4.7 Article

Dual-mode fast DMC algorithm for the control of ORC based waste heat recovery system

期刊

ENERGY
卷 244, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.122664

关键词

Dynamic matrix control; Organic rankine cycle; Waste heat recovery; Singular value decomposition; Dual-mode

资金

  1. National Key R&D Pro-gram of China [2018YFB1702802]
  2. National Natural Science Foundation of P.R. China (NSFC) [62073286]
  3. Science Fund for Cre-ative Research Groups of the National Natural Science Foundation of China [61621002]
  4. Young Innovation Talents by Department of Education of Guangdong Province, P.R.China [2020KQNCX204]

向作者/读者索取更多资源

This article proposes a dual-mode fast dynamic matrix control (FDMC) algorithm based on singular value decomposition (SVD) and dynamic matrix control (DMC) to address the issue of long computation time in model predictive control (MPC) for organic Rankine cycle (ORC) systems. The simulations demonstrate the effectiveness and rapidity of the proposed algorithm in ensuring tracking performance while improving calculation speed.
Organic Rankine Cycle (ORC) system stands out in low-grade waste heat recovery for its outstanding performance. Considering the fluctuating nature of the heat source, model predictive control (MPC) is used to control the ORC systems and has achieved good performance. However, with the increase of the number of variables and the expansion of the control/prediction horizon, MPC will take longer calcu-lation time. This may bring about the incapacity to obtain optimization problem solutions in one sam-pling instant and finally, lead to the failure of the setpoint tracking. To address this problem, in this article, a dual-mode fast dynamic matrix control (FDMC) algorithm grounded on singular value decomposition (SVD) and dynamic matrix control (DMC) is proposed. The presented algorithm features in its calculation speed improvement on the premise of ensuring tracking performance. Two simulations on disturbance rejection and setpoint tracking are performed to verify the effectiveness and rapidity of the proposed algorithm in comparison with the traditional DMC approach.(c) 2021 Elsevier Ltd. All rights reserved.

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