Peak load forecasting on national holiday using fuzzy-cuckoo for Jawa-Bali system in Indonesia

  • Authors

    • Andi Imran Department of Electrical Engineering, Institut Teknologi Sepuluh November, Indonesia
    • I Made Yulistya Negara Department of Electrical Engineering, Institut Teknologi Sepuluh November, Indonesia
    • Imam Robandi Department of Electrical Engineering, Institut Teknologi Sepuluh November, Indonesia
    2019-04-07
    https://doi.org/10.14419/ijet.v7i4.19013
  • Peak Load Forecasting, National Holiday, Fuzzy Logic Type-2, Cuckoo Search Algorithm, MAPE.

  • Abstract

    This paper discusses the peak load forecasting on national holiday. The forecasting is done by using Fuzzy Logic System Type 2 method, optimized with Cuckoo Search Algorithm (CSA). Cuckoo Search Algorithm is used to optimize Footprint of Uncertainty (FOU) on fuzzy logic which consisting of antecedent (X, Y) and consequent (Z). This method uses data from daily peak load during the holidays on the Jawa-Bali electricity system. The data is focused on load data from four days before holidays (h-4) and on holidays (h). Validation results indicate that the Fuzzy Logic System Type-2 method which is optimized with Cuckoo Search Algorithm provides a good enough forecasting with Mean Absolute Percentage Error (MAPE) is less than 2%.

     

     


  • References

    1. [1] V. Hinojosa and A. Hoese, "Short-Term Load Forecasting Using Fuzzy Inductive Reasoning and Evolutionary Algorithms," IEEE TRANSACTIONS ON POWER SYSTEMS, vol. 25, p. 565, 2010. https://doi.org/10.1109/TPWRS.2009.2036821.

      [2] M. Cho, J. Hwang, and C. Chen, "Customer short term load forecasting by using ARIMA transfer function model," in Energy Management and Power Delivery, 1995. Proceedings of EMPD'95., 1995 International Conference on, 1995, pp. 317-322. https://doi.org/10.1109/EMPD.1995.500746.

      [3] R. Weron, Modeling and forecasting electricity loads and prices: A statistical approach vol. 403: John Wiley & Sons, 2007.

      [4] K.-H. Kim, H.-S. Youn, and Y.-C. Kang, "Short-term load forecasting for special days in anomalous load conditions using neural networks and fuzzy inference method," IEEE Transactions on Power Systems, vol. 15, pp. 559-565, 2000. https://doi.org/10.1109/59.867141.

      [5] Y.-M. Wi, S.-K. Joo, and K.-B. Song, "Holiday load forecasting using fuzzy polynomial regression with weather feature selection and adjustment," IEEE Transactions on Power Systems, vol. 27, pp. 596-603, 2012. https://doi.org/10.1109/TPWRS.2011.2174659.

      [6] A. Y. Saber and A. R. Alam, "Short term load forecasting using multiple linear regression for big data," in Computational Intelligence (SSCI), 2017 IEEE Symposium Series on, 2017, pp. 1-6. https://doi.org/10.1109/SSCI.2017.8285261.

      [7] V. Mayrink and H. S. Hippert, "A hybrid method using Exponential Smoothing and Gradient Boosting for electrical short-term load forecasting," in Computational Intelligence (LA-CCI), 2016 IEEE Latin American Conference on, 2016, pp. 1-6. https://doi.org/10.1109/LA-CCI.2016.7885697.

      [8] P. S. Paretkar, L. Mili, V. Centeno, K. Jin, and C. Miller, "Short-term forecasting of power flows over major transmission interties: Using Box and Jenkins ARIMA methodology," in Power and Energy Society General Meeting, 2010 IEEE, 2010, pp. 1-8. https://doi.org/10.1109/PES.2010.5589442.

      [9] F. Zhao and H. Su, "Short-term load forecasting using Kalman filter and Elman neural network," in Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on, 2007, pp. 1043-1047. https://doi.org/10.1109/ICIEA.2007.4318567.

