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Energy Research & Social Science
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Dissecting demand response: A quantile analysis of flexibility, household attitudes, and demographics

A quantile analysis of flexibility, household attitudes, and demographics
Authors: Aman Srivastava; Steven Van Passel; Steven Van Passel; Erik Laes;

Dissecting demand response: A quantile analysis of flexibility, household attitudes, and demographics

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.

Country
Netherlands
Keywords

Demand response, Sustainability and the Environment, Energy Engineering and Power Technology, Demand side management, Household energy, User acceptance, Fuel Technology, Electricity, Nuclear Energy and Engineering, Quantile regression, SDG 7 - Affordable and Clean Energy, Renewable Energy, SDG 7 – Betaalbare en schone energie, Social Sciences (miscellaneous)

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