Applying Neural Network And Levenberg - Marquardt Algorithm for Load Forecasting in IA-Grai District, Gia Lai Province

https://doi.org/10.31130/ud-jst.2022.240ICT

##plugins.themes.academic_pro.article.main##

Author

  • Quang Huy Giap
    The University of Danang - University of Science and Technology, Danang, Vietnam
    Dang Luu Nguyen
    The FPT Group
    Thi Thanh Quynh Nguyen
    The University of Danang - University of Science and Technology, Danang, Vietnam
    Thi Minh Dung Tran
    The University of Danang - University of Science and Technology, Danang, Vietnam

Từ khóa:

Neural network
Levenberg-Marquardt algorithm
electrical load forecasting

Tóm tắt

Electrical energy is fundamental to the life and economic development. Accompany by the increasing demand for electricity by people and businesses, the electricity industry must always ensure sufficient supply for production activities. This poses an urgent need to have an accurate load forecasting tool for electricity production and distribution strategy. If the demand forecast is lower than the reality, the phenomenon of power supply shortage will occur. While if the forecast exceeds the demand for use by people and businesses, it will cause economic losses because it must mobilize power sources by using a backup as a diesel generator. For these reasons, the problem of electrical load forecasting becomes very important in terms of efficient power supply. In this paper, a load forecasting tool using Neural Network and Levenberg - Marquardt algorithm is presented.

Tài liệu tham khảo

    [1] V. C. N. Nguyen, H. T. Dung, N. S. H. Nguyen, and T. H. Nguyen, “Green technology for sustainable development:
    [2] Practice and experience of renewable energy in vietnam,” Research Nepal Journal of Development Studies, vol. 4, no. 2, pp. 79–92, 2021.
    [3] A. Azeem, I. Ismail, S. M. Jameel, and V. R. Harindran, “Electrical load forecasting models for different generation modalities: a review,” IEEE Access, 2021.
    [4] H. H. Aly, “A proposed intelligent short-term load forecasting hybrid models of ann, wnn and kf based on clustering techniques for smart grid,” Electric Power Systems Research, vol. 182, p. 106191, 2020.
    [5] P. Singh, P. Dwivedi, and V. Kant, “A hybrid method based on neural network and improved environmental adaptation method using controlled gaussian mutation with real parameter for short-term load forecasting,” Energy, vol. 174, pp. 460–477, 2019.
    [6] A. Mikhaylov and S. Tarakanov, “Development of levenbergmarquardt theoretical approach for electric networks,” in Journal of Physics: Conference Series, vol. 1515, no. 5. IOP Publishing, 2020, p. 052006.
    [7] N. Abu-Shikhah and F. Elkarmi, “Medium-term electric load forecasting using singular value decomposition,” Energy, vol. 36, no. 7, pp. 4259–4271, 2011.
    [8] M. Saviozzi, S. Massucco, and F. Silvestro, “Implementation of advanced functionalities for distribution management systems: Load forecasting and modeling through artificial neural networks ensembles,” Electric Power Systems Research, vol. 167, pp. 230–239, 2019.
    [9] M. T. Hagan, H. B. Demuth, and M. Beale, Neural network design, PWS Publishing Co., 1997.
Xem thêm

##plugins.themes.academic_pro.article.sidebar##

Đã Xuất bản

Jun 30, 2022
Download
PDF (English)
Cách trích dẫn
Giap, Q. H., D. L. Nguyen, T. T. Q. Nguyen, và T. M. D. Tran. “Applying Neural Network And Levenberg - Marquardt Algorithm for Load Forecasting in IA-Grai District, Gia Lai Province”. Tạp Chí Khoa học Và Công nghệ - Đại học Đà Nẵng, vol 20, số p.h 6.2, Tháng Sáu 2022, tr 13-18, doi:10.31130/ud-jst.2022.240ICT.

##plugins.themes.academic_pro.article.details##