Prepare network

Function suite and script to define the network to be solved. Network components are added here. Additional constraints require the linopy model and are added in the solve_network script.

These functions are currently only for the overnight mode. Myopic pathway mode contains near duplicates which need to merged in the future. Idem for solve_network.py

add_H2(network, config, nodes, costs)

Add H2 generators, storage and links to the network - currently all or nothing

Parameters:

Name	Type	Description	Default
network	Network	network object too which H2 comps will be added	required
config	dict	the config (snakemake config)	required
nodes	Index	the buses	required
costs	DataFrame	the cost database	required

Source code in workflow/scripts/prepare_network.py

def add_H2(network: pypsa.Network, config: dict, nodes: pd.Index, costs: pd.DataFrame):
    """Add H2 generators, storage and links to the network - currently all or nothing

    Args:
        network (pypsa.Network): network object too which H2 comps will be added
        config (dict): the config (snakemake config)
        nodes (pd.Index): the buses
        costs (pd.DataFrame): the cost database
    """
    # TODO, does it make sense?
    if config.get("heat_coupling", False):
        network.add(
            "Link",
            name=nodes + " H2 Electrolysis",
            bus0=nodes,
            bus1=nodes + " H2",
            bus2=nodes + " central heat",
            p_nom_extendable=True,
            carrier="H2 Electrolysis",
            efficiency=costs.at["electrolysis", "efficiency"],
            efficiency2=costs.at["electrolysis", "efficiency-heat"],
            capital_cost=costs.at["electrolysis", "capital_cost"],
            lifetime=costs.at["electrolysis", "lifetime"],
        )
    else:
        network.add(
            "Link",
            name=nodes + " H2 Electrolysis",
            bus0=nodes,
            bus1=nodes + " H2",
            p_nom_extendable=True,
            carrier="H2 Electrolysis",
            efficiency=costs.at["electrolysis", "efficiency"],
            capital_cost=costs.at["electrolysis", "capital_cost"],
            lifetime=costs.at["electrolysis", "lifetime"],
        )

    if "fuel cell" in config["Techs"]["vre_techs"]:
        network.add(
            "Link",
            name=nodes + " H2 Fuel Cell",
            bus0=nodes + " H2",
            bus1=nodes,
            p_nom_extendable=True,
            efficiency=costs.at["fuel cell", "efficiency"],
            capital_cost=costs.at["fuel cell", "efficiency"]
            * costs.at["fuel cell", "capital_cost"],
            lifetime=costs.at["fuel cell", "lifetime"],
            carrier="H2 fuel cell",
        )
    if "H2 turbine" in config["Techs"]["vre_techs"]:
        network.add(
            "Link",
            name=nodes + " H2 turbine",
            bus0=nodes + " H2",
            bus1=nodes,
            p_nom_extendable=True,
            efficiency=costs.at["H2 turbine", "efficiency"],
            capital_cost=costs.at["H2 turbine", "efficiency"]
            * costs.at["H2 turbine", "capital_cost"],
            lifetime=costs.at["H2 turbine", "lifetime"],
            carrier="H2 turbine",
        )

    H2_under_nodes_ = pd.Index(config["H2"]["geo_storage_nodes"])
    H2_type1_nodes_ = nodes.difference(H2_under_nodes_)
    H2_under_nodes = H2_under_nodes_.intersection(nodes)
    H2_type1_nodes = H2_type1_nodes_.intersection(nodes)
    if not (
        H2_under_nodes_.shape == H2_under_nodes.shape
        and H2_type1_nodes_.shape == H2_type1_nodes.shape
    ):
        logger.warning("Some H2 storage nodes are not in the network buses")

    network.add(
        "Store",
        H2_under_nodes + " H2 Store",
        bus=H2_under_nodes + " H2",
        e_nom_extendable=True,
        e_cyclic=True,
        capital_cost=costs.at["hydrogen storage underground", "capital_cost"],
        lifetime=costs.at["hydrogen storage underground", "lifetime"],
    )

    # TODO harmonize with remind (add if in techs)
    network.add(
        "Store",
        H2_type1_nodes + " H2 Store",
        bus=H2_type1_nodes + " H2",
        e_nom_extendable=True,
        e_cyclic=True,
        capital_cost=costs.at["hydrogen storage tank type 1 including compressor", "capital_cost"],
        lifetime=costs.at["hydrogen storage tank type 1 including compressor", "lifetime"],
    )
    if config["add_methanation"]:
        cost_year = snakemake.wildcards["planning_horizons"]
        network.add(
            "Link",
            nodes + " Sabatier",
            bus0=nodes + " H2",
            bus1=nodes + " gas",
            carrier="Sabatier",
            p_nom_extendable=True,
            efficiency=costs.at["methanation", "efficiency"],
            capital_cost=costs.at["methanation", "efficiency"]
            * costs.at["methanation", "capital_cost"]
            + costs.at["direct air capture", "capital_cost"]
            * costs.at["gas", "co2_emissions"]
            * costs.at["methanation", "efficiency"],
            # TODO fix me
            lifetime=costs.at["methanation", "lifetime"],
            marginal_cost=(400 - 5 * (int(cost_year) - 2020))
            * costs.at["gas", "co2_emissions"]
            * costs.at["methanation", "efficiency"],
        )

    if config["Techs"]["hydrogen_lines"]:
        edge_path = config["edge_paths"].get(config["scenario"]["topology"], None)
        if edge_path is None:
            raise ValueError(f"No grid found for topology {config['scenario']['topology']}")
        else:
            edges_ = pd.read_csv(
                edge_path, sep=",", header=None, names=["bus0", "bus1", "p_nom"]
            ).fillna(0)
            edges = edges_[edges_["bus0"].isin(nodes) & edges_["bus1"].isin(nodes)]
            if edges_.shape[0] != edges.shape[0]:
                logger.warning("Some edges are not in the network buses")

        # fix this to use map with x.y
        lengths = config["lines"]["line_length_factor"] * np.array(
            [
                haversine(
                    [network.buses.at[bus0, "x"], network.buses.at[bus0, "y"]],
                    [network.buses.at[bus1, "x"], network.buses.at[bus1, "y"]],
                )
                for bus0, bus1 in edges[["bus0", "bus1"]].values
            ]
        )

        # TODO harmonize with remind (add if in techs)
        cc = costs.at["H2 (g) pipeline", "capital_cost"] * lengths

        # === h2 pipeline with losses ====
        # NB this only works if there is an equalising constraint, which is hidden in solve_ntwk
        network.add(
            "Link",
            edges["bus0"] + "-" + edges["bus1"] + " H2 pipeline",
            suffix=" positive",
            bus0=edges["bus0"].values + " H2",
            bus1=edges["bus1"].values + " H2",
            bus2=edges["bus0"].values,
            carrier="H2 pipeline",
            p_nom_extendable=True,
            p_nom=0,
            p_nom_min=0,
            p_min_pu=0,
            efficiency=config["transmission_efficiency"]["H2 pipeline"]["efficiency_static"]
            * config["transmission_efficiency"]["H2 pipeline"]["efficiency_per_1000km"]
            ** (lengths / 1000),
            efficiency2=-config["transmission_efficiency"]["H2 pipeline"]["compression_per_1000km"]
            * lengths
            / 1e3,
            length=lengths,
            lifetime=costs.at["H2 (g) pipeline", "lifetime"],
            capital_cost=cc,
        )

        network.add(
            "Link",
            edges["bus0"] + "-" + edges["bus1"] + " H2 pipeline",
            suffix=" reversed",
            carrier="H2 pipeline",
            bus0=edges["bus1"].values + " H2",
            bus1=edges["bus0"].values + " H2",
            bus2=edges["bus1"].values,
            p_nom_extendable=True,
            p_nom=0,
            p_nom_min=0,
            p_min_pu=0,
            efficiency=config["transmission_efficiency"]["H2 pipeline"]["efficiency_static"]
            * config["transmission_efficiency"]["H2 pipeline"]["efficiency_per_1000km"]
            ** (lengths / 1000),
            efficiency2=-config["transmission_efficiency"]["H2 pipeline"]["compression_per_1000km"]
            * lengths
            / 1e3,
            length=lengths,
            lifetime=costs.at["H2 (g) pipeline", "lifetime"],
            capital_cost=0,
        )

add_biomass_chp(network, costs, nodes, biomass_potential, prov_centroids, add_beccs=True)

Add biomass to the network. Biomass is here a new build (and not a retrofit) and is not co-fired with coal. An optional CC can be added to biomass

NOTE THAT THE CC IS NOT CONSTRAINED TO THE BIOMASS?

