Skip to main content
SpringerLink
Log in

A Hybrid Genetic Based on Harmony Search Method to Schedule Electric Tasks in Smart Home

  • Conference paper
  • First Online:
Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 13))

  • 1350 Accesses

Abstract

In the residential area, high electricity demand of power-consuming household tasks has become a crucial issue. Thus, the key objectives of home energy management system (HEMS) are scheduling power-consuming household tasks to minimize electricity cost and maximize consumer’s comfort. The many utilities offer residential demand response (DR) program to shift residential customer electricity consumption during the peak time period to match demand and supply. In this paper, we propose optimal load scheduling algorithm a hybrid genetic based on harmony search (HGHS) for HEMS to schedule power-consuming household tasks. The new optimal load scheduling algorithm HGHS gives optimal solution to schedule power-consuming household tasks based on real time pricing (RTP) electricity tariff within electricity task time window during the day in order to minimize electricity cost, reduce peak-to-average ratio (PAR) and maximize user comfort. The proposed model implemented in a single smart home and simulation results of proposed HGHS algorithm are compared with genetic algorithm (GA) and harmony search algorithm (HAS) and it provides better results in reducing the daily electricity cost and PAR by reducing load at peak hours. Simulation results shown that the trade-off between electricity cost reduction and user comfort exist in two conflicting objectives.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Agarwal, S., Satyanarain, R., Sing, T.F., Vollmer, D.: Effects of construction activities on residential electricity consumption: Evidence from Singapore’s public housing estates. Energy Econ. 55, 101–111 (2016)

    Article  Google Scholar 

  2. Jalali, M.M., Kazemi, A.: Demand side management in a smart grid with multiple electricity suppliers. Energy 81, 766–776 (2015)

    Article  Google Scholar 

  3. Tascikaraoglu, A., Boynuegri, A.R., Uzunoglu, M.: A demand side management strategy based on forecasting of residential renewable sources: A smart home system in Turkey. Energy Build. 80, 309–320 (2014)

    Article  Google Scholar 

  4. Rahimi, F., Ipakchi, A.: Demand response as a market resource under the smart grid paradigm. IEEE Trans. Smart Grid 1(1), 82–88 (2010)

    Article  Google Scholar 

  5. Albadi, M.H., El-Saadany, E.F.: A summary of demand response in electricity markets. Electr. Power Syst. Res. 78(11), 1989–1996 (2008)

    Article  Google Scholar 

  6. Maharjan, S., Zhu, Q., Zhang, Y., Gjessing, S., Baar, T.: Demand response management in the smart grid in a large population regime. IEEE Trans. Smart Grid 7(1), 189–199 (2016)

    Article  Google Scholar 

  7. Zhao, Z., Lee, W.C., Shin, Y., Song, K.B.: An optimal power scheduling method for demand response in home energy management system. IEEE Trans. Smart Grid 4(3), 1391–1400 (2013)

    Article  Google Scholar 

  8. Roh, H.T., Lee, J.W.: Residential demand response scheduling with multiclass appliances in the smart grid. IEEE Trans. Smart Grid 7(1), 94–104 (2016)

    Article  Google Scholar 

  9. Rastegar, M., Fotuhi-Firuzabad, M., Zareipour, H.: Home energy management incorporating operational priority of appliances. Int. J. Electr. Power Energy Syst. 74, 286–292 (2016)

    Article  Google Scholar 

  10. Ahmed, M.S., Mohamed, A., Khatib, T., Shareef, H., Homod, R.Z., Ali, J.A.: Real time optimal schedule controller for home energy management system using new binary backtracking search algorithm. Energy Build. 138, 215–227 (2017)

    Article  Google Scholar 

  11. Basit, A., Sidhu, G.A.S., Mahmood, A., Gao, F.: Efficient and autonomous energy management techniques for the future smart homes. IEEE Trans. Smart Grid 8(2), 917–926 (2017)

    Google Scholar 

  12. Shirazi, E., Zakariazadeh, A., Jadid, S.: Optimal joint scheduling of electrical and thermal appliances in a smart home environment. Energy Convers. Manag. 106, 181–193 (2015)

    Article  Google Scholar 

  13. Anvari-Moghaddam, A., Monsef, H., Rahimi-Kian, A.: Cost-effective and comfort-aware residential energy management under different pricing schemes and weather conditions. Energy Build. 86, 782–793 (2015)

    Article  Google Scholar 

  14. Gudi, N., Wang, L., Devabhaktuni, V.: A demand side management based simulation platform incorporating heuristic optimization for management of household appliances. Int. J. Electr. Power Energy Syst. 43(1), 185–193 (2012)

    Article  Google Scholar 

  15. Arabali, A., Ghofrani, M., Etezadi-Amoli, M., Fadali, M.S., Baghzouz, Y.: Genetic-algorithm-based optimization approach for energy management. IEEE Trans. Power Delivery 28(1), 162–170 (2013)

    Article  Google Scholar 

  16. Zhang, D., Shah, N., Papageorgiou, L.G.: Efficient energy consumption and operation management in a smart building with microgrid. Energy Convers. Manag. 74, 209–222 (2013)

    Article  Google Scholar 

  17. Ma, J., Chen, H.H., Song, L., Li, Y.: Residential load scheduling in smart grid: A cost efficiency perspective. IEEE Trans. Smart Grid 7(2), 771–784 (2016)

    Google Scholar 

  18. Miao, H., Huang, X., Chen, G.: A genetic evolutionary task scheduling method for energy efficiency in smart homes. Int. Rev. Electr. Eng. (IREE) 7(5), 5897–5904 (2012)

    Google Scholar 

  19. Pipattanasomporn, M., Kuzlu, M., Rahman, S.: An algorithm for intelligent home energy management and demand response analysis. IEEE Trans. Smart Grid 3(4), 2166–2173 (2012)

    Article  Google Scholar 

  20. Logenthiran, T., Srinivasan, D., Shun, T.Z.: Demand side management in smart grid using heuristic optimization. IEEE Trans. Smart Grid 3(3), 1244–1252 (2012)

    Article  Google Scholar 

  21. Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation 76(2), 60–68 (2001)

    Article  Google Scholar 

  22. Abedini, M., Moradi, M.H., Hosseinian, S.M.: Optimal clustering of MGs based on droop controller for improving reliability using a hybrid of harmony search and genetic algorithms. ISA Trans. 61, 119–128 (2016)

    Article  Google Scholar 

  23. Rodriguez, F.J., Garcia-Martinez, C., Lozano, M.: Hybrid metaheuristics based on evolutionary algorithms and simulated annealing: taxonomy, comparison, and synergy test. IEEE Trans. Evol. Comput. 16(6), 787–800 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. COMSATS Institute of Information Technology, Islamabad, 44000, Pakistan

    Manzoor Ahmad, Asif Khan, Anila Yasmeen, Iqra Fatima, Saman Zahoor & Nadeem Javaid

  2. National University of Science and Technology, Islamabad, 44000, Pakistan

    Zunaira Nadeem

Authors
  1. Manzoor Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Asif Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zunaira Nadeem
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anila Yasmeen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Iqra Fatima
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Saman Zahoor
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nadeem Javaid
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nadeem Javaid .

Editor information

Editors and Affiliations

  1. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  2. Open University of Catalonia, Barcelona, Spain

    Santi Caballé

  3. Fukuoka Institute of Technology (FIT), Fukuoka, Japan

    Leonard Barolli

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ahmad, M. et al. (2018). A Hybrid Genetic Based on Harmony Search Method to Schedule Electric Tasks in Smart Home. In: Xhafa, F., Caballé, S., Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-69835-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-69835-9_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69834-2

  • Online ISBN: 978-3-319-69835-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation