Abstract
Industrial facilities are devoting ever greater attention to the importance of energy in their operations. Consequently, industrial energy management has advanced to include many activities in both planning and operations. Dynamic energy management has evolved as not just an extension of cost optimal production methods but also in the context of demand side management activities. And yet, the current demand side management literature is inadequate because it does not address the underlying production activities as the existential reason for energy consumption. Therefore, this paper seeks to develop a dynamic production model for industrial systems energy management drawing upon techniques from Axiomatic Design for Large Flexible Engineering Systems and timed petri-nets. The model is applied to an illustrative example to demonstrate the calculation of energy consumption and energy cost curves. This model may be later integrated into conventional industrial systems energy management techniques or into extended demand side management techniques.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 |
| Pages | 1-7 |
| Number of pages | 7 |
| ISBN (Electronic) | 9781479986965 |
| DOIs | |
| State | Published - 12 Jan 2016 |
| Event | IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 - Kowloon Tong, Hong Kong Duration: 9 Oct 2015 → 12 Oct 2015 |
Publication series
| Name | Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 |
|---|
Conference
| Conference | IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 |
|---|---|
| Country/Territory | Hong Kong |
| City | Kowloon Tong |
| Period | 9/10/15 → 12/10/15 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Demand side management
- axiomatic design
- manufacturing system
- operations control
- petri net model
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