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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.pv_power' # Photovoltaic produced power sensor in Watts
var_load: 'sensor.power_load_without_variable_loads' # Household power consumption sensor in Watts (deferrable loads should be subtracted)
load_negative: False # Set to True if the retrieved 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 retrieved variables that we would want to replace NaNs with zeros (should be a list even if empty)
var_interp: # A list of retrieved variables that we would want to interpolate NaN values using linear interpolation
'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 persistence 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: 0.4 # 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
set_nocharge_from_grid: True # avoid battery charging from the grid
set_nodischarge_to_grid: True # avoid battery discharging to the grid
set_battery_dynamic: False # add a constraint to limit the dynamic of the battery power in power per time unit
battery_dynamic_max: 0.9 # maximum dynamic positive power variation in percentage of battery maximum power
battery_dynamic_min: -0.9 # minimum dynamic negative power variation in percentage of battery maximum power
weight_battery_discharge: 0.0 # weight applied in cost function to battery usage for discharge
weight_battery_charge: 0.0 # weight applied in cost function to battery usage for charge
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' # The PV module model
- 'CSUN_Eurasia_Energy_Systems_Industry_and_Trade_CSUN295_60M' # Another PV module model option
inverter_model:
'Huawei_Technologies_Co___Ltd___SUN2000_5KTL_USL0__240V_' # The PV inverter model
- 'Fronius_International_GmbH__Fronius_Primo_5_0_1_208_240__240V_' # Another PV inverter model option
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 minimum allowable battery state of charge
SOCmax: 0.95 # If your system has a battery (set_use_battery=True), the maximum 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
To Reproduce
Trigger mpc-optim using the above config
Expected behavior
No 400
Screenshots
If applicable, add screenshots to help explain your problem.
Home Assistant installation type
Home Assistant Core
Your hardware
Synology
EMHASS installation type
Docker
Additional context
The text was updated successfully, but these errors were encountered:
Describe the bug
I get a 400 error when doing a call using:
{"pv_power_forecast":[3374.8,3245.1,3005.7999999999997,2680.8999999999996,2331.2,1985.1000000000001,1598.6,1236.5,875.1999999999999,562.9,343.5,195.1,85.5,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], "prod_price_forecast":[0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04,0.04], "load_cost_forecast":[0.186586,0.186586,2.238408,2.238408,0.944180,0.944180,0.231886,0.231886,0.182804,0.182804,0.041332,0.041332,0.041468,0.041468,0.040380,0.040380,0.040911,0.040911,0.039008,0.039008,0.214656,0.214656,0.203334,0.203334,0.192692,0.192692,0.195807,0.195807,0.190653,0.190653], "prediction_horizon":30, "def_total_hours":[5.00], "soc_init":0.97, "soc_final":0.9}
My conf:
retrieve_hass_conf:
optim_conf:
- def_total_hours: # hours
- 10
start: '00:00'
end: '23:59'
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:
- 'CSUN_Eurasia_Energy_Systems_Industry_and_Trade_CSUN295_60M' # Another PV module model option
- 'Fronius_International_GmbH__Fronius_Primo_5_0_1_208_240__240V_' # Another PV inverter model option
To Reproduce
Trigger mpc-optim using the above config
Expected behavior
No 400
Screenshots
If applicable, add screenshots to help explain your problem.
Home Assistant installation type
Your hardware
EMHASS installation type
Additional context
The text was updated successfully, but these errors were encountered: