Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak

Genrawan Hoendarto; Ahmad Saikhu; Raden Venantius Hari Ginardi

doi:10.1109/ICTS58770.2023.10330846

Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak

Genrawan Hoendarto^*
, Ahmad Saikhu
, Raden Venantius Hari Ginardi

^*Corresponding author for this work

Institut Teknologi Sepuluh Nopember
Universitas Widya Dharma

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Predicting electricity consumption for buildings has been a concern lately, as it accounts for 39% of total electricity consumption. One of the buildings that uses a lot of electricity is the campus building. Various methods are being developed and carried out in response to the fossil energy crisis to save electricity consumption. Before taking steps to reduce the use of electricity, it is necessary to predict its use. Monte Carlo simulation is a good option for predicting electricity consumption. The dataset used in this study was collected over the past year and recorded several times a day. According to the lecture days, the data used is only from Monday to Friday. Since the recording is done randomly over a day, we preprocess the data using tree regression. After the data pre-processing stage produces data in minutes, the last stage is the quartile search process to find the hourly average.

Original language	English
Title of host publication	2023 14th International Conference on Information and Communication Technology and System, ICTS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	176-181
Number of pages	6
ISBN (Electronic)	9798350312164
DOIs	https://doi.org/10.1109/ICTS58770.2023.10330846
Publication status	Published - 2023
Event	14th International Conference on Information and Communication Technology and System, ICTS 2023 - Surabaya, Indonesia Duration: 4 Oct 2023 → 5 Oct 2023

Publication series

Name	2023 14th International Conference on Information and Communication Technology and System, ICTS 2023

Conference

Conference	14th International Conference on Information and Communication Technology and System, ICTS 2023
Country/Territory	Indonesia
City	Surabaya
Period	4/10/23 → 5/10/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Campus Building
Electricity Consumption
Monte Carlo Simulation
Prediction

Access to Document

10.1109/ICTS58770.2023.10330846

Cite this

Hoendarto, G., Saikhu, A., & Ginardi, R. V. H. (2023). Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak. In 2023 14th International Conference on Information and Communication Technology and System, ICTS 2023 (pp. 176-181). (2023 14th International Conference on Information and Communication Technology and System, ICTS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICTS58770.2023.10330846

Hoendarto, Genrawan ; Saikhu, Ahmad ; Ginardi, Raden Venantius Hari. / Electricity Power Consumption Prediction With The Monte Carlo Simulation : Case Study Universitas Widya Dharma Pontianak. 2023 14th International Conference on Information and Communication Technology and System, ICTS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 176-181 (2023 14th International Conference on Information and Communication Technology and System, ICTS 2023).

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title = "Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak",

abstract = "Predicting electricity consumption for buildings has been a concern lately, as it accounts for 39\% of total electricity consumption. One of the buildings that uses a lot of electricity is the campus building. Various methods are being developed and carried out in response to the fossil energy crisis to save electricity consumption. Before taking steps to reduce the use of electricity, it is necessary to predict its use. Monte Carlo simulation is a good option for predicting electricity consumption. The dataset used in this study was collected over the past year and recorded several times a day. According to the lecture days, the data used is only from Monday to Friday. Since the recording is done randomly over a day, we preprocess the data using tree regression. After the data pre-processing stage produces data in minutes, the last stage is the quartile search process to find the hourly average.",

keywords = "Campus Building, Electricity Consumption, Monte Carlo Simulation, Prediction",

author = "Genrawan Hoendarto and Ahmad Saikhu and Ginardi, \{Raden Venantius Hari\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 14th International Conference on Information and Communication Technology and System, ICTS 2023 ; Conference date: 04-10-2023 Through 05-10-2023",

year = "2023",

doi = "10.1109/ICTS58770.2023.10330846",

language = "English",

series = "2023 14th International Conference on Information and Communication Technology and System, ICTS 2023",

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Hoendarto, G, Saikhu, A & Ginardi, RVH 2023, Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak. in 2023 14th International Conference on Information and Communication Technology and System, ICTS 2023. 2023 14th International Conference on Information and Communication Technology and System, ICTS 2023, Institute of Electrical and Electronics Engineers Inc., pp. 176-181, 14th International Conference on Information and Communication Technology and System, ICTS 2023, Surabaya, Indonesia, 4/10/23. https://doi.org/10.1109/ICTS58770.2023.10330846

Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak. / Hoendarto, Genrawan; Saikhu, Ahmad ; Ginardi, Raden Venantius Hari.
2023 14th International Conference on Information and Communication Technology and System, ICTS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 176-181 (2023 14th International Conference on Information and Communication Technology and System, ICTS 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Electricity Power Consumption Prediction With The Monte Carlo Simulation

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AU - Hoendarto, Genrawan

AU - Saikhu, Ahmad

AU - Ginardi, Raden Venantius Hari

PY - 2023

Y1 - 2023

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AB - Predicting electricity consumption for buildings has been a concern lately, as it accounts for 39% of total electricity consumption. One of the buildings that uses a lot of electricity is the campus building. Various methods are being developed and carried out in response to the fossil energy crisis to save electricity consumption. Before taking steps to reduce the use of electricity, it is necessary to predict its use. Monte Carlo simulation is a good option for predicting electricity consumption. The dataset used in this study was collected over the past year and recorded several times a day. According to the lecture days, the data used is only from Monday to Friday. Since the recording is done randomly over a day, we preprocess the data using tree regression. After the data pre-processing stage produces data in minutes, the last stage is the quartile search process to find the hourly average.

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KW - Prediction

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AN - SCOPUS:85180369458

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ER -

Hoendarto G, Saikhu A , Ginardi RVH. Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak. In 2023 14th International Conference on Information and Communication Technology and System, ICTS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 176-181. (2023 14th International Conference on Information and Communication Technology and System, ICTS 2023). doi: 10.1109/ICTS58770.2023.10330846

Electricity Power Consumption Prediction With The Monte Carlo Simulation: Case Study Universitas Widya Dharma Pontianak

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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