ENERGY USE PREDICTION BY MULTIPLE-TIME SERIES AND STATE VARIABLE MODELLING BASED ON ENERGY MONITORING SYSTEM FOR INDUSTRIAL FACILITY IN INDONESIA
Measures for energy saving and de-carbonization in industrial sector is of great importance to realize a low-carbon society. In Indonesia, promoting “Green Industry” is a critical policy carried out by national government which focuses on reducing energy consumption in industrial sector. However, th...
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| Veröffentlicht in: | Doboku Gakkai Ronbunshu. G, Kankyo = Journal of Japan Society of Civil Engineers. Ser. G, Environmental Research Ser. G (Environmental Research), 2018, Vol.74(6), pp.II_73-II_83 |
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| container_end_page | II_83 |
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| container_issue | 6 |
| container_start_page | II_73 |
| container_title | Doboku Gakkai Ronbunshu. G, Kankyo = Journal of Japan Society of Civil Engineers. Ser. G, Environmental Research |
| container_volume | 74 |
| creator | MAKI, Seiya FUJII, Minoru FUJITA, Tsuyoshi SHIRAISHI, Yasushi ASHINA, Shuichi |
| description | Measures for energy saving and de-carbonization in industrial sector is of great importance to realize a low-carbon society. In Indonesia, promoting “Green Industry” is a critical policy carried out by national government which focuses on reducing energy consumption in industrial sector. However, the current difficulty in accurately measuring energy consumption and energy-saving effects in Indonesia becomes an unavoidable barrier during policy implementation. This study conducts a survey on real-time energy consumption of industries in Indonesia based on an innovative energy monitoring system with high resolution at each device through public and private collaboration. An energy consumption prediction model is developed for each industrial process using the auto-regression exogeneous modeling and markov switching modeling. Results indicate the feasibility of developing an energy consumption prediction model in Indonesia, and reveal a high consistency between measured value and predicted value. This will also help in system design for demand response due to the high-accuracy measuring and prediction. |
| doi_str_mv | 10.2208/jscejer.74.II_73 |
| format | Article |
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In Indonesia, promoting “Green Industry” is a critical policy carried out by national government which focuses on reducing energy consumption in industrial sector. However, the current difficulty in accurately measuring energy consumption and energy-saving effects in Indonesia becomes an unavoidable barrier during policy implementation. This study conducts a survey on real-time energy consumption of industries in Indonesia based on an innovative energy monitoring system with high resolution at each device through public and private collaboration. An energy consumption prediction model is developed for each industrial process using the auto-regression exogeneous modeling and markov switching modeling. Results indicate the feasibility of developing an energy consumption prediction model in Indonesia, and reveal a high consistency between measured value and predicted value. 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G, Environmental Research</title><addtitle>J. JSCE, Ser. G</addtitle><description>Measures for energy saving and de-carbonization in industrial sector is of great importance to realize a low-carbon society. In Indonesia, promoting “Green Industry” is a critical policy carried out by national government which focuses on reducing energy consumption in industrial sector. However, the current difficulty in accurately measuring energy consumption and energy-saving effects in Indonesia becomes an unavoidable barrier during policy implementation. This study conducts a survey on real-time energy consumption of industries in Indonesia based on an innovative energy monitoring system with high resolution at each device through public and private collaboration. An energy consumption prediction model is developed for each industrial process using the auto-regression exogeneous modeling and markov switching modeling. 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| identifier | EISSN: 2185-6648 |
| ispartof | Journal of Japan Society of Civil Engineers, Ser. G (Environmental Research), 2018, Vol.74(6), pp.II_73-II_83 |
| issn | 2185-6648 |
| language | jpn |
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| source | EZB-FREE-00999 freely available EZB journals |
| subjects | Carbonization Energy Energy conservation Energy consumption Energy management Energy measurement Energy use prediction Feasibility studies Indonesia Industrial energy monitoring Industry Markov chains Modelling Monitoring Monitoring systems Multiple-time series modeling Policies Prediction models State variable State variable modeling Surveying Systems design |
| title | ENERGY USE PREDICTION BY MULTIPLE-TIME SERIES AND STATE VARIABLE MODELLING BASED ON ENERGY MONITORING SYSTEM FOR INDUSTRIAL FACILITY IN INDONESIA |
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