      [10] J. Toyoda, M.-s. Chen, and Y. Inoue, "An application of state estimation to short-term load forecasting, Part II: Implementation," IEEE Transactions on Power Apparatus and Systems, pp. 1683-1688, 1970. https://doi.org/10.1109/TPAS.1970.292824.

      [11] M. Kandil, S. M. El-Debeiky, and N. Hasanien, "Long-term load forecasting for fast developing utility using a knowledge-based expert system," IEEE transactions on Power Systems, vol. 17, pp. 491-496, 2002. https://doi.org/10.1109/TPWRS.2002.1007923.

      [12] P. Ansarimehr, I. Barghinia, H. Habibi, and N. Vafadar, "Short term load forecasting for Iran national power system using artificial neural network and fuzzy expert system," in Power System Technology, 2002. Proceedings. PowerCon 2002. International Conference on, 2002, pp. 1082-1085. https://doi.org/10.1109/ICPST.2002.1047567.

      [13] N. Farah, M. Khadir, I. Bouaziz, and H. Kennouche, "Short-term forecasting of algerian load using fuzzy logic and expert system," in Multimedia Computing and Systems, 2009. ICMCS'09. International Conference on, 2009, pp. 81-86. https://doi.org/10.1109/MMCS.2009.5256725.

      [14] A. Songpu, M. L. Kolhe, L. Jiao, and Q. Zhang, "Domestic load forecasting using neural network and its use for missing data analysis," in Advanced Topics in Electrical Engineering (ATEE), 2015 9th International Symposium on, 2015, pp. 535-538. https://doi.org/10.1109/ATEE.2015.7133866.

      [15] S. Manjang and S. Latief, "Radial basis function (RBF) neural network for load forecasting during holiday," in Power Engineering and Renewable Energy (ICPERE), 2016 3rd Conference on, 2016, pp. 235-239.

      [16] S. S. Reddy and J. A. Momoh, "Short term electrical load forecasting using back propagation neural networks," in North American Power Symposium (NAPS), 2014, 2014, pp. 1-6. https://doi.org/10.1109/NAPS.2014.6965453.

      [17] R. Mamlook, O. Badran, and E. Abdulhadi, "A fuzzy inference model for short-term load forecasting," Energy Policy, vol. 37, pp. 1239-1248, 2009. https://doi.org/10.1016/j.enpol.2008.10.051.

      [18] A. Ramadhani, A. Dharma, and I. Robandi, "Optimization FOU of Interval Type-2 Fuzzy Inference System Using Big Bang–Big Crunch Algorithm for Short Term Load Forecasting on National Holiday Case Study: South and Central Kalimantan-Indonesia," International Review of Electrical Engineering (IREE), vol. 10, 2015.

      [19] X.-S. Yang and S. Deb, "Cuckoo search via Lévy flights," in Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, 2009, pp. 210-214.

      [20] I. Fister Jr, X.-S. Yang, D. Fister, and I. Fister, "Cuckoo search: a brief literature review," in Cuckoo search and firefly algorithm, ed: Springer, 2014, pp. 49-62. https://doi.org/10.1007/978-3-319-02141-6_3.

      [21] H. Zheng and Y. Zhou, "A novel cuckoo search optimization algorithm based on Gauss distribution," Journal of Computational Information Systems, vol. 8, pp. 4193-4200, 2012.

  • Downloads

  • How to Cite

    Imran, A., Made Yulistya Negara, I., & Robandi, I. (2019). Peak load forecasting on national holiday using fuzzy-cuckoo for Jawa-Bali system in Indonesia. International Journal of Engineering & Technology, 7(4), 5565-5569. https://doi.org/10.14419/ijet.v7i4.19013

    Received date: 2018-09-05

    Accepted date: 2019-01-29

    Published date: 2019-04-07