Skip to main content

Demand Side Management Scheduling of Appliances Using Meta Heuristic Algorithms

  • Conference paper
  • First Online:
  • 1129 Accesses

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 25))

Abstract

Energy is the most needed commodity of the current era. Recently, the demand of energy is far higher than the available energy. By the incorporation of Demand Side Management (DSM) with the Smart Grid (SG) results in the solution of this problem. Different techniques are utilized in SG to minimize the electricity cost and manage load in industrial, residential areas, and commercial to minimize the Peak to Average Ratio (PAR) and decrease in the waiting time of appliances which leads to maximize user comfort. In this article, we propose six Meta heuristic techniques in Home Energy Management System (HEMS); Firefly Algorithm (FA), Bacterial foraging Algorithm (BFA), Earth Worm Optimization Algorithm (EWA), Genetic Algorithm (GA), Hybrid of Genetic and Bacterial foraging (HBG), and Harmony Search Algorithm (HSA). We have achieved minimization in PAR, electric cost, upturn user comfort through appliances scheduling using the optimization techniques.

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

Buying options

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

Learn about institutional subscriptions

References

  1. Zhu, Z., Tang, J., Lambotharan, S., Chin, W.H., Fan, Z.: An integer linear programming based optimization for home demand-side management in smart grid. In: 2012 IEEE PES Innovative Smart Grid Technologies (ISGT), pp. 1–5. IEEE (2012)

    Google Scholar 

  2. Samadi, P., Wong, V.W.S., Schober, R.: 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 

  3. 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 

  4. 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 

  5. Rahim, S., et al.: Exploiting heuristic algorithms to efficiently utilize energy management controllers with renewable energy sources. Energy Build. 129, 452–470 (2016)

    Article  Google Scholar 

  6. Ullah, I., Javaid, N., Khan, Z.A., Qasim, U., Khan, Z.A., Mehmood, S.A.: An incentive-based optimal energy consumption scheduling algorithm for residential user. Procedia Comput. Sci. 52, 851–857 (2015)

    Article  Google Scholar 

  7. 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 

  8. Ahmad, A., Alrajeh, N., Javaid, N., Khan, Z.A., Qasim, U., Rasheed, M.B.: An efficient power scheduling scheme for residential load management in smart homes (2015)

    Google Scholar 

  9. Razzaq, S., Zafar, R., Khan, N.A., Butt, A.R., Mahmood, A.: A novel prosumer-based energy sharing and management (PESM) approach for cooperative demand side management (DSM) in smart grid. Appl. Sci. 6, 275 (2016)

    Article  Google Scholar 

  10. 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 

  11. Wang, G.-G., Deb, S., Coelho, L.D.S.: Earthworm optimization algorithm: a bio-inspired metaheuristic algorithm for global optimization problems. Int. J. Bio-Inspired Comput. 33, 477–496 (2015)

    Google Scholar 

  12. Energy Information Administration, December 2015. https://www.eia.gov/todayinenergy/detail.cfm?id=12251

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

    Article  Google Scholar 

  14. Palensky, P., Dietrich, D.: Demand side management: demand response intelligent energy systems and smart loads. IEEE Trans. Ind. Inform. 7(3), 381–388 (2011)

    Article  Google Scholar 

  15. Gellings, C.W., Chamberlin, J.H.: Demand-side management, pp. 1–5. EPRI, Palo Alto (1988)

    Google Scholar 

  16. Ayub, N., et al.: An efficient scheduling of power and appliances using metaheuristic optimization technique. In: International Conference on Intelligent Networking and Collaborative Systems. Springer, Cham (2017)

    Google Scholar 

  17. Ishaq, A., et al.: An efficient scheduling using meta heuristic algorithms for home demand-side management in smart grid. In: International Conference on Intelligent Networking and Collaborative Systems. Springer, Cham (2017)

    Google Scholar 

  18. Zahoor, S.: Cloud-fog-based smart grid model for efficient resource management. Sustainability (2071-1050) 10(6), 2079 (2018)

    Article  Google Scholar 

  19. Rasheed, M.B., et al.: Real time information based energy management using customer preferences and dynamic pricing in smart homes. Energies 9(7), 542 (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

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ayub, N., Javaid, N., Abbas, A., Ishaq, A., Yousaf, A., Ishtiaq, M.A. (2019). Demand Side Management Scheduling of Appliances Using Meta Heuristic Algorithms. In: Barolli, L., Leu, FY., Enokido, T., Chen, HC. (eds) Advances on Broadband and Wireless Computing, Communication and Applications. BWCCA 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-02613-4_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-02613-4_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02612-7

  • Online ISBN: 978-3-030-02613-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics