INCAP - Inducing consumer adoption of automated reaction technology for dynamic power pricing tariffs

Can consumers be induced to adopt varying tariffs and automatic response technology for common household appliances at costs that make this socially attractive? The project implements a large scale field experiment using an automatic response application for a common appliance (e.g. refrigerators).
 

Project description

Households can help counteract variation in power demand and supply by adopting „smart"" technology for their appliances that automatically react to hourly wholesale market conditions by disengaging them during high-priced periods. In the future, many household appliances may have automated response technologies built in, however, transaction costs (e.g. because of imperfect information and disutility of effort) can cause consumers to lag in adopting these technologies. This can seriously inhibit the use of dynamic pricing and automated response technologies even when this is economically advantageous to the consumer. Such adoption barriers seem important for the reluctance of consumers to undertake economically favorable energy saving investments and habit changes. The question analyzed in INCAP is: Can consumers be induced to adopt varying tariffs and automatic response technology for common household appliances at costs that make this socially attractive? The project implements a large scale field experiment using an automatic response application for a common appliance (e.g. refrigerators). This is a novel approach allowing estimation of the distribution of adoption barriers across a large representative sample of power consumers in their natural consumption setting based on controlled variations in the application technology and intervention design. Results can point to those consumer groups where focused policies will be cost-effective and to how these policies should be designed. The representative field experimental method gives us a unique possibility for extrapolating results to general behavior patterns. We exploit this by integrating results into macro models with which we will design policy strategies for inducing household supply of regulating power and evaluating their consequences.

Key figures

Period:
2012 - 2017
Funding year:
2011
Own financial contribution:
4.81 mio. DKK
Grant:
17.94 mio. DKK
Funding rate:
79 %
Project budget:
22.75 mio. DKK

Category

Programme
Innovationsfonden
Case no.
ENMI 11-116786

Participants

Københavns Universitet (Main Responsible)
Partners and economy
Partner Subsidy Auto financing
Danmarks Tekniske Universitet (DTU) 6,43 mio. DKK 0,68 mio. DKK
University of Copenhagen, LIFE (Food and Resource Economics) 7,47 mio. DKK 1,60 mio. DKK
DEVELCO A/S 2,50 mio. DKK 1,67 mio. DKK
Stanford University 0,75 mio. DKK 0,06 mio. DKK
SydEnergi 0,80 mio. DKK 0,80 mio. DKK

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