The effect of demand response on purchase intention of distributed generation: Evidence from Japan

Participation in demand response (DR) may affect a consumer's electric consumption pattern through consumption load curtailment, a shift in the consumption timing or increasing the utilization of distributed generation (DG). This paper attempts to provide empirical evidence of DR's effect on DG adoption by household consumers. By using the original Internet survey data of 5442 household respondents in Japan conducted in January 2015, we focus on the effect of the time-of-use (TOU) tariff on the purchasing intention of photovoltaic systems (PV). The empirical results show the following: 1) current TOU plan users have stronger PV purchase intentions than the other plan users, 2) respondents who are familiar with the DR program have relatively higher purchase intentions compared with their counterparts, and 3) when the respondents are requested to assume participation in the virtual TOU plan designed for the survey, which resembles plans currently available through major companies, 1.2% of the households have decided to purchase PV. In addition, we provide calculations of TOU's impacts on the official PV adoption and emissions reduction targets, and discuss policy recommendations to increase recognitions and participations in TOU programs.

[1]  Ivana Kockar,et al.  The economics of distributed energy generation: a literature review , 2015 .

[2]  James Keirstead,et al.  Behavioural responses to photovoltaic systems in the UK domestic sector , 2007 .

[3]  E. Koukios,et al.  Simulation of acid-catalysed organosolv fractionation of wheat straw. , 2004, Bioresource technology.

[4]  Paul Thorsnes,et al.  Consumer responses to time varying prices for electricity , 2012 .

[5]  Wander Jager,et al.  Stimulating the diffusion of photovoltaic systems: A behavioural perspective , 2006 .

[6]  Guy R. Newsham,et al.  The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review , 2010 .

[7]  Vicki G. Morwitz,et al.  When Do Purchase Intentions Predict Sales? , 2006 .

[8]  Kerstin Sernhed,et al.  Pay for Load Demand. Electricity Pricing with a Load Demand Component , 2003 .

[9]  Adisa Azapagic,et al.  Motivations and barriers associated with adopting microgeneration energy technologies in the UK , 2013 .

[10]  AbuBakr S. Bahaj,et al.  Urban energy generation: The added value of photovoltaics in social housing , 2007 .

[11]  Towhidul Islam,et al.  Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data , 2014 .

[12]  Makoto Tanaka,et al.  A stated preference analysis of smart meters, photovoltaic generation, and electric vehicles in Japan: Implications for penetration and GHG reduction , 2014 .

[13]  Jin-ho Kim,et al.  Common failures of demand response , 2011 .

[14]  Tammo H. A. Bijmolt,et al.  Generalizations on Consumer Innovation Adoption: A Meta-Analysis on Drivers of Intention and Behavior , 2011 .

[15]  Chelsea Schelly Residential solar electricity adoption: What motivates, and what matters? A case study of early adopters , 2014 .

[16]  Aidan O'Driscoll,et al.  The diffusion of microgeneration technologies – assessing the influence of perceived product characteristics on home owners' willingness to pay , 2011 .

[17]  I. Vassileva,et al.  Introducing a demand-based electricity distribution tariff in the residential sector: Demand response and customer perception , 2011 .

[18]  C. Goldman,et al.  Option value of electricity demand response , 2005 .

[19]  A. Faruqui,et al.  Household response to dynamic pricing of electricity: a survey of 15 experiments , 2010 .

[20]  Avinash Unnikrishnan,et al.  Analysis of large truck crash severity using heteroskedastic ordered probit models. , 2011, Accident; analysis and prevention.

[21]  Ulf J. J. Hahnel,et al.  Intentions to adopt photovoltaic systems depend on homeowners' expected personal gains and behavior of peers , 2015 .

[22]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .