LV Network Visibility
Researchers at the University of Bath have further extended the work to high-fidelity modelling for low-carbon technologies, primarily EVs. Spatiotemporal analysis of charging behaviour was used to model charging demand in granular detail with realistic assumptions, identifying potential vulnerabilities in the distribution network, and assessing the degree of misalignment with renewable energy.
To fully realise the potential financial and environmental benefits, EV charging will be optimised over a range of spatial (e.g., town/city level, regional level and national level) and temporal scales (e.g., hour, day, week, month), and against different weather conditions and local demographics.
The work can inform how charging optimisation and behaviour should evolve with increasing renewable penetration and changing mobility patterns, and the required upgrading in charging and electrical infrastructure. The knowledge will enable network operators to better understand how EVs will affect LV networks, how the impact would aggregate and propagate to higher voltage (HV, EHV) networks, supporting them with transformative network planning and operation practices.
Following on from this research, the University of Bath have carried out a six-month feasibility study to assess the viability of a ‘digital spine’ concept for the UK energy system, in partnership with Arup and the Energy Systems Catapult. Furthermore, Bath’s extensive research in last-mile network visualisation, high-fidelity modelling and digitalisation has enabled a strategic partnership with NGED to be setup, with specific insights into low-carbon technologies modelling, asset management, network reliability and resilience. This partnership will enable Bath to work closely with NGED to develop transformative research that can help NGED, and more broadly UK electricity network operators, prepare and adapt to a low-carbon world by new technical, digital, and commercial solutions.
