Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling
Process cooling for food production is an energy-intensive industry with complex interactions and restrictions that complicate the ability to utilize energy-flexibility due to unforeseen consequences in production. Therefore, methods for assessing the potential flexibility in individual facilities t...
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| Formaat: | Artikel |
| Taal: | English |
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MDPI AG
2023-02-01
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| Reeks: | Energies |
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| Online toegang: | https://www.mdpi.com/1996-1073/16/3/1514 |
| _version_ | 1827760091304034304 |
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| author | Daniel Anthony Howard Bo Nørregaard Jørgensen Zheng Ma |
| author_facet | Daniel Anthony Howard Bo Nørregaard Jørgensen Zheng Ma |
| author_sort | Daniel Anthony Howard |
| collection | DOAJ |
| description | Process cooling for food production is an energy-intensive industry with complex interactions and restrictions that complicate the ability to utilize energy-flexibility due to unforeseen consequences in production. Therefore, methods for assessing the potential flexibility in individual facilities to enable the active participation of process-cooling facilities in the electricity system are essential, but not yet well discussed in the literature. Therefore, this paper introduces an assessment method based on multi-method simulation and multi-objective optimization for investigating energy flexibility in process cooling, with a case study of a Danish process-cooling facility for canned-meat food production. Multi-method simulation is used in this paper: multi-agent-based simulation to investigate individual entities within the process-cooling system and the system’s behavior; discrete-event simulation to explore the entire process-cooling flow; and system dynamics to capture the thermophysical properties of the refrigeration unit and states of the refrigerated environment. A simulation library is developed, and is able to represent a generic production-flow of the canned-food process cooling. A data-driven symbolic-regression approach determines the complex logic of individual agents. Using a binary tuple-matrix for refrigeration-schedule optimization, the refrigeration-cycle operation is determined, based on weather forecasts, electricity price, and electricity CO<sub>2</sub> emissions without violating individual room-temperature limits. The simulation results of one-week’s production in October 2020 show that 32% of energy costs can be saved and 822 kg of CO<sub>2</sub> emissions can be reduced. The results thereby show the energy-flexibility potential in the process-cooling facilities, with the benefit of overall production cost and CO<sub>2</sub> emissions reduction; at the same time, the production quality and throughput are not influenced. |
| first_indexed | 2024-03-11T09:45:33Z |
| format | Article |
| id | doaj.art-eaa4b778c7a64f5aac7a42ede90e9841 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T09:45:33Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-eaa4b778c7a64f5aac7a42ede90e98412023-11-16T16:38:35ZengMDPI AGEnergies1996-10732023-02-01163151410.3390/en16031514Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process CoolingDaniel Anthony Howard0Bo Nørregaard Jørgensen1Zheng Ma2SDU Center for Energy Informatics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, 5230 Odense, DenmarkSDU Center for Energy Informatics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, 5230 Odense, DenmarkSDU Center for Energy Informatics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, 5230 Odense, DenmarkProcess cooling for food production is an energy-intensive industry with complex interactions and restrictions that complicate the ability to utilize energy-flexibility due to unforeseen consequences in production. Therefore, methods for assessing the potential flexibility in individual facilities to enable the active participation of process-cooling facilities in the electricity system are essential, but not yet well discussed in the literature. Therefore, this paper introduces an assessment method based on multi-method simulation and multi-objective optimization for investigating energy flexibility in process cooling, with a case study of a Danish process-cooling facility for canned-meat food production. Multi-method simulation is used in this paper: multi-agent-based simulation to investigate individual entities within the process-cooling system and the system’s behavior; discrete-event simulation to explore the entire process-cooling flow; and system dynamics to capture the thermophysical properties of the refrigeration unit and states of the refrigerated environment. A simulation library is developed, and is able to represent a generic production-flow of the canned-food process cooling. A data-driven symbolic-regression approach determines the complex logic of individual agents. Using a binary tuple-matrix for refrigeration-schedule optimization, the refrigeration-cycle operation is determined, based on weather forecasts, electricity price, and electricity CO<sub>2</sub> emissions without violating individual room-temperature limits. The simulation results of one-week’s production in October 2020 show that 32% of energy costs can be saved and 822 kg of CO<sub>2</sub> emissions can be reduced. The results thereby show the energy-flexibility potential in the process-cooling facilities, with the benefit of overall production cost and CO<sub>2</sub> emissions reduction; at the same time, the production quality and throughput are not influenced.https://www.mdpi.com/1996-1073/16/3/1514industrial-energy flexibilityagent-based modelingsimulationprocess coolingmulti-objective optimization |
| spellingShingle | Daniel Anthony Howard Bo Nørregaard Jørgensen Zheng Ma Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling Energies industrial-energy flexibility agent-based modeling simulation process cooling multi-objective optimization |
| title | Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling |
| title_full | Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling |
| title_fullStr | Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling |
| title_full_unstemmed | Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling |
| title_short | Multi-Method Simulation and Multi-Objective Optimization for Energy-Flexibility-Potential Assessment of Food-Production Process Cooling |
| title_sort | multi method simulation and multi objective optimization for energy flexibility potential assessment of food production process cooling |
| topic | industrial-energy flexibility agent-based modeling simulation process cooling multi-objective optimization |
| url | https://www.mdpi.com/1996-1073/16/3/1514 |
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