IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v212y2020ics0360544220316947.html
   My bibliography  Save this article

Economic optimization of chemical processes based on zone predictive control with redundancy variables

Author

Listed:
  • Wan, Xin
  • Luo, Xiong-Lin

Abstract

Zone control is to extend the control target from a point to a convex set. Additional degree of freedom can improve the control performance and optimize the economic performance.This additional degree of freedom has been proven to be expressed specifically by redundant control variables.This paper proposes an optimization control strategy based on redundant control variables to improve the economic benefits of zone control. When the system is outside the zone control target, the zone predictive control algorithm is used to preferentially drive the state to the interior of the zone control target. When the system enters the zone control target, it can be directly optimized by using redundant control variables to achieve greater economic benefits. During system operation, each variable is evaluated by the steady-state mapping model, and variables that meet certain conditions are marked as redundant variables. The controller and optimizer are coordinated based on this label for system control and economic performance. Finally, the effectiveness and feasibility of this strategy are verified by numerical simulation. The results show that this strategy can reduce the economic loss of the system.

Suggested Citation

  • Wan, Xin & Luo, Xiong-Lin, 2020. "Economic optimization of chemical processes based on zone predictive control with redundancy variables," Energy, Elsevier, vol. 212(C).
    • Handle: RePEc:eee:energy:v:212:y:2020:i:c:s0360544220316947
    DOI: 10.1016/j.energy.2020.118586
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220316947
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.118586?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sun, Lin & Zha, Xinlang & Luo, Xionglin, 2018. "Coordination between bypass control and economic optimization for heat exchanger network," Energy, Elsevier, vol. 160(C), pages 318-329.
    2. Zhang, Yan & Fu, Lijun & Zhu, Wanlu & Bao, Xianqiang & Liu, Cang, 2018. "Robust model predictive control for optimal energy management of island microgrids with uncertainties," Energy, Elsevier, vol. 164(C), pages 1229-1241.
    3. Finck, Christian & Li, Rongling & Zeiler, Wim, 2019. "Economic model predictive control for demand flexibility of a residential building," Energy, Elsevier, vol. 176(C), pages 365-379.
    4. Menon, Ramanunni P. & Maréchal, François & Paolone, Mario, 2016. "Intra-day electro-thermal model predictive control for polygeneration systems in microgrids," Energy, Elsevier, vol. 104(C), pages 308-319.
    5. Aoun, Nadine & Bavière, Roland & Vallée, Mathieu & Aurousseau, Antoine & Sandou, Guillaume, 2019. "Modelling and flexible predictive control of buildings space-heating demand in district heating systems," Energy, Elsevier, vol. 188(C).
    6. Li, Xunming & Han, Lijin & Liu, Hui & Wang, Weida & Xiang, Changle, 2019. "Real-time optimal energy management strategy for a dual-mode power-split hybrid electric vehicle based on an explicit model predictive control algorithm," Energy, Elsevier, vol. 172(C), pages 1161-1178.
    7. Weeratunge, Hansani & Narsilio, Guillermo & de Hoog, Julian & Dunstall, Simon & Halgamuge, Saman, 2018. "Model predictive control for a solar assisted ground source heat pump system," Energy, Elsevier, vol. 152(C), pages 974-984.
    8. Dong, Zhe & Zhang, Zuoyi & Dong, Yujie & Huang, Xiaojin, 2018. "Multi-layer perception based model predictive control for the thermal power of nuclear superheated-steam supply systems," Energy, Elsevier, vol. 151(C), pages 116-125.
    9. Oravec, Juraj & Bakošová, Monika & Trafczynski, Marian & Vasičkaninová, Anna & Mészáros, Alajos & Markowski, Mariusz, 2018. "Robust model predictive control and PID control of shell-and-tube heat exchangers," Energy, Elsevier, vol. 159(C), pages 1-10.
    10. Shan, Kui & Fan, Cheng & Wang, Jiayuan, 2019. "Model predictive control for thermal energy storage assisted large central cooling systems," Energy, Elsevier, vol. 179(C), pages 916-927.
    11. Zhang, Dongliang & Cai, Ning & Cui, Xiaobo & Xia, Xueying & Shi, Jianzhong & Huang, Xiaoqing, 2019. "Experimental investigation on model predictive control of radiant floor cooling combined with underfloor ventilation system," Energy, Elsevier, vol. 176(C), pages 23-33.
    12. Hou, Jun & Sun, Jing & Hofmann, Heath, 2018. "Adaptive model predictive control with propulsion load estimation and prediction for all-electric ship energy management," Energy, Elsevier, vol. 150(C), pages 877-889.
    13. Yang, Duo & Pan, Rui & Wang, Yujie & Chen, Zonghai, 2019. "Modeling and control of PEMFC air supply system based on T-S fuzzy theory and predictive control," Energy, Elsevier, vol. 188(C).
    14. Lasheen, Ahmed & Saad, Mohamed S. & Emara, Hassan M. & Elshafei, Abdel Latif, 2017. "Continuous-time tube-based explicit model predictive control for collective pitching of wind turbines," Energy, Elsevier, vol. 118(C), pages 1222-1233.
    15. Ma, Fangwu & Yang, Yu & Wang, Jiawei & Liu, Zhenze & Li, Jinhang & Nie, Jiahong & Shen, Yucheng & Wu, Liang, 2019. "Predictive energy-saving optimization based on nonlinear model predictive control for cooperative connected vehicles platoon with V2V communication," Energy, Elsevier, vol. 189(C).
