Geographically disaggregated approach to integrate low carbon technologies across local electricity networks

Abstract Globally, increased deployment of low carbon technologies in the form of distributed photovoltaics (PV), heat pumps (HPs), and electric vehicles (EVs) are required to meet climate targets. Without network upgrades or increased system flexibility, these technologies would overload some local networks. The extent of overloading, which networks are most susceptible, and optimal means of avoiding overloading by context, remain unclear. This paper presents a new methodology using local-level data and network simulation to calculate future network upgrade costs in over 40,000 geographical regions across Great Britain. Network upgrade costs are found to vary substantially between localities. Costs are typically highest in urban areas, and areas with high levels of HP and EV deployment. Reduction in network upgrade cost associated with locally deployed flexibility is also calculated and found to vary substantially between localities. This geographically resolved data is used to develop a targeted approach to deployment of local network flexibility across the country, reducing network upgrade costs by more than £200 million compared to an approach treating localities as homogenous.