def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.start_time_of_curr_interval = 0
self.start_time_of_next_interval = 0
self.async_future = None
self.outputs['step'] = Output('Step',
unit='-',
info='step number, starts with 0')
self.outputs['time'] = Output('Future',
unit='s',
info='utc time in seconds since epoch')
# control
self.properties['prep_lead'] = Property(
'Time lead of Preperation step',
default=0,
data_type=int,
unit='s',
info=
'Amount of seconds the preparation step is started before the actual interval'
)
self.properties['delta_time'] = Property(
'Real time between each interval run',
default=1,
data_type=int,
unit='s',
info='Real time between iteration, 0 = as fast as possible')
def __init__(self, uuid, name :str):
super(Model, self).__init__(uuid,name)
self.inputs['times'] = Input(name='Times', unit='s', info='utc time array')
self.inputs['values'] = Input(name='Values', unit='any', info='value array')
self.outputs['data_histfore'] = Output(name='Historical and forecast data', unit='div',
info='{time_hist, time_forecast, value_hist, value_forecast}')
self.outputs['y_scaling'] = Output(name='Scaling of y axis', unit='', info='Scaling of y axis')
self.outputs['y_label'] = Output(name='y label', unit='', info='Label of y axis')
self.properties["filter"] = Property(default='', data_type=str, name='Filter',
unit='-', info='comma separated dict keys and array indexes',
example='"speed", 2')
self.properties["num_hist"] = Property(default=0, data_type=int, name='Number historical data', unit='-',
info='Number of historical data to be saved (0=unlimited)', example='100')
self.properties["scaling"] = Property(default=1, data_type=float, name='Scaling factor', unit='-',
info='Scaling factor for y axis', example='1e-9')
self.properties["y_labeling"] = Property(default='Property', data_type=str, name='y label', unit='-',
info='Label for y axis', example='Demand [GW]')
self.data_hist_forecast = {"historic": {}, "forecast": {}}
self.data_hist_forecast["historic"]["time"] = []
self.data_hist_forecast["historic"]["value"] = []
self.data_hist_forecast["forecast"]["time"] = []
self.data_hist_forecast["forecast"]["value"] = []
self.y_scaling = None
self.y_labeling = None
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['KW'] = Input(name='KW info', unit='-', info="KW information (u.a. id, lat, lon)")
self.inputs['date'] = Input(name='Futures', unit='s', info="Time vector of futures in utc timestamp [s]")
self.inputs['Demand_loc'] = Input(name='Demand locations', unit='id, lat, long', info="Demand locations (one location per country)")
# define outputs
self.outputs['KW_weather'] = Output(name='Weather data of KWs', unit='dict{id, windspeed, radiation, windmesshoehe}', info='weather data of KWs')
self.outputs['Demand_weather'] = Output(name='Weather data for demand', unit='dict{id, lat, long, temperature}', info='weather data for demand calculation')
self.outputs['Futures_weather'] = Output(name='Weather data', unit='s, °C, m/s, W/m^2', info='weather data for 25 points (time, temperature, wind speed, radiation)')
self.outputs['Map_weather'] = Output(name='Weather data for map', unit='s, °C, m/s, W/m^2',
info='weather data interpolated on grid (time, temperature, wind speed, radiation)')
# define properties
self.properties['T_offset'] = Property(default=0., data_type=float, name='temperature offset', unit='%', info="offset of temperature in %", example='100: doubles the value')
self.properties['u_offset'] = Property(default=0., data_type=float, name='wind speed offset', unit='%', info="offset of wind speed in %", example='100: doubles the value')
self.properties['P_offset'] = Property(default=0., data_type=float, name='radiation offset', unit='%', info="offset of radiation in %", example='100: doubles the value')
self.properties['ref_year'] = Property(default=2007, data_type=int, name='reference year', unit='-', info="reference year for modeled weather (2007-2016; provided data for 2006-2017)",
example='2007')
# define persistent variables
self.data_hist = None
self.ref_year = None
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.inputs['dividend'] = Input('Dividend', unit='num')
self.inputs['divisor'] = Input('Divisor', unit='num')
self.outputs['quotient'] = Output('Quotient', unit='num')
self.outputs['floor_quotient'] = Output('Floor Quotient', unit='num')
self.outputs['floor_modulus'] = Output('Floor Modulus', unit='num')
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['mode'] = Input(name='modus',
unit='-',
info="modus (is live of not")
self.inputs['KW'] = Input(name='KW info',
unit='-',
info="KW informations (u.a. id, lat, lon)")
self.inputs['date'] = Input(
name='Futures',
unit='s',
info="Time vector of futures in utc timestamp [s]")
# define outputs
self.outputs['KW_weather'] = Output(name='weather data of KWs',
unit='date, °C, m/s, W/m^2',
info='weather data of KWs')
self.outputs['Futures_weather'] = Output(
name='weather data',
unit='date, °C, m/s, W/m^2',
info='(future) weather data (temperature, wind speed, radiation)')
# define properties
self.properties['T_offset'] = Property(
default=0.,
data_type=float,
name='temperature offset',
unit='%',
info="offset of temperature in %")
self.properties['u_offset'] = Property(
default=0.,
data_type=float,
name='wind speed offset',
unit='%',
info="offset of wind speed in %")
self.properties['P_offset'] = Property(default=0.,
data_type=float,
name='radiation offset',
unit='%',
info="offset of radiation in %")
self.properties['ref_year'] = Property(
default=2007,
data_type=int,
name='reference year',
unit='-',
info="reference year for modeled weather")
# define persistent variables
self.data_hist = None
self.data_hist_year = None
self.ref_year = None
def __init__(self, uuid, name :str):
super(Model, self).__init__(uuid,name)
self.inputs['times'] = Input(name='Times', unit='s', info='utc time array')
self.inputs['values'] = Input(name='Values', unit='any', info='value array')
self.outputs['times_out'] = Output(name='Times', unit='times]', info='utc time arry')
self.outputs['values_out'] = Output(name='Filtered values', unit='values', info='filtered value array')
self.properties["filter"] = Property(default='', data_type=str, name='Filter',
unit='-', info='comma separated dict keys and array indexes',
example='"speed", 2')
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['dist_net'] = Input(name='Distribution networks',
unit='{-, {Grad, Grad}}',
info='distribution networks')
# define outputs
self.outputs['dist_cost'] = Output(name='Distribution cost',
unit='€/J',
info='distribution cost')
# define properties
cost_constant_def = 36000
cost_constant_def = json.dumps(cost_constant_def)
self.properties['cost_const'] = Property(
default=cost_constant_def,
data_type=str,
name='constant dist cost',
unit='€/km*MWh',
info='constant distribution costs',
example='36000')
# persistent variables
self.cost_constant = None
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.elapsed = 0
self.inputs['time'] = Input(name='Time',
unit='s',
info='utc time in seconds since epoch')
self.outputs['times'] = Output(
name='Futures',
unit='s',
info='utc time array in seconds since epoch')
self.properties["interval"] = Property(
default=1,
data_type=float,
name='Interval time',
unit='s',
info='Time between each time stamps')
self.properties["future_steps"] = Property(
default=1,
data_type=int,
name='Number of intervals',
unit='-',
info='Number of time stamps')
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['WTAuslastung'] = Input(
'LoadWindTurbine', info='load of all wind turbines, value[0-1]')
self.inputs['PVAuslastung'] = Input(
'LoadPhotovoltaic',
info='load of all photovoltaic power plants, value[0-1]')
self.inputs['LaufwasserKWAuslastung'] = Input(
'LoadRunningWaterPowerPlant',
info='load of all running-water power plants, value[0-1]')
self.inputs['SpeicherwasserKWAuslastung'] = Input(
'LoadStoragePowerPlant',
info='load of all storage power plants, value[0-1]')
self.inputs['KWDaten'] = Input('PowerPlantsData',
info='dict, power plant id required')
self.inputs['futures'] = Input(
'Futures', unit='s', info='utc time array in seconds since epoch')
# define outputs
self.outputs['GemeinsameAuslastung'] = Output(
'CombinedLoad',
info='combined load of all types of power plants, value[0-1]')
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.inputs['to_store'] = Input('To Store')
self.outputs['stored'] = Output('Stored')
self.stored = 0
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define outputs
self.outputs['standorte'] = Output('StandorteSPG')
# define persistent variables
self.kw_data = None
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define outputs
self.outputs['weather'] = Output('WeatherData')
# define persistent variables
self.weather = None
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.inputs['in1'] = Input('Number', unit='num')
self.inputs['in2'] = Input('Number', unit='num')
self.inputs['in3'] = Input('Number', unit='num')
self.outputs['sum'] = Output('Sum', unit='num')
def __init__(self, uuid, name :str):
super(Model, self).__init__(uuid,name)
self.inputs['number'] = Input('Number', unit='-', info="The number that gets multiplied", example='2')
self.properties['multiplier'] = Property('Multiplier', default=1, data_type=float, unit='float', info='The multiplier', example='2')
self.outputs['product'] = Output('Product', unit='-', info="The resulting product", example='2')
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.inputs['fut'] = Input(
name='Futures',
unit='s',
info='utc time array in seconds since epoch',
example='[1530792535, 1530792540, 1530792545]')
self.inputs['demand'] = Input(
name='European demand',
unit='W',
info='European power demand for each time step')
self.inputs['power'] = Input(
name='Power',
unit='W',
info='Power for each power plant and time step')
self.inputs['power_plants'] = Input(name='Power Plants',
unit='-',
info='Power Plants')
self.inputs['distance_costs'] = Input(
name='Distance costs',
unit='€/J',
info='Distance costs for each power plant and distribution network'
)
self.outputs['market_prices'] = Output(
name='Market prices',
unit='€/J',
info='Market prices for each distribution network and time step')
self.outputs['power_plants2'] = Output(
name='Power Plants',
unit='-',
info='Power Plants with additional information')
self.outputs['sorted_pp_id'] = Output(
name='Sorted power plant ids',
unit='-',
info='sorted power plant ids for each distribution network')
self.outputs['fut2'] = Output(
name='Futurs',
unit='s',
info='utc time array in seconds since epoch')
self.outputs['demands2'] = Output(
name='Demands',
unit='W',
info='European power demand for each time step')
def __init__(self, model_id, name: str):
# instantiate supermodel
super(Model, self).__init__(model_id, name)
# define inputs
self.outputs['data'] = Output({'name': 'Data'})
# define persistent variables
self.data = None
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['stock_ex_price'] = Input(name='Stock exchange price', unit='€/J', info="stock exchange price")
self.inputs['distnet_costs'] = Input(name='Distribution network cost', unit='{-, €/J}', info="distribution network cost")
self.inputs['service_cost'] = Input(name='Service cost', unit='€/J', info="service cost")
self.inputs['taxes'] = Input(name='Taxes', unit='€/J', info="taxes")
self.inputs['futures'] = Input(name='Futures', unit='s', info="Futures")
# define outputs
self.outputs['el_rate'] = Output(name='Electricity rate', unit='€/J', info='electricity rate')
self.outputs['times'] = Output(name='Times', unit='s', info='Times')
self.outputs['y_scaling'] = Output(name='Scaling of y axis', unit='', info='Scaling of y axis')
self.outputs['y_unit'] = Output(name='Unit of y axis', unit='', info='Unit of y axis')
self.outputs['y_label'] = Output(name='y label', unit='', info='Label of y axis')
# define properties
ET_def = {"location": ["Baden"],
"border": [[-1.0, -0.5, -0.2, 0.0, 0.2, 0.5, 1.0]],
"weight": [[-0.3, -0.6, -0.8, 1.1, 1.3, 1.5]]}
NT_def = {"location": ["Baden"],
"border": [[-1.0, -0.8, -0.5, 0.0, 0.4, 0.8, 1.0]],
"weight": [[-0.5, -0.6, -0.8, 1.2, 1.5, 1.8]]}
ET_def = json.dumps(ET_def)
NT_def = json.dumps(NT_def)
self.properties['weight_ET'] = Property(default=ET_def, data_type=str, name='energy tiers', unit='-',
info='borders and weights of energy tiers', example=ET_def)
self.properties['weight_NT'] = Property(default=NT_def, data_type=str, name='net tiers', unit='-',
info='borders and weights of net tiers', example=NT_def)
self.properties["scaling"] = Property(default=1, data_type=float, name='Scaling factor', unit='-',
info='Scaling factor for y axis', example='3.6e9')
self.properties["y_unit"] = Property(default='€/MWh', data_type=str, name='unit of y label', unit='-',
info='Unit of label for y axis', example='[€/MWh]')
self.properties["y_labeling"] = Property(default='Price', data_type=str, name='y label', unit='-',
info='Label for y axis', example='Price [€/MWh]')
# define persistent variables
self.weight_ET = None
self.weight_NT = None
self.y_scaling = None
self.y_unit = None
self.y_labeling = None
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.inputs['in'] = Input(name='Numbers',
unit='any',
info='number or number array')
self.outputs['sin'] = Output(name='Sin',
unit='any',
info='number or number array')
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.start_time_of_curr_interval = 0
self.start_time_of_next_interval = 0
self.simulation_time = 0
self.async_future = None
self.outputs['step'] = Output('Step', unit='-', info='step number, starts with 0')
self.outputs['time'] = Output('Future', unit='s', info='utc time in seconds since epoch')
# control
self.properties['prep_lead'] = Property('Time lead of Preperation step', default=0, data_type=int, unit='s', info='Amount of seconds the preparation step is started before the actual interval')
self.properties['sim_speed'] = Property('Simulation speed', default=1, data_type=int, unit='s', info='Seconds between simulation runs, 0 = as fast as possible')
# Simulation
self.properties['date_start'] = Property('Simulation Start (UTC)', default="2018-01-01 00:00", data_type=str, unit='YYYY-MM-DD hh:mm')
self.properties['date_delta_time'] = Property('Simulation time increase', default=1, data_type=float, unit='s', info='Amount of seconds the simulation time increases with each iteration')
self.properties['date_end'] = Property('Simulation Stop (UTC)', default="2999-01-01 00:00", data_type=str, unit='YYYY-MM-DD hh:mm')
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.outputs['const'] = Output('Number', unit='float')
self.properties['number'] = Property(
name='Number',
default=0,
data_type=float,
unit='float',
info='the constant number that gets set as output')
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['weather'] = Input('WeatherData', unit='Global radiations[W/m^2]', info='dict')
self.inputs['kwDaten'] = Input('PowerPlantsData', info='dict, power plant id required')
# define outputs
self.outputs['load'] = Output('Load', info='load of all photovoltaic power plants, value[0-1]')
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['weather'] = Input('WeatherData', unit='Wind speed[m/s], Wind measurement height[m]', info='dict')
self.inputs['kwDaten'] = Input('PowerPlantsData',unit='Hub-height[m], Ground roughness length[m]', info='dict')
# define outputs
self.outputs['load'] = Output('Load', info='load of all wind turbines, value[0-1]')
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.inputs['input'] = Input('Input')
self.outputs['output'] = Output('Output')
self.properties['sleep_amount'] = Property('Sleep Amount',
default=1,
data_type=float,
unit='s')
def __init__(self, model_id, name: str):
# instantiate supermodel
super(Model, self).__init__(model_id, name)
# define inputs
self.inputs['KWDaten'] = Input('PowerPlantsData',
unit='[€/J]',
info='complete power plant information')
# define outputs
self.outputs['Grenzkosten'] = Output('MarginalCost', unit='[€/J]')
def __init__(self, uuid, name: str):
super(Model, self).__init__(uuid, name)
self.outputs['const1'] = Output({
'name': 'Number1',
'unit': 'int',
'dimensions': []
})
self.outputs['const2'] = Output({
'name': 'Number2',
'unit': 'int',
'dimensions': []
})
self.properties['number1'] = Property(default=0,
data_type=float,
name='Number 1',
unit='-')
self.properties['number2'] = Property(default=0,
data_type=float,
name='Number 2',
unit='-')
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['futures'] = Input(
'Futures', unit='s', info='utc time array in seconds since epoch')
self.inputs['kwDaten'] = Input('PowerPlantsData',
info='dict, power plant id required ')
# define outputs
self.outputs['load'] = Output(
'Load', info='load of all running-water power plants, value[0-1]')
def __init__(self, model_id, name: str):
# instantiate supermodel
super(Model, self).__init__(model_id, name)
# define inputs
self.inputs['t'] = Input('Zeit')
# define outputs
self.outputs['kw_park'] = Output('Kraftwerkspark')
# define persistent variables
self.db = None
self.kwp = None
def __init__(self, model_id, name: str):
# instantiate supermodel
super(Model, self).__init__(model_id, name)
# define inputs
self.inputs['v'] = Input('wind speed')
self.inputs['dir'] = Input('wind direction')
# define outputs
self.outputs['p_el'] = Output('electrical power')
self.outputs['f_rot'] = Output('rotor frequency')
# define properties
self.properties['h_hub'] = Property('hub height',
default=10,
data_type=float)
self.properties['d'] = Property('diameter',
default=10,
data_type=float)
# define persistent variables
self.pers_variable_0 = 5
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['AuslastungallerKWs'] = Input(
'CombinedLoad',
info='combined load of all types of power plants, value[0-1]')
self.inputs['KWDaten'] = Input('PowerPlantsData',
unit='capex[€/W], spez_opex[1/s]',
info='dict')
# define outputs
self.outputs['opex'] = Output('OPEX', unit='[€/J]')
def __init__(self, id, name: str):
# instantiate supermodel
super(Model, self).__init__(id, name)
# define inputs
self.inputs['CombinedLoad'] = Input(
'CombinedLoad',
info='combined load of all types of power plants, value[0-1]')
self.inputs['KWDaten'] = Input('PowerPlantsData',
unit='W',
info='dict, power will be extracted')
# define outputs
self.outputs['scaled_power'] = Output('Power', unit='W')