基于因果序图的氢能一体化电站运行过程建模及能量流控制策略

doi:10.19595/j.cnki.1000-6753.tces.240015

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (3733 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Hydrogen energy storage technology is characterized by cleanliness, no self-discharge, and high energy density, making it a highly promising energy storage technology. When the grid has surplus power, hydrogen energy storage absorbs the excess power; when the grid power is insufficient, hydrogen energy is converted into electricity to supply power to users. However, currently, most research on hydrogen energy storage is still in the stage of business model and economic feasibility studies, lacking operation principles and modeling research. To solve these problems, we propose an integrated hydrogen energy power station (IHEPS) that integrates three parts: hydrogen production, hydrogen storage, and fuel cell power generation. Based on causal ordering graph (COG), we establish the operation process model and energy flow control strategy of IHEPS. The proposed model and control strategy not only clearly represent the operation process of the IHEPS but also, by using model inversion control for rigid relationships, reduce error feedback time and enhance controller performance, thus better realizing the energy flow management of the IHEPS.
Firstly, the composition structure, working principles, and control system configuration of the box-type IHEPS are proposed. Then, according to the characteristics of IHEPS electricity-hydrogen-electricity energy conversion, a control-oriented operating dynamic model of hydrogen production, storage and power generation integrated power station is established based on the COG. This model can clearly reflect the relationships between different physical quantities of the IHEPS. Next, based on the established model and the principle of natural causality, a power and hydrogen flow control strategy for the operation process of the IHEPS is designed. This strategy adopts model inversion control for processes with rigid relationships to reduce error feedback time and enhance controller performance. Finally, tests are conducted on the RT-Lab hardware-in-the-loop simulation platform to analyze the relationships between different physical quantities of the integrated station. Comparison results with PID and ADRC methods indicate that the proposed strategy outperforms traditional methods in terms of response speed, convergence accuracy, and operational efficiency, and can realize the energy flow management of IHEPS more effectively.
According to the results of the RT-Lab semi-physical simulation test, the proposed COG method for electro-hydrogen storage operation control does not have start-up and shut-down dead zones, and can achieve fast and accurate convergence across all operating conditions, reducing the convergence time by about 300 seconds compared to PID and ADRC methods; In the hydrogen-to-electricity generation control process, the steady-state overshoot of the COG method is only 0.128%, which is a reduction of 46.7% and 34% compared to PID and ADRC respectively; throughout the operating process, the operating efficiency of the IHEPS controlled by the proposed COG method increased from 21.2% under PID control or ADRC to 26%, an increase of approximately 22.6%. Therefore, the proposed strategy is superior to traditional methods in response speed, convergence accuracy, and operational efficiency, and can more effectively manage the energy flow in the operation of IHEPS.
The conclusions are as follows: (1) This paper proposes a type-box IHEPS that can be combined with renewable energy sources for large-scale consumption of new energy. (2) Based on COG, a control-oriented dynamic model for the IHEPS operation process is established. This model can clearly reflect the relationships between different physical quantities in the integrated power station and characterize the electro-hydrogen-electric operation process of the integrated station. (3) A COG-based control strategy for power and hydrogen flow in the integrated power station has been proposed, realizing the energy flow management of the integrated power station. (4) The results of semi-physical simulation show that compared with the traditional control methods, the proposed control strategy has the advantages of no start-stop dead zone, fast response speed, high convergence accuracy and high operating efficiency.

Key words： Integrated hydrogen energy power station energy flow control causal ordering graph hardware in loop test

Received: 04 January 2024

PACS:

TM615

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Ma Libo
	Zhao Hongshan
	Yu Yang
	Pan Sichao

Cite this article:

Ma Libo,Zhao Hongshan,Yu Yang等. Operation Process Modeling and Energy Flow Control Strategy of Integrated Hydrogen Energy Power Station Based on Causal Ordering Graph[J]. Transactions of China Electrotechnical Society, 2024, 39(16): 5220-5237.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.240015 OR https://dgjsxb.ces-transaction.com/EN/Y2024/V39/I16/5220

[1] 郜捷, 宋洁, 王剑晓, 等. 支撑中国能源安全的电氢耦合系统形态与关键技术[J]. 电力系统自动化, 2023, 47(19): 1-15.
Gao Jie, Song Jie, Wang Jianxiao, et al.Form and key technologies of integrated electricity-hydrogen system supporting energy security in China[J]. Automation of Electric Power Systems, 2023, 47(19): 1-15.
[2] Jiao Kui, Xuan Jin, Du Qing, et al.Designing the next generation of proton-exchange membrane fuel cells[J]. Nature, 2021, 595(7867): 361-369.
[3] 郑先娜, 林瑞全. 质子交换膜燃料电池控制策略综述[J]. 电气技术, 2017, 18(11): 1-5, 24.
Zheng Xianna, Lin Ruiquan.Summarization of control strategy for proton exchange membrane fuel cell[J]. Electrical Engineering, 2017, 18(11): 1-5, 24.
[4] 马睿, 任子俊, 谢任友, 等. 基于模型特征分析的质子交换膜燃料电池建模研究综述[J]. 中国电机工程学报, 2021, 41(22): 7712-7730.
Ma Rui, Ren Zijun, Xie Renyou, et al.A comprehensive review for proton exchange membrane fuel cell modeling based on model feature analysis[J]. Proceedings of the CSEE, 2021, 41(22): 7712-7730.
[5] 敖文杰, 陈家伟, 陈杰, 等. 燃料电池-锂电池混合供电系统的无源控制策略及参数设计方法[J]. 电工技术学报, 2024, 39(2): 580-594.
Ao Wenjie, Chen Jiawei, Chen Jie, et al.Passivity-based control strategy and parameter design method for fuel cell-lithium battery hybrid power supply system[J]. Transactions of China Electrotechnical Society, 2024, 39(2): 580-594.
[6] Hu Peng, Cao Guangyi, Zhu Xinjian, et al.Modeling of a proton exchange membrane fuel cell based on the hybrid particle swarm optimization with Levenberg-Marquardt neural network[J]. Simulation Modelling Practice and Theory, 2010, 18(5): 574-588.
[7] Zhong Zhidan, Zhu Xinjian, Cao Guangyi.Modeling a PEMFC by a support vector machine[J]. Journal of Power Sources, 2006, 160(1): 293-298.
[8] 杨德友, 崔冬晓, 蔡国伟. 基于云智能控制器的燃料电池最大功率跟踪策略[J]. 电工技术学报, 2018, 33(14): 3362-3370.
Yang Deyou, Cui Dongxiao, Cai Guowei.A maximum power point tracking technology for fuel cells using cloud model based intelligent controller[J]. Tran-sactions of China Electrotechnical Society, 2018, 33(14): 3362-3370.
[9] 张雪霞, 黄平, 蒋宇, 等. 动态机车工况下质子交换膜燃料电池电堆衰退性能分析[J]. 电工技术学报, 2022, 37(18): 4798-4806.
Zhang Xuexia, Huang Ping, Jiang Yu, et al.Degradation performance analysis of proton exchange membrane fuel cell stack under dynamic locomotive conditions[J]. Transactions of China Electrotechnical Society, 2022, 37(18): 4798-4806.
[10] 罗悦齐, 张嵩, 高丽萍, 等. 质子交换膜燃料电池低温启动水热管理特性及优化[J]. 电工技术学报, 2018, 33(11): 2626-2635.
Luo Yueqi, Zhang Song, Gao Liping, et al.Optimization of water and thermal management in proton exchange membrane fuel cell during low temperature startup[J]. Transactions of China Electrotechnical Society, 2018, 33(11): 2626-2635.
[11] McKay D A, Stefanopoulou A G, Cook J. Model and experimental validation of a controllable membrane-type humidifier for fuel cell applications[C]//2008 American Control Conference, Seattle, WA, USA, 2008: 312-317.
[12] Pukrushpan J T, Peng Huei, Stefanopoulou A G.Control-oriented modeling and analysis for automotive fuel cell systems[J]. Journal of Dynamic Systems, Measurement, and Control, 2004, 126(1): 14-25.
[13] 孙鹤旭, 李争, 陈爱兵, 等. 风电制氢技术现状及发展趋势[J]. 电工技术学报, 2019, 34(19): 4071-4083.
Sun Hexu, Li Zheng, Chen Aibing, et al.Current status and development trend of hydrogen production technology by wind power[J]. Transactions of China Electrotechnical Society, 2019, 34(19): 4071-4083.
