Neural network based projection of electricity demand in Indonesia using repetitive training method

  • Authors

    • Arbain .
    • Mohammad Zainuddin
    • Emmilya Umma Aziza Gaffar
    • Ansar Rizal
    2018-03-05
    https://doi.org/10.14419/ijet.v7i2.2.12733
  • total electricity demand, electricity sales, AR/ARX models, repetitive NNBP

  • Abstract

    Indonesia Energy Outlook (IEO) 2016 published by BPPT projected the electricity demand in 2025 significantly will increase more than twice to 513 TWh from 203 TWh in 2015. This projection is based on the target of 100% electrification ratio in 2025. Assuming an average population growth of 1.2% in 2025 and a nominal GDP growth of 5.02% in 2014 which are expected to increase to 8% in 2025.This study projected the total electricity demand for the period 2016-2025 based on GDP, population, and electricity sales per sector (household, commercial, and industry) from the period of 2000-2015. Time series data modeling using Auto Regressive (AR) model and Autoregressive model with exogenous input (ARX) implemented using Artificial Neural Network Back-Propagation (ANN-BP). The repetitive training method is used to achieve the specified target error.

     

     

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  • How to Cite

    ., A., Zainuddin, M., Umma Aziza Gaffar, E., & Rizal, A. (2018). Neural network based projection of electricity demand in Indonesia using repetitive training method. International Journal of Engineering & Technology, 7(2.2), 57-61. https://doi.org/10.14419/ijet.v7i2.2.12733

    Received date: 2018-05-12

    Accepted date: 2018-05-12

    Published date: 2018-03-05