Note

You can download this example as a Jupyter notebook or start it in interactive mode.

Multi-Link usage: CHP with fixed heat-power ratio#

This notebook if a demonstration of Link with multiple outputs: Combined-Heat-and-Power (CHP) with fixed heat-power ratio

For a CHP with a more complicated heat-power feasible operational area, see the power-to-gas example

This example demonstrates a Link component with more than one bus output (“bus2” in this case). In general links can have many output buses.

In this example a CHP must be heat-following because there is no other supply of heat to the bus “Frankfurt heat”.

[1]:

import pypsa, numpy as np

First tell PyPSA that links will have a 2nd bus by overriding the component_attrs. This can be done for as many buses as you need with format busi for i = 2,3,4,5,….

[2]:

override_component_attrs = pypsa.descriptors.Dict(
    {k: v.copy() for k, v in pypsa.components.component_attrs.items()}
)
override_component_attrs["Link"].loc["bus2"] = [
    "string",
    np.nan,
    np.nan,
    "2nd bus",
    "Input (optional)",
]
override_component_attrs["Link"].loc["efficiency2"] = [
    "static or series",
    "per unit",
    1.0,
    "2nd bus efficiency",
    "Input (optional)",
]
override_component_attrs["Link"].loc["p2"] = [
    "series",
    "MW",
    0.0,
    "2nd bus output",
    "Output",
]

[3]:

network = pypsa.Network(override_component_attrs=override_component_attrs)

network.add("Bus", "Frankfurt", carrier="AC")
network.add("Load", "Frankfurt", bus="Frankfurt", p_set=5)


network.add("Bus", "Frankfurt heat", carrier="heat")
network.add("Load", "Frankfurt heat", bus="Frankfurt heat", p_set=3)


network.add("Bus", "Frankfurt gas", carrier="gas")
network.add("Store", "Frankfurt gas", e_initial=1e6, e_nom=1e6, bus="Frankfurt gas")

network.add(
    "Link",
    "OCGT",
    bus0="Frankfurt gas",
    bus1="Frankfurt",
    p_nom_extendable=True,
    capital_cost=600,
    efficiency=0.4,
)


network.add(
    "Link",
    "CHP",
    bus0="Frankfurt gas",
    bus1="Frankfurt",
    bus2="Frankfurt heat",
    p_nom_extendable=True,
    capital_cost=1400,
    efficiency=0.3,
    efficiency2=0.3,
)

[4]:

network.lopf();

INFO:pypsa.linopf:Prepare linear problem
INFO:pypsa.linopf:Total preparation time: 0.09s
INFO:pypsa.linopf:Solve linear problem using Glpk solver
INFO:pypsa.linopf:Optimization successful. Objective value: 1.70e+04

[5]:

network.loads_t.p

[5]:

Load	Frankfurt	Frankfurt heat
snapshot
now	5.0	3.0

[6]:

network.links_t.p0

[6]:

Link	OCGT	CHP
snapshot
now	5.0	10.0

[7]:

network.links_t.p1

[7]:

Link	OCGT	CHP
snapshot
now	-2.0	-3.0

[8]:

network.links_t.p2

[8]:

Link	OCGT	CHP
snapshot
now	0.0	-3.0