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Merged
springfall2008 merged 6 commits into from
Sep 28, 2025
Merged

Dynamic load feature #2702

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aebe6ca
Dynamic load feature
springfall2008 Sep 28, 2025
5264e8d
[pre-commit.ci lite] apply automatic fixes
pre-commit-ci-lite[bot] Sep 28, 2025
7877af9
Fixes
springfall2008 Sep 28, 2025
c76c0de
Merge branch 'fixes6' of github.com:springfall2008/batpred into fixes6
springfall2008 Sep 28, 2025
f48cd12
Fixes to ge cloud timeout
springfall2008 Sep 28, 2025
8f7b075
[pre-commit.ci lite] apply automatic fixes
pre-commit-ci-lite[bot] Sep 28, 2025
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6 changes: 6 additions & 0 deletions apps/predbat/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -504,6 +504,12 @@
"name": "metric_pv_calibration_enable",
"friendly_name": "Enable use of Calibrated PV data",
"type": "switch",
"default": True,
},
{
"name": "metric_dynamic_load_adjust",
"friendly_name": "Dynamic Load Adjust",
"type": "switch",
"default": False,
},
{
Expand Down
2 changes: 0 additions & 2 deletions apps/predbat/energydataservice.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,6 @@ def fetch_energidataservice_rates(self, entity_id, adjust_key=None):
if data_all:
# Sort to be safe
data_all.sort(key=lambda e: self._parse_iso(e.get("hour")) or datetime.min)
print(data_all)

# Add tariffs (HH:MM → H → HH → raw ISO)
for entry in data_all:
Expand All @@ -53,7 +52,6 @@ def fetch_energidataservice_rates(self, entity_id, adjust_key=None):
scale=1.0,
use_cent=use_cent,
)
print(rate_data)

return rate_data

Expand Down
8 changes: 8 additions & 0 deletions apps/predbat/fetch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,6 +87,7 @@ def step_data_history(
base_offset=None,
flip=False,
load_adjust={},
load_baseline={},
):
"""
Create cached step data for historical array
Expand Down Expand Up @@ -132,6 +133,10 @@ def step_data_history(
load_extra = max(load_extra, -value) # Don't allow going to negative load values
values[minute] = dp4((value + load_extra) * scaling_dynamic * scale_today * scale_fixed)

# Apply dynamic baseline
if minute_absolute in load_baseline:
values[minute] = max(values[minute], load_baseline[minute_absolute])

# Simple divergence model keeps the same total but brings PV/Load up and down every 5 minutes
if cloud_factor and cloud_factor > 0:
for minute in range(0, self.forecast_minutes, step):
Expand Down Expand Up @@ -954,11 +959,13 @@ def fetch_sensor_data(self):
self.load_minutes, self.load_minutes_age = self.minute_data_load(self.now_utc, "load_today", self.max_days_previous, required_unit="kWh", load_scaling=self.load_scaling)
self.log("Found {} load_today datapoints going back {} days".format(len(self.load_minutes), self.load_minutes_age))
self.load_minutes_now = max(self.load_minutes.get(0, 0) - self.load_minutes.get(self.minutes_now, 0), 0)
self.load_last_period = (self.load_minutes.get(0, 0) - self.load_minutes.get(PREDICT_STEP, 0)) * 60 / PREDICT_STEP
else:
if self.load_forecast:
self.log("Using load forecast from load_forecast sensor")
self.load_minutes_now = self.load_forecast.get(0, 0)
self.load_minutes_age = 0
self.load_last_period = 0
else:
self.log("Error: You have not set load_today or load_forecast, you will have no load data")
self.record_status(message="Error: load_today not set correctly", had_errors=True)
Expand Down Expand Up @@ -2063,6 +2070,7 @@ def fetch_config_options(self):
self.metric_future_rate_offset_export = self.get_arg("metric_future_rate_offset_export")
self.metric_inday_adjust_damping = self.get_arg("metric_inday_adjust_damping")
self.metric_pv_calibration_enable = self.get_arg("metric_pv_calibration_enable")
self.metric_dynamic_load_adjust = self.get_arg("metric_dynamic_load_adjust")
self.rate_low_threshold = self.get_arg("rate_low_threshold")
self.rate_high_threshold = self.get_arg("rate_high_threshold")
self.inverter_soc_reset = self.get_arg("inverter_soc_reset")
Expand Down
6 changes: 4 additions & 2 deletions apps/predbat/gecloud.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
import asyncio
import random
import time
from config import PREDICT_STEP