Parameters:

Name	Type	Description	Default
network	Network	the pypsa network	required
costs	DataFrame	the costs dataframe	required
nodes	Index	the nodes	required
biomass_potential	DataFrame	the biomass potential	required
prov_centroids	GeoDataFrame	the x,y locations of the nodes	required
add_beccs	bool	whether to add BECCS. Defaults to True.	True

Source code in workflow/scripts/prepare_network.py

def add_biomass_chp(
    network: pypsa.Network,
    costs: pd.DataFrame,
    nodes: pd.Index,
    biomass_potential: pd.DataFrame,
    prov_centroids: gpd.GeoDataFrame,
    add_beccs: bool = True,
):
    """Add biomass to the network. Biomass is here a new build (and not a retrofit)
    and is not co-fired with coal. An optional CC can be added to biomass

    NOTE THAT THE CC IS NOT CONSTRAINED TO THE BIOMASS?

    Args:
        network (pypsa.Network): the pypsa network
        costs (pd.DataFrame): the costs dataframe
        nodes (pd.Index): the nodes
        biomass_potential (pd.DataFrame): the biomass potential
        prov_centroids (gpd.GeoDataFrame): the x,y locations of the nodes
        add_beccs (bool, optional): whether to add BECCS. Defaults to True.
    """

    suffix = " biomass"
    biomass_potential.index = biomass_potential.index.map(
        lambda x: x + suffix if not x.endswith(suffix) else x
    )

    network.add(
        "Bus",
        nodes,
        suffix=suffix,
        x=prov_centroids.x,
        y=prov_centroids.y,
        carrier="biomass",
    )
    logger.info("Adding biomass buses")
    logger.info(f"{nodes + suffix}")
    logger.info("potentials")
    # aggricultural residue biomass
    # NOTE THIS CURRENTLY DOESN'T INCLUDE TRANSPORT between nodes
    # NOTE additional emissions from treatment/remedials are missing
    network.add(
        "Store",
        nodes + suffix,
        bus=nodes + suffix,
        e_nom_extendable=False,
        e_nom=biomass_potential,
        e_initial=biomass_potential,
        carrier="biomass",
    )
    biomass_co2_intsty = estimate_co2_intensity_xing()
    network.add(
        "Link",
        nodes + " central biomass CHP",
        bus0=nodes + " biomass",
        bus1=nodes,
        bus2=nodes + " central heat",
        bus3=nodes + " CO2",
        p_nom_extendable=True,
        carrier="biomass",
        efficiency=costs.at["biomass CHP", "efficiency"],
        efficiency2=costs.at["biomass CHP", "efficiency-heat"],
        efficiency3=biomass_co2_intsty,
        capital_cost=costs.at["biomass CHP", "efficiency"]
        * costs.at["biomass CHP", "capital_cost"],
        marginal_cost=costs.at["biomass CHP", "efficiency"]
        * costs.at["biomass CHP", "marginal_cost"]
        + costs.at["solid biomass", "fuel"],
        lifetime=costs.at["biomass CHP", "lifetime"],
    )
    if add_beccs:
        network.add(
            "Link",
            nodes + " central biomass CHP capture",
            bus0=nodes + " CO2",
            bus1=nodes + " CO2 capture",
            bus2=nodes,
            p_nom_extendable=True,
            carrier="CO2 capture",
            efficiency=costs.at["biomass CHP capture", "capture_rate"],
            efficiency2=-1
            * costs.at["biomass CHP capture", "capture_rate"]
            * costs.at["biomass CHP capture", "electricity-input"],
            capital_cost=costs.at["biomass CHP capture", "capture_rate"]
            * costs.at["biomass CHP capture", "capital_cost"],
            lifetime=costs.at["biomass CHP capture", "lifetime"],
        )

    network.add(
        "Link",
        nodes + " decentral biomass boiler",
        bus0=nodes + " biomass",
        bus1=nodes + " decentral heat",
        p_nom_extendable=True,
        carrier="biomass",
        efficiency=costs.at["biomass boiler", "efficiency"],
        capital_cost=costs.at["biomass boiler", "efficiency"]
        * costs.at["biomass boiler", "capital_cost"],
        marginal_cost=costs.at["biomass boiler", "efficiency"]
        * costs.at["biomass boiler", "marginal_cost"]
        + costs.at["biomass boiler", "pelletizing cost"]
        + costs.at["solid biomass", "fuel"],
        lifetime=costs.at["biomass boiler", "lifetime"],
    )

add_carriers(network, config, costs)

Add the various carriers to the network based on the config file

Parameters:

Name	Type	Description	Default
network	Network	the pypsa network	required
config	dict	the config file	required
costs	DataFrame	the costs dataframe	required

Source code in workflow/scripts/prepare_network.py

def add_carriers(network: pypsa.Network, config: dict, costs: pd.DataFrame):
    """Add the various carriers to the network based on the config file

    Args:
        network (pypsa.Network): the pypsa network
        config (dict): the config file
        costs (pd.DataFrame): the costs dataframe
    """

    network.add("Carrier", "AC")
    if config.get("heat_coupling", False):
        network.add("Carrier", "heat")
    for carrier in config["Techs"]["vre_techs"]:
        network.add("Carrier", carrier)
        if carrier == "hydroelectricity":
            network.add("Carrier", "hydro_inflow")
    for carrier in config["Techs"]["store_techs"]:
        network.add("Carrier", carrier)
        if carrier == "battery":
            network.add("Carrier", "battery discharger")

    # add fuel carriers, emissions in # in t_CO2/MWht
    if config["add_gas"]:
        network.add("Carrier", "gas", co2_emissions=costs.at["gas", "co2_emissions"])
    if config["add_coal"]:
        network.add("Carrier", "coal", co2_emissions=costs.at["coal", "co2_emissions"])
    if "CCGT-CCS" in config["Techs"]["conv_techs"]:
        network.add("Carrier", "gas ccs", co2_emissions=costs.at["gas ccs", "co2_emissions"])
    if "coal-CCS" in config["Techs"]["conv_techs"]:
        network.add("Carrier", "coal ccs", co2_emissions=costs.at["coal ccs", "co2_emissions"])

add_co2_capture_support(network, nodes, prov_centroids)

Add the necessary CO2 capture carriers & stores to the network Args: network (pypsa.Network): the network object nodes (pd.Index): the nodes prov_centroids (gpd.GeoDataFrame): the x,y locations of the nodes

