Influence of advertisement control to residential energy savings in large networks

Feng Du, Hong Yue, Jiangfeng Zhang

Research output: Contribution to journalArticlepeer-review

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Abstract

User awareness and behaviour have a strong impact on energy savings especially through large-scale mass rollout programmes for new energy products. Such energy programmes are mostly funded by government with specific energy saving targets. In this work, we aim to investigate the influence of advertisement control to residential energy savings in large population networks. A mathematical model is established to predict the expected energy savings (EES) in a network where advertisement is used to influence user adoption rate of energy efficient product. The proposed dynamic network model consists of information diffusion, EES calculation, and advertisement control. It can be applied to mass rollout programmes to forecast the EES and the adoption rate of new energy products, based on which the advertising investment required to accelerate energy savings can be determined by optimisation design. The proposed approach is tested first with a small population network involving 40 participants, then applied to a large population network with one million internet users. Case studies for different scenarios consider various optimisation targets including adoption rate, time cost, advertisement cost, and total energy savings subject to programme budget and time constraints. The optimisation results show that 32.21% and 18.15% of EES are achieved for the small- and large-scale networks, respectively, suggesting the potential benefits of taking advertisement as a means to promote energy efficient product through social networks.
Original languageEnglish
Article number120661
Number of pages12
JournalApplied Energy
Volume333
Early online date13 Jan 2023
DOIs
Publication statusPublished - 1 Mar 2023

Keywords

  • connected population network
  • expected energy savings (EES)
  • energy efficiency
  • mass rollout programme
  • advertisement control
  • optimisation design

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