1. An Introduction

2. Partners and Funding Funded by Ofgem under the Low Carbon Network Fund (LCNF). – Delivery through partnership with Northern Powergrid (DNO) British Gas DEI EA Technologies Ltd

3. The Problems: 1.Broken Value chain in energy system innovation 2.Uncertain responses to hardware change 3.Need more, smarter solutions for network maintenance The ‘engineering world view’ of mechanistic, predictable, levers is challenged – The grid = networks + people – A complex adaptive system – Less predictable, levers are unreliable – Therefore ROI is unknown

4. Learning Outcomes 1.Current and future load profiles 2.Flexibility of demand, costs of flexibility 3.Flexibility of supply, costs of flexibility 4.Optimum solution to overcome network constraints? 5.Optimum means of delivery of these solutions to end users?

5. Socio-Technical Approach Socio-technical > social + technical We are interested not only in the social and technical aspects of electricity supply and demand, but in the way in which these are interlinked and inter- dependent. We are seeking to develop theoretical perspectives, research design methodologies and analysis that enable us to develop a socio-technical analysis of the emergence and implications of the ‘smart grid’.

6. Customers: Propositions LO1 – current usage LO2 – responses to: Time of Use Tariffs Restricted Hours Direct control – Mixed with HP EV PV

7. Types of Customer in the Study 5 Variables for Domestic Customers – Tenure – Income – Composition – Gas Grid Connection – Rural / Urban Skewed by BG Smart Meter Roll Out – Flats, pre-payment, E7, poor credit rating Problems…

8. Networks Wooler Rise Carr

9. Research Process 1.Survey I.~12,000 participants II.Response rate?? 2.Qualitative visits to ~200 customers I.Home tour(s) II.Semi-structured conversation about energy use flexibility, technologies, habits 3.Consumption Data from Smart Meters 4.Network Data from ‘the wires’ Analysis

10. Smart Grids through the Cynefin Framework Complex Complicated - Domain of expertise, best practice -Sense, Analyse, Respond - If Smart Grids were just about engineering they’d be here -Predictive Expectations -Domain of emergent practice - Probe, Sense, Respond - The social side of our project is here - Explanatory Expectations Smart Grid CLNR = Probe, Sense, RespondDevelop more predictive powerMake investment less uncertain CLNR

11. Connection to Fuel Poverty GP’s previous research with DU and NEA Interest in affordability of ‘smart’ grid and associated technologies Interest in the equity of smart – Who’s paying and who’s benefitting – Energy bills go up to create something that not everyone can access – Related to Smart Meter roll out over next 8 years

12. Currently… Completed evidence reviews, research design About to launch survey and pilot the qualitative research For more info: Gareth Powells Gareth.powells@durham.ac.uk