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Economic optimization for process transition based on redundant control variables in the framework of zone model predictive control
This paper proposes an optimization strategy based on redundant control variables under the zone control framework and can improve the economic optimization effect. First, we briefly reviewed the general concepts of redundant control and zone control. Then we analyzed the limitations of this optimiz...
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Published in: | Energy (Oxford) 2022-02, Vol.241, p.122942, Article 122942 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This paper proposes an optimization strategy based on redundant control variables under the zone control framework and can improve the economic optimization effect. First, we briefly reviewed the general concepts of redundant control and zone control. Then we analyzed the limitations of this optimization strategy, the reason is the impact of the change of redundant control variables on the system state variables. This will cause the switching of the controller on the boundary of the zone control target, which will affect the economic benefits of the system. Based on the above problems, we have designed two different optimization strategies to avoid this switching action. The first method is to temporarily disable the switching conditions during the process transition to avoid triggering the switching action. The second method is to dynamically change the rate of change of redundant control variables so that the system can not trigger the switching conditions. Finally, we verified the feasibility of the two improved optimization strategies we proposed through numerical simulation, and achieved greater economic benefits compared with previous studies.
•The factors were analyzed which affect energy consumption in the transition process.•A smooth transition strategy was designed in the zone control framework.•The transition process was used to abstract as a generally overlooked stage in optimization. |
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ISSN: | 0360-5442 1873-6785 |
DOI: | 10.1016/j.energy.2021.122942 |