip_address
self.port = port
self.client = ModbusTcpClient(self.ip, port=self.port)
self.client = None
self.connect_to_modbus()
self.registers = None
self.get_registers()
self.excel_path = excel_path
self.sheet_name = sheet_name
self.registers = self.get_registers()
# -------------
# Connection
# -------------
def connect(self) -> bool:
ok = self.client.connect()
if not ok:
def connect_to_modbus(self):
port = self.port
self.client = ModbusTcpClient(self.ip, port=port)
try:
if not self.client.connect():
print("Verbindung zur Wärmepumpe fehlgeschlagen.")
return ok
def close(self):
try:
exit(1)
print("Verbindung zur Wärmepumpe erfolgreich.")
except KeyboardInterrupt:
print("Beendet durch Benutzer (Ctrl+C).")
finally:
self.client.close()
except Exception:
pass
# -------------
# Excel parsing
# -------------
def get_registers(self) -> dict:
df = pd.read_excel(self.excel_path, sheet_name=self.sheet_name)
df = df[df["Register_Type"].astype(str).str.upper() == "IR"].copy()
def get_registers(self):
# Excel-Datei mit den Input-Registerinformationen
excel_path = "modbus_registers/heat_pump_registers.xlsx"
xls = pd.ExcelFile(excel_path)
df_input_registers = xls.parse('04 Input Register')
df["Address"] = df["Address"].astype(int)
df["Length"] = df["Length"].astype(int)
df["Data_Type"] = df["Data_Type"].astype(str).str.upper()
df["Byteorder"] = df["Byteorder"].astype(str).str.upper()
# Relevante Spalten bereinigen
df_clean = df_input_registers[['MB Adresse', 'Variable', 'Beschreibung', 'Variabel Typ']].dropna()
df_clean['MB Adresse'] = df_clean['MB Adresse'].astype(int)
df["Scaling"] = df.get("Scaling", 1.0)
df["Scaling"] = df["Scaling"].fillna(1.0).astype(float)
df["Offset"] = df.get("Offset", 0.0)
df["Offset"] = df["Offset"].fillna(0.0).astype(float)
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(),
# Dictionary aus Excel erzeugen
self.registers = {
row['MB Adresse']: {
'desc': row['Beschreibung'],
'type': 'REAL' if row['Variabel Typ'] == 'REAL' else 'INT'
}
for _, row in df_clean.iterrows()
}
return regs
# -------------
# Byteorder handling
# -------------
@staticmethod
def _registers_to_bytes(registers: list[int], byteorder_code: str) -> bytes:
"""
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)
def get_state(self):
data = {}
data['Zeit'] = time.strftime('%Y-%m-%d %H:%M:%S')
for address, info in self.registers.items():
reg_type = info['type']
result = self.client.read_input_registers(address, count=2 if reg_type == 'REAL' else 1)
if result.isError():
print(f"Fehler beim Lesen von Adresse {address}: {result}")
continue
try:
value = self._decode_value(result.registers, meta)
except Exception as e:
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()
if reg_type == 'REAL':
value = result.registers[0] / 10.0
else:
value = result.registers[0]
print(f"Adresse {address} - {info['desc']}: {value}")
data[f"{address} - {info['desc']}"] = value
return data

68
main.py
View File

@@ -1,12 +1,19 @@
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
@@ -16,30 +23,61 @@ db = DataBaseInflux(
url="http://192.168.1.146:8086",
token="Cw_naEZyvJ3isiAh1P4Eq3TsjcHmzzDFS7SlbKDsS6ZWL04fMEYixWqtNxGThDdG27S9aW5g7FP9eiq5z1rsGA==",
org="allmende",
bucket="allmende_db_v3"
bucket="allmende_db"
)
hp_master = HeatPump(device_name='hp_master', ip_address='10.0.0.10', port=502)
hp_slave = HeatPump(device_name='hp_slave', ip_address='10.0.0.11', port=502)
shelly = ShellyPro3m(device_name='wohnung_2_6', ip_address='192.168.1.121')
wr = PvInverter(device_name='solaredge_master', ip_address='192.168.1.112')
# hp_master = HeatPump(device_name='hp_master', ip_address='10.0.0.10', port=502)
# hp_slave = HeatPump(device_name='hp_slave', ip_address='10.0.0.11', port=502)
# shelly = ShellyPro3m(device_name='wohnung_2_6', ip_address='192.168.1.121')
wr_master = PvInverter(device_name='solaredge_master', ip_address='192.168.1.112', unit=1)
wr_slave = PvInverter(device_name='solaredge_slave', ip_address='192.168.1.112', unit=3)
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)
now = datetime.now()
es.add_components(wr_master, wr_slave)#hp_master, hp_slave, shelly, wr_master, wr_slave, 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:
state = es.get_state_and_store_to_database(db)
mode = controller.perform_action(heat_pump_name='hp_master', meter_name='solaredge_meter', state=state)
# mode = controller.perform_action(heat_pump_name='hp_master', meter_name='solaredge_meter', state=state)
#
# if mode == 'mode1':
# mode_as_binary = 0
# else:
# 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)
if mode == 'mode1':
mode_as_binary = 0
else:
mode_as_binary = 1
db.store_data('sg_ready', {'mode': mode_as_binary})
time.sleep(0.1)

View File

@@ -1,139 +1,155 @@
import time
import struct
import pandas as pd
from typing import Dict, Any, List, Tuple, Optional
# pv_inverter.py
# -*- coding: utf-8 -*-
from typing import Optional, Dict, Any, List
from pymodbus.client import ModbusTcpClient
from pymodbus.exceptions import ModbusIOException
import struct
import time
EXCEL_PATH = "modbus_registers/pv_inverter_registers.xlsx"
# Obergrenze: bis EXKLUSIVE 40206 (d.h. max. 40205)
MAX_ADDR_EXCLUSIVE = 40121
class PvInverter:
def __init__(self, device_name: str, ip_address: str, port: int = 502, unit: int = 1):
self.device_name = device_name
self.ip = ip_address
self.port = port
self.unit = unit
self.client: Optional[ModbusTcpClient] = None
self.registers: Dict[int, Dict[str, Any]] = {} # addr -> {"desc":..., "type":...}
self.connect_to_modbus()
self.load_registers(EXCEL_PATH)
"""
Minimaler Reader für einen SolarEdge-Inverter hinter Modbus-TCP→RTU-Gateway.
