Social Networking and Consumer Preference Based Power Peak Reduction for Safe Smart Grid

Shen Wang, Peng Zhang, Jun Wu, Yutao Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Efficient power peak reduction is a classic scheduling target to make smart grid more safe. To handle multiple energy consumers, energy management are usually built based on game theory. Despite their effectiveness, they do not consider consumer preferences, which are however important in developing salient scheduling frameworks. This work explores consumer preference based social networking in computing optimized schedules to facilitate the incorporation in energy management. We propose the consumer preference driven intelligent energy management technique for smart cities using game theoretic social tie. In our technique, social communities are constructed based on the preference of electricity usage. Community pricing strategy is adjusted during each time period through leveraging cooperative game theory. The simulation results demonstrate the effectiveness and efficiency of the proposed intelligent energy management technique.

Original languageEnglish
Title of host publication2018 6th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-98
Number of pages5
ISBN (Electronic)9781538664100
DOIs
Publication statusPublished - 2018 Oct 18
Externally publishedYes
Event6th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2018 - Oshawa, Canada
Duration: 2018 Aug 122018 Aug 15

Publication series

Name2018 6th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2018

Conference

Conference6th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2018
Country/TerritoryCanada
CityOshawa
Period18/8/1218/8/15

Keywords

  • Consumer preference
  • Demand response
  • Game theory
  • Smart grid
  • Social networking

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Control and Optimization

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