Electric DAC

Contents

Overview | Asset Structure | Flow Equations | Input File (Standard Format) | Types - Asset Structure | Constructors | Examples | Best Practices | Input File (Advanced Format)

Overview

Electric DAC (Direct Air Capture) assets in Macro represent carbon capture technologies that use electricity to capture CO₂ directly from the atmosphere. These assets are defined using either JSON or CSV input files placed in the assets directory, typically named electricdac.json or electricdac.csv.

Asset Structure

An electric DAC asset consists of one transformation component and three edge components:

1. Transformation Component: Balances flows of electricity, CO₂, and CO₂ captured
2. Electricity Edge: Incoming edge representing electricity consumption
3. CO₂ Edge: Incoming edge representing CO₂ absorption from atmosphere
4. CO₂ Captured Edge: Outgoing edge representing captured CO₂

Here is a graphical representation of the electric DAC asset:

Flow Equations

The electric DAC asset follows these stoichiometric relationships:

\[\begin{aligned} \phi_{elec} &= \phi_{co2\_captured} \cdot \epsilon_{elec\_consumption} \\ \phi_{co2} &= \phi_{co2\_captured} \\ \end{aligned}\]

Where:

• $\phi$ represents the flow of each commodity
• $\epsilon$ represents the stoichiometric coefficients defined in the table below (see table Conversion Process Parameters)

Input File (Standard Format)

The easiest way to include an electric DAC asset in a model is to create a new file (either JSON or CSV) and place it in the assets directory together with the other assets.

your_case/
├── assets/
│   ├── electricdac.json    # or electricdac.csv
│   ├── other_assets.json
│   └── ...
├── system/
├── settings/
└── ...

This file can either be created manually, or using the template_asset function, as shown in the Adding an Asset to a System section of the User Guide. The file will be automatically loaded when you run your Macro model.

The following is an example of an electric DAC asset input file:

{
    "ElectricDAC": [
        {
            "type": "ElectricDAC",
            "instance_data": [
                {
                    "id": "SE_Sorbent_DAC",
                    "location": "SE",
                    "investment_cost": 1050000,
                    "fixed_om_cost": 837000,
                    "variable_om_cost": 24.64,
                    "electricity_consumption": 4.38,
                    "co2_sink": "co2_sink"
                }
            ]
        }
    ]
}

The following tables outline the attributes that can be set for an electric DAC asset.

Essential Attributes

Conversion Process Parameters

The following parameters control the conversion process and stoichiometry of the electricdac asset (see Flow Equations for more details).

Constraints Configuration

Electric DAC assets can have different constraints applied to them, and the user can configure them using the following fields:

For example, if the user wants to apply the BalanceConstraint to the transformation component and the CapacityConstraint to the CO₂ edge, the constraints fields should be set as follows:

{
    "transform_constraints": {
        "BalanceConstraint": true
    },
    "co2_constraints": {
        "CapacityConstraint": true
    }
}

Users can refer to the Adding Asset Constraints to a System section of the User Guide for a list of all the constraints that can be applied to the different components of an electric DAC asset.

Default constraints

To simplify the input file and the asset configuration, the following constraints are applied to the electric DAC asset by default:

• Balance constraint (applied to the transformation component)
• Capacity constraint (applied to the CO₂ edge)

Investment Parameters

Additional Investment Parameters

Maximum and minimum capacity constraints

If MaxCapacityConstraint or MinCapacityConstraint are added to the constraints dictionary for the CO₂ edge, the following parameters are used by Macro:

Economic Parameters

Operational Parameters

Additional Operational Parameters

Minimum flow constraint

If MinFlowConstraint is added to the constraints dictionary for the CO₂ edge, the following parameter is used:

Ramping limit constraint

If RampingLimitConstraint is added to the constraints dictionary for the CO₂ edge, the following parameters are used:

Types - Asset Structure

The ElectricDAC asset is defined as follows:

struct ElectricDAC <: AbstractAsset
    id::AssetId
    electricdac_transform::Transformation
    co2_edge::Edge{<:CO2}
    elec_edge::Edge{<:Electricity}
    co2_captured_edge::Edge{<:CO2Captured}
end

Constructors

Default constructor

ElectricDAC(id::AssetId, electricdac_transform::Transformation, co2_edge::Edge{<:CO2}, elec_edge::Edge{<:Electricity}, co2_captured_edge::Edge{<:CO2Captured})

Factory constructor

make(asset_type::Type{ElectricDAC}, data::AbstractDict{Symbol,Any}, system::System)

Examples

This section contains examples of how to use the electric DAC asset in a Macro model.

Simple Electric DAC Asset

This example shows a single electric DAC asset with ramping limits and availability time series.

JSON Format:

{
    "ElectricDAC": [
        {
            "type": "ElectricDAC",
            "instance_data": [
                {
                    "id": "SE_Sorbent_DAC",
                    "location": "SE",
                    "investment_cost": 1050000,
                    "fixed_om_cost": 837000,
                    "variable_om_cost": 24.64,
                    "electricity_consumption": 4.38,
                    "co2_sink": "co2_sink",
                    "co2_constraints": {
                        "RampingLimitConstraint": true
                    },
                    "ramp_up_fraction": 1.0,
                    "ramp_down_fraction": 1.0,
                    "availability": {
                        "timeseries": {
                            "path": "system/availability.csv",
                            "header": "SE_Sorbent_DAC"
                        }
                    }
                }
            ]
        }
    ]
}

CSV Format:

Multiple Electric DAC Assets in Different Zones

JSON Format:

Note that the global_data field is used to set the fields and constraints that are common to all instances of the same asset type.

{
    "ElectricDAC": [
        {
            "type": "ElectricDAC",
            "global_data": {
                "electricity_consumption": 4.38,
                "co2_sink": "co2_sink",
                "co2_constraints": {
                    "RampingLimitConstraint": true
                },
                "investment_cost": 1050000,
                "fixed_om_cost": 837000,
                "variable_om_cost": 24.64,
                "ramp_up_fraction": 1.0,
                "ramp_down_fraction": 1.0
            },
            "instance_data": [
                {
                    "id": "SE_Sorbent_DAC",
                    "location": "SE",
                    "availability": {
                        "timeseries": {
                            "path": "system/availability.csv",
                            "header": "SE_Sorbent_DAC"
                        }
                    }
                },
                {
                    "id": "MIDAT_Sorbent_DAC",
                    "location": "MIDAT",
                    "availability": {
                        "timeseries": {
                            "path": "system/availability.csv",
                            "header": "MIDAT_Sorbent_DAC"
                        }
                    }
                },
                {
                    "id": "NE_Sorbent_DAC",
                    "location": "NE",
                    "availability": {
                        "timeseries": {
                            "path": "system/availability.csv",
                            "header": "NE_Sorbent_DAC"
                        }
                    }
                }
            ]
        }
    ]
}

CSV Format:

Best Practices

1. Use global data for common fields and constraints: Use the global_data field to set the fields and constraints that are common to all instances of the same asset type.
2. Set realistic electricity consumption: Ensure electricity consumption per unit CO₂ captured reflects actual technology performance
3. Use meaningful IDs: Choose descriptive identifiers that indicate location and technology type
4. Consider availability profiles: Use availability time series to model operational constraints
5. Validate costs: Ensure investment and O&M costs are in appropriate units
6. Test configurations: Start with simple configurations and gradually add complexity

Input File (Advanced Format)

Macro provides an advanced format for defining electric DAC assets, offering users and modelers detailed control over asset specifications. This format builds upon the standard format and is ideal for those who need more comprehensive customization.

To understand the advanced format, consider the graph representation and the type definition of an electric DAC asset. The input file mirrors this hierarchical structure.

An electric DAC asset in Macro is composed of a transformation component, represented by a Transformation object, and three edges, each represented by an Edge object. The input file for an electric DAC asset is therefore organized as follows:

{
    "transforms":{
        // ... transformation-specific attributes ...
    },
    "edges":{
        "elec_edge": {
            // ... elec_edge-specific attributes ...
        },
        "co2_edge": {
            // ... co2_edge-specific attributes ...
        },
        "co2_captured_edge": {
            // ... co2_captured_edge-specific attributes ...
        }
    }
}

Each top-level key (e.g., "transforms" or "edges") denotes a component type. The second-level keys either specify the attributes of the component (when there is a single instance) or identify the instances of the component (e.g., "elec_edge", "co2_edge", etc.) when there are multiple instances. For multiple instances, a third-level key details the attributes for each instance.

Below is an example of an input file for an electric DAC asset that sets up a single instance at three different locations, SE, MIDAT, and NE.

{
    "ElectricDAC": [
        {
            "type": "ElectricDAC",
            "global_data": {
                "transforms": {
                    "timedata": "Electricity",
                    "constraints": {
                        "BalanceConstraint": true
                    }
                },
                "edges": {
                    "co2_edge": {
                        "commodity": "CO2",
                        "unidirectional": true,
                        "has_capacity": true,
                        "start_vertex": "co2_sink",
                        "can_retire": true,
                        "can_expand": true,
                        "uc": false,
                        "constraints": {
                            "CapacityConstraint": true,
                            "RampingLimitConstraint": true
                        },
                        "integer_decisions": false
                    },
                    "elec_edge": {
                        "commodity": "Electricity",
                        "unidirectional": true,
                        "has_capacity": false
                    },
                    "co2_captured_edge": {
                        "commodity": "CO2Captured",
                        "unidirectional": true,
                        "has_capacity": false
                    }
                }
            },
            "instance_data": [
                {
                    "id": "SE_Sorbent_DAC",
                    "transforms": {
                        "electricity_consumption": 4.38
                    },
                    "edges": {
                        "co2_edge": {
                            "availability": {
                                "timeseries": {
                                    "path": "system/availability.csv",
                                    "header": "SE_Sorbent_DAC"
                                }
                            },
                            "existing_capacity": 0.0,
                            "investment_cost": 1050000,
                            "fixed_om_cost": 837000,
                            "variable_om_cost": 24.64,
                            "ramp_up_fraction": 1.0,
                            "ramp_down_fraction": 1.0
                        },
                        "elec_edge": {
                            "start_vertex": "elec_SE"
                        },
                        "co2_captured_edge": {
                            "end_vertex": "co2_captured_SE"
                        }
                    }
                },
                {
                    "id": "MIDAT_Sorbent_DAC",
                    "transforms": {
                        "electricity_consumption": 4.38
                    },
                    "edges": {
                        "co2_edge": {
                            "availability": {
                                "timeseries": {
                                    "path": "system/availability.csv",
                                    "header": "MIDAT_Sorbent_DAC"
                                }
                            },
                            "existing_capacity": 0.0,
                            "investment_cost": 1050000,
                            "fixed_om_cost": 837000,
                            "variable_om_cost": 24.64,
                            "ramp_up_fraction": 1.0,
                            "ramp_down_fraction": 1.0
                        },
                        "elec_edge": {
                            "start_vertex": "elec_MIDAT"
                        },
                        "co2_captured_edge": {
                            "end_vertex": "co2_captured_MIDAT"
                        }
                    }
                },
                {
                    "id": "NE_Sorbent_DAC",
                    "transforms": {
                        "electricity_consumption": 4.38
                    },
                    "edges": {
                        "co2_edge": {
                            "availability": {
                                "timeseries": {
                                    "path": "system/availability.csv",
                                    "header": "NE_Sorbent_DAC"
                                }
                            },
                            "existing_capacity": 0.0,
                            "investment_cost": 1050000,
                            "fixed_om_cost": 837000,
                            "variable_om_cost": 24.64,
                            "ramp_up_fraction": 1.0,
                            "ramp_down_fraction": 1.0
                        },
                        "elec_edge": {
                            "start_vertex": "elec_NE"
                        },
                        "co2_captured_edge": {
                            "end_vertex": "co2_captured_NE"
                        }
                    }
                }
            ]
        }
    ]
}

Key Points

• The global_data field is utilized to define attributes and constraints that apply universally to all instances of a particular asset type.
• The start_vertex and end_vertex fields indicate the nodes to which the edges are connected. These nodes must be defined in the nodes.json file.
• By default, only the CO₂ edge is allowed to have capacity variables and constraints, as this represents the main capacity decision for the DAC facility (see note below).
• The CO₂ edge uses availability time series to model operational constraints.
• For a comprehensive list of attributes that can be configured for the transformation and edge components, refer to the transformation and edges pages of the Macro manual.