[1]王定标,段鸿鑫,王光辉,等.跨临界 CO2 循环系统控制优化策略的研究进展[J].郑州大学学报(工学版),2024,45(02):1-11.[doi:10.13705/j.issn.1671-6833.2024.02.013]
 WANG Dingbiao,DUAN Hongxin,WANG Guanghui,et al.Research Progress of Control Optimization Strategies for Transcritical CO2 Cycle System[J].Journal of Zhengzhou University (Engineering Science),2024,45(02):1-11.[doi:10.13705/j.issn.1671-6833.2024.02.013]
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跨临界 CO2 循环系统控制优化策略的研究进展()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
45卷
期数:
2024年02期
页码:
1-11
栏目:
出版日期:
2024-03-06

文章信息/Info

Title:
Research Progress of Control Optimization Strategies for Transcritical CO2 Cycle System
作者:
王定标12 段鸿鑫12 王光辉12 申奥奇12 刘鹤羽1秦翔12
1. 郑州大学 机械与动力工程学院,河南 郑州 450001;2. 新能源清洁利用技术与节能装备河南省国际联合实验 室,河南 郑州 450001
Author(s):
WANG Dingbiao 12 DUAN Hongxin 12 WANG Guanghui 12 SHEN Aoqi 12 LIU Heyu 12 QIN Xiang 12
1. School of Mechanical and Power Engineering, Zhengzhou University, Zhengzhou 450001, China; 2. Henan International Joint Laboratory of New Energy Clean Utilization Technology and Energy Saving Equipment, Zhengzhou 450001, China
关键词:
跨临界 CO2 循环系统 优化 控制策略 预测控制
Keywords:
transcritical CO2 cycle system optimization control strategy predictive control
分类号:
TK123;TB65;TP13
DOI:
10.13705/j.issn.1671-6833.2024.02.013
文献标志码:
A
摘要:
控制策略作为跨临界 CO2 循环系统的重要组成部分,是保证系统高效节能运行的关键。 介绍了系统最优 排气压力经验计算和泊金汉 π 定理的反馈控制、基于梯度追踪和极值寻优的实时在线控制以及基于神经网络的预 测控制等,详细分析了系统控制策略的发展历程和未来发展趋势,并总结如下:离线控制建立简单、成本低,但易受 到环境因素和系统部件变化的影响而导致控制性能降低;实时在线控制策略可以实时追踪系统最大能源效率对应 的排气压力,但由于寻优过程费时较长,导致控制系统的收敛时间过长;模型预测控制系统可以实现实时优化和快 速收敛,有着良好的发展前景。 结合新能源汽车、建筑供暖、轨道交通、商超冷藏、军工等实际场景对跨临界 CO2 循 环系统控制策略的应用特点和未来发展趋势进行分析,进一步说明了提高控制策略的适用性是未来研究的重要方 向,并分析将广义预测控制、强化学习等具有自适应属性的方法应用于跨临界 CO2 循环系统控制策略的可行性,同 时探讨了开发适用于大规模循环系统和储能系统控制策略在我国“双碳”背景下的重要意义。
Abstract:
As an important part of the transcritical CO2 cycle system, the control strategy played the key role to ensure the high efficiency and energy saving operation of the system. Studies of control strategies were examined such as the feedback control based on the empirical calculation of the optimal diacharge pressure of the system and the Buckingham π theorem, the real-time online control based on gradient tracking and extreme seeking, and the predictive control based on the neural network, etc. The development history and future development trend of the system control strategy were analysed and summarized in detail. Off-line control was easy to establish with low cost, but it was easily affected by environmental factors and changes in system components, resulting in reducing control performance; The real-time online control strategy could track the discharge pressure corresponding to the maximum energy efficiency of the system in real time, but due to the long optimization process, the convergence time of the control system was too long. Model predictive control system could realize real-time optimization and rapid convergence, and had a good development prospect. Combined with the practical scenarios of new energy vehicles, building heating, rail transit, commercial refrigeration, military industry and other practical scenarios, the application characteristics and future development trend of the control strategy of the transcritical CO2 cycle system were explored, and it was further explained that improving the applicability of the control strategy was an important direction for future research. The feasibility of applying adaptive methods such as generalized predictive control and reinforcement learning to the control strategy of transcritical CO2 cycle system was proposed, and the significance of developing control strategy for large-scale cycle system and energy storage system in China with the background of “ double-carbon” was discussed.

参考文献/References:

[1] International Energy Agency. The future of heat pumps [R] . Paris: IEA, 2022.

[2] XIANG X Y, ZHAO X C, JIANG P N, et al. Scenario analysis of hydrofluorocarbons emission reduction in China′s mobile air-conditioning sector[ J] . Advances in Climate Change Research, 2022, 13(5) : 578-586. 
