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Author Srivastava, A.; Van Passel, S.; Laes, E. pdf  doi
openurl 
  Title Dissecting demand response : a quantile analysis of flexibility, household attitudes, and demographics Type A1 Journal article
  Year (down) 2019 Publication Energy Research and Social Science Abbreviated Journal  
  Volume 52 Issue 52 Pages 169-180  
  Keywords A1 Journal article; Economics; Engineering Management (ENM)  
  Abstract Demand response (DR) can aid with grid integration of renewables, ensuring security of supply, and reducing generation costs. However, not enough is known about how residential customers’ perceptions of DR shape their response to such programs. This paper offers a deeper understanding of – and reveals the heterogeneity in – this relationship by conducting a quantile regression analysis of a Belgian DR trial, combining data on response with information on household attitudes towards smart appliances. Results overall suggest that improving response requires subtle shifts in electricity consumption behaviour, which can be achieved through changes in user perceptions. Specifically, if customers are inclined to be flexible, a stronger perception of smart appliances as being beneficial can greatly improve response. With those who are less flexible, the cost of smart appliances is a bigger concern. Thus, when designing DR programs, policymakers should aim to promote modest behaviour changes – so as to minimise inconvenience – in customers, by improving awareness on the benefits of smart appliances. Uptake of such DR programs may be improved by explaining the financial benefits or offering incentives to less flexible population segments. Lastly, improving response among older population segments will require a deeper investigation into their concerns.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos 000468215900016 Publication Date 2019-03-04  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2214-6296 ISBN Additional Links UA library record; WoS full record  
  Impact Factor Times cited 1 Open Access  
  Notes ; This work continued on the results and data of the project Linear that was supported by the Flemish Ministry of Science and organised by the Institute for Science and Technology (IWT). The authors gratefully acknowledge the support extended by Wim Cardinaels at VITO in helping them access the underlying Linear data. ; Approved Most recent IF: NA  
  Call Number UA @ admin @ c:irua:158910 Serial 6183  
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Author Srivastava, A.; Van Passel, S.; Laes, E. pdf  url
doi  openurl
  Title Assessing the success of electricity demand response programs : a meta-analysis Type A1 Journal article
  Year (down) 2018 Publication Energy Research and Social Science Abbreviated Journal  
  Volume 40 Issue 40 Pages 110-117  
  Keywords A1 Journal article; Economics; Engineering Management (ENM)  
  Abstract This paper conducts a meta-analysis of 32 electricity demand response programs in the residential sector to understand whether their success is dependent on specific characteristics. The paper analyses several regression models using various combinations of variables that capture the designs of the programs and the socio-economic conditions in which the programs are implemented. The analysis reveals that demand response programs are more likely to succeed in highly urbanized areas, in areas where economic growth rates are high, and in areas where the renewable energy policy is favorable. These findings provide useful guidance in determining where and how to implement future demand response programs.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos 000430737800014 Publication Date 2017-12-28  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2214-6296 ISBN Additional Links UA library record; WoS full record; WoS citing articles; WoS full record; WoS citing articles  
  Impact Factor Times cited 18 Open Access  
  Notes ; ; Approved Most recent IF: NA  
  Call Number UA @ admin @ c:irua:149027 Serial 6154  
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