TY - GEN
T1 - Electricity Power Consumption Prediction With The Monte Carlo Simulation
T2 - 14th International Conference on Information and Communication Technology and System, ICTS 2023
AU - Hoendarto, Genrawan
AU - Saikhu, Ahmad
AU - Ginardi, Raden Venantius Hari
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
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.
KW - Campus Building
KW - Electricity Consumption
KW - Monte Carlo Simulation
KW - Prediction
UR - http://www.scopus.com/inward/record.url?scp=85180369458&partnerID=8YFLogxK
U2 - 10.1109/ICTS58770.2023.10330846
DO - 10.1109/ICTS58770.2023.10330846
M3 - Conference contribution
AN - SCOPUS:85180369458
T3 - 2023 14th International Conference on Information and Communication Technology and System, ICTS 2023
SP - 176
EP - 181
BT - 2023 14th International Conference on Information and Communication Technology and System, ICTS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 October 2023 through 5 October 2023
ER -
