A geographically disaggregated approach to integrate low-carbon technologies across local electricity networks

Abstract

Meeting climate targets requires widespread deployment of low-carbon technologies such as distributed photovoltaics, heat pumps and electric vehicles. Without mitigating actions, changing power flows associated with these technologies would adversely impact some local networks. The extent of these impacts, and the optimal means of avoiding them, remains unclear. Here we use local-level data and network simulation to estimate variation in future network upgrade costs in over 40,000 geographical regions comprising all of Great Britain. We find that costs vary substantially between localities, and are typically highest in urban areas, and areas with highest deployment of heat pumps and electric vehicles. We estimate reductions in required upgrades associated with local flexibility, which vary substantially between localities. We show that using geographically disaggregated data to inform flexibility deployment across the country could reduce network upgrade costs by hundreds of millions of pounds relative to an approach that treats localities as homogeneous. Increased deployment of electrification through solar power, heat pumps and electric vehicles requires power-network upgrades, but their full impacts are unclear. Few et al. take a local-level approach to examine network upgrade needs, finding large regional variations, and explore how flexibility can minimize impacts.