Generating value from smart electricity meter data

The rollout of smart electricity meters heralds an explosion in the quantity and resolution of meter data: 500Bn consumption datapoints annually contrasts with the current volume of some 100M meter readings. If leveraged effectively the resulting dataset can support the transition to a low carbon economy by improving the efficiency, sophistication and spatiotemporal disaggregation of system management, from load prediction and demand-side management (DSM) to system balancing. This project will enable the electricity industry to make the required business sense of the data. Using the now finalised Energy Demand Research Project (EDRP) smart meter database it will develop scaleable new approaches to these large volumes of data by: (i) linking to other datasets to add dimensions to the EDRP data; (ii) building an environment for interrogating, analysing, visualising and reporting on patterns in the data. The system will be designed to address a set of identified industry business needs, such as: (a) improved demand prediction algorithms at arbitrary spatiotemporal scales; (b) prediction and verification of distributed DSM interventions; (c) identification of system state signatures for use in automated DSM; (d) visualisation of load profiles to assist network planning and management.