SPD DFES Totals by Substation — 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. 33kV 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 a geographically granular view of key metrics, presented at both primary substation level and also at Grid Supply Point (GSP) level.

It provides data for 88 GSPs (132/33kV transformers providing 33kV (or EHV (Extra High Voltage)) network) and 390 primary substations (33/11kV transformers providing 11kV (or HV (High Voltage)) network). This is a complete view of all substations that supply multiple demand customers (i.e. single-customer sites are excluded from the forecasts).

The date corresponds to the previous NG Electricity System Operator's Future Energy Scenarios (FES) release.

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

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Data Triage:

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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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Substation

This specifies the substation that the forecast is for.

[Substation name] - Substation name

No description available for this field.

Name (identifier)	substation
Type	text
Sample

Substation Level

This specifies the type of substation.

PSS - Primary substation (33kV/HV)
GSP - Grid supply ppint (33kV supply point)

No description available for this field.

Name (identifier)	substation_level
Type	text
Sample

Technology

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

Total generation - All generation types.
Wind - Wind generation – total of both onshore and offshore turbines
PV - Both 'SOLAR-DG ' and 'SOLAR-BTM' types (see Table 1 for definitions)
Storage - Both 'STORAGE-DG ' and 'STORAGE-BTM' types (see Table 1 for definitions)
Total peak demand - All demand types
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

Attribute

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

Installed generation capacity - This is total capacity of the generation installed. This is not necessarily equal to the export capacity or the amount that will be generating at any one time.
Peak demand (with flex) - The contribution to the most onerous averaged half hourly period(s) over the course of the year. Assumes that some peak demand is avoided by consumers switching their electricity use to avoid peak times (demand flexibility).
Peak demand (without flex) - The contribution to the most onerous averaged half hourly period(s) over the course of the year. Modelled without the impact of demand flexibility.
Total number - The total number of installations (for LCTs only)

No description available for this field.

Name (identifier)	attribute
Type	text
Sample

Units

This specifies the unit that the attribute is measured in.

MW - Megawatts (power or rate of energy transfer)
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.

As peak demand is key to our modelling, the year corresponds to winter of that year (i.e. 2022 corresponds to 'December 2022') when the peak is likely to happen, although more widely it overlaps with 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	date
Sample

Value

This gives the data value, type: float.

No description available for this field.

Name (identifier)	value
Type	decimal
Sample

concat_subname_level

No description available for this field.

Name (identifier)	concat_subname_level
Type	text
Sample

JSON Schema

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

{

"title":"spd-dfes-site-forecasts",
"type":"object",
"oneOf":
[
- {
  - "$ref":"#/definitions/spd-dfes-site-forecasts"
  }
]
,
"definitions":
{
- "spd-dfes-site-forecasts":
  {
  - "properties":
    {
    "records":
    {
    "type":"array",
    "items":
    {
    "$ref":"#/definitions/spd-dfes-site-forecasts_records"
    }
    }
    }
  }
  ,
- "spd-dfes-site-forecasts_records":
  {
  - "properties":
    {
    "fields":
    {
    "type":"object",
    "properties":
    {
    "substation":
    {
    "type":"string",
    "title":"Substation",
    "description":"This specifies the substation that the forecast is for. [Substation name] - Substation name "
    }
    ,
    "substation_level":
    {
    "type":"string",
    "title":"Substation Level",
    "description":"This specifies the type of substation. PSS - Primary substation (33kV/HV) GSP - Grid supply ppint (33kV supply point)"
    }
    ,
    "technology":
    {
    "type":"string",
    "title":"Technology",
    "description":"This specifies the technology type that forecast is being provided for. Total generation - All generation types. Wind - Wind generation – total of both onshore and offshore turbines PV - Both 'SOLAR-DG ' and 'SOLAR-BTM' types (see Table 1 for definitions) Storage - Both 'STORAGE-DG ' and 'STORAGE-BTM' types (see Table 1 for definitions) Total peak demand - All demand types Heat pumps - All heat pump types Residential EVs - Residential EVs / EVs that charge at domestic properties Total EVs - All EV types"
    }
    ,
    "attribute":
    {
    "type":"string",
    "title":"Attribute",
    "description":"This specifies the attribute (or metric) that is forecast. Installed generation capacity - This is total capacity of the generation installed. This is not necessarily equal to the export capacity or the amount that will be generating at any one time. Peak demand (with flex) - The contribution to the most onerous averaged half hourly period(s) over the course of the year. Assumes that some peak demand is avoided by consumers switching their electricity use to avoid peak times (demand flexibility). Peak demand (without flex) - The contribution to the most onerous averaged half hourly period(s) over the course of the year. Modelled without the impact of demand flexibility. 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. MW - Megawatts (power or rate of energy transfer) 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",
    "format":"date",
    "title":"Year",
    "description":"This specifies the year - DFES starting position is the last complete calendar year, and forecasts per year, out to 2050. As peak demand is key to our modelling, the year corresponds to winter of that year (i.e. 2022 corresponds to 'December 2022') when the peak is likely to happen, although more widely it overlaps with 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."
    }
    ,
    "concat_subname_level":
    {
    "type":"string",
    "title":"concat_subname_level",
    "description":""
    }
    }
    }
    }
  }
}

}

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