IN Brief:
- UK Power Networks’ DSO has launched an open-source Python package called ukpyn.
- The toolkit helps users access, filter, combine, and analyse Open Data Portal datasets.
- It supports work on flexibility, power flows, network planning, forecasting, and research.
UK Power Networks’ Distribution System Operator has launched an open-source Python package designed to make electricity network data easier to access and analyse.
The toolkit, called ukpyn, allows users to discover, filter, combine, and analyse datasets from UK Power Networks’ Open Data Portal. It is intended for renewable generators, flexibility providers, researchers, students, energy businesses, and other users working with network data.
The package was developed with researchers at the University of Birmingham through work linked to the Supergen Energy Networks Hub. It is available through Python’s packaging index and on GitHub, supported by tutorials, reference documents, and API guidance.
The toolkit provides a consistent way to work with datasets including flexibility dispatches, power flows, network data, and other records. It reduces the need to manually search for information, request data from separate sources, or write custom code to connect directly to raw data feeds.
Users can access the ukpyn GitHub repository to raise issues, suggest examples, and contribute improvements. Automated processes are used to keep the package aligned with changes or new data on the Open Data Portal, supporting reliability as datasets evolve.
Python is widely used across the energy sector for research, forecasting, modelling, and data processing, yet practical barriers still slow the use of network data. Raw feeds, inconsistent formats, API handling, data cleaning, and documentation gaps can absorb time before analysis begins. A maintained client library turns access into a repeatable workflow and allows users to spend more time on modelling and interpretation.
The package also reflects the changing role of distribution system operation. Distribution networks are no longer managed only through asset inspection, reinforcement planning, and connection studies. They increasingly require data-led visibility of load, generation, flexibility, constraints, forecasts, and local energy scenarios.
UK Power Networks’ DSO has been building a more active network operation model, with open data forming part of the infrastructure needed for flexibility markets, planning, and research. Open data becomes more useful when it can be queried and combined directly within the tools used by analysts, engineers, and developers.
The data challenge is closely connected to future demand planning. UK Power Networks has modelled electric HGV grid demand, examining where future heavy transport load could emerge and how it may affect the distribution network. Tools such as ukpyn support the same move toward earlier, better-informed network analysis.
The package includes support for Long Term Development Statement data, Distribution Future Energy Scenarios, Distribution Network Options Assessment information, network metrics, flexibility market records, GIS data, power-flow information, and curtailment events. It supports synchronous and asynchronous workflows, exports to multiple formats, type hints, and use in notebooks and scripts.
Open-source tooling is becoming part of the grid digitalisation toolkit. Network operators are under pressure to make better use of existing assets, support faster connections, and bring flexibility into operational planning. Those objectives all depend on accessible, trustworthy, and usable data.
By giving its open data a practical route into Python-based workflows, UK Power Networks’ DSO is lowering the technical barrier between published datasets and applied analysis. The physical network still requires reinforcement, but the decisions around where, when, and how that reinforcement is delivered increasingly depend on data that can be used quickly and consistently.