Source code in workflow/scripts/prepare_network.py

def add_co2_capture_support(
    network: pypsa.Network, nodes: pd.Index, prov_centroids: gpd.GeoDataFrame
):
    """Add the necessary CO2 capture carriers & stores to the network
    Args:
        network (pypsa.Network): the network object
        nodes (pd.Index): the nodes
        prov_centroids (gpd.GeoDataFrame): the x,y locations of the nodes
    """

    network.add("Carrier", "CO2", co2_emissions=0)
    network.add(
        "Bus",
        nodes,
        suffix=" CO2",
        x=prov_centroids.x,
        y=prov_centroids.y,
        carrier="CO2",
    )

    network.add("Store", nodes + " CO2", bus=nodes + " CO2", carrier="CO2")
    # normally taking away from carrier generates CO2, but here we are
    # adding CO2 stored, so the emissions will point the other way ?
    network.add("Carrier", "CO2 capture", co2_emissions=1)
    network.add(
        "Bus",
        nodes,
        suffix=" CO2 capture",
        x=prov_centroids.x,
        y=prov_centroids.y,
        carrier="CO2 capture",
    )

    network.add(
        "Store",
        nodes + " CO2 capture",
        bus=nodes + " CO2 capture",
        e_nom_extendable=True,
        carrier="CO2 capture",
    )

add_conventional_generators(network, nodes, config, prov_centroids, costs)

Add conventional generators to the network

Parameters:

Name	Type	Description	Default
network	Network	the pypsa network object	required
nodes	Index	the nodes	required
config	dict	the snakemake config	required
prov_centroids	GeoDataFrame	the x,y locations of the nodes	required
costs	DataFrame	the costs data base	required

Source code in workflow/scripts/prepare_network.py

def add_conventional_generators(
    network: pypsa.Network,
    nodes: pd.Index,
    config: dict,
    prov_centroids: gpd.GeoDataFrame,
    costs: pd.DataFrame,
):
    """Add conventional generators to the network

    Args:
        network (pypsa.Network): the pypsa network object
        nodes (pd.Index): the nodes
        config (dict): the snakemake config
        prov_centroids (gpd.GeoDataFrame): the x,y locations of the nodes
        costs (pd.DataFrame): the costs data base
    """
    if config["add_gas"]:
        # add converter from fuel source
        network.add(
            "Bus",
            nodes,
            suffix=" gas",
            x=prov_centroids.x,
            y=prov_centroids.y,
            carrier="gas",
            location=nodes,
        )

        network.add(
            "Generator",
            nodes,
            suffix=" gas fuel",
            bus=nodes + " gas",
            carrier="gas",
            p_nom_extendable=True,
            p_nom=1e7,
            marginal_cost=costs.at["gas", "fuel"],
        )

        # gas prices identical per region, pipelines ignored
        network.add(
            "Store",
            nodes + " gas Store",
            bus=nodes + " gas",
            e_nom_extendable=True,
            carrier="gas",
            e_nom=1e7,
            e_cyclic=True,
        )

    # add gas will then be true
    gas_techs = ["OCGT", "CCGT"]
    for tech in gas_techs:
        if tech in config["Techs"]["conv_techs"]:
            network.add(
                "Link",
                nodes,
                suffix=f" {tech}",
                bus0=nodes + " gas",
                bus1=nodes,
                marginal_cost=costs.at[tech, "efficiency"]
                * costs.at[tech, "VOM"],  # NB: VOM is per MWel
                capital_cost=costs.at[tech, "efficiency"]
                * costs.at[tech, "capital_cost"],  # NB: capital cost is per MWel
                p_nom_extendable=True,
                efficiency=costs.at[tech, "efficiency"],
                lifetime=costs.at[tech, "lifetime"],
                carrier=f"gas {tech}",
            )

    if "CCGT-CCS" in config["Techs"]["conv_techs"]:
        network.add(
            "Generator",
            nodes,
            suffix=" CCGT-CCS",
            bus=nodes,
            carrier="gas ccs",
            p_nom_extendable=True,
            efficiency=costs.at["CCGT-CCS", "efficiency"],
            marginal_cost=costs.at["CCGT-CCS", "marginal_cost"],
            capital_cost=costs.at["CCGT-CCS", "efficiency"]
            * costs.at["CCGT-CCS", "capital_cost"],  # NB: capital cost is per MWel
            lifetime=costs.at["CCGT-CCS", "lifetime"],
            p_max_pu=0.9,  # planned and forced outages
        )

    if config["add_coal"]:
        ramps = config.get(
            "fossil_ramps", {"coal": {"ramp_limit_up": np.nan, "ramp_limit_down": np.nan}}
        )
        ramps = ramps.get("coal", {"ramp_limit_up": np.nan, "ramp_limit_down": np.nan})
        ramps = {k: v * config["snapshots"]["frequency"] for k, v in ramps.items()}
        # this is the non sector-coupled approach
        # for industry may have an issue in that coal feeds to chem sector
        # no coal in Beijing - political decision
        network.add(
            "Generator",
            nodes[nodes != "Beijing"],
            suffix=" coal power",
            bus=nodes[nodes != "Beijing"],
            carrier="coal",
            p_nom_extendable=True,
            efficiency=costs.at["coal", "efficiency"],
            marginal_cost=costs.at["coal", "marginal_cost"],
            capital_cost=costs.at["coal", "efficiency"]
            * costs.at["coal", "capital_cost"],  # NB: capital cost is per MWel
            lifetime=costs.at["coal", "lifetime"],
            ramp_limit_up=ramps["ramp_limit_up"],
            ramp_limit_down=ramps["ramp_limit_down"],
            p_max_pu=0.9,  # planned and forced outages
        )

        if "coal-CCS" in config["Techs"]["conv_techs"]:
            network.add(
                "Generator",
                nodes,
                suffix=" coal-CCS",
                bus=nodes,
                carrier="coal ccs",
                p_nom_extendable=True,
                efficiency=costs.at["coal ccs", "efficiency"],
                marginal_cost=costs.at["coal ccs", "marginal_cost"],
                capital_cost=costs.at["coal ccs", "efficiency"]
                * costs.at["coal ccs", "capital_cost"],  # NB: capital cost is per MWel
                lifetime=costs.at["coal ccs", "lifetime"],
                p_max_pu=0.9,  # planned and forced outages
            )

add_heat_coupling(network, config, nodes, prov_centroids, costs, planning_year, paths)

Add the heat-coupling links and generators to the network

Parameters:

Name	Type	Description	Default
network	Network	the network object	required
config	dict	the config	required
nodes	Index	the node names. Defaults to pd.Index.	required
prov_centroids	GeoDataFrame	the node locations.	required
costs	DataFrame	the costs dataframe for emissions	required
paths	dict	the paths to the data files	required

Source code in workflow/scripts/prepare_network.py

def add_heat_coupling(
    network: pypsa.Network,
    config: dict,
    nodes: pd.Index,
    prov_centroids: gpd.GeoDataFrame,
    costs: pd.DataFrame,
    planning_year: int,
    paths: dict,
):
    """Add the heat-coupling links and generators to the network