[3] LORENTZEN G, PETTERSEN J. A new, efficient and environmentally benign system for car air-conditioning [ J ] . International Journal of Refrigeration, 1993, 16 (1) : 4-12. 
[4] QIN X, ZHANG Y X, WANG D B, et al. System development and simulation investigation on a novel compression / ejection transcritical CO2 heat pump system for simultaneous cooling and heating[ J] . Energy Conversion and Management, 2022, 259: 115579. 
[5] FENG F, ZHANG Z, LIU X F, et al. The influence of internal heat exchanger on the performance of transcritical CO2 water source heat pump water heater[ J] . Energies, 2020, 13(7) : 1787. 
[6] GHAZIZADE-AHSAEE H, AMERI M, BANIASAD ASKARI I. A comparative exergo-economic analysis of four configurations of carbon dioxide direct-expansion geothermal heat pump[ J] . Applied Thermal Engineering, 2019, 163: 114347. 
[7] AGHAGOLI A, SORIN M. CFD modelling and exergy analysis of a heat pump cycle with Tesla turbine using CO2 as a working fluid [ J] . Applied Thermal Engineering, 2020, 178: 115587. 
[8] 王迪, 王定标, 杨雨燊, 等. 跨临界 CO2 热泵系统最 优排气压力模拟与实验研究[ J] . 郑州大学学报( 工 学版) , 2021, 42(4) : 33-39. WANG D, WANG D B, YANG Y S, et al. Simulation and experimental analyses on the optimal discharge pressure of a transcritical CO2 heat pump system[ J] . Journal of Zhengzhou University ( Engineering Science) , 2021, 42(4) : 33-39.
[9] 胡斌, 李耀宇, 曹锋, 等. 跨临界 CO2 热泵系统最优 排气压力的极值搜索控制 [ J] . 制冷学报, 2016, 37 (3) : 81-87. HU B, LI Y Y, CAO F, et al. Extremum seeking control of discharge pressure optimization for transcritical CO2 heat pump systems [ J] . Journal of Refrigeration, 2016, 37(3) : 81-87. 
[10] WANG W Y, ZHAO Z F, ZHOU Q, et al. Model predictive control for the operation of a transcritical CO2 air source heat pump water heater [ J ] . Applied Energy, 2021, 300: 117339.
[11] YANG L X, QIN X, ZHAO L H, et al. Analysis and comparison of influence factors of hot water temperature in transcritical CO2 heat pump water heater: an experimental study[ J] . Energy Conversion and Management, 2019, 198: 111836. [12] CHEN Y, GU J J. The optimum high pressure for CO2 transcritical refrigeration systems with internal heat exchangers [ J ] . International Journal of Refrigeration, 2005, 28(8) : 1238-1249. 
[13] QI P C, HE Y L, WANG X L, et al. Experimental investigation of the optimal heat rejection pressure for a transcritical CO2 heat pump water heater [ J ] . Applied Thermal Engineering, 2013, 56(1 / 2) : 120-125. 
[14] LIANG X Y, HE Y J, CHENG J H, et al. Difference analysis on optimal high pressure of transcritical CO2 cycle in different applications[ J] . International Journal of Refrigeration, 2019, 106: 384-391. 
[15] 刘遵超. 二氧化碳车用空调系统气冷器关键技术研究 [D] . 郑州: 郑州大学, 2018. LIU Z C. Research on key technology of gas cooler in carbon dioxide automotive air conditioning system [ D ] . Zhengzhou: Zhengzhou University, 2018.
[16] YIN X, CAO F, WANG J, et al. Investigations on optimal discharge pressure in CO2 heat pumps using the GMDH and PSO-BP type neural network———part A: theoretical modeling[ J] . International Journal of Refrigeration, 2019, 106: 549-557. 
[17] QIN X, ZHANG F, ZHANG D W, et al. Experimental and theoretical analysis of the optimal high pressure and peak performance coefficient in transcritical CO2 heat pump [ J ] . Applied Thermal Engineering, 2022, 210: 118372. 
[18] KAUF F. Determination of the optimum high pressure for transcritical CO2 -refrigeration cycles [ J ] . International Journal of Thermal Sciences, 1999, 38(4) : 325-330.
[19] WANG S G, TUO H F, CAO F, et al. Experimental investigation on air-source transcritical CO2 heat pump water heater system at a fixed water inlet temperature[ J] . International Journal of Refrigeration, 2013, 36( 3): 701 - 716. 
[20] LIAO S M, ZHAO T S, JAKOBSEN A. A correlation of optimal heat rejection pressures in transcritical carbon dioxide cycles [ J] . Applied Thermal Engineering, 2000, 20(9) : 831-841. 
[21] LI C H, JIANG P X, ZHU Y H. Optimal compressor discharge pressure and performance characteristics of transcritical CO2 heat pump for crude oil heating[ J] . International Journal of Refrigeration, 2022, 144: 99-107.
[22] POPOV G, LEGUTKO S, KLIMENTOV K, et al. Aplying criteria equations in studying the energy efficiency of pump systems[ J] . Energies, 2021, 14(17) : 5256. 
[23] QIN X, LIU H D, MENG X R, et al. A study on the compressor frequency and optimal discharge pressure of the transcritical CO2 heat pump system[ J] . International Journal of Refrigeration, 2019, 99: 101-113. 
[24] QIN X, ZHANG D W, ZHANG F, et al. Experimental and numerical study on heat transfer of gas cooler under the optimal discharge pressure[ J] . International Journal of Refrigeration, 2020, 112: 229-239. 
[25] DAI C, QIN X. Experimental study on heating performance and a novel calculation method of water outlet temperature based on air source transcritical CO2 heat pump system [ J ] . Frontiers in Energy Research, 2022, 10: 888562. [26] 赵靖华, 陶晶, 解方喜, 等. 用于跨临界 CO2 汽车空 调系统 性 能 优 化 的 控 制 仿 真 [ J] . 系 统 仿 真 学 报, 2016, 28(2) : 492-497. ZHAO J H, TAO J, XIE F X, et al. Simulation of performance optimization control about transcritical CO2 automotive air conditioning system [ J ] . Journal of System Simulation, 2016, 28(2) : 492-497. 
[27] 王静, 孙西峰, 方健珉, 等. 跨临界 CO2 汽车空调多 PID 控制动态性能仿真研究[ J] . 西安交通大学学报, 2020, 54(8) : 168-176. WANG J, SUN X F, FANG J M, et al. Dynamic simulation of PID control in transcritical CO2 automobile air conditioning system[ J] . Journal of Xi′an Jiaotong University, 2020, 54(8) : 168-176. 
[28] ZHANG W J, ZHANG C L. A correlation-free on-line optimal control method of heat rejection pressures in CO2 transcritical systems[ J] . International Journal of Refrigeration, 2011, 34(4) : 844-850. 
[29] PEÑARROCHA I, LLOPIS R, TÁRREGA L, et al. A new approach to optimize the energy efficiency of CO2 transcritical refrigeration plants[ J] . Applied Thermal Engineering, 2014, 67(1 / 2) : 137-146. 
[30] KIM M S, SHIN C S, KIM M S. A study on the real time optimal control method for heat rejection pressure of a CO2 refrigeration system with an internal heat exchanger [J]. International Journal of Refrigeration, 2014, 48: 87- 99. 
[31] KIM M S, KANG D H, KIM M S, et al. Investigation on the optimal control of gas cooler pressure for a CO2 refrigeration system with an internal heat exchanger[ J] . International Journal of Refrigeration, 2017, 77: 48-59. 
[32] HU B, LI Y Y, WANG R Z, et al. Real-time minimization of power consumption for air-source transcritical CO2 heat pump water heater system[ J] . International Journaof Refrigeration, 2018, 85: 395-408.
[33] RAMPAZZO M, CERVATO A, CORAZZOL C, et al. Energy-efficient operation of transcritical and subcritical CO2 inverse cycles via extremum seeking control [ J ] . Journal of Process Control, 2019, 81: 87-97. 
[34] CUI C, REN J H, SONG Y L, et al. Multi-variable extreme seeking control for efficient operation of sub-cooler vapor injection trans-critical CO2 heat pump water heater [ J ] . Applied Thermal Engineering, 2021, 184: 116261. 
[35] CUI C, ZONG S, SONG Y L, et al. Experimental investigation of the extreme seeking control on a transcritical CO2 heat pump water heater[ J] . International Journal of Refrigeration, 2022, 133: 111-122. 
[36] CUI C, REN J H, RAMPAZZO M, et al. Real-time energy-efficient operation of a dedicated mechanical subcooling based transcritical CO2 heat pump water heater via multi-input single-output extreme seeking control[ J] . International Journal of Refrigeration, 2022, 144: 76-89. 
[37] SONG Y L, CAO F. The evaluation of optimal discharge pressure in a water-precooler-based transcritical CO2 heat pump system [ J] . Applied Thermal Engineering, 2018, 131: 8-18.
[38] SONG Y L, CAO F. The evaluation of the optimal medium temperature in a space heating used transcritical airsource CO2 heat pump with an R134a subcooling device [ J] . Energy Conversion and Management, 2018, 166: 409-423. [39] MAIER L, SCHÖNEGGE M, HENN S, et al. Assessing mixed-integer-based heat pump modeling approaches for model predictive control applications in buildings [ J ] . Applied Energy, 2022, 326: 119894. 
[40] ESTRADA-FLORES S, MERTS I, DE KETELAERE B, et al. Development and validation of “ grey-box” models for refrigeration applications: a review of key concepts [ J ] . International Journal of Refrigeration, 2006, 29 (6) : 931-946. 
[41] WANG H D, WANG W Y, SONG Y L, et al. Data-driven model predictive control of transcritical CO2 systems for cabin thermal management in cooling mode[ J] . Applied Thermal Engineering, 2023, 235: 121337. 
[42] WANG L Y, ZHU Y L. Neural-network-based nonlinear model predictive control of multiscale crystallization process[ J] . Processes, 2022, 10(11) : 2374. 
[43] SONG Y L, YANG D F, LI M J, et al. Investigations on optimal discharge pressure in CO2 heat pumps using the GMDH and PSO-BP type neural network———part B: experimental study [ J] . International Journal of Refrigeration, 2019, 106: 248-257.
[44] ZHANG T, CAO F, SONG Y L, et al. The model predictive control strategy of the transcritical CO2 air conditioning system used in railway vehicles [ J ] . Applied Thermal Engineering, 2023, 218: 119376. 
[45] TAHERI S, HOSSEINI P, RAZBAN A. Model predictive control of heating, ventilation, and air conditioning ( HVAC) systems: a state-of-the-art review[ J] . Journal of Building Engineering, 2022, 60: 105067. 
[46] GOTO H, GOTO M, SUEYOSHI T. Consumer choice on ecologically efficient water heaters: marketing strategy and policy implications in Japan[ J] . Energy Economics, 2011, 33(2) : 195-208.
[47] 武悦, 郑铭铸, 杨坚, 等. 电动汽车 CO2 热泵系统采 暖实 验 研 究 及 模 拟 分 析 [ J] . 制 冷 技 术, 2019, 39 (5) : 33-38. WU Y, ZHENG M Z, YANG J, et al. Experimental study and simulation analysis on heating performance of CO2 heat pump system for electric vehicles[ J] . Chinese Journal of Refrigeration Technology, 2019, 39 ( 5 ) : 33 -38. 
[48] 中车大连机车研究所有限公司. 一种轨道交通车辆 CO2 空调系统压力保护控制系统: CN202120260818. 2 [ P] . 2021-11-09. CRRC Dalian Locomotive. A pressure protection control system for CO2 air conditioning system of rail transit vehicles: CN202120260818. 2[ P] . 2021-11-09. 
[49] 陈威. R744 双温超市制冷系统的优化控制研究[ D] . 济南: 山东大学, 2020. CHEN W. Study on optimal control of a R744 two-temperature supermarket refrigeration system [ D ] . Jinan: Shandong University, 2020. 
[50] GE Y T, TASSOU S A. Control optimisation of CO2 cycles for medium temperature retail food refrigeration systems[ J] . International Journal of Refrigeration, 2009, 32(6) : 1376-1388. 
[51] DADPOUR D, GHOLIZADEH M, ESTIRI M, et al. Multi objective optimization and 3E analyses of a novel supercritical / transcritical CO2 waste heat recovery from a ship exhaust[ J] . Energy, 2023, 278: 127843. 
[52] YANG D Z, LI Y, XIE J, et al. Energetic and entropy analysis of a novel transcritical CO2 two-stage compression / ejector refrigeration cycle for shipboard cold chamber[ J] . Thermal Science, 2023, 27(4) : 2607-2621. 
[53] SUN G, CHEN J L, YONG Y Q, et al. Generalized predictive control of spacecraft attitude with adaptive predictive period[ J] . International Journal of Adaptive Control and Signal Processing, 2022, 36(3) : 596-606. 
[54] HU Z, ZHANG J F, XIE L, et al. A generalized predictive control for remote cardiovascular surgical systems[ J] . ISA Transactions, 2020, 104: 336-344. 
[55] CHEN Z, CUI J L, LEI Z Z, et al. Design of an improved implicit generalized predictive controller for temperature control systems [ J ] . IEEE Access, 2020, 8: 13924-13936. 
[56] HAN G, JOO H J, LIM H W, et al. Data-driven heat pump operation strategy using rainbow deep reinforcement learning for significant reduction of electricity cost [ J] . Energy, 2023, 270:126913. 
[57] WANG Y C, FENG H R, XI X Y. Monitoring and autonomous control of Beijing Subway HVAC system for enersustainability[ J] . Energy for Sustainable Development, 2017, 39: 1-12. 
[58] WANG Y Q, RAO, Z H, LIU J X, et al. An optimized control strategy for integrated solar and air-source heat pump water heating system with cascade storage tanks [ J] . Energy and Buildings, 2020,210:109766.
[59] HAN Z W, BAI C G, MA X, et al. Study on the performance of solar-assisted transcritical CO2 heat pump system with phase change energy storage suitable for rural houses[ J] . Solar Energy, 2018, 174: 45-54.

更新日期/Last Update: 2024-03-08