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Infographic - How can people get the heat they want at home without carbon ?


Citation ETI Infographic - How can people get the heat they want at home without carbon ?, ETI, 2015. https://doi.org/10.5286/UKERC.EDC.000568.
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Author(s) ETI
Project partner(s) ETI
Publisher ETI
DOI https://doi.org/10.5286/UKERC.EDC.000568
Download Infographic-How-can-people-get-the-heat-they-want-at-home-without-the-carbon.pdf document type
Abstract Infographic on Domestic Energy Services: To move consumers to low-carbon heat we need to rethink the consumer proposition. The emergence of the “connected home” allows us to look at heat and comfort as a packaged service not simply the purchase of units of fuel. This slide shows how the customer might react, as a guide to businesses.
Associated Project(s) ETI-SS1403: Smart Systems and Heat (SSH) Programme - Home Energy Management System (HEMS)
Associated Dataset(s)

Home Energy Management System (HEMS) ICT Market Study - HEMS ICT Market Forecast Tool

Associated Publication(s)

ETI Insights Report - Domestic Energy Services

Home Energy Management System (HEMS) ICT Market Study - Main Report

Home Energy Management System (HEMS) ICT Market Study - Market Forecast Supplemental Report

Home Energy Management System (HEMS) ICT Market Study - Request for proposals

Infographic - Domestic Heat

List of projects for the ETI Smart Systems and Heat (SSH) Programme

SSH Stagegate 1 - Review of International Smart Systems and Heat Initiatives - Final Report

WP1 Appliance Disaggregation: Data Analysis Pre-processing

WP1 Appliance Disaggregation: Data Quality Report

WP1 Appliance Disaggregation: Dynamic Modelling

WP1 Appliance Disaggregation: Final Report

WP1 Appliance Disaggregation: High Frequency Appliance Disaggregation Analysis Handover

WP1 Appliance Disaggregation: High Frequency Appliance Disaggregation Analysis: Insights Overview

WP1 Appliance Disaggregation: Incorporation of Appliance and layout information

WP1 Appliance Disaggregation: Online learning and distributed learning

WP1 Appliance Disaggregation: Pattern Mining