    Args:
        network (pypsa.Network): the network object
        config (dict): the config
        nodes (pd.Index): the node names. Defaults to pd.Index.
        prov_centroids (gpd.GeoDataFrame): the node locations.
        costs (pd.DataFrame): the costs dataframe for emissions
        paths (dict): the paths to the data files
    """
    central_fraction = pd.read_hdf(paths["central_fraction"])
    with pd.HDFStore(paths["heat_demand_profile"], mode="r") as store:
        heat_demand = store["heat_demand_profiles"]
        # TODO fix this if not working
        heat_demand.index = heat_demand.index.tz_localize(None)
        heat_demand = heat_demand.loc[network.snapshots]

    network.add(
        "Bus",
        nodes,
        suffix=" decentral heat",
        x=prov_centroids.x,
        y=prov_centroids.y,
        carrier="heat",
        location=nodes,
    )

    network.add(
        "Bus",
        nodes,
        suffix=" central heat",
        x=prov_centroids.x,
        y=prov_centroids.y,
        carrier="heat",
        location=nodes,
    )

    network.add(
        "Load",
        nodes,
        suffix=" decentral heat",
        bus=nodes + " decentral heat",
        p_set=heat_demand[nodes].multiply(1 - central_fraction[nodes]),
    )

    network.add(
        "Load",
        nodes,
        suffix=" central heat",
        bus=nodes + " central heat",
        p_set=heat_demand[nodes].multiply(central_fraction[nodes]),
    )

    if "heat pump" in config["Techs"]["vre_techs"]:
        logger.info(f"loading cop profiles from {paths['cop_name']}")
        with pd.HDFStore(paths["cop_name"], mode="r") as store:
            ashp_cop = store["ashp_cop_profiles"]
            ashp_cop.index = ashp_cop.index.tz_localize(None)
            ashp_cop = shift_profile_to_planning_year(
                ashp_cop, snakemake.wildcards.planning_horizons
            )
            gshp_cop = store["gshp_cop_profiles"]
            gshp_cop.index = gshp_cop.index.tz_localize(None)
            gshp_cop = shift_profile_to_planning_year(
                gshp_cop, snakemake.wildcards.planning_horizons
            )

        for cat in [" decentral ", " central "]:
            network.add(
                "Link",
                nodes,
                suffix=cat + "heat pump",
                bus0=nodes,
                bus1=nodes + cat + "heat",
                carrier="heat pump",
                efficiency=(
                    ashp_cop.loc[network.snapshots, nodes]
                    if config["time_dep_hp_cop"]
                    else costs.at[cat.lstrip() + "air-sourced heat pump", "efficiency"]
                ),
                capital_cost=costs.at[cat.lstrip() + "air-sourced heat pump", "efficiency"]
                * costs.at[cat.lstrip() + "air-sourced heat pump", "capital_cost"],
                marginal_cost=costs.at[cat.lstrip() + "air-sourced heat pump", "efficiency"]
                * costs.at[cat.lstrip() + "air-sourced heat pump", "marginal_cost"],
                p_nom_extendable=True,
                lifetime=costs.at[cat.lstrip() + "air-sourced heat pump", "lifetime"],
            )

        network.add(
            "Link",
            nodes,
            suffix=" ground heat pump",
            bus0=nodes,
            bus1=nodes + " decentral heat",
            carrier="heat pump",
            efficiency=(
                gshp_cop.loc[network.snapshots, nodes]
                if config["time_dep_hp_cop"]
                else costs.at["decentral ground-sourced heat pump", "efficiency"]
            ),
            marginal_cost=costs.at[cat.lstrip() + "ground-sourced heat pump", "efficiency"]
            * costs.at[cat.lstrip() + "ground-sourced heat pump", "marginal_cost"],
            capital_cost=costs.at[cat.lstrip() + "ground-sourced heat pump", "efficiency"]
            * costs.at["decentral ground-sourced heat pump", "capital_cost"],
            p_nom_extendable=True,
            lifetime=costs.at["decentral ground-sourced heat pump", "lifetime"],
        )

    if "water tanks" in config["Techs"]["store_techs"]:
        for cat in [" decentral ", " central "]:
            network.add(
                "Bus",
                nodes,
                suffix=cat + "water tanks",
                x=prov_centroids.x,
                y=prov_centroids.y,
                carrier="water tanks",
                location=nodes,
            )

            network.add(
                "Link",
                nodes + cat + "water tanks charger",
                bus0=nodes + cat + "heat",
                bus1=nodes + cat + "water tanks",
                carrier="water tanks",
                efficiency=costs.at["water tank charger", "efficiency"],
                p_nom_extendable=True,
            )

            network.add(
                "Link",
                nodes + cat + "water tanks discharger",
                bus0=nodes + cat + "water tanks",
                bus1=nodes + cat + "heat",
                carrier="water tanks",
                efficiency=costs.at["water tank discharger", "efficiency"],
                p_nom_extendable=True,
            )
            # [HP] 180 day time constant for centralised, 3 day for decentralised
            tes_tau = config["water_tanks"]["tes_tau"][cat.strip()]
            network.add(
                "Store",
                nodes + cat + "water tank",
                bus=nodes + cat + "water tanks",
                carrier="water tanks",
                e_cyclic=True,
                e_nom_extendable=True,
                standing_loss=1 - np.exp(-1 / (24.0 * tes_tau)),
                capital_cost=costs.at[cat.lstrip() + "water tank storage", "capital_cost"],
                lifetime=costs.at[cat.lstrip() + "water tank storage", "lifetime"],
            )

    if "resistive heater" in config["Techs"]["vre_techs"]:
        for cat in [" decentral ", " central "]:
            network.add(
                "Link",
                nodes + cat + "resistive heater",
                bus0=nodes,
                bus1=nodes + cat + "heat",
                carrier="resistive heater",
                efficiency=costs.at[cat.lstrip() + "resistive heater", "efficiency"],
                capital_cost=costs.at[cat.lstrip() + "resistive heater", "efficiency"]
                * costs.at[cat.lstrip() + "resistive heater", "capital_cost"],
                marginal_cost=costs.at[cat.lstrip() + "resistive heater", "efficiency"]
                * costs.at[cat.lstrip() + "resistive heater", "marginal_cost"],
                p_nom_extendable=True,
                lifetime=costs.at[cat.lstrip() + "resistive heater", "lifetime"],
            )

    if (
        "H2 CHP" in config["Techs"]["vre_techs"]
        and config["add_H2"]
        and config.get("heat_coupling", False)
    ):
        network.add(
            "Bus",
            nodes,
            suffix=" central H2 CHP",
            x=prov_centroids.x,
            y=prov_centroids.y,
            carrier="H2",
            location=nodes,
        )
        network.add(
            "Link",
            name=nodes + " central H2 CHP",
            bus0=nodes + " H2",
            bus1=nodes,
            bus2=nodes + " central heat",
            p_nom_extendable=True,
            efficiency=costs.at["central hydrogen CHP", "efficiency"],
            efficiency2=costs.at["central hydrogen CHP", "efficiency"]
            / costs.at["central hydrogen CHP", "c_b"],
            capital_cost=costs.at["central hydrogen CHP", "efficiency"]
            * costs.at["central hydrogen CHP", "capital_cost"],
            lifetime=costs.at["central hydrogen CHP", "lifetime"],
            carrier="H2 CHP",
        )

    if "CHP gas" in config["Techs"]["conv_techs"]:
        # TODO apply same as for coal (include Cb)
        # OCGT CHP
        network.add(
            "Link",
            nodes,
            suffix=" CHP gas",
            bus0=nodes + " gas",
            bus1=nodes,
            bus2=nodes + " central heat",
            p_nom_extendable=True,
            marginal_cost=costs.at["central gas CHP", "efficiency"]
            * costs.at["central gas CHP", "VOM"],  # NB: VOM is per MWel
            capital_cost=costs.at["central gas CHP", "efficiency"]
            * costs.at["central gas CHP", "capital_cost"],  # NB: capital cost is per MWel
            efficiency=costs.at["central gas CHP", "efficiency"],
            efficiency2=config["chp_parameters"]["eff_th"],
            lifetime=costs.at["central gas CHP", "lifetime"],
            carrier="CHP gas",
        )

    if "CHP coal" in config["Techs"]["conv_techs"]:
        logger.info("Adding CHP coal to network")

        network.add(
            "Bus",
            nodes,
            suffix=" coal fuel",
            x=prov_centroids.x,
            y=prov_centroids.y,
            carrier="coal",
            location=nodes,
        )

        network.add(
            "Generator",
            nodes + " coal fuel",
            bus=nodes + " coal fuel",
            carrier="coal",
            p_nom_extendable=False,
            p_nom=1e8,
            marginal_cost=costs.at["coal", "fuel"],
        )

        # NOTE generator | boiler is a key word for the constraint
        network.add(
            "Link",
            name=nodes,
            suffix=" CHP coal generator",
            bus0=nodes + " coal fuel",
            bus1=nodes,
            p_nom_extendable=True,
            marginal_cost=costs.at["central coal CHP", "efficiency"]
            * costs.at["central coal CHP", "VOM"],  # NB: VOM is per MWel
            capital_cost=costs.at["central coal CHP", "efficiency"]
            * costs.at["central coal CHP", "capital_cost"],  # NB: capital cost is per MWel
            efficiency=costs.at["central coal CHP", "efficiency"],
            c_b=costs.at["central coal CHP", "c_b"],
            p_nom_ratio=1.0,
            lifetime=costs.at["central coal CHP", "lifetime"],
            carrier="CHP coal",
        )

        network.add(
            "Link",
            nodes,
            suffix=" central CHP coal boiler",
            bus0=nodes + " coal fuel",
            bus1=nodes + " central heat",
            carrier="CHP coal",
            p_nom_extendable=True,
            marginal_cost=costs.at["central coal CHP", "efficiency"]
            * costs.at["central coal CHP", "VOM"],  # NB: VOM is per MWel
            efficiency=costs.at["central coal CHP", "efficiency"]
            / costs.at["central coal CHP", "c_v"],
            lifetime=costs.at["central coal CHP", "lifetime"],
        )

    if "coal boiler" in config["Techs"]["conv_techs"]:
        for cat in ["decentral", "central"]:
            network.add(
                "Link",
                nodes + f" {cat} coal boiler",
                p_nom_extendable=True,
                bus0=nodes + " coal fuel",
                bus1=nodes + f" {cat} heat",
                efficiency=costs.at[f"{cat} coal boiler", "efficiency"],
                marginal_cost=costs.at[f"{cat} coal boiler", "efficiency"]
                * costs.at[f"{cat} coal boiler", "VOM"],
                capital_cost=costs.at[f"{cat} coal boiler", "efficiency"]
                * costs.at[f"{cat} coal boiler", "capital_cost"],
                lifetime=costs.at[f"{cat} coal boiler", "lifetime"],
                carrier=f"coal boiler {cat}",
            )

    if "gas boiler" in config["Techs"]["conv_techs"]:
        for cat in ["decentral", "central"]:
            network.add(
                "Link",
                nodes + cat + "gas boiler",
                p_nom_extendable=True,
                bus0=nodes + " gas",
                bus1=nodes + f" {cat} heat",
                efficiency=costs.at[f"{cat} gas boiler", "efficiency"],
                marginal_cost=costs.at[f"{cat} gas boiler", "VOM"],
                capital_cost=costs.at[f"{cat} gas boiler", "efficiency"]
                * costs.at[f"{cat} gas boiler", "capital_cost"],
                lifetime=costs.at[f"{cat} gas boiler", "lifetime"],
                carrier=f"gas boiler {cat}",
            )

    if "solar thermal" in config["Techs"]["vre_techs"]:
        # this is the amount of heat collected in W per m^2, accounting
        # for efficiency
        with pd.HDFStore(paths["solar_thermal_name"], mode="r") as store:
            # 1e3 converts from W/m^2 to MW/(1000m^2) = kW/m^2
            solar_thermal = config["solar_cf_correction"] * store["solar_thermal_profiles"] / 1e3

        solar_thermal.index = solar_thermal.index.tz_localize(None)
        solar_thermal = shift_profile_to_planning_year(solar_thermal, planning_year)
        solar_thermal = solar_thermal.loc[network.snapshots]

        for cat in [" decentral ", " central "]:
            network.add(
                "Generator",
                nodes,
                suffix=cat + "solar thermal",
                bus=nodes + cat + "heat",
                carrier="solar thermal",
                p_nom_extendable=True,
                capital_cost=costs.at[cat.lstrip() + "solar thermal", "capital_cost"],
                p_max_pu=solar_thermal[nodes].clip(1.0e-4),
                lifetime=costs.at[cat.lstrip() + "solar thermal", "lifetime"],
            )

add_hydro(network, config, nodes, prov_shapes, costs, planning_horizons)

Add the hydropower plants (dams) to the network. Due to the spillage/basin calculations these have real locations not just nodes. WARNING: the node is assigned based on the damn province name (turbine link) NOT future proof

Parameters:

Name	Type	Description	Default
network	Network	the network object	required
config	dict	the yaml config	required
nodes	Index	the buses	required
prov_shapes	GeoDataFrame	the province shapes GDF	required
costs	DataFrame	the costs dataframe	required
planning_horizons	int	the year	required

Source code in workflow/scripts/prepare_network.py

def add_hydro(
    network: pypsa.Network,
    config: dict,
    nodes: pd.Index,
    prov_shapes: gpd.GeoDataFrame,
    costs: pd.DataFrame,
    planning_horizons: int,
):
    """Add the hydropower plants (dams) to the network.
    Due to the spillage/basin calculations these have real locations not just nodes.
    WARNING: the node is assigned based on the damn province name (turbine link)
            NOT future proof

    Args:
        network (pypsa.Network): the network object
        config (dict): the yaml config
        nodes (pd.Index): the buses
        prov_shapes (gpd.GeoDataFrame): the province shapes GDF
        costs (pd.DataFrame): the costs dataframe
        planning_horizons (int): the year
    """

    logger.info("\tAdding dam cascade")

    # load dams
    df = pd.read_csv(config["hydro_dams"]["dams_path"], index_col=0)
    points = df.apply(lambda row: Point(row.Lon, row.Lat), axis=1)
    dams = gpd.GeoDataFrame(df, geometry=points, crs=CRS)
    # store all info, then filter by selected nodes
    dam_provinces = dams.Province
    all_dams = dams.index.values
    dams = dams[dams.Province.isin(nodes)]

    logger.debug(f"Hydro dams in {nodes} provinces: {dams.index}")

    hourly_rng = pd.date_range(
        config["hydro_dams"]["inflow_date_start"],
        config["hydro_dams"]["inflow_date_end"],
        freq="1h",  # THIS IS THE INFLOW RES
        inclusive="left",
    )
    # TODO implement inflow calc, understand resolution (seems daily!)
    inflow = pd.read_pickle(config["hydro_dams"]["inflow_path"])
    # select inflow year
    hourly_rng = hourly_rng[hourly_rng.year == INFLOW_DATA_YR]
    inflow = inflow.loc[inflow.index.year == INFLOW_DATA_YR]
    inflow = inflow.reindex(hourly_rng, fill_value=0)
    inflow.columns = all_dams  # TODO dangerous
    # select only the dams in the network
    inflow = inflow.loc[:, inflow.columns.map(dam_provinces).isin(nodes)]
    inflow = shift_profile_to_planning_year(inflow, planning_horizons)
    inflow = inflow.loc[network.snapshots]
    # m^3/KWh -> m^3/MWh
    water_consumption_factor = dams.loc[:, "Water_consumption_factor_avg"] * 1e3

