Long-term electrical consumption forecasting using Artificial Neural Network (ANN)-Reference-Cited by-同舟云学术

Long-term electrical consumption forecasting using Artificial Neural Network (ANN)

Published:2019-12-01 Issue:3 Volume:1402 Page:033081
ISSN:1742-6588
Container-title:Journal of Physics: Conference Series
language:
Short-container-title:J. Phys.: Conf. Ser.

Author:

Adhiswara R,Abdullah A G,Mulyadi Y

Abstract

Abstract Long-term forecasting of electricity energy consumption has become one of the main fields in the electricity sector in each country. This study aims to compare the accuracy of the results of the method used in this study with research conducted by the government to estimate electricity consumption in Indonesia. Many methods can be used to estimate electrical energy consumption such as statistic methods (Exponential Smoothing, ARIMA, Regression), fuzzy logic and artificial neural network algorithms. The method used in RUPTL is Simple E (Simple Econometric) and method used in this study is the Artificial Neural Network algorithm. The results of this research are data on estimates of electricity consumption in Indonesia for 2019-2025. This research is expected to prove the accuracy of the Artificial Neural Network (ANN) method to estimate electricity consumption in Indonesia.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Link

https://iopscience.iop.org/article/10.1088/1742-6596/1402/3/033081/pdf

Reference34 articles.

1. Particle swarm optimization for long-term Demand Forecasting;Hafez,2017

2. Medium to Long-term Peak Load Forecasting for Riyadh City Using Artificial Neural Networks;Alturki;Journal of King Saud University Engineering Sciences,2000

3. Research on long term load forecasting based on improved genetic neural network;Yingling,2008

4. The study of long-term load forecasting based on method combination innovation;Chuanseng,2011

5. Uzun Dönem Elektrik Ġhtiyaç Talep Kestiriminde GiriĢ DeğiĢkenlerinin Performansa Etkisi Investigation of Performance Effect of Input Diversity on Long Term Electricity Demand Forecasting;Altınöz,2015

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