Liest nur die bekannten Register (wie im funktionierenden Skript).
Kompatibel mit pymodbus 2.5.x und 3.x kein retry_on_empty.
"""
# ---------- Verbindung ----------
def connect_to_modbus(self):
self.client = ModbusTcpClient(self.ip, port=self.port, timeout=3.0, retries=3)
def __init__(
self,
device_name: str,
ip_address: str,
port: int = 502,
unit_id: int = 1,
timeout: float = 1.5,
silent_interval: float = 0.02,
):
self.device_name = device_name
self.host = ip_address
self.port = port
self.unit = unit_id
self.timeout = timeout
self.silent_interval = silent_interval
self.client: Optional[ModbusTcpClient] = None
self._connect()
# ---------------- Verbindung ----------------
def _connect(self):
# retries=0: keine internen Mehrfachversuche
self.client = ModbusTcpClient(self.host, port=self.port, timeout=self.timeout, retries=0)
if not self.client.connect():
print("Verbindung zu Wechselrichter fehlgeschlagen.")
raise SystemExit(1)
print("✅ Verbindung zu Wechselrichter hergestellt.")
raise ConnectionError(f"Verbindung zu {self.device_name} ({self.host}:{self.port}) fehlgeschlagen.")
print(f"✅ Verbindung hergestellt zu {self.device_name} ({self.host}:{self.port}, unit={self.unit})")
def close(self):
if self.client:
self.client.close()
self.client = None
# ---------- Register-Liste ----------
def load_registers(self, excel_path: str):
xls = pd.ExcelFile(excel_path)
df = xls.parse()
# Passe Spaltennamen hier an, falls nötig:
cols = ["MB Adresse", "Beschreibung", "Variabel Typ"]
df = df[cols].dropna()
df["MB Adresse"] = df["MB Adresse"].astype(int)
# 1) Vorab-Filter: nur Adressen < 40206 übernehmen
df = df[df["MB Adresse"] < MAX_ADDR_EXCLUSIVE]
self.registers = {
int(row["MB Adresse"]): {
"desc": str(row["Beschreibung"]).strip(),
"type": str(row["Variabel Typ"]).strip()
}
for _, row in df.iterrows()
}
# ---------- Low-Level Lesen ----------
def _try_read(self, fn_name: str, address: int, count: int) -> Optional[List[int]]:
fn = getattr(self.client, fn_name)
# pymodbus 3.8.x hat 'slave='; Fallbacks schaden nicht
for kwargs in (dict(address=address, count=count, slave=self.unit),
dict(address=address, count=count)):
# ---------------- Low-Level Lesen ----------------
def _read_regs(self, addr: int, count: int) -> Optional[List[int]]:
"""Liest 'count' Holding-Register ab base-0 'addr' für die konfigurierte Unit-ID."""
try:
res = fn(**kwargs)
if res is None or (hasattr(res, "isError") and res.isError()):
continue
return res.registers
except TypeError:
continue
rr = self.client.read_holding_registers(address=addr, count=count, slave=self.unit)
except ModbusIOException:
time.sleep(self.silent_interval)
return None
except Exception:
time.sleep(self.silent_interval)
return None
def _read_any(self, address: int, count: int) -> Optional[List[int]]:
regs = self._try_read("read_holding_registers", address, count)
if regs is None:
regs = self._try_read("read_input_registers", address, count)
return regs
time.sleep(self.silent_interval)
if not rr or rr.isError():
return None
return rr.registers
# ---------- Decoding ----------
@staticmethod
def _to_i16(u16: int) -> int:
def _to_int16(u16: int) -> int:
return struct.unpack(">h", struct.pack(">H", u16))[0]
@staticmethod
def _to_f32_from_two(u16_hi: int, u16_lo: int, msw_first: bool = True) -> float:
b = struct.pack(">HH", u16_hi, u16_lo) if msw_first else struct.pack(">HH", u16_lo, u16_hi)
return struct.unpack(">f", b)[0]
def _apply_sf(raw: int, sf: int) -> float:
return raw * (10 ** sf)