"""
GE Cloud data download
Expand Down Expand Up @@ -1332,9 +1333,9 @@ def download_ge_data(self, now_utc):
url = "https://api.givenergy.cloud/v1/inverter/{}/data-points/{}".format(geserial, datestr)
while url:
if "?" in url:
url += "&pageSize=4096"
url += "&pageSize=8000"
else:
url += "?pageSize=4096"
url += "?pageSize=8000"
Comment on lines +1336 to +1338

Copilot AI Sep 28, 2025

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The magic number 8000 for page size should be defined as a named constant (e.g., GE_API_PAGE_SIZE = 8000) to improve maintainability and make it easier to adjust if needed.

Copilot uses AI. Check for mistakes.
data = self.get_ge_url(url, headers, now_utc, 30 if days_prev == 0 else 8 * 60)
darray = data.get("data", None)
if darray is None:
Expand Down Expand Up @@ -1386,6 +1387,7 @@ def download_ge_data(self, now_utc):
self.pv_today = self.minute_data(mdata, self.max_days_previous, now_utc, "pv", "last_updated", backwards=True, smoothing=True, scale=self.import_export_scaling, clean_increment=True)

self.load_minutes_now = self.load_minutes.get(0, 0) - self.load_minutes.get(self.minutes_now, 0)
self.load_last_period = (self.load_minutes.get(0, 0) - self.load_minutes.get(PREDICT_STEP, 0)) * 60 / PREDICT_STEP
self.import_today_now = self.import_today.get(0, 0) - self.import_today.get(self.minutes_now, 0)
self.export_today_now = self.export_today.get(0, 0) - self.export_today.get(self.minutes_now, 0)
self.pv_today_now = self.pv_today.get(0, 0) - self.pv_today.get(self.minutes_now, 0)
Expand Down
47 changes: 43 additions & 4 deletions apps/predbat/plan.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,7 @@
import traceback
from datetime import datetime, timedelta
from multiprocessing import Pool, cpu_count
from config import PREDICT_STEP, TIME_FORMAT
from config import PREDICT_STEP, TIME_FORMAT, MINUTE_WATT
from utils import calc_percent_limit, dp0, dp1, dp2, dp3, dp4, remove_intersecting_windows, calc_percent_limit
from prediction import Prediction, wrapped_run_prediction_single, wrapped_run_prediction_charge, wrapped_run_prediction_charge_min_max, wrapped_run_prediction_export, wrapped_run_prediction_charge_min_max

Expand All @@ -36,6 +36,38 @@ def get(self):


class Plan:
def dynamic_load(self):

# Last period load analysis
self.load_last_status = "baseline"
if self.load_last_period > self.battery_rate_max_discharge * MINUTE_WATT / 1000:

Copilot AI Sep 28, 2025

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The magic number 1000 appears to be a unit conversion factor. Consider defining it as a named constant (e.g., WATTS_TO_KW = 1000) to improve code readability and maintainability.

Copilot uses AI. Check for mistakes.
self.load_last_status = "high"
elif (self.load_last_period < self.battery_rate_max_discharge * 0.9 * MINUTE_WATT / 1000) and (self.load_last_period < self.car_charging_threshold * 0.9):
Comment on lines +39 to +44

Copilot AI Sep 28, 2025

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The magic number 0.9 appears twice in this condition. Consider defining it as a named constant (e.g., LOW_LOAD_FACTOR = 0.9) to improve maintainability and make the threshold configurable.

