Energy optimization in smart urban buildings using bio-inspired ant colony optimization

Fakhri Alam Khan*, Kifayat Ullah, Atta ur Rahman, Sajid Anwar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


In this paper, a smart home energy management system is proposed to improve the efficiency of the electricity infrastructure of residential buildings. To solve the scheduling problem of a smart building, we propose bacterial foraging ant colony optimization (HB-ACO). The primary objective of scheduling is to shift load from on-peak hours to off-peak hours to reduce electricity cost and peak-to-average ratio. A comparison of these algorithms is also presented in terms of performance parameters, electricity cost, reduction of PAR, and user comfort in terms of waiting time. The proposed techniques are evaluated using two pricing schemes: (1) time of use and (2) critical peak pricing. Moreover, coordination among home appliances is presented for real-time scheduling. We represent this as a knapsack problem and solve it through ant colony optimization algorithm. The HB-ACO shows better performance than ACO and BFA in reducing electricity cost, PAR, and increased user comfort, which is evident from the simulation results.

Original languageEnglish
Pages (from-to)973-989
Number of pages17
JournalSoft Computing
Issue number2
StatePublished - Jan 2023

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.


  • Ant colony optimization
  • Bacterial foraging optimization
  • Day-ahead and real-time scheduling
  • Real-time pricing
  • Smart home

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Geometry and Topology


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