Nothing Special   »   [go: up one dir, main page]

Skip to main content

Pigeon Inspired Optimization and Enhanced Differential Evolution Using Time of Use Tariff in Smart Grid

  • Conference paper
  • First Online:
Advances in Intelligent Networking and Collaborative Systems (INCoS 2017)

Abstract

In this paper, a scheduler for Home Energy Management (HEM) is proposed using Pigeon Inspired Optimization (PIO) and Enhanced Differential Evolution (EDE). Performance of these two optimization algorithms is evaluated in this study. Performance is determined by the amount of energy consumed by the appliances in on-peak hours and off-peak hours. Time Of Use (TOU) tariff is used for bill calculation of the consumed energy. Evaluation is performed in terms of Peak to Average Ratio (PAR) and electricity cost. Simulation results show that PIO outperforms EDE in terms of cost, PAR reduction and waiting time.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

References

  1. 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 

  2. Rottondi, C., Barbato, A., Chen, L., Verticale, G.: Enabling privacy in a distributed game-theoretical scheduling system for domestic appliances. IEEE Trans. Smart Grid 8(3), 1220–1230 (2017)

    Article  Google Scholar 

  3. Alam, M.R., Reaz, M.B.I., Ali, M.A.M.: A review of smart homes past, present, and future. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 42(6), 1190–1203 (2012)

    Article  Google Scholar 

  4. Meng, F.-L., Zeng, X.-J.: An optimal real-time pricing algorithm for the smart grid: a bi-level programming approach. In: OASIcs-OpenAccess Series in Informatics, vol. 35. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik (2013)

    Google Scholar 

  5. Javaid, N., Javaid, S., Abdul, W., Ahmed, I., Almogren, A., Alamri, A., Niaz, I.A.: A hybrid genetic wind driven heuristic optimization algorithm for demand side management in smart grid. Energies 10(3), 319 (2017)

    Article  Google Scholar 

  6. Samadi, P., Wong, V.W.S.: Load scheduling and power trading in systems with high penetration of renewable energy resources. IEEE Trans. Smart Grid 7(4), 1802–1812 (2016)

    Article  Google Scholar 

  7. Liu, Y., Yuen, C., Rong, Y., Zhang, Y., Xie, S.: Queuing-based energy consumption management for heterogeneous residential demands in Smart Grid. IEEE Trans. Smart Grid 7(3), 1650–1659 (2016)

    Article  Google Scholar 

  8. Erol-Kantarci, M., Mouftah, H.T.: Energy-efficient information and communication infrastructures in the smart grid: a survey on interactions and open issues. IEEE Commun. Surv. Tutorials 17(1), 179–197 (2015)

    Article  Google Scholar 

  9. Khan, M.A., Javaid, N., Mahmood, A., Khan, Z.A., Alrajeh, N.: A generic demand side management model for Smart Grid. Int. J. Energy Res. 39(7), 954–964 (2015)

    Article  Google Scholar 

  10. Zhu, Z., et al.: An integer linear programming based optimization for home demand-side management in Smart Grid. In: 2012 IEEE PES Innovative Smart Grid Technologies (ISGT). IEEE (2012)

    Google Scholar 

  11. 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)

    Article  Google Scholar 

  12. Ma, K., Yao, T., Yang, J., Guan, X.: Residential power scheduling for demand response in Smart Grid. Int. J. Electr. Power Energy Syst. 78, 320–325 (2016)

    Article  Google Scholar 

  13. 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 

  14. Duan, H., Qiao, P.: Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning. Int. J. Intell. Comput. Cybern. 7(1), 24–37 (2014)

    Article  MathSciNet  Google Scholar 

  15. Zhang, B., Duan, H.: Predator-prey pigeon-inspired optimization for UAV three-dimensional path planning. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds.) ICSI 2014. LNCS, vol. 8795, pp. 96–105. Springer, Cham (2014). doi:10.1007/978-3-319-11897-0_12

    Google Scholar 

  16. Zafar, A., Shah, S., Khalid, R., Hussain, S.M., Rahim, H., Javaid, N.: A meta-heuristic home energy management system, January 2017

    Google Scholar 

  17. Safdarian, A., Fotuhi-Firuzabad, M., Lehtonen, M.: Optimal residential load management in smart grids: a decentralized framework. IEEE Trans. Smart Grid 7(4), 1836–1845 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nadeem Javaid .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Arshad, H., Batool, S., Amjad, Z., Ali, M., Aimal, S., Javaid, N. (2018). Pigeon Inspired Optimization and Enhanced Differential Evolution Using Time of Use Tariff in Smart Grid. In: Barolli, L., Woungang, I., Hussain, O. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-65636-6_51

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-65636-6_51

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65635-9

  • Online ISBN: 978-3-319-65636-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics