Skip to main content

A Social Spider Optimization Based Home Energy Management System

  • Conference paper
  • First Online:
Advances in Network-Based Information Systems (NBiS 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 7))

Included in the following conference series:

  • 1510 Accesses

Abstract

Home energy management within the traditional grid is difficult, so Smart Grid (SG) is introduced by upgrading the traditional grid, i.e., adding the Information Technology (IT) and Sensors Network (SN) to traditional grids. SG manages the Demand of electricity and help in solving the electricity load management problem. Demand Side response has two parts monitoring the electricity and notify consumers about its pricing scheme and bill, this can be done using smart meters. In smart metering system homes are integrated with Energy Management Controller (EMC) which uses Demand Side Management (DSM) systems based on a optimization technique. In this paper a system is proposed which manages the load by shifting from peak hours to off peak hours, reduce electricity bill, reduce waiting time and reduce Peak to Average Ratio (PAR). For simulations we use classification consist of 3 classes of appliances, Time of Use (ToU) as our pricing signal and Social Spider Optimization (SSO) our technique. The simulations results show the achievements of the system.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
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. In, B.S.: Smart-Grid Security Issues, 8185, February 2010

    Google Scholar 

  2. Kopka, H., Daly, P.W.: A Guide to LATEX, 3rd edn. Addison-Wesley, Harlow (1999)

    Google Scholar 

  3. 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 

  4. Khoury, J., Mbayedb, R., Salloumb, G., Monmasson, E.: Predictive demand side management of a residential house under intermittent primary energy source conditions. Energy Build. 112, 110–120 (2015)

    Article  Google Scholar 

  5. Zhu, Z., Tang, J., Lambotharan, S., Chin, W.H., Fan, Z.: A n integer linear programming based optimization for home demand-side management in smart grid. In: 2012 IEEE PES, Innovative Smart Grid Technologies (ISGT), p. 15. IEEE (2012)

    Google Scholar 

  6. 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 

  7. Huang, Y., Wang, L., Guo, W., Kang, Q., Wu, Q.: Chance Constrained Optimization in a Home Energy Management System

    Google Scholar 

  8. Aghajani, G.R., Shayanfar, H.A., Shayeghi, H.: Demand side management in a smart micro-grid in the presence of renewable generation and demand response. Energy 126, 622–637 (2017)

    Article  Google Scholar 

  9. 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 

  10. 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 103, 319 (2017)

    Article  Google Scholar 

  11. Zhao, Z., Lee, W.C., Shin, Y., Song, K.B.: An optimal power scheduling method for demand response in home energy management system (2013)

    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

Ur Rehman, M., Bilal, T., Awais, M., Junaid, M., Zahra, A., Javaid, N. (2018). A Social Spider Optimization Based Home Energy Management System. In: Barolli, L., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-65521-5_69

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-65521-5_69

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65520-8

  • Online ISBN: 978-3-319-65521-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics