Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs
Anna Kowalska-Pyzalska (),
Katarzyna Maciejowska (),
Katarzyna Sznajd-Weron () and
Rafał Weron ()
No HSC/13/05, HSC Research Reports from Hugo Steinhaus Center, Wroclaw University of Technology
Using an agent-based modeling approach we show how personal attributes, like conformity or indifference, impact the opinions of individual electricity consumers regarding switching to innovative dynamic tariff programs. We also examine the influence of advertising, discomfort of usage and the expectations of financial savings on opinion dynamics. Our main finding is that currently the adoption of dynamic electricity tariffs is virtually impossible due to the high level of indifference in today's societies. However, if in the future the indifference level is reduced, e.g., through educational programs that would make the customers more engaged in the topic, factors like tariff pricing schemes and intensity of advertising will became the focal point.
Keywords: Dynamic pricing; Time-of-use tariff; Demand response; Diffusion of innovations; Agent-based model; Spinson (search for similar items in EconPapers)
JEL-codes: C63 O33 Q48 Q55 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp, nep-cwa, nep-ene, nep-env, nep-hme, nep-mkt and nep-reg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_13_05.pdf Original version, 2013 (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:wuu:wpaper:hsc1305
Access Statistics for this paper
More papers in HSC Research Reports from Hugo Steinhaus Center, Wroclaw University of Technology Contact information at EDIRC.
Bibliographic data for series maintained by Rafal Weron ().