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Differential-Evolution-Earthworm Hybrid Meta-heuristic Optimization Technique for Home Energy Management System in Smart Grid

  • Nadeem Javaid
  • Ihtisham Ullah
  • Syed Shahab Zarin
  • Mohsin Kamal
  • Babatunji Omoniwa
  • Abdul Mateen
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 773)

Abstract

In recent years, advanced technology is increasing rapidly, especially in the field of smart grids. A home energy management systems are implemented in homes for scheduling of power for cost minimization. In this paper, for management of home energy we propose a meta-heuristic technique which is hybrid of existing techniques enhanced differential evolution (EDE) and earthworm optimization algorithm (EWA) and it is named as earthworm EWA (EEDE). Simulations show that EWA performed better in term of reducing cost and EDE performed better in reducing peak to average ratio (PAR). However proposed scheme outperformed in terms of both cost and PAR. For evaluating the performance of proposed technique a home energy system proposed by us. In our work we are considering a single home, consists of many appliances. Appliances are categorized into two groups: Interruptible and un-interruptible. Simulations and results show that both algorithms performed well in terms of reducing costs and PAR. We also measured waiting time to find out user comfort and energy consumption.

Keywords

EDE algorithm EWA algorithm User comfort Hybrid meta-heuristic technique 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Nadeem Javaid
    • 1
  • Ihtisham Ullah
    • 1
  • Syed Shahab Zarin
    • 1
  • Mohsin Kamal
    • 1
  • Babatunji Omoniwa
    • 1
  • Abdul Mateen
    • 1
  1. 1.COMSATS Institute of Information TechnologyIslamabadPakistan

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