[14] 胡俊杰, 童宇轩, 刘雪涛, 等. 计及精细化氢能利用的综合能源系统多时间尺度鲁棒优化策略[J]. 电工技术学报, 2024, 39(5): 1419-1435.
Hu Junjie, Tong Yuxuan, Liu Xuetao, et al.Multi-time-scale robust optimization strategy for integrated energy system considering the refinement of hydrogen energy use[J]. Transactions of China Electrotechnical Society, 2024, 39(5): 1419-1435.
[15] Atlam O, Kolhe M.Equivalent electrical model for a proton exchange membrane (PEM) electrolyser[J]. Energy Conversion and Management, 2011, 52(8/9): 2952-2957.
[16] Guilbert D, Vitale G.Variable parameters model of a PEM electrolyzer based model reference adaptive system approach[C]//2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Madrid, Spain, 2020: 1-6.
[17] Hernández-Gómez Á, Ramirez V, Guilbert D, et al.Cell voltage static-dynamic modeling of a PEM electrolyzer based on adaptive parameters: development and experimental validation[J]. Renewable Energy, 2021, 163: 1508-1522.
[18] Mohamed A, Ibrahem H, Yang Rui, et al.Optimization of proton exchange membrane electrolyzer cell design using machine learning[J]. Energies, 2022, 15(18): 6657.
[19] Guilbert D, Zasadzinski M, Rafaralahy H, et al.Modeling of the dynamic behavior of a PEM electrolyzer[C]//2022 10th International Conference on Systems and Control (ICSC), Marseille, France, 2022: 78-84.
[20] 任和, 刘宏伟, 顾亚京, 等. 基于Hammerstein模型的PEM电解槽动态模型[J]. 工程热物理学报, 2022, 43(9): 2324-2332.
Ren He, Liu Hongwei, Gu Yajing, et al.Dynamic modeling of PEM electrolyzer based on Hammerstein model[J]. Journal of Engineering Thermophysics, 2022, 43(9): 2324-2332.
[21] 江悦, 沈小军, 吕洪, 等. 碱性电解槽运行特性数字孪生模型构建及仿真[J]. 电工技术学报, 2022, 37(11): 2897-2908.
Jiang Yue, Shen Xiaojun, Lü Hong, et al.Construction and simulation of operation digital twin model for alkaline water electrolyzer[J]. Transactions of China Electrotechnical Society, 2022, 37(11): 2897-2908.
[22] Selamet Ö F, Acar M C, Mat M D, et al.Effects of operating parameters on the performance of a high-pressure proton exchange membrane electrolyzer[J]. International Journal of Energy Research, 2013, 37(5): 457-467.
[23] Espinosa-López M, Darras C, Poggi P, et al.Modelling and experimental validation of a 46 kW PEM high pressure water electrolyzer[J]. Renewable Energy, 2018, 119: 160-173.
[24] 陈锦洲, 林飞, 何洪文, 等. 质子交换膜燃料电池/电解槽系统建模及负荷追踪策略[J]. 电工技术学报, 2020, 35(增刊2): 636-643.
Chen Jinzhou, Lin Fei, He Hongwen, et al.Proton exchange membrane fuel cell/electrolyzer hybrid power system modeling and load tracking strategy[J]. Transactions of China Electrotechnical Society, 2020, 35(S2): 636-643.
[25] 李建林, 梁忠豪, 李光辉, 等. 质子交换膜电解槽控制策略研究[J]. 电工技术学报, 2023, 38(17): 4787-4799.
Li Jianlin, Liang Zhonghao, Li Guanghui, et al.Research on control strategy of proton exchange membrane electrolyzer[J]. Transactions of China Electrotechnical Society, 2023, 38(17): 4787-4799.
[26] Dale N V, Mann M D, Salehfar H.Semiempirical model based on thermodynamic principles for determining 6kW proton exchange membrane electrolyzer stack characteristics[J]. Journal of Power Sources, 2008, 185(2): 1348-1353.
[27] De Lorenzo G, Agostino R, Fragiacomo P.Dynamic electric simulation model of a proton exchange membrane electrolyzer system for hydrogen production[J]. Energies, 2022, 15: 6437.