    #######
    # ### Add hydro stations as buses
    network.add(
        "Bus",
        dams.index,
        suffix=" station",
        carrier="stations",
        x=dams["geometry"].to_crs("+proj=cea").centroid.to_crs(prov_shapes.crs).x,
        y=dams["geometry"].to_crs("+proj=cea").centroid.to_crs(prov_shapes.crs).y,
        location=dams["Province"],
    )

    dam_buses = network.buses[network.buses.carrier == "stations"]

    # ===== add hydro reservoirs as stores ======
    initial_capacity = pd.read_pickle(config["hydro_dams"]["reservoir_initial_capacity_path"])
    effective_capacity = pd.read_pickle(config["hydro_dams"]["reservoir_effective_capacity_path"])
    initial_capacity.index = all_dams
    effective_capacity.index = all_dams
    initial_capacity = initial_capacity / water_consumption_factor
    effective_capacity = effective_capacity / water_consumption_factor

    # select relevant dams in nodes
    effective_capacity = effective_capacity.loc[
        effective_capacity.index.map(dam_provinces).isin(nodes)
    ]
    initial_capacity = initial_capacity.loc[initial_capacity.index.map(dam_provinces).isin(nodes)]

    network.add(
        "Store",
        dams.index,
        suffix=" reservoir",
        bus=dam_buses.index,
        e_nom=effective_capacity,
        e_initial=initial_capacity,
        e_cyclic=True,
        # TODO fix all config["costs"]
        marginal_cost=config["hydro"]["marginal_cost"]["reservoir"],
    )

    # add hydro turbines to link stations to provinces
    network.add(
        "Link",
        dams.index,
        suffix=" turbines",
        bus0=dam_buses.index,
        bus1=dams["Province"],
        carrier="hydroelectricity",
        p_nom=10 * dams["installed_capacity_10MW"],
        capital_cost=(
            costs.at["hydro", "capital_cost"] if config["hydro"]["hydro_capital_cost"] else 0
        ),
        efficiency=1,
        location=dams["Province"],
        p_nom_extendable=False,
    )

    # ===  add rivers to link station to station
    dam_edges = pd.read_csv(config["hydro_dams"]["damn_flows_path"], delimiter=",")
    in_nodes = dam_edges.bus0.map(dam_provinces).isin(nodes) & dam_edges.end_bus.map(
        dam_provinces
    ).isin(nodes)
    dam_edges = dam_edges[in_nodes]

    # === normal flow ====
    for row in dam_edges.iterrows():
        bus0 = row[1].bus0 + " turbines"
        bus2 = row[1].end_bus + " station"
        network.links.at[bus0, "bus2"] = bus2
        network.links.at[bus0, "efficiency2"] = 1.0

    # === spillage ====
    # TODO WHY EXTENDABLE - weather year?
    for row in dam_edges.iterrows():
        bus0 = row[1].bus0 + " station"
        bus1 = row[1].end_bus + " station"
        network.add(
            "Link",
            f"{bus0}-{bus1}" + " spillage",
            bus0=bus0,
            bus1=bus1,
            p_nom_extendable=True,
        )

    dam_ends = [
        dam
        for dam in np.unique(dams.index.values)
        if dam not in dam_edges["bus0"]
        or dam not in dam_edges["end_bus"]
        or (dam in dam_edges["end_bus"].values & dam not in dam_edges["bus0"])
    ]
    # need some kind of sink to absorb spillage (e,g ocean).
    # here hack by flowing to existing bus with 0 efficiency (lose)
    # TODO make more transparent -> generator with neg sign and 0 c0st
    for bus0 in dam_ends:
        network.add(
            "Link",
            bus0 + " spillage",
            bus0=bus0 + " station",
            bus1=bus0 + " station",
            p_nom_extendable=True,
            efficiency=0.0,
        )

    # add inflow as generators
    # only feed into hydro stations which are the first of a cascade
    inflow_stations = [
        dam for dam in np.unique(dams.index.values) if dam not in dam_edges["end_bus"].values
    ]

    for inflow_station in inflow_stations:
        # p_nom = 1 and p_max_pu & p_min_pu = p_pu, compulsory inflow
        p_nom = (inflow / water_consumption_factor)[inflow_station].max()
        p_pu = (inflow / water_consumption_factor)[inflow_station] / p_nom
        p_pu.index = network.snapshots
        network.add(
            "Generator",
            inflow_station + " inflow",
            bus=inflow_station + " station",
            carrier="hydro_inflow",
            p_max_pu=p_pu.clip(1.0e-6),
            # p_min_pu=p_pu.clip(1.0e-6),
            p_nom=p_nom,
        )

        # p_nom*p_pu = XXX m^3 then use turbines efficiency to convert to power

    # ======= add other existing hydro power (not lattitude resolved) ===
    hydro_p_nom = pd.read_hdf(config["hydro_dams"]["p_nom_path"]).loc[nodes]
    hydro_p_max_pu = (
        pd.read_hdf(
            config["hydro_dams"]["p_max_pu_path"],
            key=config["hydro_dams"]["p_max_pu_key"],
        ).tz_localize(None)
    )[nodes]

    hydro_p_max_pu = shift_profile_to_planning_year(hydro_p_max_pu, planning_horizons)
    # sort buses (columns) otherwise stuff will break
    hydro_p_max_pu.sort_index(axis=1, inplace=True)

    hydro_p_max_pu = hydro_p_max_pu.loc[snapshots]
    hydro_p_max_pu.index = network.snapshots

    logger.info("\tAdding extra hydro capacity (regionally aggregated)")

    network.add(
        "Generator",
        nodes,
        suffix=" hydroelectricity",
        bus=nodes,
        carrier="hydroelectricity",
        p_nom=hydro_p_nom,
        p_nom_min=hydro_p_nom,
        p_nom_extendable=False,
        p_max_pu=hydro_p_max_pu,
        capital_cost=(
            costs.at["hydro", "capital_cost"] if config["hydro"]["hydro_capital_cost"] else 0
        ),
    )

add_voltage_links(network, config)

Add HVDC/AC links (no KVL)

Parameters:

Name	Type	Description	Default
network	Network	the network object	required
config	dict	the snakemake config	required

Raises:

Type	Description
ValueError	Invalid Edge path in config options

Source code in workflow/scripts/prepare_network.py

def add_voltage_links(network: pypsa.Network, config: dict):
    """Add HVDC/AC links (no KVL)

    Args:
        network (pypsa.Network): the network object
        config (dict): the snakemake config

    Raises:
        ValueError: Invalid Edge path in config options
    """

    represented_hours = network.snapshot_weightings.sum()[0]
    n_years = represented_hours / 8760.0

    # determine topology
    edge_path = config["edge_paths"].get(config["scenario"]["topology"], None)
    if edge_path is None:
        raise ValueError(f"No grid found for topology {config['scenario']['topology']}")
    else:
        edges_ = pd.read_csv(
            edge_path, sep=",", header=None, names=["bus0", "bus1", "p_nom"]
        ).fillna(0)
        edges = edges_[edges_["bus0"].isin(PROV_NAMES) & edges_["bus1"].isin(PROV_NAMES)]
        if edges_.shape[0] != edges.shape[0]:
            logger.warning("Some edges are not in the network")
    # fix this to use map with x.y
    lengths = config["lines"]["line_length_factor"] * np.array(
        [
            haversine(
                [network.buses.at[bus0, "x"], network.buses.at[bus0, "y"]],
                [network.buses.at[bus1, "x"], network.buses.at[bus1, "y"]],
            )
            for bus0, bus1 in edges[["bus0", "bus1"]].values
        ]
    )

