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Swarm Intelligence Based Home Energy Management Controller Under Dynamic Pricing Scheme

  • Adnan Ahmed
  • Muhammad Hassan Rahim
  • Fozia Feroze
  • Ayesha Zafar
  • Itrat Fatima
  • Sheraz Aslam
  • Nadeem Javaid
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 12)

Abstract

Energy management controller (EMC) is widely adopted for residential load management in smart grid (SG). Its main focus is on minimizing cost with minimal consumer interaction. EMC effectiveness is improved in the context of demand response (DR) program. In the era of demand side management (DSM) EMC plays a significant role in residential energy management by curtailing the peak to average ratio (PAR) and electricity bill. In this research work, we are reducing the electricity cost and PAR by maximizing the user comfort. In our research work, we consider a smart home with three smart appliances and schedule these appliances energy consumption and user comfort by using heuristic techniques: binary particle swarm optimization (BPSO) and firefly algorithm (FA). Simulations are conducted by utilizing the day-ahead real time pricing (DA-RTP). Simulation results depict that firefly algorithm (FA) has better performance as compared to BPSO in term of minimizing cost and PAR, while also maximizing user satisfaction level. A trade-off analysis between user satisfaction and energy consumption cost is demonstrated in simulations.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Adnan Ahmed
    • 1
  • Muhammad Hassan Rahim
    • 1
  • Fozia Feroze
    • 1
  • Ayesha Zafar
    • 1
  • Itrat Fatima
    • 1
  • Sheraz Aslam
    • 1
  • Nadeem Javaid
    • 1
  1. 1.COMSATS Institute of Information TechnologyIslamabadPakistan

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