[28] Abdin Z, Webb C J, Gray E M.Modelling and simulation of a proton exchange membrane (PEM) electrolyser cell[J]. International Journal of Hydrogen Energy, 2015, 40(39): 13243-13257.
[29] 马若冉, 赵晓丽, 张荣达. 新型电力系统背景下氢能综合利用站发展的商业模式分析[J]. 科技管理研究, 2024, 44(1): 183-191.
Ma Ruoran, Zhao Xiaoli, Zhang Rongda.Research on the business model for the development of hydrogen energy comprehensive utilization station under the background of the new power system[J]. Science and Technology Management Research, 2024, 44(1): 183-191.
[30] 滕越, 王缔, 赵骞, 等. 氢综合能源电站应用前景[J]. 科技与创新, 2022(23): 131-133, 139.
[31] 毕丽敏. 某兆瓦级氢能综合利用站消防水系统设计[J]. 工业用水与废水, 2022, 53(3): 77-80.
Bi Limin.Design of fire water system for a MW hydrogen energy comprehensive utilization station[J]. Industrial Water & Wastewater, 2022, 53(3): 77-80.
[32] 徐圆圆, 滕越, 赵骞, 等. 质子交换膜燃料电池电站多米诺事故概率和风险研究[J]. 中国安全生产科学技术, 2022, 18(7): 187-192.
Xu Yuanyuan, Teng Yue, Zhao Qian, et al.Probability and risk analysis of domino accidents in proton exchange membrane fuel cell power plants[J]. Journal of Safety Science and Technology, 2022, 18(7): 187-192.
[33] 王金全, 王春明, 张永, 等. 氢能发电及其应用前景[J]. 解放军理工大学学报(自然科学版), 2002, 3(6): 50-56.
Wang Jinquan, Wang Chunming, Zhang Yong, et al.Hydrogen-power and its prospects for applications[J]. Journal of PLA University of Science and Technology (Natural Science), 2002, 3(6): 50-56.
[34] Zeng Jia, Barre P J, Degobert P.Modeling and thrust control of PMLSM Using principle of local energy[C]//ICEMS 2003-Proceedings of the 6th International Conference on Electrical Machines and Systems, Beijing, China, 2003, 1: 26-30.
[35] Li P, Degobert P, Francois B, et al.Modeling and control of a gas micro turbine generator by using a causal ordering graph[C]//The Proceedings of the Multiconference on Computational Engineering in Systems Applications, Beijing, China, 2006: 271-277.
[36] Hautier J P, Barre P J.The causal ordering graph a tool for system modelling and control law synthesis[J]. Studies in Informatics and Control, 2004, 13(4): 265-283.
[37] 林渭勋. 现代电力电子技术[M]. 北京: 机械工业出版社, 2006.
[38] Tiktak J.Heat management of PEM electrolysis[D]. Delft: Delft University of Technology, 2019.
[39] Roy A, Watson S, Infield D.Comparison of electrical energy efficiency of atmospheric and high-pressure electrolysers[J]. International Journal of Hydrogen Energy, 2006, 31(14): 1964-1979.
[40] 张瑜, 张桥. 考虑压缩比和进口温度的多级压缩总能耗分析[J]. 计算机与应用化学, 2018, 35(9): 711-718.
Zhang Yu, Zhang Qiao.Analysis of energy consumption for multi-stage compression considering the compression ratio and inlet temperature[J]. Computers and Applied Chemistry, 2018, 35(9): 711-718.
[41] Heywood J.Internal Combustion Engine Fundamentals[M]. 2nd ed. New York: McGraw-Hill Education, 2019.
[42] O’Hayre R, Cha S W, Colella W, et al. Fuel Cell Fundamentals[M]. Hoboken: John Wiley & Sons, 2016.
[43] Liu Zhixiang, Yang Lizhai, Mao Zongqiang, et al.Behavior of PEMFC in starvation[J]. Journal of Power Sources, 2006, 157(1): 166-176.
[44] Ma Libo, Zhao Hongshan, Qu Yuehan, et al.Reduced-order active disturbance rejection control method for PEMFC air intake system based on the estimation of oxygen excess ratio[J]. IET Renewable Power Generation, 2023, 17(4): 951-963.