Not sure, as I mentioned I don’t know whether this is something appeared in the latest release or not.
If you restart the add-on do you see the same?
{
"adjusted_pv_model_max_age": 24,
"adjusted_pv_regression_model": "LassoRegression",
"adjusted_pv_solar_elevation_threshold": 10,
"battery_charge_efficiency": 0.95,
"battery_charge_power_max": 7100,
"battery_discharge_efficiency": 0.95,
"battery_discharge_power_max": 7100,
"battery_dynamic_max": 0.9,
"battery_dynamic_min": -0.9,
"battery_maximum_state_of_charge": 1,
"battery_minimum_state_of_charge": 0,
"battery_nominal_energy_capacity": 27000,
"battery_stress_cost": 0,
"battery_stress_segments": 10,
"battery_target_state_of_charge": 0.2,
"compute_curtailment": false,
"continual_publish": false,
"costfun": "self-consumption",
"delta_forecast_daily": 3,
"end_timesteps_of_each_deferrable_load": [
0
],
"historic_days_to_retrieve": 31,
"influxdb_database": "homeassistant",
"influxdb_host": "localhost",
"influxdb_measurement": "W",
"influxdb_password": "",
"influxdb_port": 8086,
"influxdb_retention_policy": "autogen",
"influxdb_use_ssl": false,
"influxdb_username": "",
"influxdb_verify_ssl": false,
"inverter_ac_input_max": 1000,
"inverter_ac_output_max": 1000,
"inverter_efficiency_ac_dc": 1,
"inverter_efficiency_dc_ac": 1,
"inverter_is_hybrid": false,
"inverter_stress_cost": 0,
"inverter_stress_segments": 10,
"load_cost_forecast_method": "hp_hc_periods",
"load_forecast_method": "naive",
"load_negative": false,
"load_offpeak_hours_cost": 0.1419,
"load_peak_hour_periods": {
"period_hp_1": [
{
"start": "07:00"
},
{
"end": "23:00"
}
]
},
"load_peak_hours_cost": 0.1907,
"logging_level": "INFO",
"lp_solver": "COIN_CMD",
"lp_solver_path": "/usr/bin/cbc",
"lp_solver_timeout": 45,
"maximum_power_from_grid": 5000,
"maximum_power_to_grid": 8000,
"method_ts_round": "first",
"minimum_power_of_deferrable_loads": [
0,
0
],
"model_type": "load_forecast",
"modules_per_string": [
9,
14
],
"nominal_power_of_deferrable_loads": [
0
],
"num_lags": 48,
"num_threads": 0,
"number_of_deferrable_loads": 1,
"open_meteo_cache_max_age": 30,
"operating_hours_of_each_deferrable_load": [
1
],
"optimization_time_step": 15,
"perform_backtest": false,
"photovoltaic_production_sell_price": 0.065,
"production_price_forecast_method": "constant",
"pv_inverter_model": [
"SMA_America__SB3000TL_US_22__240V_",
"SMA_America__STP50_US_40__480V_"
],
"pv_module_model": [
"SunPower_SPR_E20_327",
"SunPower_SPR_MAX3_400_COM"
],
"sensor_linear_interp": [
"sensor.consumption_filtered_w",
"sensor.production_pv_w"
],
"sensor_power_load_no_var_loads": "sensor.consumption_filtered_w",
"sensor_power_photovoltaics": "sensor.production_pv_w",
"sensor_power_photovoltaics_forecast": "sensor.p_pv_forecast",
"sensor_replace_zero": [
"sensor.production_pv_w"
],
"set_battery_dynamic": false,
"set_deferrable_load_single_constant": [
false
],
"set_deferrable_startup_penalty": [
0
],
"set_nocharge_from_grid": false,
"set_nodischarge_to_grid": true,
"set_total_pv_sell": false,
"set_use_adjusted_pv": false,
"set_use_battery": true,
"set_use_pv": true,
"set_zero_min": true,
"sklearn_model": "KNeighborsRegressor",
"split_date_delta": "48h",
"start_timesteps_of_each_deferrable_load": [
0
],
"strings_per_inverter": [
1,
1
],
"surface_azimuth": [
225,
225
],
"surface_tilt": [
17,
17
],
"treat_deferrable_load_as_semi_cont": [
true
],
"use_influxdb": false,
"use_websocket": false,
"var_model": "sensor.power_load_no_var_loads",
"weather_forecast_method": "open-meteo",
"weight_battery_charge": 0,
"weight_battery_discharge": 0.05
}
Major Optimization Engine Overhaul
CVXPY & Vectorization: The constraint generation logic has been rewritten using vectorization. This mathematical streamlining allows EMHASS to construct optimization problems significantly faster, reducing overhead especially for complex configurations or long prediction horizons. Benchmarks show optimization times are 4-5x faster, clocking in at approximately 0.1s per iteration for standard use cases compared to previous implementation.
HiGHS Solver Standard: We have adopted HiGHS as the new default solver. HiGHS is a state-of-the-art, open-source linear optimization solver that offers vastly superior performance and stability compared to the legacy CBC/GLPK solvers.
Simplified Dependencies: No more system-level dependencies! Because HiGHS is bundled as a Python wheel, the Docker image is lighter, and installation is more robust—you no longer need to install 
Commercial Solver Support: Power users with licenses for Gurobi or CPLEX can now easily plug them in via environment variables (
Modular Architecture: The optimization class has been refactored into smaller, testable helper methods, improving code maintainability and making it easier for contributors to add new constraints (like the new internal gains logic for thermal batteries) without breaking existing features.
BREAKING CHANGE: Solver Configuration
