Skip to main content
SpringerLink
Log in

A Knapsack Problem Based Algorithm for Local Level Management in Smart Grid

  • Conference paper
  • First Online:
Advances in Internet, Data and Web Technologies (EIDWT 2020)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 47))

  • 896 Accesses

Abstract

The world is adapting the renewable energy sources to produce clean energy. Because of this modernization in production, storage and consumers of energy, the conventional grid systems are facing a lot problems e.g. effective control of consumers or recompense of supply instability. The smart grid has the ability to overpower these shortcomings. In this study, we are considering a model of smart grid which has three levels: transmission, micro-grid and local level. We have propose an algorithm for energy management at local level, based on renowned algorithms of scheduling. We model the problem into knapsack problem and then find an optimize solution set using our algorithm which partially based on least cost branch and bound algorithm. This algorithm controls adaptable and shift-able load of smart homes. This algorithm is able to normalize the peak demand and control the preference of home appliances, through distributing energy among appliances depending on their consumption and priority, without exceeding the already decided total energy.

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. Shum, C., et al.: Co-simulation of distributed smart grid software using direct-execution simulation. IEEE Access 6, 20531–20544 (2018)

    Article  Google Scholar 

  2. Technology in micro-grid control. Electron. Sci. Technol. Appl. 5(1) (2018)

    Google Scholar 

  3. Ahat, M., Amor, S., Bui, M., Bui, A., Guérard, G., Petermann, C.: Smart grid and optimization. Am. J. Oper. Res. 03(01), 196–206 (2013)

    Google Scholar 

  4. Liang, Y., He, L., Cao, X., Shen, Z.: Stochastic control for smart grid users with flexible demand. IEEE Trans. Smart Grid 4(4), 2296–2308 (2013)

    Article  Google Scholar 

  5. Parisio, A., Glielmo, L.: A mixed integer linear formulation for microgrid economic scheduling. In: 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm), Brussels, pp. 505–510 (2011)

    Google Scholar 

  6. Abdella, J., Shuaib, K.: Peer to peer distributed energy trading in smart grids: a survey. Energies 11(6), 1560 (2018)

    Article  Google Scholar 

  7. Panda, R., Tiwari, P.: Economic risk-based bidding strategy for profit maximisation of wind-integrated day-ahead and real-time double-auctioned competitive power markets. IET Gener. Transm. & Distrib. 13(2), 209–218 (2019)

    Article  Google Scholar 

  8. Noor, S., Guo, M., van Dam, K., Shah, N., Wang, X.: Energy demand side management with supply constraints: game theoretic approach. Energy Procedia 145, 368–373 (2018)

    Article  Google Scholar 

  9. Guérard, G., Amor, S., Bui, A.: Survey on smart grid modelling. Int. J. Syst. Control Commun. 4(4), 262 (2012)

    Article  Google Scholar 

  10. Yoldaş, Y., Önen, A., Muyeen, S., Vasilakos, A., Alan, I.: Enhancing smart grid with microgrids: challenges and opportunities. Renew. Sustain. Energy Rev. 72, 205–214 (2017)

    Article  Google Scholar 

  11. Colak, I., Kabalci, E., Fulli, G., Lazarou, S.: A survey on the contributions of power electronics to smart grid systems. Renew. Sustain. Energy Rev. 47, 562–579 (2015)

    Article  Google Scholar 

  12. Wright, A., Firth, S.: The nature of domestic electricity-loads and effects of time averaging on statistics and on-site generation calculations. Appl. Energy 84(4), 389–403 (2007)

    Article  Google Scholar 

  13. Ali, U., Arif, K.S., Qamar, U.: A hybrid scheme for feature selection of high dimensional educational data. In: 2019 International Conference on Communication Technologies (ComTech), Rawalpindi, Pakistan, pp. 71–75 (2019)

    Google Scholar 

  14. Dantzig, G.B.: Discrete-variable extremum problems. Oper. Res. 5, 266–288 (1956). Rand Corporation, Santa Monica, California

    Article  MathSciNet  Google Scholar 

  15. Horowitz, E., Sahni, S.: Computing partitions with applications to the knapsack problem. J. ACM 21(2), 277–292 (1974)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National University of Sciences and Technology (NUST), H-12, Islamabad, Pakistan

    Usman Ali, Usman Qamar, Kanwal Wahab & Khawaja Sarmad Arif

Authors
  1. Usman Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Usman Qamar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kanwal Wahab
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Khawaja Sarmad Arif
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Usman Qamar .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Innovation Center for Educational Resources, University Library, Kyushu University, Fukuoka, Japan

    Yoshihiro Okada

  3. Department of Electrical Engineering and Information Technology, University of Naples "Frederico II", Naples, Italy

    Flora Amato

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ali, U., Qamar, U., Wahab, K., Arif, K.S. (2020). A Knapsack Problem Based Algorithm for Local Level Management in Smart Grid. In: Barolli, L., Okada, Y., Amato, F. (eds) Advances in Internet, Data and Web Technologies. EIDWT 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-030-39746-3_32

Download citation

Publish with us

Policies and ethics

Search

Navigation