Describe the bug Getting the following errors after downloading the newest version of EMHASS: 2024-05-15T09:37:13.923695795Z | stdout | web_server.py: error: unrecognized arguments: python3 src/emhass/web_server.py 2024-05-15T09:37:13.923564580Z | stdout | [--no_response NO_RESPONSE] 2024-05-15T09:37:13.922609527Z | stdout | usage: web_server.py [-h] [--url URL] [--key KEY] [--addon ADDON]

To Reproduce My config:

Configuration file for EMHASS

retrieve_hass_conf:

freq: 30 # The time step to resample retrieved data from hass in minutes
days_to_retrieve: 30 # We will retrieve data from now and up to days_to_retrieve days
var_PV: 'sensor.power_ac_fronius_inverter_1_http_192_168_0_140' # Photovoltaic produced power sensor in Watts
var_load: 'sensor.power_load_without_variable_loads' # Household power consumption sensor in Watts (deferrable loads should be substracted)
load_negative: False # Set to True if the retrived load variable is negative by convention
set_zero_min: True # A special treatment for a minimum value saturation to zero. Values below zero are replaced by nans
var_replace_zero: # A list of retrived variables that we would want to replace nans with zeros
- 'sensor.power_ac_fronius_inverter_1_http_192_168_0_140'
var_interp: # A list of retrived variables that we would want to interpolate nan values using linear interpolation
- 'sensor.power_ac_fronius_inverter_1_http_192_168_0_140'
- 'sensor.power_load_without_variable_loads'
method_ts_round: 'first' # Set the method for timestamp rounding, options are: first, last and nearest

optim_conf:

set_use_battery: True # consider a battery storage
delta_forecast: 1 # days
num_def_loads: 1
P_deferrable_nom: # Watts
- 643.0
def_total_hours: # hours
- 10
treat_def_as_semi_cont: # treat this variable as semi continuous
- True
set_def_constant: # set as a constant fixed value variable with just one startup for each 24h
- False
weather_forecast_method: 'scrapper' # options are 'scrapper' and 'csv'
load_forecast_method: 'naive' # options are 'csv' to load a custom load forecast from a CSV file or 'naive' for a persistance model
load_cost_forecast_method: 'hp_hc_periods' # options are 'hp_hc_periods' for peak and non-peak hours contracts and 'csv' to load custom cost from CSV file
list_hp_periods: # list of different tariff periods (only needed if load_cost_forecast_method='hp_hc_periods')
- period_hp_1:
  - start: '00:00'
  - end: '23:59'
load_cost_hp: 0.3 # peak hours load cost in €/kWh (only needed if load_cost_forecast_method='hp_hc_periods')
load_cost_hc: 0.3 # non-peak hours load cost in €/kWh (only needed if load_cost_forecast_method='hp_hc_periods')
prod_price_forecast_method: 'constant' # options are 'constant' for constant fixed value or 'csv' to load custom price forecast from a CSV file
prod_sell_price: 0.25 # power production selling price in €/kWh (only needed if prod_price_forecast_method='constant')
set_total_pv_sell: False # consider that all PV power is injected to the grid (self-consumption with total sell)
lp_solver: 'PULP_CBC_CMD' # set the name of the linear programming solver that will be used
- lp_solver: 'COIN_CMD' # set the name of the linear programming solver that will be used

- lp_solver_path: '/usr/bin/cbc' # set the path to the LP solver

plant_conf:

P_grid_max: 15000 # The maximum power that can be supplied by the utility grid in Watts
module_model:
- 'JA_Solar_JAM72S01_385_PR' #- 'CSUN_Eurasia_Energy_Systems_Industry_and_Trade_CSUN295_60M' # The PV module model
inverter_model:
- 'Huawei_Technologies_CoLtdSUN2000_5KTL_USL0_240V' #- 'Fronius_International_GmbHFronius_Primo_5_0_1_208_240240V_' # The PV inverter model
surface_tilt:
- 45 # The tilt angle of your solar panels
surface_azimuth:
- 0 # The azimuth angle of your PV installation
modules_per_string:
- 8 # The number of modules per string
strings_per_inverter:
- 2 # The number of used strings per inverter
Pd_max: 4000 # If your system has a battery (set_use_battery=True), the maximum discharge power in Watts
Pc_max: 4000 # If your system has a battery (set_use_battery=True), the maximum charge power in Watts
eta_disch: 0.95 # If your system has a battery (set_use_battery=True), the discharge efficiency
eta_ch: 0.95 # If your system has a battery (set_use_battery=True), the charge efficiency
Enom: 6400 # If your system has a battery (set_use_battery=True), the total capacity of the battery stack in Wh
SOCmin: 0.1 # If your system has a battery (set_use_battery=True), the minimun allowable battery state of charge
SOCmax: 0.95 # If your system has a battery (set_use_battery=True), the minimun allowable battery state of charge
SOCtarget: 0.6 # If your system has a battery (set_use_battery=True), the desired battery state of charge at the end of each optimization cycle

retrieve_hass_conf:

freq: 30 # The time step to resample retrieved data from hass in minutes
days_to_retrieve: 30 # We will retrieve data from now and up to days_to_retrieve days
var_PV: 'sensor.power_ac_fronius_inverter_1_http_192_168_0_140' # Photovoltaic produced power sensor in Watts
var_load: 'sensor.power_load_without_variable_loads' # Household power consumption sensor in Watts (deferrable loads should be substracted)
load_negative: False # Set to True if the retrived load variable is negative by convention
set_zero_min: True # A special treatment for a minimum value saturation to zero. Values below zero are replaced by nans
var_replace_zero: # A list of retrived variables that we would want to replace nans with zeros
- 'sensor.power_ac_fronius_inverter_1_http_192_168_0_140'
var_interp: # A list of retrived variables that we would want to interpolate nan values using linear interpolation
- 'sensor.power_ac_fronius_inverter_1_http_192_168_0_140'
- 'sensor.power_load_without_variable_loads'
method_ts_round: 'first' # Set the method for timestamp rounding, options are: first, last and nearest

optim_conf:

set_use_battery: True # consider a battery storage
delta_forecast: 1 # days
num_def_loads: 1
P_deferrable_nom: # Watts
- 643.0
def_total_hours: # hours
- 10
treat_def_as_semi_cont: # treat this variable as semi continuous
- True
set_def_constant: # set as a constant fixed value variable with just one startup for each 24h
- False
weather_forecast_method: 'scrapper' # options are 'scrapper' and 'csv'
load_forecast_method: 'naive' # options are 'csv' to load a custom load forecast from a CSV file or 'naive' for a persistance model
load_cost_forecast_method: 'hp_hc_periods' # options are 'hp_hc_periods' for peak and non-peak hours contracts and 'csv' to load custom cost from CSV file
list_hp_periods: # list of different tariff periods (only needed if load_cost_forecast_method='hp_hc_periods')
- period_hp_1:
  - start: '00:00'
  - end: '23:59'
load_cost_hp: 0.3 # peak hours load cost in €/kWh (only needed if load_cost_forecast_method='hp_hc_periods')
load_cost_hc: 0.3 # non-peak hours load cost in €/kWh (only needed if load_cost_forecast_method='hp_hc_periods')
prod_price_forecast_method: 'constant' # options are 'constant' for constant fixed value or 'csv' to load custom price forecast from a CSV file
prod_sell_price: 0.25 # power production selling price in €/kWh (only needed if prod_price_forecast_method='constant')
set_total_pv_sell: False # consider that all PV power is injected to the grid (self-consumption with total sell)
lp_solver: 'PULP_CBC_CMD' # set the name of the linear programming solver that will be used
- lp_solver: 'COIN_CMD' # set the name of the linear programming solver that will be used

- lp_solver_path: '/usr/bin/cbc' # set the path to the LP solver

plant_conf:

P_grid_max: 15000 # The maximum power that can be supplied by the utility grid in Watts
module_model:
- 'JA_Solar_JAM72S01_385_PR' #- 'CSUN_Eurasia_Energy_Systems_Industry_and_Trade_CSUN295_60M' # The PV module model
inverter_model:
- 'Huawei_Technologies_CoLtdSUN2000_5KTL_USL0_240V' #- 'Fronius_International_GmbHFronius_Primo_5_0_1_208_240240V_' # The PV inverter model
surface_tilt:
- 45 # The tilt angle of your solar panels
surface_azimuth:
- 0 # The azimuth angle of your PV installation
modules_per_string:
- 8 # The number of modules per string
strings_per_inverter:
- 2 # The number of used strings per inverter
Pd_max: 4000 # If your system has a battery (set_use_battery=True), the maximum discharge power in Watts
Pc_max: 4000 # If your system has a battery (set_use_battery=True), the maximum charge power in Watts
eta_disch: 0.95 # If your system has a battery (set_use_battery=True), the discharge efficiency
eta_ch: 0.95 # If your system has a battery (set_use_battery=True), the charge efficiency
Enom: 6400 # If your system has a battery (set_use_battery=True), the total capacity of the battery stack in Wh
SOCmin: 0.1 # If your system has a battery (set_use_battery=True), the minimun allowable battery state of charge
SOCmax: 0.95 # If your system has a battery (set_use_battery=True), the minimun allowable battery state of charge
SOCtarget: 0.6 # If your system has a battery (set_use_battery=True), the desired battery state of charge at the end of each optimization cycle

Expected behavior A starting Docker container

Screenshots If applicable, add screenshots to help explain your problem.

Home Assistant installation type

Home Assistant Core (Docker)

Your hardware

OS: Docker on Synology

EMHASS installation type

Docker Standalone

Additional context

davidusb-geek / emhass

Docker not starting, web_server.py: error: unrecognized arguments: python3 src/emhass/web_server.py #286

Configuration file for EMHASS

- lp_solver: 'COIN_CMD' # set the name of the linear programming solver that will be used

- lp_solver_path: '/usr/bin/cbc' # set the path to the LP solver

- lp_solver: 'COIN_CMD' # set the name of the linear programming solver that will be used

- lp_solver_path: '/usr/bin/cbc' # set the path to the LP solver