    # get for backward compatibility
    security_config = config.get("security", {"line_security_margin": 70})
    line_margin = security_config.get("line_security_margin", 70) / 100

    line_cost = (
        lengths * costs.at["HVDC overhead", "capital_cost"] * FOM_LINES * n_years
    ) + costs.at["HVDC inverter pair", "capital_cost"]  # /MW

    # ==== lossy transport model (split into 2) ====
    # NB this only works if there is an equalising constraint, which is hidden in solve_ntwk
    if config["line_losses"]:
        network.add(
            "Link",
            edges["bus0"] + "-" + edges["bus1"],
            bus0=edges["bus0"].values,
            bus1=edges["bus1"].values,
            suffix=" positive",
            p_nom_extendable=True,
            p_nom=edges["p_nom"].values,
            p_nom_min=edges["p_nom"].values,
            p_min_pu=0,
            p_max_pu=line_margin,
            efficiency=config["transmission_efficiency"]["DC"]["efficiency_static"]
            * config["transmission_efficiency"]["DC"]["efficiency_per_1000km"] ** (lengths / 1000),
            length=lengths,
            capital_cost=line_cost,
            carrier="AC",  # Fake - actually DC
        )
        # 0 len for reversed in case line limits are specified in km. Limited in constraints to fwdcap
        network.add(
            "Link",
            edges["bus0"] + "-" + edges["bus1"],
            bus0=edges["bus1"].values,
            bus1=edges["bus0"].values,
            suffix=" reversed",
            p_nom_extendable=True,
            p_nom=edges["p_nom"].values,
            p_nom_min=edges["p_nom"].values,
            p_min_pu=0,
            efficiency=config["transmission_efficiency"]["DC"]["efficiency_static"]
            * config["transmission_efficiency"]["DC"]["efficiency_per_1000km"] ** (lengths / 1000),
            length=0,
            capital_cost=0,
            carrier="AC",
        )
    # lossless transport model
    else:
        network.add(
            "Link",
            edges["bus0"] + "-" + edges["bus1"],
            p_nom=edges["p_nom"].values,
            p_nom_min=edges["p_nom"].values,
            bus0=edges["bus0"].values,
            bus1=edges["bus1"].values,
            p_nom_extendable=True,
            p_min_pu=-1,
            length=lengths,
            capital_cost=line_cost,
            carrier="AC",
        )

add_wind_and_solar(network, techs, paths, year, costs)

Adds wind and solar generators for each grade of renewable energy technology

Parameters:

Name	Type	Description	Default
network	Network	The PyPSA network to which the generators will be added	required
techs	list	A list of renewable energy technologies to add. (e.g., ["solar", "onwind", "offwind"])	required
paths	PathLike	file paths containing renewable profiles (snakemake.input)	required
year	int	planning year	required
costs	DataFrame	cost parameters for each technology	required

Raises: ValueError: for unsupported technologies or missing paths.

Source code in workflow/scripts/prepare_network.py

def add_wind_and_solar(
    network: pypsa.Network,
    techs: list,
    paths: os.PathLike,
    year: int,
    costs: pd.DataFrame,
):
    """
    Adds wind and solar generators for each grade of renewable energy technology

    Args:
        network (pypsa.Network): The PyPSA network to which the generators will be added
        techs (list): A list of renewable energy technologies to add.
            (e.g., ["solar", "onwind", "offwind"])
        paths (os.PathLike): file paths containing renewable profiles (snakemake.input)
        year (int): planning year
        costs (pd.DataFrame): cost parameters for each technology
    Raises:
        ValueError: for unsupported technologies or missing paths.
    """

    unsupported = set(techs).difference({"solar", "onwind", "offwind"})
    if unsupported:
        raise ValueError(f"Carrier(s) {unsupported} not wind or solar pv")
    prof_paths = {f"profile_{tech}": paths[f"profile_{tech}"] for tech in techs}
    if len(prof_paths) != len(techs):
        raise ValueError(f"Paths do not correspond to techs  ({prof_paths} vs {techs})")

    for tech in techs:
        # load the renewable profiles
        logger.info(f"Attaching {tech} to network")
        with xr.open_dataset(prof_paths[f"profile_{tech}"]) as ds:
            if ds.indexes["bus"].empty:
                continue
            if "year" in ds.indexes:
                ds = ds.sel(year=ds.year.min(), drop=True)

            timestamps = pd.DatetimeIndex(ds.time)
            def shift_weather_to_planning_yr(t):
                """Shift weather data to planning year."""
                return t.replace(year=int(year))
            timestamps = timestamps.map(shift_weather_to_planning_yr)
            ds = ds.assign_coords(time=timestamps)

            mask = ds.time.isin(network.snapshots)
            ds = ds.sel(time=mask)

            if not len(ds.time) == len(network.snapshots):
                err = f"{len(ds.time)} and {len(network.snapshots)}"
                raise ValueError("Mismatch in profile and network timestamps " + err)
            ds = ds.stack(bus_bin=["bus", "bin"])

        # remove low potential bins
        cutoff = config.get("renewable_potential_cutoff", 0)
        ds = ds.where(ds["p_nom_max"] > cutoff, drop=True)

        # bins represent renewable generation grades
        def flatten(t):
            """Flatten tuple to string with ' grade' separator."""
            return " grade".join(map(str, t))
        buses = ds.indexes["bus_bin"].get_level_values("bus")
        bus_bins = ds.indexes["bus_bin"].map(flatten)

        p_nom_max = ds["p_nom_max"].to_pandas()
        p_nom_max.index = p_nom_max.index.map(flatten)

        p_max_pu = ds["profile"].to_pandas()
        p_max_pu.columns = p_max_pu.columns.map(flatten)

        # add renewables
        network.add(
            "Generator",
            bus_bins,
            suffix=f" {tech}",
            bus=buses,
            carrier=tech,
            p_nom_extendable=True,
            p_nom_max=p_nom_max,
            capital_cost=costs.at[tech, "capital_cost"],
            marginal_cost=costs.at[tech, "marginal_cost"],
            p_max_pu=p_max_pu,
            lifetime=costs.at[tech, "lifetime"],
        )

generate_periodic_profiles(dt_index=None, col_tzs=pd.Series(index=PROV_NAMES, data=(len(PROV_NAMES) * ['Shanghai'])), weekly_profile=range(24 * 7))

Give a 24*7 long list of weekly hourly profiles, generate this for each country for the period dt_index, taking account of time zones and Summer Time.

Source code in workflow/scripts/prepare_network.py

def generate_periodic_profiles(
    dt_index=None,
    col_tzs=pd.Series(index=PROV_NAMES, data=len(PROV_NAMES) * ["Shanghai"]),
    weekly_profile=range(24 * 7),
):
    """Give a 24*7 long list of weekly hourly profiles, generate this
    for each country for the period dt_index, taking account of time
    zones and Summer Time.
    """

    weekly_profile = pd.Series(weekly_profile, range(24 * 7))
    # TODO fix, no longer take into accoutn summer time
    # ALSO ADD A TODO in base_network
    week_df = pd.DataFrame(index=dt_index, columns=col_tzs.index)
    for ct in col_tzs.index:
        week_df[ct] = [24 * dt.weekday() + dt.hour for dt in dt_index.tz_localize(None)]
        week_df[ct] = week_df[ct].map(weekly_profile)
    return week_df

prepare_network(config, costs, snapshots, biomass_potential=None, paths=None)

Prepares/makes the network object for overnight mode according to config & at 1 node per region/province

Parameters:

Name	Type	Description	Default
config	dict	the snakemake config	required
costs	DataFrame	the costs dataframe (anualised capex and marginal costs)	required
snapshots	date_range	the snapshots for the network	required
biomass_potential	(Optional, DataFrame)	biomass potential dataframe. Defaults to None.	None
paths	(Optional, dict)	the paths to the data files. Defaults to None.	None

Returns:

Type	Description
Network	pypsa.Network: the pypsa network object

Source code in workflow/scripts/prepare_network.py

def prepare_network(
    config: dict,
    costs: pd.DataFrame,
    snapshots: pd.date_range,
    biomass_potential: pd.DataFrame = None,
    paths: dict = None,
) -> pypsa.Network:
    """Prepares/makes the network object for overnight mode according to config &
    at 1 node per region/province

    Args:
        config (dict): the snakemake config
        costs (pd.DataFrame): the costs dataframe (anualised capex and marginal costs)
        snapshots (pd.date_range): the snapshots for the network
        biomass_potential (Optional, pd.DataFrame): biomass potential dataframe. Defaults to None.
        paths (Optional, dict): the paths to the data files. Defaults to None.

