Advertisement

Short Term Load Forcasting Using Heuristic Algorithm and Support Vector Machine

  • Orooj Nazeer
  • Nadeem Javaid
  • Abdul Basit Majeed Khan
  • Arif Hussain
  • Tariq Basheer
  • Muhammad Mukhtar Ahmed Ratyal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 772)

Abstract

Analysis of data is very important for accurate prediction. Particle Swarm Optimization (PSO) and Support Vector Machine (SVM) is used for load forcasting. Features are selected using PSO and redundant features are removed. Data is divided into training and testing data. Load forecasting is done by using SVM classifier. However, SVM classifier predicts short term load accurately and efficiently. Multiple time testing is done on data for checking accuracy of PSO. SVM shows efficient performance as compared to Principle Component Analysis (PCA).

References

  1. 1.
    Haupt, S.E., Kosovi, B.: Variable generation power forecasting as a big data problem. IEEE Trans. Sustain. Energy 8(2), 725–732 (2017)CrossRefGoogle Scholar
  2. 2.
    Wang, K., Wang, Y., Xiaoxuan, H., Sun, Y., Deng, D.-J., Vinel, A., Zhang, Y.: Wireless big data computing in smart grid. IEEE Wirel. Commun. 24(2), 58–64 (2017)CrossRefGoogle Scholar
  3. 3.
    Jain, K., Purohit, A.: Feature selection using modified particle swarm optimization. Int. J. Comput. Appl. 161(7) (2017)CrossRefGoogle Scholar
  4. 4.
    Jain, I., Jain, V.K., Jain, R.: Correlation feature selection based improved-Binary Particle Swarm Optimization for gene selection and cancer classification. Appl. Soft Comput. 62, 203–215 (2018)CrossRefGoogle Scholar
  5. 5.
    Moradi, P., Gholampour, M.: A hybrid particle swarm optimization for feature subset selection by integrating a novel local search strategy. Appl. Soft Comput. 43, 117–130 (2016)CrossRefGoogle Scholar
  6. 6.
    Bazi, Y., Melgani, F.: Semisupervised PSO-SVM regression for biophysical parameter estimation. IEEE Trans. Geosci. Remote Sens. 45(6), 1887–1895 (2007)CrossRefGoogle Scholar
  7. 7.
    Fan, S., Chen, L.: Short-term load forecasting based on an adaptive hybrid method. IEEE Trans. Power Syst. 21(1), 392–401 (2006)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Cao, L.-J., Tay, F.E.H.: Support vector machine with adaptive parameters in financial time series forecasting. IEEE Trans. Neural Netw. 14(6), 1506–1518 (2003)CrossRefGoogle Scholar
  9. 9.
    Ahmad, A.S., Hassan, M.Y., Abdullah, M.P., Rahman, H.A., Hussin, F., Abdullah, H., Saidur, R.: A review on applications of ANN and SVM for building electrical energy consumption forecasting. Renew. Sustain. Energy Rev. 33, 102–109 (2014)CrossRefGoogle Scholar
  10. 10.
    Barbu, A., She, Y., Ding, L., Gramajo, G.: Feature selection with annealing for computer vision and big data learning. IEEE Trans. Pattern Anal. Mach. Intell. 39(2), 272–286 (2017)CrossRefGoogle Scholar
  11. 11.
    Zhou, K., Chao, F., Yang, S.: Big data driven smart energy management: from big data to big insights. Renew. Sustain. Energy Rev. 56, 215–225 (2016)CrossRefGoogle Scholar
  12. 12.
    Xu, X., He, X., Ai, Q., Qiu, R.C.: A correlation analysis method for power systems based on random matrix theory. IEEE Trans. Smart Grid 8(4), 1811–1820 (2017)CrossRefGoogle Scholar
  13. 13.
    Guo, X., Li, D.C., Zhang, A.: Improved support vector machine oil price forecast model based on genetic algorithm optimization parameters. Aasri Procedia 1, 525–530 (2012)CrossRefGoogle Scholar
  14. 14.
    Zhu, B., Ye, S., Wang, P., He, K., Zhang, T., Wei, Y.-M.: A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting. Energy Economics 70, 143–157 (2018)CrossRefGoogle Scholar
  15. 15.
    Wang, Y., Chen, Q., Sun, M., Kang, C., Xia, Q.: An ensemble forecasting method for the aggregated load with sub profiles. IEEE Trans. Smart Grid (2018)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Orooj Nazeer
    • 1
  • Nadeem Javaid
    • 2
  • Abdul Basit Majeed Khan
    • 1
  • Arif Hussain
    • 3
  • Tariq Basheer
    • 4
  • Muhammad Mukhtar Ahmed Ratyal
    • 5
  1. 1.Abasyn University Department of Computing and TechnologyIslamabadPakistan
  2. 2.COMSATS Institute of Information TechnologyIslamabadPakistan
  3. 3.Islamic International UniversityIslamabadPakistan
  4. 4.The University of Lahore, Gujrat CampusGujranwalaPakistan
  5. 5.Mirpur University of Science and TechnologyAzad KashmirPakistan

Personalised recommendations