Statistical Analysis and SARIMA Forecasting Model Applied to Electrical Energy Consumption in University Facilities
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| Format: | Artículo científico |
| Language: | en |
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Instituto Politécnico Nacional
2022
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| _version_ | 1876489348827840512 |
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| author | José Luis Reyes Reyes |
| author_facet | José Luis Reyes Reyes |
| contents | Statistical Analysis and SARIMA Forecasting Model Applied to Electrical Energy Consumption in University Facilities José Luis Reyes Reyes Guillermo Urriolagoitia Sosa Francisco Javier Gallegos Funes Beatriz Romero Ángeles Israel Flores Baez Misael Flores Baez Ingeniería SARIMA models scholar buildings Energy consumption time series forecasting Analyzing the energy consumption behavior in buildings is essential for implementing energy-saving and efficient energy use measures without losing attention to the comfort inside the buildings. In this study, a statistical analysis and time series forecast of the energy situation of a group of buildings in a university academic unit in Mexico City was conducted. Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used for the forecast with electrical energy consumption data from 55 months. Training and test partitions were created with these data to generate two SARIMA models. The results showed a strong dependence on the school cycle of electricity consumption, in addition to a shift in the cycle in the first year of the study. The mean absolute percentage error (MAPE) for the training partitions created shows that the best fit is provided by the SARIMA (3,1,1) (1,0,0)12 model for the 48-month separation. In comparison, the SARIMA (2,1,2) (1,0,0)12 model does so for the 43-month test partition. The confidence intervals for the 7- and 12-month forecast are less wide for the SARIMA (3,1,1) (1,0,0)12 model than for the SARIMA (2,1,2) (1,0,0)12 model. Statistical analysis and time series modeling allows a better understanding of the building stock's energy performance and strengthens the energy audit to design or implement energy saving or efficient energy use measures. 2022 artículo científico 1665-0654 https://www.redalyc.org/articulo.oa?id=61472445004 https://www.redalyc.org/journal/614/61472445004/ https://www.redalyc.org/journal/614/61472445004/html/ https://www.redalyc.org/journal/614/61472445004/61472445004.epub https://www.redalyc.org/journal/614/61472445004/movil en http://www.redalyc.org/revista.oa?id=614 Científica application/pdf Instituto Politécnico Nacional Científica (México) Num.2 Vol.26 |
| format | Artículo científico |
| id | redalyc_61472445004 |
| institution | Redalyc |
| language | en |
| publishDate | 2022 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | Statistical Analysis and SARIMA Forecasting Model Applied to Electrical Energy Consumption in University Facilities José Luis Reyes Reyes Ingeniería SARIMA models scholar buildings Energy consumption time series forecasting Statistical Analysis and SARIMA Forecasting Model Applied to Electrical Energy Consumption in University Facilities José Luis Reyes Reyes Guillermo Urriolagoitia Sosa Francisco Javier Gallegos Funes Beatriz Romero Ángeles Israel Flores Baez Misael Flores Baez Ingeniería SARIMA models scholar buildings Energy consumption time series forecasting Analyzing the energy consumption behavior in buildings is essential for implementing energy-saving and efficient energy use measures without losing attention to the comfort inside the buildings. In this study, a statistical analysis and time series forecast of the energy situation of a group of buildings in a university academic unit in Mexico City was conducted. Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used for the forecast with electrical energy consumption data from 55 months. Training and test partitions were created with these data to generate two SARIMA models. The results showed a strong dependence on the school cycle of electricity consumption, in addition to a shift in the cycle in the first year of the study. The mean absolute percentage error (MAPE) for the training partitions created shows that the best fit is provided by the SARIMA (3,1,1) (1,0,0)12 model for the 48-month separation. In comparison, the SARIMA (2,1,2) (1,0,0)12 model does so for the 43-month test partition. The confidence intervals for the 7- and 12-month forecast are less wide for the SARIMA (3,1,1) (1,0,0)12 model than for the SARIMA (2,1,2) (1,0,0)12 model. Statistical analysis and time series modeling allows a better understanding of the building stock's energy performance and strengthens the energy audit to design or implement energy saving or efficient energy use measures. 2022 artículo científico 1665-0654 https://www.redalyc.org/articulo.oa?id=61472445004 https://www.redalyc.org/journal/614/61472445004/ https://www.redalyc.org/journal/614/61472445004/html/ https://www.redalyc.org/journal/614/61472445004/61472445004.epub https://www.redalyc.org/journal/614/61472445004/movil en http://www.redalyc.org/revista.oa?id=614 Científica application/pdf Instituto Politécnico Nacional Científica (México) Num.2 Vol.26 |
| title | Statistical Analysis and SARIMA Forecasting Model Applied to Electrical Energy Consumption in University Facilities |
| topic | Ingeniería SARIMA models scholar buildings Energy consumption time series forecasting |
| url | https://www.redalyc.org/articulo.oa?id=61472445004 https://www.redalyc.org/journal/614/61472445004/ https://www.redalyc.org/journal/614/61472445004/html/ https://www.redalyc.org/journal/614/61472445004/61472445004.epub https://www.redalyc.org/journal/614/61472445004/movil |