Regulation of tower-valve joint optimization model based on directed sampling multi-objective evolutionary algorithm

Yu ZHAI, Xiaolian LIU, Xueni WANG, Leike ZHANG, Bei YI, Yu TIAN

Journal of Tsinghua University(Science and Technology) ›› 2026, Vol. 66 ›› Issue (2) : 309-323.

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Journal of Tsinghua University(Science and Technology) ›› 2026, Vol. 66 ›› Issue (2) : 309-323. DOI: 10.16511/j.cnki.qhdxxb.2026.27.002
Hydraulic Engineering

Regulation of tower-valve joint optimization model based on directed sampling multi-objective evolutionary algorithm

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Abstract

Objective: Water supply systems with branch pipes, relying exclusively on valve control, frequently demonstrate deficiencies in effectively mitigating water hammer during valve closure. This inadequacy often results in transient system pressures surpassing safety thresholds, thereby compromising operational safety. Consequently, there is an imperative for research on the combined protection of bidirectional surge tanks and valves in such systems. However, the coordinated control of tanks and valves involves numerous variables and strongly coupled nonlinear relationships, in which parameters interact, rendering it a complex optimization problem. In light of the challenges associated with meeting multiple safety requirements concurrently, it is essential to conduct a comprehensive investigation into the synergistic mechanisms between tanks and valves and to formulate a corresponding optimization and decision-making method that will facilitate the attainment of globally optimal control strategies. Methods: The present study developed an integrated optimization model for the coordinated control of tanks and valves. The model treats the control parameters of both the valves and the bidirectional surge tank as decision variables. The objective functions were defined as minimizing the extreme pressure values in the system and shortening the valve closure duration. A novel optimization and decision-making method was proposed, which utilizes a large-scale multi-objective evolutionary algorithm with directed sampling combined with the technique for order preference by similarity to ideal solution (LMOEA-DS-TOPSIS). To solve the optimization model, LMOEA-DS was employed, and TOPSIS was applied to select the optimal solution from the generated Pareto front. Results: An investigation into a particular water supply project in Shandong, China, revealed that the combined control of the main pipeline's end valve and the branch pipe's end valve was inadequate in ensuring safety compliance. This finding necessitated further optimization of the subsequent tank-valve joint control strategy. To address this challenge, the LMOEA-DS algorithm was employed to solve the established multi-objective optimization model for tank-valve coordination. The parameters were set as follows: 50 individuals, 30 guiding solutions, and a total population size of 8 000. The hypervolume (HV) and spacing (SP) metrics were 32 062.6 and 0.527 8, respectively, indicating adequate convergence performance. Moreover, the resulting Pareto front demonstrates considerable spans of 14.62 m, 4.36 m, and 240 s across the three objective dimensions, with solutions exhibiting uniform distribution and adequate accessibility. This outcome suggests that Pareto solutions, when distributed widely, can be obtained in a relatively brief computational time. The optimization effect is particularly noteworthy in the context of the positive pressure protection objective. The collective analysis of these results substantiates the effectiveness of the LMOEA-DS algorithm in addressing the proposed model and validates the rationality of the parameter settings. Subsequently, employing a TOPSIS analysis to select the optimal tank-valve joint scheme from the Pareto front resulted in reductions of 21.25% and 47.72%, respectively, in the amplitude of the maximum and minimum pressure envelope lines. Furthermore, a 5.43% shortening of the total valve closure time was demonstrated. This outcome significantly enhanced the operational stability of the system and confirmed the superiority of the LMOEA-DS-TOPSIS optimization and decision-making method. Conclusions: The results verify that the synergistic strategy employing a bidirectional surge tank and valves exhibits significantly superior effectiveness in safeguarding against transient processes in comparison to conventional single-method approaches. Moreover, the outcomes corroborate the effectiveness of the proposed LMOEA-DS-TOPSIS optimization and decision-making method for coordinated tank-valve control. The research findings not only successfully achieve effective transient protection for water supply systems with branch pipes but also provide an innovative solution for the design and optimization of water hammer protection systems in the field of engineering.