# Hilfsfunktion: wie viele 16-Bit-Register braucht dieser Typ?
@staticmethod
def _word_count_for_type(rtype: str) -> int:
rt = (rtype or "").lower()
# Passe hier an deine Excel-Typen an:
if "uint32" in rt or "real" in rt or "float" in rt or "string(32)" in rt:
return 2
# Default: 1 Wort (z.B. int16/uint16)
return 1
def _read_string_from_regs(regs: List[int]) -> Optional[str]:
b = b"".join(struct.pack(">H", r) for r in regs)
s = b.decode("ascii", errors="ignore").rstrip("\x00 ").strip()
return s or None
def read_one(self, address_excel: int, rtype: str) -> Optional[float]:
"""
Liest einen Wert nach Typ ('INT' oder 'REAL' etc.).
Es werden ausschließlich Register < 40206 gelesen.
"""
addr = int(address_excel)
words = self._word_count_for_type(rtype)
# 2) Harte Grenze prüfen: höchstes angefasstes Register muss < 40206 sein
if addr + words - 1 >= MAX_ADDR_EXCLUSIVE:
# Überspringen, da der Lesevorgang die Grenze >= 40206 berühren würde
# ---------------- Hilfsfunktionen ----------------
def _read_string(self, addr: int, words: int) -> Optional[str]:
regs = self._read_regs(addr, words)
if regs is None:
return None
return self._read_string_from_regs(regs)
if words == 2:
regs = self._read_any(addr, 2)
if not regs or len(regs) < 2:
def _read_scaled(self, value_addr: int, sf_addr: int) -> Optional[float]:
regs = self._read_regs(value_addr, 1)
sf = self._read_regs(sf_addr, 1)
if regs is None or sf is None:
return None
# Deine bisherige Logik interpretiert 2 Worte als Float32:
return self._to_f32_from_two(regs[0], regs[1])
else:
regs = self._read_any(addr, 1)
if not regs:
return None
return float(self._to_i16(regs[0]))
raw = self._to_int16(regs[0])
sff = self._to_int16(sf[0])
return self._apply_sf(raw, sff)
def _read_u32_with_sf(self, value_addr: int, sf_addr: int) -> Optional[float]:
regs = self._read_regs(value_addr, 2)
sf = self._read_regs(sf_addr, 1)
if regs is None or sf is None:
return None
u32 = (regs[0] << 16) | regs[1]
sff = self._to_int16(sf[0])
return self._apply_sf(u32, sff)
# ---------------- Öffentliche API ----------------
def get_state(self) -> Dict[str, Any]:
"""
Liest ALLE Register aus self.registers und gibt dict zurück.
Achtet darauf, dass keine Adresse (inkl. Mehrwort) >= 40206 gelesen wird.
"""
data = {"Zeit": time.strftime("%Y-%m-%d %H:%M:%S")}
for address, meta in sorted(self.registers.items()):
words = self._word_count_for_type(meta["type"])
# 3) Nochmals Schutz auf Ebene der Iteration:
if address + words - 1 >= MAX_ADDR_EXCLUSIVE:
continue
val = self.read_one(address, meta["type"])
if val is None:
continue
key = f"{address} - {meta['desc']}"
data[key] = val
return data
"""Liest exakt die bekannten Register und gibt ein Dict zurück."""
state: Dict[str, Any] = {}
# --- Common Block ---
state["C_Manufacturer"] = self._read_string(40004, 16)
state["C_Model"] = self._read_string(40020, 16)
state["C_Version"] = self._read_string(40044, 8)
state["C_SerialNumber"] = self._read_string(40052, 16)
# --- Inverter Block ---
state["I_AC_Power_W"] = self._read_scaled(40083, 40084)
state["I_AC_Voltage_V"] = self._read_scaled(40079, 40082)
state["I_AC_Frequency_Hz"] = self._read_scaled(40085, 40086)
state["I_DC_Power_W"] = self._read_scaled(40100, 40101)
state["I_AC_Energy_Wh_total"] = self._read_u32_with_sf(40093, 40095)
status_regs = self._read_regs(40107, 2)
if status_regs:
state["I_Status"] = status_regs[0]
state["I_Status_Vendor"] = status_regs[1]
else:
state["I_Status"] = None
state["I_Status_Vendor"] = None
return state
# ---------------- Beispiel ----------------
if __name__ == "__main__":
MODBUS_IP = "192.168.1.112"
MODBUS_PORT = 502
master = PvInverter("solaredge_master", MODBUS_IP, port=MODBUS_PORT, unit_id=1)
slave = PvInverter("solaredge_slave", MODBUS_IP, port=MODBUS_PORT, unit_id=3)
try:
sm = master.get_state()
ss = slave.get_state()
print("\n=== MASTER ===")
for k, v in sm.items():
print(f"{k:22s}: {v}")
print("\n=== SLAVE ===")
for k, v in ss.items():
print(f"{k:22s}: {v}")
finally:
master.close()
slave.close()