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 languageEnglish
Title of host publication2023 14th International Conference on Information and Communication Technology and System, ICTS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages176-181
Number of pages6
ISBN (Electronic)9798350312164
DOIs
Publication statusPublished - 2023
Event14th International Conference on Information and Communication Technology and System, ICTS 2023 - Surabaya, Indonesia
Duration: 4 Oct 20235 Oct 2023

Publication series

Name2023 14th International Conference on Information and Communication Technology and System, ICTS 2023

Conference

Conference14th International Conference on Information and Communication Technology and System, ICTS 2023
Country/TerritoryIndonesia
CitySurabaya
Period4/10/235/10/23

Keywords

  • Campus Building
  • Electricity Consumption
  • Monte Carlo Simulation
  • Prediction

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