Converters

A Converter enforces linear coupling between input and output flows. It models devices like boilers, heat pumps, and CHP plants.

See Converters (Math) for the formulation.

Factory Methods

Boiler

Single input (fuel), single output (heat), with thermal efficiency:

from fluxopt import Converter, Flow

fuel = Flow('gas', size=300)
heat_out = Flow('heat', size=200)

boiler = Converter.boiler('boiler', thermal_efficiency=0.9, fuel_flow=fuel, thermal_flow=heat_out)

This creates the conversion equation: 0.9 * P_gas - P_heat = 0, so 10 MW gas input produces 9 MW heat.

Power-to-Heat

Electric resistance heater — single input (electricity), single output (heat):

el = Flow('elec', size=50)
th = Flow('heat', size=50)

p2h = Converter.power2heat('p2h', efficiency=0.99, electrical_flow=el, thermal_flow=th)

Conversion equation: 0.99 * P_el - P_heat = 0.

Heat Pump

Two inputs (electricity + environmental source), single output (heat), with COP:

el = Flow('elec', size=50)
src = Flow('env', size=200)
th = Flow('heat', size=200)

hp = Converter.heat_pump('hp', cop=3.5, electrical_flow=el, source_flow=src, thermal_flow=th)

Two conversion equations:

• 3.5 * P_el - P_heat = 0 (COP definition)
• P_el + P_env - P_heat = 0 (energy balance)

CHP (Combined Heat and Power)

Single input (fuel), two outputs (electricity + heat). Two conversion equations, one per output:

fuel = Flow('gas', size=100)
el = Flow('elec', size=50)
th = Flow('heat', size=60)

chp = Converter.chp('chp', eta_el=0.4, eta_th=0.5,
                     fuel_flow=fuel, electrical_flow=el, thermal_flow=th)

This produces two equations:

• 0.4 * P_fuel - P_el = 0
• 0.5 * P_fuel - P_heat = 0

So 10 MW fuel input produces 4 MW electrical + 5 MW thermal.

Custom Conversion Factors

For devices not covered by factory methods, pass conversion_factors directly. Each dict in the list is one conversion equation, mapping flow short ids to their coefficients:

in1 = Flow('a', size=100)
in2 = Flow('b', size=100)
out = Flow('c', size=100)

conv = Converter(
    id='custom',
    inputs=[in1, in2],
    outputs=[out],
    conversion_factors=[{'a': 0.5, 'b': 0.3, 'c': -1}],
)

This enforces: 0.5 * P_a + 0.3 * P_b - P_c = 0.

Time-Varying Coefficients

Coefficients can vary per timestep (e.g., a heat pump with weather-dependent COP):

cop_profile = [3.2, 3.5, 3.8, 3.1]  # one value per timestep
hp = Converter.heat_pump('hp', cop=cop_profile, electrical_flow=el, source_flow=src, thermal_flow=th)

Full Example

Gas boiler serving a heat demand:

from datetime import datetime
from fluxopt import Carrier, Converter, Effect, Flow, Port, optimize

timesteps = [datetime(2024, 1, 1, h) for h in range(4)]
demand = [40.0, 70.0, 50.0, 60.0]

gas_source = Flow('gas', size=500, effects_per_flow_hour={'cost': 0.04})
fuel = Flow('gas', size=300)
heat_out = Flow('heat', size=200)
demand_flow = Flow('heat', size=100, fixed_relative_profile=[0.4, 0.7, 0.5, 0.6])

gas = Carrier('gas')
heat = Carrier('heat')

result = optimize(
    timesteps=timesteps,
    carriers=[gas, heat],
    effects=[Effect('cost', is_objective=True)],
    ports=[Port('grid', imports=[gas_source]), Port('demand', exports=[demand_flow])],
    converters=[Converter.boiler('boiler', thermal_efficiency=0.9, fuel_flow=fuel, thermal_flow=heat_out)],
)

# Gas consumed = heat / efficiency
print(result.flow_rate('boiler(gas)'))