[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

Multi-objective power scheduling problem in smart homes using grey wolf optimiser

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

In this paper, the multi-objective grey wolf optimiser is utilised for the power scheduling problem (PSP). The grey wolf optimiser (GWO) is a recent swarm-based optimisation algorithm tailored for various optimisation problems. PSP is addressed by scheduling home appliances to a certain time horizon to minimise the electricity bill and peak-to-average ratio (PAR) and increase the comfort level of users. The multi-objective function is formalised and utilised in GWO to obtain an optimal schedule. Seven consumption profiles and seven real-time electricity prices with various characteristics are considered to evaluate the proposed multi-objective GWO. The performance of the proposed algorithm is tested against three factors, namely, electricity bill, PAR and user comfort level. The obtained schedule shows that all evaluation factors are optimally timetabled. For a comparative evaluation, the proposed method is firstly compared with the genetic algorithm. The proposed method exhibits and yield better performance than GA under the same consumption profiles. Secondly, the proposed method is compared with 19 state-of-the-art methods by using the recommended consumption profiles of these methods and their evaluation criteria. The proposed method nearly outperforms the compared methods in terms of minimisation of electricity bill and PAR. User comfort level is a criterion proposed in this study and has not been considered previously. It exerts a significant impact on the final schedule.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Ali W, Rehman AU, Junaid M, Shaukat SAA, Faiz Z, Javaid N (2017) Home energy management using social spider and bacterial foraging algorithm. In: International conference on network-based information systems. Springer, pp 245–256

  • Aman S, Simmhan Y, Prasanna VK (2013) Energy management systems: state of the art and emerging trends. IEEE Commun Mag 51(1):114–119

    Article  Google Scholar 

  • Asif S, Ambreen K, Iftikhar H, Khan H. N, Maroof R, Javaid N (2017) Energy management in residential area using genetic and strawberry algorithm. In: International conference on network-based information systems. Springer, pp 165–176

  • Azevedo JPC (2013) Effective scheduling of energy consumption in smart grids. FEUP—Dissertação

  • Batool S, Khalid A, Amjad Z, Arshad H, Aimal S, Farooqi M, Javaid N (2017) Pigeon inspired optimization and bacterial foraging optimization for home energy management. In: International conference on broadband and wireless computing, communication and applications. Springer, pp 14–24

  • BCU Commission (2017) Bcuc issues report to bc government on residential inclining block rates. http://www.bcuc.com/Documents/Proceedings/2017/DOC_49001_03-28-2017_BCUC-RIB-Rate-Report.pdf

  • CE Company (2017) Real-time pricing for residential customers. Retrieved from https://hourlypricing.comed.com/live-prices/

  • Faiz Z, Bilal T, Awais M, Gull S, Javaid N, et al., (2017) Demand side management using chicken swarm optimization, in: International conference on intelligent networking and collaborative systems. Springer, pp 155–165

  • Gao C, Chen S, Li X, Huang J, Zhang Z (2017) A physarum-inspired optimization algorithm for load-shedding problem. Appl Soft Comput 61:239–255

    Article  Google Scholar 

  • Gelazanskas L, Gamage KA (2014) Demand side management in smart grid: a review and proposals for future direction. Sustain Cities Soc 11:22–30

    Article  Google Scholar 

  • Gellings CW (1985) The concept of demand-side management for electric utilities. Proc IEEE 73(10):1468–1470

    Article  Google Scholar 

  • Hafeez G, Javaid N, Iqbal S, Khan FA (2018) Optimal residential load scheduling under utility and rooftop photovoltaic units. Energies 11(3):611

    Article  Google Scholar 

  • Iftikhar H, Asif S, Maroof R, Ambreen K, Khan H. N, Javaid N (2017) Biogeography based optimization for home energy management in smart grid. In: International conference on network-based information systems. Springer, pp 177–190

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

    Article  Google Scholar 

  • Khan MA, Javaid N, Mahmood A, Khan ZA, Alrajeh N (2015) A generic demand-side management model for smart grid. Int J Energy Res 39(7):954–964

    Article  Google Scholar 

  • Logenthiran T, Srinivasan D, Shun TZ (2012) Demand side management in smart grid using heuristic optimization. IEEE Trans Smart Grid 3(3):1244–1252

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Mechanics C (2014) Heating and air conditioning blog. Retrieved from http://www.climatemechanics.com/how-long-will-it-take-for-my-water-heater-to-heat-up/

  • Miao H, Huang X, Chen G (2012) A genetic evolutionary task scheduling method for energy efficiency in smart homes. Int Rev Electri Eng (IREE) 7(5):5897–5904

    Google Scholar 

  • Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61

    Article  Google Scholar 

  • Mohsenian-Rad A-H, Wong VW, Jatskevich J, Schober R (2010) Optimal and autonomous incentive-based energy consumption scheduling algorithm for smart grid. In: Innovative smart grid technologies (ISGT), 2010. IEEE, pp 1–6

  • Mohsenian-Rad A-H, Wong VW, Jatskevich J, Schober R, Leon-Garcia A (2010) Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Trans Smart Grid 1(3):320–331

    Article  Google Scholar 

  • Muralitharan K, Sakthivel R, Shi Y (2016) Multiobjective optimization technique for demand side management with load balancing approach in smart grid. Neurocomputing 177:110–119

    Article  Google Scholar 

  • Peretto L (2010) The role of measurements in the smart grid era. IEEE Instrum Meas Mag 13(3):22–25

    Article  Google Scholar 

  • Pipattanasomporn M, Kuzlu M, Rahman S (2012) An algorithm for intelligent home energy management and demand response analysis. IEEE Trans Smart Grid 3(4):2166–2173

    Article  Google Scholar 

  • Qayyum F, Naeem M, Khwaja AS, Anpalagan A, Guan L, Venkatesh B (2015) Appliance scheduling optimization in smart home networks. IEEE Access 3:2176–2190

    Article  Google Scholar 

  • Rahim MH, Khalid A, Javaid N, Alhussein M, Aurangzeb K, Khan ZA (2018) Energy efficient smart buildings using coordination among appliances generating large data. IEEE Access

  • Rahim S, Javaid N, Ahmad A, Khan SA, Khan ZA, Alrajeh N, Qasim U (2016) Exploiting heuristic algorithms to efficiently utilize energy management controllers with renewable energy sources. Energy Build 129:452–470

    Article  Google Scholar 

  • Rasheed MB, Javaid N, Ahmad A, Khan ZA, Qasim U, Alrajeh N (2015) An efficient power scheduling scheme for residential load management in smart homes. Appl Sci 5(4):1134–1163

    Article  Google Scholar 

  • Rehman A. U, Aslam S, Abideen Z. U, Zahra A, Ali W, Junaid M, Javaid J (2017) Efficient energy management system using firefly and harmony search algorithm. In: International conference on broadband and wireless computing, communication and applications. Springer, pp 37–49

  • Sales G (2017) Home appliances power consumption. Retrieved from http://www.centralmainediesel.com/wattage-calculator.asp

  • Samadi P, Mohsenian-Rad H, Schober R, Wong VW (2012) Advanced demand side management for the future smart grid using mechanism design. IEEE Trans Smart Grid 3(3):1170–1180

    Article  Google Scholar 

  • Space B (2017) Home dehumidifiers. Retrieved from https://www.breathingspace.co.uk/dehumidifier-frequently-asked-questions-i62

  • Yearbook GES (2017) Statistical analysis for global energy. Retrieved from https://yearbook.enerdata.net/#energy-intensity-GDP-by-region.html

  • Yi W, Dong W (2015) Modeling and simulation of discharging characteristics of external melt ice-on coil storage system. Int J Smart Home 9(2):179–192

    Article  Google Scholar 

  • Zhao Z, Lee WC, Shin Y, Song K-B (2013) An optimal power scheduling method for demand response in home energy management system. IEEE Trans Smart Grid 4(3):1391–1400

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Sciences, Universiti Sains Malaysia, 11800, Gelugor, Penang, Malaysia

    Sharif Naser Makhadmeh, Ahamad Tajudin Khader & Syibrah Naim

  2. Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, Irbid, Jordan

    Mohammed Azmi Al-Betar

Authors
  1. Sharif Naser Makhadmeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ahamad Tajudin Khader
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohammed Azmi Al-Betar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Syibrah Naim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sharif Naser Makhadmeh.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Makhadmeh, S.N., Khader, A.T., Al-Betar, M.A. et al. Multi-objective power scheduling problem in smart homes using grey wolf optimiser. J Ambient Intell Human Comput 10, 3643–3667 (2019). https://doi.org/10.1007/s12652-018-1085-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-018-1085-8

Keywords

Search

Navigation