Suggested change
def dynamic_load(self):
# Last period load analysis
self.load_last_status = "baseline"
if self.load_last_period > self.battery_rate_max_discharge * MINUTE_WATT / 1000:
self.load_last_status = "high"
elif (self.load_last_period < self.battery_rate_max_discharge * 0.9 * MINUTE_WATT / 1000) and (self.load_last_period < self.car_charging_threshold * 0.9):
LOW_LOAD_FACTOR = 0.9
def dynamic_load(self):
# Last period load analysis
self.load_last_status = "baseline"
if self.load_last_period > self.battery_rate_max_discharge * MINUTE_WATT / 1000:
self.load_last_status = "high"
elif (self.load_last_period < self.battery_rate_max_discharge * self.LOW_LOAD_FACTOR * MINUTE_WATT / 1000) and (self.load_last_period < self.car_charging_threshold * self.LOW_LOAD_FACTOR):

Copilot uses AI. Check for mistakes.
# Check if the load is less than car charging threshold
self.load_last_status = "low"
else:
self.load_last_status = "baseline"

self.dynamic_load_baseline = {}
if self.metric_dynamic_load_adjust:
minutes_now = self.minutes_now
minutes_end_slot = int((self.minutes_now + 30) / 30) * 30

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The magic number 30 (representing a 30-minute period) appears multiple times. Consider defining it as a named constant (e.g., SLOT_DURATION_MINUTES = 30) to improve maintainability.

Copilot uses AI. Check for mistakes.
# When dynamic load is enabled we try can do two things
# 1. Increase the load prediction in the current 30 minute period to match the actual load (if its low)
# 2. If its low and car charging is predicted then cancel off that car slot
if self.load_last_status == "low":
for car_n in range(0, self.num_cars):
for slot in self.car_charging_slots[car_n]:
if (slot["start"] < minutes_end_slot) and (slot["end"] > minutes_now):
# If the slot is within the current 30 minute period
slot["kwh"] = 0
if self.load_last_status == "high":
for minute_absolute in range(minutes_now, minutes_end_slot, PREDICT_STEP):
car_load = self.in_car_slot(minute_absolute)
load_last_period = self.load_last_period / 60 * PREDICT_STEP
load_last_period = max(load_last_period - car_load, 0)
self.dynamic_load_baseline[minute_absolute] = load_last_period

def find_price_levels(
self,
price_set,
Expand Down Expand Up @@ -791,6 +823,7 @@ def calculate_plan(self, recompute=True, debug_mode=False, publish=True):
load_scaling_dynamic=self.load_scaling_dynamic,
cloud_factor=self.metric_load_divergence,
load_adjust=self.manual_load_adjust,
load_baseline=self.dynamic_load_baseline,
)
load_minutes_step10 = self.step_data_history(
self.load_minutes,
Expand All @@ -803,6 +836,7 @@ def calculate_plan(self, recompute=True, debug_mode=False, publish=True):
load_scaling_dynamic=self.load_scaling_dynamic,
cloud_factor=min(self.metric_load_divergence + 0.5, 1.0) if self.metric_load_divergence else None,
load_adjust=self.manual_load_adjust,
load_baseline=self.dynamic_load_baseline,
)
pv_forecast_minute_step = self.step_data_history(self.pv_forecast_minute, self.minutes_now, forward=True, cloud_factor=self.metric_cloud_coverage)
pv_forecast_minute10_step = self.step_data_history(self.pv_forecast_minute10, self.minutes_now, forward=True, cloud_factor=min(self.metric_cloud_coverage + 0.2, 1.0) if self.metric_cloud_coverage else None, flip=True)
Expand Down Expand Up @@ -3306,7 +3340,7 @@ def run_prediction(self, charge_limit, charge_window, export_window, export_limi
self.dashboard_item(
self.prefix + ".export_energy_h0",
state=dp3(export_kwh_h0),
attributes={"friendly_name": "Current export kWh", "state_class": "measurement", "unit_of_measurement": "kWh", "icon": "mdi:transmission-tower-export"},
attributes={"friendly_name": "Current export", "state_class": "measurement", "unit_of_measurement": "kWh", "icon": "mdi:transmission-tower-export"},
)
self.dashboard_item(
self.prefix + ".load_energy",
Expand All @@ -3323,7 +3357,12 @@ def run_prediction(self, charge_limit, charge_window, export_window, export_limi
self.dashboard_item(
self.prefix + ".load_energy_h0",
state=dp3(load_kwh_h0),
attributes={"friendly_name": "Current load kWh", "state_class": "measurement", "unit_of_measurement": "kWh", "icon": "mdi:home-lightning-bolt"},
attributes={"friendly_name": "Current load", "state_class": "measurement", "unit_of_measurement": "kWh", "icon": "mdi:home-lightning-bolt"},
)
self.dashboard_item(
self.prefix + ".load_energy_last_period",
state=dp3(self.load_last_period),
attributes={"friendly_name": "Last period load", "state_class": "measurement", "unit_of_measurement": "kW", "icon": "mdi:home-lightning-bolt", "status" : self.load_last_status},
)
self.dashboard_item(
self.prefix + ".pv_energy",
Expand All @@ -3333,7 +3372,7 @@ def run_prediction(self, charge_limit, charge_window, export_window, export_limi
self.dashboard_item(
self.prefix + ".pv_energy_h0",
state=dp3(pv_kwh_h0),
attributes={"friendly_name": "Current PV kWh", "state_class": "measurement", "unit_of_measurement": "kWh", "icon": "mdi:solar-power"},
attributes={"friendly_name": "Current PV", "state_class": "measurement", "unit_of_measurement": "kWh", "icon": "mdi:solar-power"},
)
self.dashboard_item(
self.prefix + ".import_energy",
Expand Down
8 changes: 7 additions & 1 deletion apps/predbat/predbat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@
import requests
import asyncio

THIS_VERSION = "v8.25.3"
THIS_VERSION = "v8.25.4"

# fmt: off
PREDBAT_FILES = ["predbat.py", "config.py", "prediction.py", "gecloud.py","utils.py", "inverter.py", "ha.py", "download.py", "unit_test.py", "web.py", "web_helper.py", "predheat.py", "futurerate.py", "octopus.py", "solcast.py","execute.py", "plan.py", "fetch.py", "output.py", "userinterface.py", "energydataservice.py", "alertfeed.py", "compare.py", "db_manager.py", "db_engine.py", "plugin_system.py", "ohme.py", "components.py", "fox.py"]
Expand Down Expand Up @@ -427,6 +427,9 @@ def reset(self):
self.metric_inday_adjust_damping = 1.0
self.metric_standing_charge = 0.0
self.metric_self_sufficiency = 0.0
self.metric_dynamic_load_adjust = False
self.metric_pv_calibration_enable = True
self.dynamic_load_baseline = {}
self.iboost_value_scaling = 1.0
self.rate_import = {}
self.rate_export = {}
Expand Down Expand Up @@ -526,6 +529,8 @@ def reset(self):
self.load_minutes = {}
self.load_minutes_now = 0
self.load_minutes_age = 0
self.load_last_period = 0
self.load_last_status = "baseline"
self.battery_capacity_nominal = False
self.releases = {}
self.balance_inverters_enable = False
Expand Down Expand Up @@ -681,6 +686,7 @@ def update_pred(self, scheduled=True):
self.fetch_config_options()
self.fetch_sensor_data()
self.fetch_inverter_data()
self.dynamic_load()

recompute = False
if not scheduled or not self.plan_valid:
Expand Down
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