Skip to main content

Demand Side Management Using Harmony Search Algorithm and BAT Algorithm

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

Abstract

In this paper performance of Home Energy Management System (HEMS) is evaluated using two meta-heuristic techniques: Harmony Search Algorithm (HSA) and BAT Algorithm. Appliances are classified into three categories according to their characteristics. Critical peak pricing is used for electricity price calculation as electricity pricing scheme. The main purpose is electricity cost reduction, electricity consumption, peak to average ratio reduction and maximizing User Comfort (UC) by reducing waiting time. Simulation results show the overall effectiveness of HSA.

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. 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). http://ieeexplore.ieee.org/document/7120135/

    Article  Google Scholar 

  2. 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). http://ieeexplore.ieee.org/document/6525433/

    Article  Google Scholar 

  3. 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, January 2012. http://ieeexplore.ieee.org/document/6175785/

  4. Ma, X.G.K., Yao, T., Yang, J.: Residential Power Scheduling for Demand Response in Smart Grid. Elsevier (2015)

    Google Scholar 

  5. Javaid, N., Javaid, S., Abdul, W., Ahmed, I., Almogren, A., Alamri, A., Niaz, I.: A hybrid genetic wind driven heuristic optimization algorithm for demand side management in Smart Grid. Energies 10(3), 319 (2017). http://www.mdpi.com/1996-1073/10/3/319

    Article  Google Scholar 

  6. Iqbal, Z., Javaid, N., Khan, M.R., Ahmed, I., Khan, Z.A., Qasim, U.: Cost and load reduction using heuristic algorithms in Smart Grid. In: 2016 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA), pp. 24–30. IEEE, March 2016. http://ieeexplore.ieee.org/document/7471167/

  7. 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). http://www.sciencedirect.com/science/article/pii/S0378778816306867

    Article  Google Scholar 

  8. Gupta, I., Anandini, G., Gupta, M.: An hour wise device scheduling approach for demand side management in Smart Grid using particle swarm optimization. In: 2016 National Power Systems Conference (NPSC), pp. 1–6. IEEE, December 2016. http://ieeexplore.ieee.org/document/7858965/

  9. Diamantoulakis, P.D., Pappi, K.N., Kong, P.-Y., Karagiannidis, G.K.: Game theoretic approach to demand side management in Smart Grid with user-dependent acceptance prices. In: 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), pp. 1–5. IEEE, September 2016. http://ieeexplore.ieee.org/document/7881024/

  10. Ogwumike, C., Short, M., Denai, M.: Near-optimal scheduling of residential smart home appliances using heuristic approach. In: 2015 IEEE International Conference on Industrial Technology (ICIT), pp. 3128–3133. IEEE, March 2015. http://ieeexplore.ieee.org/document/7125560/

  11. Anvari-Moghaddam, A., Monsef, H., Rahimi-Kian, A.: Optimal smart home energy management considering energy saving, a comfortable lifestyle. In: 2016 IEEE Power, Energy Society General Meeting (PESGM), p. 1. IEEE, July 2016. http://ieeexplore.ieee.org/document/7741432/

  12. Graditi, G., Di Silvestre, M.L., Gallea, R., Sanseverino, E.R.: Heuristic-based shiftable loads optimal management in smart micro-grids. IEEE Trans. Industr. Inform. 11(1), 271–280 (2015). http://ieeexplore.ieee.org/document/6834796/

    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

Farooqi, M., Awais, M., Abdeen, Z.U., Batool, S., Amjad, Z., Javaid, N. (2018). Demand Side Management Using Harmony Search Algorithm and BAT 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_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-65636-6_17

  • 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