Network Capacity

No description

Data Assets: 6
network-capacity Collection
Big Data

Smart Meter LV Feeder Usage

Smart meter LV feeder half hourly usage data is collected directly from smart meters in homes and businesses and anonymised through aggregation to no less than 5 properties through SSEN’s smart meter adapter. There is a postcode and LV Feeder Dataset ID lookup to provide the aggregated half hourly consumption data in Wh (combined primary and secondary active import Wh), from the relevant secondary transformer and low voltage feeder IDs with a total count of smart meters.

7 months ago
Graph

Generation Availability and Network Capacity

Our Generation Availability and Contracted demand map for both north and south. Our map provides an indication of the networks capability to connect large-scale developments to major substations. Accompanying the map, the heat map spreadsheets for both of our network regions provides Grid Supply Point (GSP) details, GSP and substation transformer ratings, Fault level information, and contracted and quoted generation projects at each GSP.

1 year ago
XLSX

Embedded Capacity Register

The Embedded Capacity Register (ECR) has been developed to provide better information to electricity network stakeholders on connected resources and network requirements. Each Distribution Network Operator (DNO) will host a register which will provide accessible information at a local and national level. The register uses a format agreed through the Energy Networks Association's Open Networks project, an industry initiative aimed at transforming the operation of energy networks and delivering a smart grid. Our register provides information on generation and storage resources (>=50kW) that are connected, or accepted to connect, to the electricity distribution networks owned and operated by us and it will be updated on a monthly basis. The register also includes information on the flexibility services that are being provided by connected resources, assisting to control or schedule demand and/or generation to reduce network constraints.

1 year ago
PowerBI

SSEN Secondary Transformer - Asset Capacity and Low Carbon Technology Growth

The load model is a machine learning product which estimates a half-hourly annual demand profile for each household based on a series of demographic, geographic and heating type factors. To enable us to estimate capacity on the electricity network while protecting individual customers data privacy by using modelled data. These views are then aggregated up the networks hierarchy based on the combinations of customers associated with each asset. This view is supplemented with the forward Distribution Future Energy Scenarios (DFES) which highlight the expected impact of low carbon technology on the network (LCT) such as heat-pumps or electricity vehicles. The view demonstrated here represents a sample iteration of our evolving network capacity & load model - highlighting estimated peak usage against asset rating.

1 year ago
PDF

SHEPD Network Development Report

This is Scottish and Southern Electricity Networks (SSEN) Distribution's first Network Development Report and is part of a suite of new information that sets out our longer-term Network Development Plans for our distribution networks. It gives users access to information pertaining to our network plans for the next ten years in relation to our 11 kV networks and above, allowing all interested parties to better assess and identify the future opportunities to use and engage with us and the network.

1 year ago
PDF

SEPD Network Development Report

This is Scottish and Southern Electricity Networks (SSEN) Distribution's first Network Development Report and is part of a suite of new information that sets out our longer-term Network Development Plans for our distribution networks. It gives users access to information pertaining to our network plans for the next ten years in relation to our 11 kV networks and above, allowing all interested parties to better assess and identify the future opportunities to use and engage with us and the network.

1 year ago