    Returns:
        pypsa.Network: the pypsa network object
    """

    # determine whether gas/coal to be added depending on specified conv techs
    config["add_gas"] = (
        True
        if [tech for tech in config["Techs"]["conv_techs"] if ("gas" in tech or "CGT" in tech)]
        else False
    )
    config["add_coal"] = (
        True if [tech for tech in config["Techs"]["conv_techs"] if "coal" in tech] else False
    )

    planning_horizons = snakemake.wildcards["planning_horizons"]

    # Build the Network object, which stores all other objects
    network = pypsa.Network()
    network.set_snapshots(snapshots)
    network.snapshot_weightings[:] = config["snapshots"]["frequency"]
    # load graph
    nodes = pd.Index(PROV_NAMES)
    # toso soft code
    countries = ["CN"] * len(nodes)

    # TODO check crs projection correct
    # load provinces
    prov_shapes = read_province_shapes(paths["province_shape"])
    prov_centroids = prov_shapes.to_crs("+proj=cea").centroid.to_crs(CRS)

    # add AC buses
    network.add(
        "Bus", nodes, x=prov_centroids.x, y=prov_centroids.y, location=nodes, country=countries
    )

    # add carriers
    add_carriers(network, config, costs)

    # load electricity demand data
    demand_path = paths["elec_load"].replace("{planning_horizons}", f"{cost_year}")
    with pd.HDFStore(demand_path, mode="r") as store:
        load = store["load"].loc[network.snapshots, PROV_NAMES]  # MWHr

    network.add("Load", nodes, bus=nodes, p_set=load[nodes])

    ws_carriers = [c for c in config["Techs"]["vre_techs"] if c.find("wind") >= 0 or c == "solar"]
    add_wind_and_solar(network, ws_carriers, paths, planning_horizons, costs)

    add_conventional_generators(network, nodes, config, prov_centroids, costs)

    # nuclear is brownfield
    if "nuclear" in config["Techs"]["vre_techs"]:
        nuclear_nodes = pd.Index(NUCLEAR_EXTENDABLE)
        network.add(
            "Generator",
            nuclear_nodes,
            suffix=" nuclear",
            p_nom_extendable=True,
            p_max_pu=config["nuclear_reactors"]["p_max_pu"],
            p_min_pu=config["nuclear_reactors"]["p_min_pu"],
            bus=nuclear_nodes,
            carrier="nuclear",
            efficiency=costs.at["nuclear", "efficiency"],
            capital_cost=costs.at["nuclear", "capital_cost"],  # NB: capital cost is per MWel
            marginal_cost=costs.at["nuclear", "marginal_cost"],
            lifetime=costs.at["nuclear", "lifetime"],
        )

    # TODO add coal CC? no retrofit option

    if "PHS" in config["Techs"]["store_techs"]:
        # pure pumped hydro storage, fixed, 6h energy by default, no inflow
        cc = costs.at["PHS", "capital_cost"]

        network.add(
            "StorageUnit",
            nodes,
            suffix=" PHS",
            bus=nodes,
            carrier="PHS",
            p_nom_extendable=True,
            max_hours=config["hydro"]["PHS_max_hours"],
            efficiency_store=np.sqrt(costs.at["PHS", "efficiency"]),
            efficiency_dispatch=np.sqrt(costs.at["PHS", "efficiency"]),
            cyclic_state_of_charge=True,
            capital_cost=cc,
            marginal_cost=0.0,
        )

    if config["add_hydro"]:
        logger.info("Adding hydro to network")
        add_hydro(network, config, nodes, prov_centroids, costs, planning_horizons)

    if config["add_H2"]:
        logger.info("Adding H2 buses to network")
        # do beore heat coupling to avoid warning
        network.add(
            "Bus",
            nodes,
            suffix=" H2",
            x=prov_centroids.x,
            y=prov_centroids.y,
            carrier="H2",
            location=nodes,
        )

    if config.get("heat_coupling", False):
        logger.info("Adding heat and CHP to the network")
        add_heat_coupling(network, config, nodes, prov_centroids, costs, planning_horizons, paths)

        if config["add_biomass"]:
            logger.info("Adding biomass to network")
            add_co2_capture_support(network, nodes, prov_centroids)
            add_biomass_chp(
                network,
                costs,
                nodes,
                biomass_potential[nodes],
                prov_centroids,
                add_beccs="beccs" in config["Techs"]["vre_techs"],
            )

    if config["add_H2"]:
        logger.info("Adding H2 to network")
        add_H2(network, config, nodes, costs)

    if "battery" in config["Techs"]["store_techs"]:
        network.add(
            "Bus",
            nodes,
            suffix=" battery",
            x=prov_centroids.x,
            y=prov_centroids.y,
            carrier="battery",
            location=nodes,
        )

        # TODO Why no standing loss?: test with
        min_charge = config["electricity"].get("min_charge", {"battery": 0})
        min_charge = min_charge.get("battery", 0)
        network.add(
            "Store",
            nodes + " battery",
            bus=nodes + " battery",
            e_cyclic=True,
            e_nom_extendable=True,
            e_min_pu=min_charge,
            capital_cost=costs.at["battery storage", "capital_cost"],
            lifetime=costs.at["battery storage", "lifetime"],
        )

        # TODO understand/remove sources, data should not be in code
        # Sources:
        # [HP]: Henning, Palzer http://www.sciencedirect.com/science/article/pii/S1364032113006710
        # [B]: Budischak et al. http://www.sciencedirect.com/science/article/pii/S0378775312014759

        network.add(
            "Link",
            nodes + " battery charger",
            bus0=nodes,
            bus1=nodes + " battery",
            efficiency=costs.at["battery inverter", "efficiency"] ** 0.5,
            capital_cost=costs.at["battery inverter", "efficiency"]
            * costs.at["battery inverter", "capital_cost"],
            p_nom_extendable=True,
            carrier="battery",
            lifetime=costs.at["battery inverter", "lifetime"],
        )

        network.add(
            "Link",
            nodes + " battery discharger",
            bus0=nodes + " battery",
            bus1=nodes,
            efficiency=costs.at["battery inverter", "efficiency"] ** 0.5,
            marginal_cost=0.0,
            p_nom_extendable=True,
            carrier="battery discharger",
        )

    # ============= add lines =========
    # The lines are implemented according to the transport model (no KVL) and without losses.
    # see Neumann et al 10.1016/j.apenergy.2022.118859
    # TODO make not lossless optional (? - increases computing cost)

    if not config["no_lines"]:
        add_voltage_links(network, config)

    assign_locations(network)
    return network