Key words

water hammer protection / tower-valve joint regulation / multi-objective optimization / urban water supply

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Yu ZHAI , Xiaolian LIU , Xueni WANG , et al . Regulation of tower-valve joint optimization model based on directed sampling multi-objective evolutionary algorithm[J]. Journal of Tsinghua University(Science and Technology). 2026, 66(2): 309-323 https://doi.org/10.16511/j.cnki.qhdxxb.2026.27.002

References

1
ZHANG X Q , QIAO W B , HUANG J F , et al. Impact and analysis of urban water system connectivity project on regional water environment based on storm water management model (SWMM)[J]. Journal of Cleaner Production, 2023, 423, 138840.
2
张卉, 周俊阳, 王张弛, 等. 给水管网爆管水力水质综合影响分析方法的研究[J]. 安全与环境学报, 2024, 24 (12): 4705- 4713.
ZHANG H , ZHOU J Y , WANG Z C , et al. Research on integrated analysis method of hydraulic and water quality impacts of burst pipes in water supply network[J]. Journal of Safety and Environment, 2024, 24 (12): 4705- 4713.
3
WANG P F , JIANG Z Q , DUAN J F . Burst analysis of water supply pipe based on hydrodynamic simulation[J]. Water Resources Management, 2023, 37 (5): 2161- 2179.
4
WAN W Y , ZHOU Y , GENG C L , et al. Numerical modeling of cavity collapse water hammer in pipeline systems: Internal mechanisms and influential factors of transient flow and secondary pressure rise dynamics[J]. Physics of Fluids, 2024, 36 (8): 087167.
5
薛长青, 叶焰中, 李良庚, 等. 长距离有压管道输水系统的停泵水锤安全防护及优化[J]. 中国农村水利水电, 2016 (8): 205- 208.
XUE C Q , YE Y Z , LI L G , et al. Safety protection and optimization of water hammer in long-distance pressurized pipeline water supply systems[J]. China Rural Water and Hydropower, 2016 (8): 205- 208.
6
LI L T , LI Z W , WANG F F , et al. Study on optimal water hammer protection for high-head and multi-undulation water conveyance system and empirical formulae for pressure head at nodes[J]. Water Supply, 2024, 24 (6): 2127- 2142.
7
杨瑞虎, 王彤, 尚渝钧, 等. 供水管网气液两相流关阀水锤[J]. 排灌机械工程学报, 2022, 40 (6): 596- 602.
YANG R H , WANG T , SHANG Y J , et al. Water hammer of gas-liquid two-phase flow shutoff valve in pipe network[J]. Journal of Drainage and Irrigation Machinery Engineering, 2022, 40 (6): 596- 602.
8
雷春元, 杨瑞虎, 王伟, 等. 傍河多井水源系统水锤模拟及防护研究[J]. 中国给水排水, 2022, 38 (13): 51- 58.
LEI C Y , YANG R H , WANG W , et al. Simulation of water hammer in riverside multi-well water source system and its protection[J]. China Water & Wastewater, 2022, 38 (13): 51- 58.
9
周领, 王小龙, 张海丽, 等. 基于有限体积法的含无压段泵站水锤模拟及调压井优化[J]. 农业工程学报, 2023, 39 (20): 66- 75.
ZHOU L , WANG X L , ZHANG H L , et al. Finite volume method for simulating water hammer in pumping stations with free-surface flow and optimization of surge chamber[J]. Transactions of the Chinese Society of Agricultural Engineering, 2023, 39 (20): 66- 75.
10
石林, 张健, 俞晓东, 等. 长距离多支线输水系统稳压塔降高方案研究[J]. 华中科技大学学报(自然科学版), 2023, 51 (8): 67- 73.
SHI L , ZHANG J , YU X D , et al. Study on reducing height of surge tank in long-distance and multi-branch water conveyance system[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2023, 51 (8): 67- 73.
11
LIU X L , LIU Z R , HOU X P , et al. A parallel multi-objective optimization based on adaptive surrogate model for combined operation of multiple hydraulic facilities in water diversion project[J]. Journal of Hydroinformatics, 2024, 26 (6): 1351- 1369.
12
GHANBARI K , MALEKI A , OCHBELAGH D R . Optimal design of solar/wind/energy storage system-powered RO desalination unit: Single and multi-objective optimization[J]. Energy Conversion and Management, 2024, 315, 118768.
