Effective energy consumption scheduling in smart homes

O. M. Longe, K. Ouahada, S. Rimer, H. Zhu, H. C. Ferreira

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Citations (Scopus)


Monthly expenditure on electricity by most households in South Africa take beyond acceptable percentage of their income. In order to keep the household energy expenditure below the energy poverty threshold, a daily electricity optimization problem is formulated using mixed integer linear programming (MILP) method. The energy optimization scheduling was carried out by a device called the Daily Maximum Energy Scheduling (DMES) device proposed to be incorporated into smart meters of households. The DMES algorithm was tested with household data set and was shown to be capable of ensuring that households spend less than 10% of their income on electricity bill monthly. This technique therefore, would be beneficial to consumers (for better financial savings and planning), utility (for effective energy and financial savings, and energy network planning) and cleaner environments as proposed for smart grid. Also, number of households in the nation living below the energy expenditure-based poverty threshold would increase.

Original languageEnglish
Title of host publicationProceeding of the 2015 12th IEEE AFRICON International Conference
Subtitle of host publicationGreen Innovation for African Renaissance
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479974986
Publication statusPublished - 18 Nov 2015
Event12th IEEE AFRICON International Conference, AFRICON 2015 - Addis Ababa, Ethiopia
Duration: 14 Sept 201517 Sept 2015

Publication series

NameIEEE AFRICON Conference
ISSN (Print)2153-0025
ISSN (Electronic)2153-0033


Conference12th IEEE AFRICON International Conference, AFRICON 2015
CityAddis Ababa


  • Daily Maximum Energy Scheduling (DMES)
  • electricity consumption
  • low-income households
  • smart home appliances
  • Smart meter

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering


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