2023
DOI: 10.1016/j.energy.2023.126959
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Data-Driven model identification and efficient MPC via quasi-linear parameter varying representation for ORC waste heat recovery system

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Cited by 6 publications
(2 citation statements)
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“…-MPC utilizes a dynamic process model to predict future trend and optimize control actions. -It is suitable for variation of the setpoint and constraints [77]. -It could handle multivariable and complex system [74], making it ideal for complex ORC technology combined with TES [75] and two-phase expansion system.…”
Section: Mpcmentioning
confidence: 99%
“…-MPC utilizes a dynamic process model to predict future trend and optimize control actions. -It is suitable for variation of the setpoint and constraints [77]. -It could handle multivariable and complex system [74], making it ideal for complex ORC technology combined with TES [75] and two-phase expansion system.…”
Section: Mpcmentioning
confidence: 99%
“…The increase in greenhouse temperature is reported to be about 7.5 ° C. The payback period for that project was reported to be nearly 5 years. By developing a data-based model and efficient predictive control approach, Shi et al [ 35 ] indicated that an ORC unit is significantly distinct in waste heat recovery.…”
Section: Introductionmentioning
confidence: 99%