    16. Wu, Xialai & Chen, Junghui & Xie, Lei, 2019. "Fast economic nonlinear model predictive control strategy of Organic Rankine Cycle for waste heat recovery: Simulation-based studies," Energy, Elsevier, vol. 180(C), pages 520-534.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Seferlis, Panos & Varbanov, Petar Sabev & Papadopoulos, Athanasios I. & Chin, Hon Huin & Klemeš, Jiří Jaromír, 2021. "Sustainable design, integration, and operation for energy high-performance process systems," Energy, Elsevier, vol. 224(C).
    2. Wan, Xin & Xu, Feng & Luo, Xiong-Lin, 2022. "Economic optimization for process transition based on redundant control variables in the framework of zone model predictive control," Energy, Elsevier, vol. 241(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Oravec, Juraj & Horváthová, Michaela & Bakošová, Monika, 2020. "Energy efficient convex-lifting-based robust control of a heat exchanger," Energy, Elsevier, vol. 201(C).
    2. Dong, Zhe & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2020. "Multilayer perception based reinforcement learning supervisory control of energy systems with application to a nuclear steam supply system," Applied Energy, Elsevier, vol. 259(C).
    3. Nyong-Bassey, Bassey Etim & Giaouris, Damian & Patsios, Charalampos & Papadopoulou, Simira & Papadopoulos, Athanasios I. & Walker, Sara & Voutetakis, Spyros & Seferlis, Panos & Gadoue, Shady, 2020. "Reinforcement learning based adaptive power pinch analysis for energy management of stand-alone hybrid energy storage systems considering uncertainty," Energy, Elsevier, vol. 193(C).
    4. Brage Rugstad Knudsen & Hanne Kauko & Trond Andresen, 2019. "An Optimal-Control Scheme for Coordinated Surplus-Heat Exchange in Industry Clusters," Energies, MDPI, vol. 12(10), pages 1-22, May.
    5. Dongsu Kim & Jongman Lee & Sunglok Do & Pedro J. Mago & Kwang Ho Lee & Heejin Cho, 2022. "Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends," Energies, MDPI, vol. 15(19), pages 1-30, October.
    6. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    7. Wan, Xin & Xu, Feng & Luo, Xiong-Lin, 2022. "Economic optimization for process transition based on redundant control variables in the framework of zone model predictive control," Energy, Elsevier, vol. 241(C).
    8. Seferlis, Panos & Varbanov, Petar Sabev & Papadopoulos, Athanasios I. & Chin, Hon Huin & Klemeš, Jiří Jaromír, 2021. "Sustainable design, integration, and operation for energy high-performance process systems," Energy, Elsevier, vol. 224(C).
    9. Joe, Jaewan & Im, Piljae & Cui, Borui & Dong, Jin, 2023. "Model-based predictive control of multi-zone commercial building with a lumped building modelling approach," Energy, Elsevier, vol. 263(PA).
    10. Oravec, Juraj & Bakošová, Monika & Galčíková, Lenka & Slávik, Michal & Horváthová, Michaela & Mészáros, Alajos, 2019. "Soft-constrained robust model predictive control of a plate heat exchanger: Experimental analysis," Energy, Elsevier, vol. 180(C), pages 303-314.
    11. Liu, Teng & Wang, Bo & Yang, Chenglang, 2018. "Online Markov Chain-based energy management for a hybrid tracked vehicle with speedy Q-learning," Energy, Elsevier, vol. 160(C), pages 544-555.
    12. Shan, Kui & Wang, Shengwei & Zhuang, Chaoqun, 2021. "Controlling a large constant speed centrifugal chiller to provide grid frequency regulation: A validation based on onsite tests," Applied Energy, Elsevier, vol. 300(C).
    13. Yanfeng Liu & Yaxing Wang & Xi Luo, 2020. "Design and Operation Optimization of Distributed Solar Energy System Based on Dynamic Operation Strategy," Energies, MDPI, vol. 14(1), pages 1-26, December.
    14. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    15. Peixiao Fan & Jia Hu & Song Ke & Yuxin Wen & Shaobo Yang & Jun Yang, 2022. "A Frequency–Pressure Cooperative Control Strategy of Multi-Microgrid with an Electric–Gas System Based on MADDPG," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    16. Zhu, Tao & Wills, Richard G.A. & Lot, Roberto & Ruan, Haijun & Jiang, Zhihao, 2021. "Adaptive energy management of a battery-supercapacitor energy storage system for electric vehicles based on flexible perception and neural network fitting," Applied Energy, Elsevier, vol. 292(C).
    17. Miretti, Federico & Misul, Daniela & Gennaro, Giulio & Ferrari, Antonio, 2022. "Hybridizing waterborne transport: Modeling and simulation of low-emissions hybrid waterbuses for the city of Venice," Energy, Elsevier, vol. 244(PB).
    18. Çetin, Gürcan & Özkaraca, Osman & Keçebaş, Ali, 2021. "Development of PID based control strategy in maximum exergy efficiency of a geothermal power plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    19. Bi, Huibo & Shang, Wen-Long & Chen, Yanyan & Wang, Kezhi & Yu, Qing & Sui, Yi, 2021. "GIS aided sustainable urban road management with a unifying queueing and neural network model," Applied Energy, Elsevier, vol. 291(C).
    20. Hu, Haowen & Ou, Kai & Yuan, Wei-Wei, 2023. "Fused multi-model predictive control with adaptive compensation for proton exchange membrane fuel cell air supply system," Energy, Elsevier, vol. 284(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:212:y:2020:i:c:s0360544220316947. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.