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http://hdl.handle.net/1942/29003
Title: | Dissecting demand response: A quantile analysis of flexibility, household attitudes, and demographics | Authors: | Srivastava, Aman VAN PASSEL, Steven Laes, Erik |
Issue Date: | 2019 | Publisher: | ELSEVIER SCIENCE BV | Source: | ENERGY RESEARCH & SOCIAL SCIENCE, 52, p. 169-180 | 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. | Notes: | [Srivastava, Aman; Van Passel, Steven] Univ Antwerp, Fac Appl Econ, Prinsstr 13, Antwerp, Belgium. [Srivastava, Aman; Laes, Erik] VITO Energyville, Smart Energy & Built Environm Unit, Thor Pk, B-8310 Poort Genk, Belgium. [Van Passel, Steven] Hasselt Univ, Fac Business Econ, Martelarenlaan 42, Hasselt, Belgium. | Keywords: | Demand response; Demand side management; Electricity; Household energy; User acceptance; Quantile regression;Demand response; Demand side management; Electricity; Household energy; User acceptance; Quantile regression | Document URI: | http://hdl.handle.net/1942/29003 | ISSN: | 2214-6296 | e-ISSN: | 2214-6326 | DOI: | 10.1016/j.erss.2019.02.011 | ISI #: | 000468215900016 | Rights: | 2019 Elsevier Ltd. All rights reserved. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2020 |
Appears in Collections: | Research publications |
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srivastava 1.pdf Restricted Access | Published version | 2.88 MB | Adobe PDF | View/Open Request a copy |
Srivastava.2019.pdf | Peer-reviewed author version | 424.3 kB | Adobe PDF | View/Open |
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