How information propagation in social networks can improve energy savings based on time of use tariff
| dc.contributor.author | Ekpenyong, Uduakobong Edet | |
| dc.contributor.author | Zhang, Jiangfeng | |
| dc.contributor.author | Xia, Xiaohua | |
| dc.contributor.email | uduak.ekpenyong@up.ac.za | en_ZA |
| dc.date.accessioned | 2015-11-26T09:19:35Z | |
| dc.date.issued | 2015-12 | |
| dc.description.abstract | The expected savings from energy efficiency projects are divided into two, direct savings and indirect savings. Direct savings refer to savings obtained through the personal effort of an individual implemen-ting some energy efficiency measures. Indirect savings are achieved through information transmission of energy efficiency measures from an individual to his/her neighbours. In this paper information trans-mission is seen as human contribution for energy savings through interactions within the social network. This paper formulates a mathematical model that calculates an expected energy cost savings model that consists of direct and indirect savings. Indirect savings are made through social interactions of people in a network over time. Direct savings calculations are based on the Homeflex time of use tariff of South Africa. A case study of thirty-six households is used to illustrate the impact individuals have on the rest of their network in transferring information about the energy efficiency measures they have implemented. The results show that social interactions can improve energy efficiency savings and consequently reduce electricity cost. | en_ZA |
| dc.description.embargo | 2016-12-31 | |
| dc.description.librarian | hb2015 | en_ZA |
| dc.description.sponsorship | National Hub for the post-graduate programme in Energy Efficiency and Demand Side Management at the University of Pretoria, South Africa. | en_ZA |
| dc.description.uri | http://www.elsevier.com/locate/scs | en_ZA |
| dc.identifier.citation | Ekpenyong, UE, Zhang, J & Xia, X 2015, 'How information propagation in social networks can improve energy savings based on time of use tariff', Sustainable Cities and Society, vol. 19, pp. 26-33. | en_ZA |
| dc.identifier.issn | 2210-6707 | |
| dc.identifier.issn | 10.1016/j.scs.2015.07.005 | |
| dc.identifier.other | 10.1016/j.scs.2015.07.005 | |
| dc.identifier.uri | http://hdl.handle.net/2263/50934 | |
| dc.language.iso | en | en_ZA |
| dc.publisher | Elsevier | en_ZA |
| dc.rights | © 2015 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Sustainable Cities and Society. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Sustainable Cities and Society, vol. 19, pp. 26-33, 2015. doi : 10.1016/j.scs.2015.07.005. | en_ZA |
| dc.subject | Energy efficiency | en_ZA |
| dc.subject | Information entropy | en_ZA |
| dc.subject | Information distribution | en_ZA |
| dc.subject | Probability | en_ZA |
| dc.subject | Social network | en_ZA |
| dc.subject | Time of use tariff | en_ZA |
| dc.title | How information propagation in social networks can improve energy savings based on time of use tariff | en_ZA |
| dc.type | Postprint Article | en_ZA |