Projects

Completed

Applied Research and Development

PHYSICAL SCIENCES AND MATHEMATICS (Statistics and Operational Research)
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering)

Systems Analysis related to energy R&D (Energy modelling)

Project Contact
UK Power Networks

Network Innovation Allowance

Ofgem

01 August 2025

31 March 2026

ENA months

£358,000

Power

London

Network Innovation Allowance

Project Contact, UK Power Networks

Project Contact, South Eastern Power Networks plc
Project Contact, Eastern Power Networks plc

This project will support the development of the open-source Python based tool to be fully compatible with UK Power Networks' network models. Validating this open-source Python tool on GB DNO network models marks a step forward for the industry in power systems analysis.In the first instance, the project will convert UK Power Networks' network models to be used within the tool. This requires the development of several features currently missing from the tools existing converter and identifying/fixing issues. The project will ensure full compatibility with extensive and reproducible tests and demonstrate convergent power flow using the tool.In addition, this project will develop tooling to support DNO use cases. This includes functionality to flexibly isolate sub-networks, for more computationally efficient constraint analysis, state estimation and bespoke tools for integration of forecasts and importing of near real time network configuration. The project is comprised of the following work packages: Adjustments to enhance the existing software to successfully import network models Developing and testing a tool for the identification of sub-networks for constraint analysis Integration with forecasting methods State estimation based on partial measurements or forecasts for loads and generation which is not metered Interoperability with different network modelling exports to obtain near real time network configuration The project will set out to achieve the following objectives:1. Enable UK Power Networks' network models to be compatible with the chosen software and demonstrate power flow convergence on these network models.2. Ingestion of network models into the Python network model, and demonstration of convergent power flow.3. Implementation and analysis of state estimation, enabling more complete coverage of the power flow model under incomplete/uncertain measurements or forecasts.4. Implementation of functionality to easily segment the network into smaller sub-networks to reduce compute time for localised analysis.

The project aims to enhance Distribution Network Operator (DNO) network modelling capabilities to make them scalable and future proof. This involves developing additional features and integrating the required datasets. If successful, the project will enable network modelling use cases including functionality to flexibly isolate sub-networks, state estimation, and integration of forecasts.Once complete, this open-source tool will enable members of the public to run power flow simulations using published models. This project will offer accessibility to network modelling capabilities for customers supporting innovation across the sector. Python Power will support the transition to Net Zero through better use of data and open innovation.

24/04/26