13
WANG X N , MA X M , LIU X L , et al. Research on optimal operation of cascade pumping stations based on an improved sparrow search algorithm[J]. Water Science & Technology, 2023, 88 (8): 1982- 2001.
14
YAZDI J , HOKMABADI A , JALILIGHAZIZADEH M R . Optimal size and placement of water hammer protective devices in water conveyance pipelines[J]. Water Resources Management, 2019, 33 (2): 569- 590.
15
YANG Y , CHEN S J , ZHOU Y R , et al. Method for quantitatively assessing the impact of an inter-basin water transfer project on ecological environment-power generation in a water supply region[J]. Journal of Hydrology, 2023, 618, 129250.
16
LIU Q , LI X F , LIU H T , et al. Multi-objective metaheuristics for discrete optimization problems: A review of the state-of-the-art[J]. Applied Soft Computing, 2020, 93, 106382.
17
宁君, 马一帆, 李志慧, 等. 带有状态/输入量化的无人船有限时间航向跟踪控制[J]. 哈尔滨工程大学学报, 2025, 46 (9): 1701- 1708.
NING J , MA Y F , LI Z H , et al. Unmanned surface vehicle finite-time course tracking control with state and input quantization[J]. Journal of Harbin Engineering University, 2025, 46 (9): 1701- 1708.
18
邱俊明. 弦支穹顶结构的预应力多目标优化及静力稳定性分析[D]. 广州: 华南理工大学, 2022.
QIU J M. Analysis of prestress multi-objective optimization and static stability for suspended dome structures[D]. Guangzhou: South China University of Technology, 2022. (in Chinese)
19
ZHANG Q F , LI H . MOEA/D: A multiobjective evolutionary algorithm based on decomposition[J]. IEEE Transactions on Evolutionary Computation, 2007, 11 (6): 712- 731.
20
QIN S F , SUN C L , JIN Y C , et al. Large-scale evolutionary multiobjective optimization assisted by directed sampling[J]. IEEE Transactions on Evolutionary Computation, 2021, 25 (4): 724- 738.
21
杨文晋, 李永东, 王洪广, 等. 采用多准则决策分析的高功率微波源多目标优化设计[J]. 西安交通大学学报, 2023, 57 (6): 74-85, 94.
YANG W J , LI Y D , WANG H G , et al. Multi-objective optimization design of high-power microwave source based on multi-criteria decision making[J]. Journal of Xi'an Jiaotong University, 2023, 57 (6): 74-85, 94.
22
LAN X Y , GU N B , EGUSQUIZA M , et al. Parameter optimization decision framework for transient process of a pumped storage hydropower system[J]. Energy Conversion and Management, 2023, 286, 117064.
23
杨博, 王俊婷, 俞磊, 等. 基于孔雀优化算法的配电网储能系统双层多目标优化配置[J]. 上海交通大学学报, 2022, 56 (10): 1294- 1307.
YANG B , WANG J T , YU L , et al. Peafowl optimization algorithm based bi-level multi-objective optimal allocation of energy storage systems in distribution network[J]. Journal of Shanghai Jiao Tong University, 2022, 56 (10): 1294- 1307.
24
PENG T , JIN Z Y , XIAO L J . Evaluating low-carbon competitiveness under a DPSIR-Game Theory-TOPSIS model: A case study[J]. Environment, Development and Sustainability, 2022, 24 (4): 5962- 5990.
25
于超. 高校学术创业生态系统形成机理研究——基于学术创业者视角[D]. 成都: 四川大学, 2021.
YU C. Research on the formation mechanism of university academic entrepreneurship ecosystem: From the perspective of academic entrepreneurs[D]. Chengdu: Sichuan University, 2021. (in Chinese)
26
LIU B N , ZHOU J Z , XU Y H , et al. An optimization decision-making framework for the optimal operation strategy of pumped storage hydropower system under extreme conditions[J]. Renewable Energy, 2022, 182, 254- 273.
27
ZHAO Z G , YANG J D , YANG W J , et al. A coordinated optimization framework for flexible operation of pumped storage hydropower system: Nonlinear modeling, strategy optimization and decision making[J]. Energy Conversion and Management, 2019, 194, 75- 93.
