Advertisement

Efficient Utilization of HEM Controller Using Heuristic Optimization Techniques

  • Asif Khan
  • Nadeem Javaid
  • Adnan Ahmed
  • Saqib Kazmi
  • Hafiz Majid Hussain
  • Zahoor Ali Khan
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 6)

Abstract

The performance and comparative analysis of home energy management controller using three optimization techniques; genetic algorithm (GA), enhanced differential evolution (EDE) and optimal stopping rule (OSR) has been evaluated in this paper. In this regard, a generic system model consisting of home area network, advanced metering infrastructure, home energy management controller, and smart appliances has been proposed. Price threshold policy and priority of appliance have also been considered to depict monthly and yearly average electricity bill savings and appliance delay using day-ahead real-time pricing (DA-RTP). Simulation results validate that all our proposed schemes successfully shifts the appliance operations to off-peak times and results in reduced electricity bill with reasonable waiting time.

Keywords

Genetic Algorithm Smart Grid Demand Response Demand Side Management Electricity Bill 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Tuballa, M.L., Abundo, M.L.: A review of the development of smart grid technologies. Renew. Sustain. Energy Rev. 59, 710–725 (2016)CrossRefGoogle Scholar
  2. 2.
    Vardakas, J.S., Zorba, N., Verikoukis, C.V.: A survey on demand response programs in smart grids: pricing methods and optimization algorithms. IEEE Commun. Surv. Tutorials 17(1), 152–178 (2015)CrossRefGoogle Scholar
  3. 3.
    Hossain, M.S., Madlool, N.A., Rahim, N.A., Selvaraj, J., Pandey, A.K., Khan, A.F.: Role of smart grid in renewable energy: an overview. Renew. Sustain. Energy Rev. 60, 1168–1184 (2016)CrossRefGoogle Scholar
  4. 4.
    Vardakas, J.S., Zorba, N., Verikoukis, C.V.: Performance evaluation of power demand scheduling scenarios in a smart grid environment. Appl. Energy 142, 164–178 (2015)CrossRefGoogle Scholar
  5. 5.
    Moon, S., Lee, J.-W.: Multi-Residential Demand Response Scheduling with Multi-Class Appliances in Smart Grid. IEEE Trans. Smart Grid (2016)Google Scholar
  6. 6.
    Rahim, S., Javaid, N., Ahmad, A., Khan, S.A., Khan, Z.A., Alrajeh, N., Qasim, U.: Exploiting heuristic algorithms to efficiently utilize energy management controllers with renewable energy sources. Energy Build. 129, 452–470 (2016)CrossRefGoogle Scholar
  7. 7.
    Yi, P., Dong, X., Iwayemi, A., Zhou, C., Li, S.: Real-time opportunistic scheduling for residential demand response. IEEE Trans. Smart Grid 4(1), 227–234 (2013)CrossRefGoogle Scholar
  8. 8.
    Rasheed, M.B., Javaid, N., Ahmad, A., Awais, M., Khan, Z.A., Qasim, U., Alrajeh, N.: Priority and delay constrained demand side management in real time price environment with renewable energy source. Int. J. Energy Res. 40(14), 2002–2021 (2016)CrossRefGoogle Scholar
  9. 9.
    Shirazi, E., Jadid, S.: Optimal residential appliance scheduling under dynamic pricing scheme via HEMDAS. Energy Build. 93, 40–49 (2015)CrossRefGoogle Scholar
  10. 10.
    Storn, R., Price, K.: Differential evolution a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11(4), 341–359 (1997)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Arafa, M., Sallam, E.A., Fahmy, M.M.: An enhanced differential evolution optimization algorithm. In: 2014 Fourth International Conference on Digital Information and Communication Technology and Its Applications (DICTAP), Bangkok, pp. 216–225 (2014). doi: 10.1109/DICTAP.2014.6821685
  12. 12.
    Iwayemi, A., Yi, P., Dong, X., Zhou, C.: Knowing when to act: an optimal stopping method for smart grid demand response. IEEE Netw. 25(5), 44–49 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Asif Khan
    • 1
  • Nadeem Javaid
    • 1
  • Adnan Ahmed
    • 1
  • Saqib Kazmi
    • 1
  • Hafiz Majid Hussain
    • 2
  • Zahoor Ali Khan
    • 3
  1. 1.COMSATS Institute of Information TechnologyIslamabadPakistan
  2. 2.Center for Advanced Studies in Engineering (CASE)IslamabadPakistan
  3. 3.Higher Colleges of TechnologyFujairahUAE

Personalised recommendations