Objective
Founded in 2009, Green Running are a fast growth EU SME working with a range of key electricity sector partners (Centrica, UK Power Networks). Having already established a portfolio of commercial and industrial sector electricity analytics tools, in 2014 Green Running began development of a domestic solution -verv.
Verv applies patented machine learning algorithms to detect and profile all sources of electrical activity (generation, storage and consumption) active on a household's electrical system. Generating real time, itemised (iappliance level), usage data across metrics such as energy (kWh), cost (€), environmental impact (tCO2) and power quality (Hz) - verv generates valuable outputs for electricity retailers to customise/extend their services.
With continental Europe subject to many of the same drivers, and several of Green Running's target customers (electricity retailers) active in multiple EU markets, Green Running now seek a H2020 Phase 1 feasibility study to validate verv's pan-European commercial and technical potential. A 5 month project including market study, proposition refinement, partner engagement, IP strategy management, technology road map updating for multi-market operation and risk management will provide Green Running with the comprehensive knowledge, and partners it requires to first undertake a follow on multi-market field trial, and then launch verv in non-UK markets by 2020. Current projections suggest doing so can boost verv's customer acquisitions by 200%, generate annual revenues of >€6m by 2022 and an operating EBIT of €1.7m supporting creation of 38 new jobs, 23 of which will be high skilled positions at Green Running. >30,000tCO2 are also forecast to be avoided, making a valuable contribution to EU decarbonisation.
This Phase 1 study will accelerate and extend the growth of a high potential EU SME, allowing it to establish Europe's presence in the cutting edge innovation fields of artificial intelligence, and data analytics.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencesdata science
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectrical engineeringelectric energy
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
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Programme(s)
- H2020-EU.3.3. - SOCIETAL CHALLENGES - Secure, clean and efficient energy Main Programme
- H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
- H2020-EU.2.3.1. - Mainstreaming SME support, especially through a dedicated instrument
Call for proposal
(opens in new window) H2020-SMEInst-2016-2017
See other projects for this callSub call
H2020-SMEINST-1-2016-2017
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
BA1 1UD BATH
United Kingdom
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.