Energy Saving Potential Prediction and Anomaly Detection in College Buildings

Nur Inayah, Madona Yunita Wijaya, Nina Fitriyati

2018

Abstract

Prediction of building electricity consumption has been studied in recent years. Several approaches have been applied to get accurate and robust prediction of electricity usage. In this report, we highlight methods to make buildings and college campus more efficient in using electricity through statistical modeling. We focus on four main buildings in Syarif Hidayatullah State Islamic University Jakarta and collect each building’s kWh energy consumption on a monthly basis. Two methods are utilized to the time series data, SARIMA model and Artificial Neural Network (ANN) model. The ANN was found to have better model performance than SARIMA with the smallest error prediction.

Paper Citation

in Harvard Style

Inayah N., Wijaya M. and Fitriyati N. (2018). Energy Saving Potential Prediction and Anomaly Detection in College Buildings.In Proceedings of the International Conference on Mathematics and Islam - Volume 1: ICMIs, ISBN 978-989-758-407-7, pages 15-22. DOI: 10.5220/0008516500150022

in Bibtex Style

@conference{icmis18,
author={Nur Inayah and Madona Yunita Wijaya and Nina Fitriyati},
title={Energy Saving Potential Prediction and Anomaly Detection in College Buildings},
booktitle={Proceedings of the International Conference on Mathematics and Islam - Volume 1: ICMIs,},
year={2018},
pages={15-22},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008516500150022},
isbn={978-989-758-407-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Mathematics and Islam - Volume 1: ICMIs,
TI - Energy Saving Potential Prediction and Anomaly Detection in College Buildings
SN - 978-989-758-407-7
AU - Inayah N.
AU - Wijaya M.
AU - Fitriyati N.
PY - 2018
SP - 15
EP - 22
DO - 10.5220/0008516500150022