Recent Additions to the EDC

Many energy suppliers market their electricity as renewable while continuing to buy fossil-fuelled power, a practice enabled by outdated regulations. To resolve this confusion, Matched uses public data to track what electricity households and businesses are actually receiving, hour by hour, all year.
The Matched Clean Power Index translates public data from Elexon, NESO, and Ofgem into clear, comparable ratings of the renewable electricity customers actually receive, hour by hour. Our methodology has been reviewed by 30+ experts across the sector, including Oxford, Imperial, and leading suppliers.
Matched is an independent, not-for-profit, open-source initiative. We work with suppliers to highlight best practices, with consumer groups to inform households and businesses, and with policymakers to shape stronger standards.
Our goal is to accelerate the practices that most rapidly decarbonise power.

The 'Clean energy jobs plan' sets out, for the first time, the workforce needed to deliver our clean energy ambitions and how the government will work in partnership with industry and trade unions to deliver it. It explains how we will help workers in all parts of the country benefit from these opportunities - supporting our existing workforce to find new opportunities, training up the next generation, and helping our young people to get good jobs.

The increasing need for residential cooling in Great Britain due to rising temperatures could pose significant challenges to the electricity infrastructure. This study estimates the spatiotemporal cooling demand for residential buildings in Great Britain in 2050. A bottom-up methodology using a lumped parameter dynamic thermal model of building was applied to estimate half-hourly cooling demand and the electricity consumptions of cooling devices for representative dwelling archetypes in 41,726 local areas. The upper estimate for annual and peak electricity consumptions for cooling technologies have been estimated to be 9.3 TWh and 62.6 GW, respectively. The study highlights regional demand variations, correlations between the electricity consumption of cooling technologies and electricity generation by distributed photovoltaics, and the moderating effect of higher dwelling thermal capacities on cooling peak demand. These insights highlight the need for electricity infrastructure reinforcement, and integrated strategies for buildings retrofit and renewable energy to ensure system resilience. This is the data behind this study.

Energy consumption readings for a sample of 5,567 London Households that took part in the UK Power Networks led Low Carbon London project between November 2011 and February 2014. Readings were taken at half hourly intervals. The customers in the trial were recruited as a balanced sample representative of the Greater London population. The dataset contains energy consumption, in kWh (per half hour), unique household identifier, date and time. The CSV file is around 10GB when unzipped and contains around 167million rows. Within the data set are two groups of customers. The first is a sub-group, of approximately 1100 customers, who were subjected to Dynamic Time of Use (dToU) energy prices throughout the 2013 calendar year period. The tariff prices were given a day ahead via the Smart Meter IHD (In Home Display) or text message to mobile phone. Customers were issued High (67.20p/kWh), Low (3.99p/kWh) or normal (11.76p/kWh) price signals and the times of day these applied. The dates/times and the price signal schedule is availaible as part of this dataset. All non-Time of Use customers were on a flat rate tariff of 14.228pence/kWh. The signals given were designed to be representative of the types of signal that may be used in the future to manage both high renewable generation (supply following) operation and also test the potential to use high price signals to reduce stress on local distribution grids during periods of stress. The remaining sample of approximately 4500 customers energy consumption readings were not subject to the dToU tariff.