Must Run

Contents

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

Overview

Must-run assets in Macro represent electricity generation technologies that must operate at their full available capacity when available. These assets are typically used for small hydroelectric plants, or other generation that has contractual or operational requirements to run when available. They are defined using either JSON or CSV input files placed in the assets directory, typically named with descriptive identifiers like mustrun.json or mustrun.csv.

Asset Structure

A must-run asset consists of two main components:

1. Transformation Component
2. Electricity Edge: Represents the electricity production flow to the grid

Here is a graphical representation of the must-run asset:

Input File (Standard Format)

The easiest way to include a must-run 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/
│   ├── mustrun.json    # or mustrun.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 a must-run asset input file:

{
    "mustrun": [
        {
            "type": "MustRun",
            "instance_data": [
                {
                    "id": "SE_small_hydroelectric_1",
                    "location": "SE",
                    "can_expand": false,
                    "can_retire": false,
                    "fixed_om_cost": 45648,
                    "existing_capacity": 249.895,
                    "capacity_size": 1.219,
                    "availability": {
                        "timeseries": {
                            "path": "system/availability.csv",
                            "header": "SE_small_hydroelectric_1"
                        }
                    }
                }
            ]
        }
    ]
}

The following tables outline the attributes that can be set for a must-run asset.

Essential Attributes

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 a must-run asset.

Constraints configuration

Must-run assets can have different constraints applied to them, and the user can configure them using the following fields:

Default constraints

To simplify the input file and the asset configuration, the following constraints are applied to the must-run asset by default:

• Balance constraint (applied to the transformation component)
• Must run constraint (applied to the electricity edge)

Investment Parameters

Additional Investment Parameters

Maximum and minimum capacity constraints

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

Economic Parameters

Operational Parameters

Types - Asset Structure

The MustRun asset is defined as follows:

struct MustRun <: AbstractAsset
    id::AssetId
    energy_transform::Transformation
    elec_edge::Edge{<:Electricity}
end

Constructors

Default constructor

MustRun(id::AssetId, energy_transform::Transformation, elec_edge::Edge{<:Electricity})

Factory constructor

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

Examples

This section contains examples of how to use the must-run asset in a Macro model.

Multiple must-run assets in different zones

This example shows three small hydroelectric plants in different regions, with existing and fixed capacity (capacity cannot be expanded or retired).

JSON Format:

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

{
    "mustrun": [
        {
            "type": "MustRun",
            "global_data": {
                "can_expand": false,
                "can_retire": false,
                "fixed_om_cost": 45648
            },
            "instance_data": [
                {
                    "id": "SE_small_hydroelectric_1",
                    "location": "SE",
                    "existing_capacity": 249.895,
                    "capacity_size": 1.219,
                    "availability": {
                        "timeseries": {
                            "path": "system/availability.csv",
                            "header": "SE_small_hydroelectric_1"
                        }
                    }
                },
                {
                    "id": "MIDAT_small_hydroelectric_1",
                    "location": "MIDAT",
                    "existing_capacity": 263.268,
                    "capacity_size": 1.236,
                    "availability": {
                        "timeseries": {
                            "path": "system/availability.csv",
                            "header": "MIDAT_small_hydroelectric_1"
                        }
                    }
                },
                {
                    "id": "NE_small_hydroelectric_1",
                    "location": "NE",
                    "existing_capacity": 834.494,
                    "capacity_size": 1.051,
                    "availability": {
                        "timeseries": {
                            "path": "system/availability.csv",
                            "header": "NE_small_hydroelectric_1"
                        }
                    }
                }
            ]
        }
    ]
}

CSV Format:

Best Practices

1. Use global data for common fields: Use the global_data field to set the fields that are common to all instances of the same asset type.
2. Set realistic availability profiles: Ensure availability profiles reflect actual operational constraints
3. Use meaningful IDs: Choose descriptive identifiers that indicate location and technology type
4. Consider capacity constraints: Set appropriate capacity limits based on technology and location
5. Use constraints selectively: Only enable constraints that are necessary for your modeling needs
6. Validate costs: Ensure investment and O&M costs are in appropriate units
7. Test configurations: Start with simple configurations and gradually add complexity

Input File (Advanced Format)

Macro provides an advanced format for defining must-run 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 a must-run asset. The input file mirrors this hierarchical structure.

A must-run asset in Macro is composed of a transformation component, represented by a Transformation object, and an electricity edge, represented by an Edge object. The input file for a must-run asset is therefore organized as follows:

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

Each top-level key (such as "transforms" or "edges") represents a type of component. The second-level keys either define the attributes of the component (for storage and transformation components) or specify the instances of the component (for edges). For edges, a third-level key provides the attributes for each specific instance.

Below is an example of an input file for a must-run asset that sets up three small hydroelectric plants in different regions.

{
    "mustrun": [
        {
            "type": "MustRun",
            "global_data": {
                "nodes": {},
                "transforms": {
                    "timedata": "Electricity"
                },
                "edges": {
                    "elec_edge": {
                        "unidirectional": true,
                        "can_expand": false,
                        "can_retire": false,
                        "has_capacity": true,
                        "constraints": {
                            "MustRunConstraint": true
                        }
                    }
                }
            },
            "instance_data": [
                {
                    "id": "SE_small_hydroelectric_1",
                    "edges": {
                        "elec_edge": {
                            "end_vertex": "elec_SE",
                            "existing_capacity": 249.895,
                            "capacity_size": 1.219,
                            "fixed_om_cost": 45648,
                            "availability": {
                                "timeseries": {
                                    "path": "system/availability.csv",
                                    "header": "SE_small_hydroelectric_1"
                                }
                            }
                        }
                    }
                },
                {
                    "id": "MIDAT_small_hydroelectric_1",
                    "edges": {
                        "elec_edge": {
                            "end_vertex": "elec_MIDAT",
                            "existing_capacity": 263.268,
                            "capacity_size": 1.236,
                            "fixed_om_cost": 45648,
                            "availability": {
                                "timeseries": {
                                    "path": "system/availability.csv",
                                    "header": "MIDAT_small_hydroelectric_1"
                                }
                            }
                        }
                    }
                },
                {
                    "id": "NE_small_hydroelectric_1",
                    "edges": {
                        "elec_edge": {
                            "end_vertex": "elec_NE",
                            "existing_capacity": 834.494,
                            "capacity_size": 1.051,
                            "fixed_om_cost": 45648,
                            "availability": {
                                "timeseries": {
                                    "path": "system/availability.csv",
                                    "header": "NE_small_hydroelectric_1"
                                }
                            }
                        }
                    }
                }
            ]
        }
    ]
}

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 end_vertex field indicates the node to which the electricity edge is connected. This node must be defined in the nodes.json file.
• For a comprehensive list of attributes that can be configured for the transformation and edge components, refer to the transformations and edges pages of the Macro manual.