The Near Real-time Data Access project was a small-scale demonstration project which made real-time data available to stakeholders. The original NeRDA project focused on the Oxford and Green Recovery areas, the NeRDA 2 project will make real-time network data available across the entirety of the SSEN network. In addition, NeRDA 2 will make connectivity and load model data available alongside near real-time monitoring data to provide stakeholders with enhanced visibility of our network utilisation to allow them to make better informed decisions.
Benefits
At a high level we expect the benefits for consumers will be;
• Reduced costs for households (such as bills, appliance maintenance, etc.)
• Improved exchange of information between DNOs and customers
• Improve the DNOs understanding of customers' needs and the ability to address these
• The NeRDA project will not adversely impact or exclude consumers in vulnerable situations, the benefits will be applicable to all consumers.
Learnings
Outcomes
The NIA project was extremely successful as the NeRDA portal made real-time network data available to stakeholders both via the portal and dedicated APIs (Application Protocol Interfaces), this involved building data pipelines to safely expose the monitoring data produced by substation (LV) monitoring devices and our existing SCADA data from HV sites. As well as extensive internal data pipelines to prepare and surface the data for ‘front end.’ NeRDA is a data portal and API that provides near real-time power flow information from electricity distribution networks. It enables stakeholders—such as energy developers, flexibility providers, and local energy projects—to access granular network data, including:
- EHV, HV, and LV network loading information
- Connectivity models
- Load forecasts
- Long Term Development Statement (LTDS) data
This data can be accessed via:
- A dashboard portal (visual interface)
- APIs for automated integration into tools and applications.
For the past two years the software company Kraken, has been consuming the NeRDA API for the purposes of a trial to explore the consequences of pricing the network to more accurately reflect cost variability of serving demand. Alongside this, the supplier Octopus Energy (leveraging Kraken’s grid and flexibility capabilities) implemented a trial, which looked at grid congestion at a specific point in the distribution network (around Dundee, in Scotland), and reflected this in a day-ahead dynamic grid tariff to encourage the shifting of flexible loads.
Kraken Flex Case Study https://kraken.tech/case-studies/ssen
The project has successfully reached TRL 9 and the ownership for the platform has been transferred to the SSEN Smart Energy Systems team. The feedback from stakeholder engagement and the Kraken Flex case study has demonstrated the value and necessity for energy stakeholders to have continued access to this data.
Lessons Learnt
The project learning has shown the demand for NeRDA (access to real-time network data) arises from fundamental changes in electricity demand and the increasing complexity of managing distributed energy resources (DERs). As electrification accelerates—driven by electric vehicles (EVs), heat pumps, and other low-carbon technologies—demand patterns are becoming more dynamic and less predictable. This creates new challenges for network operators in maintaining system stability, managing constraints, and delivering cost-efficient connections. NeRDA provides the underlying data infrastructure to address these challenges by enabling:
- Flexible Management of DERs: Real-time visibility of network conditions supports active network management and flexibility services.
- Dynamic Pricing Enablement: Accurate, granular network data allows suppliers and flexibility providers to implement dynamic tariffs that reflect real network costs, incentivising demand-side response and reducing congestion. As demonstrated in a case study by Kraken flex. (Kraken Flex Case Study https://kraken.tech/case-studies/ssen)
- Improved Connections Process: Enhanced transparency of capacity and constraints reduces the time and cost of providing connection studies, while enables customers to self-assess feasibility.