28
李海, 王伟, 范磊. 云制造环境下机床装备资源选择方法[J]. 航空学报, 2020, 41 (7): 623540.
LI H , WANG W , FAN L . Selection method of machine tool resources in cloud manufacturing environment[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41 (7): 623540.
29
柯宏发, 刘思峰, 陈永光, 等. 基于灰关联度的多目标规划新求解算法[J]. 系统工程与电子技术, 2010, 32 (3): 544- 547.
KE H F , LIU S F , CHEN Y G , et al. New solution algorithm for multiple objective programming model based on grey relational degree[J]. Systems Engineering and Electronics, 2010, 32 (3): 544- 547.
30
XIAO H L , ZHANG J P , XU M , et al. Study on spatial variability evaluation of hydrometeorological elements based on TOPSIS model[J]. Journal of Hydrology, 2023, 619, 129359.
31
LU Z M , GAO Y , ZHAO W H . A TODIM-based approach for environmental impact assessment of pumped hydro energy storage plant[J]. Journal of Cleaner Production, 2020, 248, 119265.
32
LEI L W , CHEN D Y , MA C , et al. Optimization and decision making of guide vane closing law for pumped storage hydropower system to improve adaptability under complex conditions[J]. Journal of Energy Storage, 2023, 73, 109038.
33
XIN Q L , DU J Y , LIU M S , et al. Experimental study on the effects of two-stage valve closure on the maximum water hammer pressure in micro-hydroelectric system[J]. Journal of Water Process Engineering, 2024, 65, 105886.
34
ZHOU Z , MU Z W , ZHANG H H , et al. Analysis and research on water hammer protection measures based on KY PIPE for long distance pumping station water transmission engineering with pump stoppage[J]. Scientific Reports, 2025, 15 (1): 158.
35
LI Z L , JIN J , PAN Z P , et al. Impact of branch pipe valve closure procedures on pipeline water hammer pressure: A case study of Xinlongkou Hydropower Station[J]. Applied Sciences, 2025, 15 (2): 897.
36
LU M Y , LIU X L , XU G T , et al. Optimal pump-valve coupling operation strategy of complex long-distance water-conveyance systems based on MOC[J]. Ain Shams Engineering Journal, 2024, 15 (1): 102318.
37
WYLIE E B , STREETER V L . Fluid transients in systems[M]. New York: McGraw-Hill Companies, 1993.
38
程永光, 杨建东. 用三维计算流体力学方法计算调压室阻抗系数[J]. 水利学报, 2005, 36 (7): 787- 792.
CHENG Y G , YANG J D . Hydraulic resistance coefficient determination of throttled surge tanks by means of computational fluid dynamics[J]. Journal of Hydraulic Engineering, 2005, 36 (7): 787- 792.
39
练继建, 郑政, 李琳, 等. 多孔并联分段低压输水系统的水力特性和控制[J]. 水利学报, 2006, 37 (8): 950- 957.
LIAN J J , ZHENG Z , LI L , et al. Hydraulic characteristics and control approach of stepped low-pressurized water diversion system with parallel multi-holes in regulation tanks[J]. Journal of Hydraulic Engineering, 2006, 37 (8): 950- 957.
40
REZGHI A , RIASI A , TAZRAEI P . Multi-objective optimization of hydraulic transient condition in a pump-turbine hydropower considering the wicket-gates closing law and the surge tank position[J]. Renewable Energy, 2020, 148, 478- 491.
41
DEB K , PRATAP A , AGARWAL S , et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002, 6 (2): 182- 197.
42
GUERREIRO A P , FONSECA C M , PAQUETE L . The hypervolume indicator: Computational problems and algorithms[J]. ACM Computing Surveys, 2022, 54 (6): 119.
43
MAO Z Y , LIU M D . A local search-based many-objective five-element cycle optimization algorithm[J]. Swarm and Evolutionary Computation, 2022, 68, 101009.

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