SPM DFES LCT Totals by Local Authority — SPENOpenDataPortal

The Distribution Future Energy Scenarios (DFES) provides forecasts of the uptake of Low Carbon Technologies (LCTs), changes to peak demand, and changes to installed Distributed Generation (DG) and storage. The forecasts are in the form of a scenario range out to 2050, covering changes to our distribution networks (i.e. 132kV and below) as a result of GB’s transition to Net Zero Forecasts.

There are four credible future scenarios covering a range of uncertainties, including differing levels of consumer ambition, policy support, economic growth and technology development.

This DFES table provides the forecast numbers of heat pumps, EVs, and residential EVs only, aggregated to local authority level.

Reports and methodology documents can be found in the DFES section of our website: Distribution Future Energy Scenarios - SP Energy Networks

For additional information on column definitions, please click on the Dataset schema link below.

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Data Triage:

As part of our commitment to enhancing the transparency, and accessibility of the data we share, we publish the results of our Data Triage process.

Our Data Triage documentation includes our Risk Assessments; detailing any controls we have implemented to prevent exposure of sensitive information. Click here to access the Data Triage documentation for the Distribution Future Energy Scenarios dataset.

To access our full suite of Data Triage documentation, visit the SP Energy Networks Data & Information page.

Attachments

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Dataset schema

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Local Authority

This specifies the Local Authority that the forecast is for.

No description available for this field.

Name (identifier)	local_authority
Type	text
Sample

Technology

This specifies the technology type that forecast is being provided for. 

Heat pumps - all heat pump types
Residential EVs - residential EVs / EVs that charge at domestic properties
Total EVs - all EV types

No description available for this field.

Name (identifier)	technology
Type	text
Sample

Metric

This specifies the attribute (or metric) that is forecast. 

Total number - the total number of installations (for LCTs only)

No description available for this field.

Name (identifier)	metric
Type	text
Sample

Units

This specifies the unit that the attribute is measured in.

Number - the number of LCTs

No description available for this field.

Name (identifier)	units
Type	text
Sample

Scenario

This specifies the scenario. 

HT - Holistic Transition
EE - Electric Engagement
HE - Hydrogen Evolution
CF - Counterfactual

No description available for this field.

Name (identifier)	scenario
Type	text
Sample

Year

This specifies the year - DFES starting position is the last complete calendar year, and forecasts per year, out to 2050/

2022 - As peak demand is key to our modelling, the year corresponds to winter of that year (i.e. 'December 2022') when the peak is likely to happen, although more widely it corresponds and takes data from the financial year ending the following March in line with regulatory reporting - e.g. 2022 = 2022/23.

The first year is historic data. Following years are predominantly forecast data.

No description available for this field.

Name (identifier)	year
Type	text
Sample

Value

This gives the data value, type: float.

No description available for this field.

Name (identifier)	value
Type	decimal
Sample

NAME

No description available for this field.

Name (identifier)	name
Type	text
Sample

JSON Schema

The following JSON object is a standardized description of your dataset's schema. More about JSON schema.

{

"title":"spm-dfes-local-authority-lcts",
"type":"object",
"oneOf":
[
- {
  - "$ref":"#/definitions/spm-dfes-local-authority-lcts"
  }
]
,
"definitions":
{
- "spm-dfes-local-authority-lcts":
  {
  - "properties":
    {
    "records":
    {
    "type":"array",
    "items":
    {
    "$ref":"#/definitions/spm-dfes-local-authority-lcts_records"
    }
    }
    }
  }
  ,
- "spm-dfes-local-authority-lcts_records":
  {
  - "properties":
    {
    "fields":
    {
    "type":"object",
    "properties":
    {
    "local_authority":
    {
    "type":"string",
    "title":"Local Authority",
    "description":"This specifies the Local Authority that the forecast is for."
    }
    ,
    "technology":
    {
    "type":"string",
    "title":"Technology",
    "description":"This specifies the technology type that forecast is being provided for. Heat pumps - all heat pump types Residential EVs - residential EVs / EVs that charge at domestic properties Total EVs - all EV types"
    }
    ,
    "metric":
    {
    "type":"string",
    "title":"Metric",
    "description":"This specifies the attribute (or metric) that is forecast. Total number - the total number of installations (for LCTs only)"
    }
    ,
    "units":
    {
    "type":"string",
    "title":"Units",
    "description":"This specifies the unit that the attribute is measured in. Number - the number of LCTs "
    }
    ,
    "scenario":
    {
    "type":"string",
    "title":"Scenario",
    "description":"This specifies the scenario. HT - Holistic Transition EE - Electric Engagement HE - Hydrogen Evolution CF - Counterfactual "
    }
    ,
    "year":
    {
    "type":"string",
    "title":"Year",
    "description":"This specifies the year - DFES starting position is the last complete calendar year, and forecasts per year, out to 2050/ 2022 - As peak demand is key to our modelling, the year corresponds to winter of that year (i.e. 'December 2022') when the peak is likely to happen, although more widely it corresponds and takes data from the financial year ending the following March in line with regulatory reporting - e.g. 2022 = 2022/23. The first year is historic data. Following years are predominantly forecast data. "
    }
    ,
    "value":
    {
    "type":"number",
    "title":"Value",
    "description":"This gives the data value, type: float. "
    }
    ,
    "name":
    {
    "type":"string",
    "title":"NAME",
    "description":""
    }
    }
    }
    }
  }
}

}

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