Skip to main content
SpringerLink
Log in

Energy Optimization in Home Energy Management System Using Artificial Fish Swarm Algorithm and Genetic Algorithm

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

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 8))

Abstract

In this paper, we have evaluated the performance of heuristic algorithms: Genetic Algorithm (GA) and Artificial Fish Swarm Algorithm (AFSA) for Demand Side Management. Our prime focus in this paper, is to optimally schedule appliances in a smart home in such a way that the Peak to Average Ratio (PAR) and the electricity cost can be reduced. The pricing scheme used in this paper is real time pricing. Our Simulation results validate that the two nature inspired schemes successfully reduce PAR and electricity cost by transferring load of on peak hours to off peak hours. Our results also depict a trade off between electricity cost and comfort of a user.

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. 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: Innovative Smart Grid Technologies (ISGT), 2012 IEEE PES, pp. 1–5. IEEE (2012)

    Google Scholar 

  2. 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 

  3. 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 

  4. 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 

  5. 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 

  6. 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 

  7. Huang, Y., Mao, S., Nelms, R.M.: Smooth scheduling for electricity distribution in the smart grid. IEEE Trans. Smart Grid

    Google Scholar 

  8. Tushar, W., Chai, B., Yuen, C., Smith, D.B., Wood, K.L., Yang, Z., Poor, H.V.: Three-party energy management with distributed energy resources in smart grid. IEEE Trans. Ind. Electron. 62(4), 2487–2498 (2015)

    Article  Google Scholar 

  9. Samadi, P., Wong, V.W., 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 

  10. Anvari-Moghaddam, A., Monsef, H., Rahimi-Kian, A.: Optimal smart home energy management considering energy saving and a comfortable lifestyle. IEEE Trans. Smart Grid 6(1), 324–332 (2015)

    Article  Google Scholar 

  11. Ma, J., Chen, H.H., Song, L., Li, Y.: Residential load scheduling in smart grid: a cost efficiency 483 perspective. IEEE Trans. Smart Grid 7(2), 771–784 (2016)

    Google Scholar 

  12. Jiang, B., Fei, Y.: Smart home in smart microgrid: a cost-effective energy ecosystem with intelligent hierarchical agents. IEEE Trans. Smart Grid 6(1), 3–13 (2015)

    Article  Google Scholar 

  13. Wikipedia: Energy Shortfall in India. https://en.wikipedia.org/wiki/Electricity_sector_in_India. Accessed May 2017

  14. Wikipedia: Energy Shortfall in Pakistan. https://en.wikipedia.org/wiki/Electricity_sector_in_Pakistan. Accessed May 2017

  15. Wikipedia: Energy Shortfall in Pakistan. https://en.wikipedia.org/wiki/Electricity_sector_in_Bangladesh. Accessed May 2017

Download references

Author information

Authors and Affiliations

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

    Muhammad Talha, Muhammad Shahid Saeed, Ghulam Mohiuddin, Musa Ahmad, Muhammad Junaid Nazar & Nadeem Javaid

Authors
  1. Muhammad Talha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Muhammad Shahid Saeed
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ghulam Mohiuddin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Musa Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Muhammad Junaid Nazar
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. 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. Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Computer Science, Ryerson University, Toronto, Ontario, Canada

    Isaac Woungang

  3. School of Business, UNSW Australia, Canberra, Aust Capital Terr, Australia

    Omar Khadeer Hussain

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Talha, M., Saeed, M.S., Mohiuddin, G., Ahmad, M., Nazar, M.J., Javaid, N. (2018). Energy Optimization in Home Energy Management System Using Artificial Fish Swarm Algorithm and Genetic Algorithm. 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_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-65636-6_18

  • 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

Search

Navigation