Multi-objective optimization water hammer protection model establishment method and system based on long-distance gravity flow water delivery system

Abstract

The invention discloses a multi-objective optimization water hammer protection model establishment method and system based on a long-distance gravity flow water delivery system, and relates to the technical field of water hammers, and the method comprises the steps: based on a basic equation of a non-constant flow of a pressure pipeline, employing a characteristic line method for solving, and obtaining two pairs of characteristic line compatible equations; a multi-objective genetic algorithm is adopted, size parameters of the protection equipment are optimized, and two optimization objective functions are obtained through fitting by taking the water hammer protection effects of different combined protection schemes and the construction cost as objectives; and on the basis of meeting the constraint condition, substituting the optimized objective function into an NSGA-II algorithm for solving until the objective function is minimized, and obtaining a pareto optimal solution set of the protection scheme. According to the method, the NSGA-II algorithm is adopted, the safety index and the economic index serve as main objects, the multi-target optimization model is constructed, and multi-target optimization of long-distance gravity flow water conveying system protection under the multi-target requirement is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of water hammer, and more particularly to a method and system for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system. Background Art

[0002] Long-distance gravity flow water transfer projects are an effective means to solve the problem of uneven spatial distribution of freshwater resources in some parts of my country. However, the hazard of water hammer is an issue that cannot be ignored in gravity flow hydraulic conveying systems. In actual engineering applications, the protection against gravity flow water hammer and the optimization of the economy and safety of protection measures have always been a hot topic and difficulty in research in this field.

[0003] How to reduce the economic cost of protective measures while ensuring system safety, achieve multi-objective optimization, and obtain the optimal protective measures has become a problem to be solved. At present, the existing research results mainly focus on the optimization of pump valve closing rules or single water hammer protection measures, but there is little research on the multi-objective optimization of multiple protection measures for long-distance gravity flow water supply projects. According to the current technical level of water hammer protection and general protection measures, the main water hammer protection equipment includes exhaust valves, check valves, overpressure relief valves (safety valves) and water hammer elimination tanks, one-way pressure regulating towers, two-way pressure regulating towers, etc. With the development of science and technology, various advanced water hammer protection measures have emerged, such as new high-performance air pressure tanks, pressure reducing valves, pressure regulating valves, pressure regulating towers, exhaust valves, water hammer control valves, etc. It is worth noting that the performance and application of these water hammer protection equipment. With the increase in the complexity and diversity of water supply projects, the combined protection of protective equipment has become more common. The water hammer protection effect and economy of combined protection deserve further study.

[0004] Previous studies have failed to fully consider the correlation between different protective measures, which greatly limits their engineering applications and safety evaluation. In actual engineering, it is often necessary to consider multiple objective factors at the same time, such as safety indicators and economic indicators. Therefore, studying the multi-objective optimization design of water hammer phenomenon in long-distance gravity flow water supply systems is of great significance to actual engineering applications, and can provide a reference for multi-objective optimization of other similar gravity flow water supply projects. It is a technical problem that technicians in this field urgently need to solve. Summary of the invention

[0005] In view of this, the present invention provides a method and system for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system, which solves the problems existing in the background technology.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system comprises the following steps:

[0008] S1: Based on the basic equation of unsteady flow in a pressurized pipeline, the characteristic line method is used to solve the two pairs of characteristic line compatible equations;

[0009] S2: A multi-objective genetic algorithm is used to optimize the size parameters of the protective equipment, and two optimization objective functions are fitted based on the water hammer protection effect and engineering cost of different combined protection schemes;

[0010] S3: On the basis of satisfying the constraints, the optimization objective function is substituted into the NSGA-Ⅱ algorithm for solution until the objective function is minimized and the Pareto optimal solution set of the protection scheme is obtained.

[0011] Optionally, the S1 includes the following steps:

[0012] S11: The basic mathematical equations for establishing the pressurized water pipeline system model are as follows:

[0013]

[0014] Where: H is the water head of the pressure tube, t is time, V is the flow velocity, x is the node coordinate, α is the pipe inclination, a is the water hammer wave velocity, g is the gravity acceleration, f is the resistance coefficient along the way, and D is the pipe diameter;

[0015] S12: Use the characteristic line method to solve formulas (1) and (2) and obtain the characteristic line compatibility equation as follows:

[0016]

[0017] C P =H i-1 +BQ i-1 -RQ i-1 |Q i-1 | (5);

[0018] C M =H i+1 -BQ i+1 +RQ i+1 |Q i+1 | (6);

[0019] In the formula: B=a / gA, R=fΔx / 2gDA 2 ; C p , C M , B, R are all calculation constants; H pi represents the water head of the calculated section i in the pipe at time t, Q pi represents the flow rate of the calculated section i in the pipe at time t, A represents the cross-sectional area; Hi-1 represents the water head of the calculated section i-1 in the pipe, Q i-1 represents the flow rate of the calculated section i-1 in the pipe, Δx represents the length of the characteristic line grid pipe section; H i+1 represents the water head of the calculated section i+1 in the pipe, Q i+1 Represents the flow rate at the calculated section i+1 in the pipe.

[0020] Optionally, S2 includes the following steps:

[0021] S21: Select decision variables based on air valve, water surge relief valve, one-way surge tower, two-way surge tower and air tank;

[0022] S22: Design three water hammer protection schemes: air valve + one-way pressure regulating tower + water hammer pressure relief valve, air valve + two-way pressure regulating tower, and air valve + air tank. Optimize the water hammer protection effect and engineering cost of different protection schemes to obtain safety and economic indicators.

[0023] Optionally, it is characterized in that the decision variables include: the diameter D of the three-action air valve q1 , D q2 , D q3 , Water hammer relief valve diameter D s , the diameter of the one-way pressure regulating tower is D t , initial effective water head H t , water supply pipe diameter D b , the diameter of the bidirectional pressure regulating tower is D j , water supply pipe diameter D a and the volume V of the air tank k , connecting pipe diameter D k , initial internal pressure P k ;

[0024] The expression of the objective function is:

[0025]

[0026]

[0027] Where: F 1 It represents the average value of water hammer pressure difference at each node, i.e. safety index; F 2 It represents the engineering cost index after each parent is assigned a weight and then linearly superimposed, i.e., the economic index; i is the node number, n is the number of nodes, i = 1, 2, ..., n; H max (i) represents the maximum water hammer pressure at each node, H max (i') represents the maximum allowable pressure of the pipeline at each node; I is the protection type, I = 1, 2, 3 represent the protection of various protective equipment respectively; k Irepresents the weight of each protection type sub-goal, and the sum of the weights of each sub-goal is 1; f I represents the normalized value of the I-th sub-goal; N I Indicates the number of devices used for protection type I, W I Indicates the unit price of the equipment used for protection type I, W z Represents the total investment in pipeline projects.

[0028] Optionally, S3 includes the following steps:

[0029] S31: Under the premise of ensuring the safe operation of the water delivery system, determine the various constraints of water hammer protection parameters and decision variables based on the inherent characteristics of the protection equipment;

[0030] S32: Fit the relationship between the objective function and each decision variable and substitute it into the NSGA-Ⅱ algorithm. Through the methods of selection, crossover and mutation, the optimal performance of the parent line is transferred to the offspring until the engineering safety index F is reached. 1 and engineering economic index F 2 Reach the minimum and converge to the Pareto solution set.

[0031] Optionally, constraints include:

[0032] a. System constraints: basic equations of transient flow, system upstream boundary conditions, air valve boundary conditions, water hammer relief valve boundary conditions, one-way surge tower boundary conditions, two-way surge tower boundary conditions, air tank boundary conditions, system downstream boundary conditions;

[0033] b. Maximum water hammer pressure rise constraint meets: H max (i)<(1.5~2.0)H(i) L,max ; Among them, H max (i) represents the maximum water hammer pressure at each node, H(i) L,max Indicates the maximum static pressure at the lowest point of the pipeline;

[0034] c. Input variable upper and lower limit constraints: The value of each decision variable is within the specified range, that is:

[0035]

[0036] d. Pressure upper and lower limit constraints: The maximum and minimum water hammer pressures at each point in the pipeline system are within the allowable range, that is:

[0037] H max (i)-H max (i')<0H min (i)-H min (i')<0

[0038] e. The investment in water hammer protection equipment shall not exceed 30% of the total investment in the pipeline project, namely:

[0039] N 1 W 1 +N 2 W 2 +N 3 W 3 <0.3W z

[0040] Where: W I Indicates the unit price of the equipment used for protection type I, where I is the protection type and I=1,2,3 represent the protection of various protective equipment respectively; W z Represents the total investment in pipeline projects.

[0041] A system for implementing any of the above-mentioned methods for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system, comprising:

[0042] The characteristic line solving module is used to solve the basic equations of unsteady flow in a pressurized pipeline using the characteristic line method to obtain two pairs of characteristic line compatible equations;

[0043] The fitting module is used to optimize the size parameters of the protective equipment by adopting a multi-objective genetic algorithm, and to obtain two optimization objective functions by fitting the water hammer protection effect and engineering cost of different combined protection schemes;

[0044] The optimization calculation module is used to substitute the optimization objective function into the NSGA-Ⅱ algorithm for solution on the basis of satisfying the constraint conditions until the objective function is minimized and the Pareto optimal solution set of the protection scheme is obtained.

[0045] It can be seen from the above technical scheme that, compared with the prior art, the present invention discloses a method and system for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water supply system. The water hammer protection of the long-distance gravity flow water supply system is taken as the research object, and two optimization objective functions are fitted by using the existing data set, and the safety and economy of the combination scheme of protective equipment used in the project are optimized and studied; based on the non-dominated sorting genetic algorithm, a multi-objective optimization model is established, and the multi-objective optimization of the protection of the long-distance gravity flow water supply system under multi-objective requirements is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0047] Figure 1 A flow chart of a method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system provided by the present invention;

[0048] Figure 2 A pipeline cross-section elevation diagram provided by the present invention;

[0049] Figure 3 The Pareto frontier solution sets of the three protection schemes provided by the present invention; among them, 3a is the Pareto frontier of air valve + one-way pressure regulating tower + water hammer pressure relief valve, 3b is the Pareto frontier of air valve + two-way pressure regulating tower, and 3c is the Pareto frontier of air valve + air tank;

[0050] Figure 4 This is a comparison chart between the optimization scheme provided by the present invention and the original scheme. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] The embodiment of the present invention discloses a method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system. Figure 1 As shown, the following steps are included:

[0053] S1: Based on the basic equations of unsteady flow in pressurized pipelines (equations of motion and continuity), the characteristic line method is used to solve them and two pairs of characteristic line compatible equations are obtained.

[0054] The specific steps are as follows:

[0055] S11: The basic mathematical equations for establishing the pressurized water pipeline system model are as follows:

[0056]

[0057] Where: H is the water head of the pressure tube, t is time, V is the flow velocity, x is the node coordinate, α is the pipe inclination, a is the water hammer wave velocity, g is the gravity acceleration, f is the resistance coefficient along the way, and D is the pipe diameter;

[0058] S12: Use the characteristic line method to solve formulas (1) and (2) and obtain the characteristic line compatibility equation as follows:

[0059]

[0060] C P =H i-1 +BQ i-1 -RQ i-1 |Q i-1 | (5);

[0061] C M =H i+1 -BQ i+1 +RQ i+1 |Q i+1 | (6);

[0062] In the formula: B=a / gA, R=fΔx / 2gDA 2 ; C p , C M , B, R are all calculation constants; H pi represents the water head of the calculated section i in the pipe at time t, Q pi represents the flow rate of the calculated section i in the pipe at time t, A represents the cross-sectional area; H i-1 represents the water head of the calculated section i-1 in the pipe, Q i-1 represents the flow rate of the calculated section i-1 in the pipe, Δx represents the length of the characteristic line grid pipe section; H i+1 represents the water head of the calculated section i+1 in the pipe, Q i+1 Represents the flow rate at the calculated section i+1 in the pipe.

[0063] S2: A multi-objective genetic algorithm is used to optimize the size parameters of the protective equipment. Taking the water hammer protection effect and engineering cost of different combined protection schemes as the objectives, two optimization objective functions are fitted.

[0064] The specific steps are as follows:

[0065] S21: The closing law of the valve at the end of the gravity flow water supply project has been determined by preliminary numerical calculation. Select the three-action air valve caliber D q1 , D q2 , D q3 , Water hammer relief valve diameter D s , the diameter of the one-way pressure regulating tower is D t , initial effective water head H t , water supply pipe diameter D b , the diameter of the bidirectional pressure regulating tower is D j , water supply pipe diameter D a and the volume V of the air tank k , connecting pipe diameter D k , initial internal pressure P k , a total of 12 decision variables;

[0066] S22: Design three water hammer protection schemes: air valve + one-way pressure regulating tower + water hammer pressure relief valve, air valve + two-way pressure regulating tower, and air valve + air tank. Optimize the water hammer protection effect and engineering cost of different protection schemes to obtain safety and economic indicators;

[0067] Among them, the expression of the objective function is:

[0068]

[0069] Where: F 1 It represents the average value of water hammer pressure difference at each node, i.e. safety index; F 2 It represents the engineering cost index after each parent is assigned a weight and then linearly superimposed, i.e., the economic index; i is the node number, n is the number of nodes, i = 1, 2, ..., n; H max (i) represents the maximum water hammer pressure at each node, H max (i') represents the maximum allowable pressure of the pipeline at each node; I is the protection type, I = 1, 2, 3 represent the protection of various protective equipment respectively; k I represents the weight of each protection type sub-goal, and the sum of the weights of each sub-goal is 1; f I represents the normalized value of the I-th sub-goal; N I Indicates the number of devices used for protection type I, W I Indicates the unit price of the equipment used for protection type I, W z Represents the total investment in pipeline projects.

[0070] S3: On the basis of satisfying the constraints, the optimization objective function is substituted into the NSGA-Ⅱ algorithm for solution until the objective function is minimized and the Pareto optimal solution set of the protection scheme is obtained.

[0071] The specific steps are as follows:

[0072] S31: Under the premise of ensuring the safe operation of the water delivery system, determine the various constraints of water hammer protection parameters and decision variables based on the inherent characteristics of the protection equipment;

[0073] The constraints include:

[0074] a. System constraints: basic equations of transient flow, system upstream boundary conditions, air valve boundary conditions, water hammer pressure relief valve boundary conditions, one-way surge tower boundary conditions, two-way surge tower boundary conditions, air tank boundary conditions, system downstream boundary conditions, etc.;

[0075] b. The maximum water hammer pressure rise constraint meets the "Design Code for Water Hammer Protection of Pressurized Water Pipelines DB65-T4718-2023" requirement that "for gravity flow water pipelines, the maximum static pressure at the lowest point of the pipeline should not exceed 1.5 to 2.0 times", that is:

[0076] H max (i)<(1.5~2.0)H(i) L,max

[0077] Among them, H max (i) represents the maximum water hammer pressure at each node, H(i) L,max Indicates the maximum static pressure at the lowest point of the pipeline;

[0078] c. Input variable upper and lower limit constraints: The value of each decision variable is within the specified range, that is:

[0079]

[0080] d. Pressure upper and lower limit constraints: The maximum and minimum water hammer pressures at each point in the pipeline system are within the allowable range, that is:

[0081] H max (i)-H max (i')<0H min (i)-H min (i')<0

[0082] e. The investment in water hammer protection equipment shall not exceed 30% of the total investment in the pipeline project, namely:

[0083] N 1 W 1 +N 2 W 2 +N 3 W 3 <0.3W z

[0084] Where: W I Indicates the unit price of the equipment used for protection type I, where I is the protection type and I=1,2,3 represent the protection of various protective equipment respectively; W z Represents the total investment in pipeline projects.

[0085] S32: The solution target is the parameter D of the water hammer protection scheme q1 , D q2 , D q3 , D s , D t , H t , D b , D j , D a 、V k , D k , P k In order to make the engineering safety index F 1 and economic index F 2To achieve the minimum, we must first fit the relationship between the objective function and each decision variable and substitute it into the NSGA-Ⅱ algorithm. Through selection, crossover, mutation and other methods, the excellent performance of the paternal line is transferred to the offspring. Under the premise of greatly reducing the amount of calculation, the optimal performance of this method is transferred to the offspring until the engineering safety index F is reached. 1 and engineering economic index F 2 Reach the minimum and finally converge to the Pareto solution set.

[0086] S4: Taking actual engineering as an example, an improved multi-objective genetic algorithm is used to select the optimal preservation strategy and adaptive crossover and mutation operations for the two objective functions. When the number of identical individuals in the population reaches a certain proportion, the population is reinitialized and a calculation program is compiled for optimization calculation to obtain the Pareto optimal solution set of the protection scheme. The effectiveness of this optimization method is verified by comparing the optimized scheme with the original scheme.

[0087] The specific steps are as follows:

[0088] S41: Taking a pressurized gravity flow water supply project in a certain area of ​​Xinjiang as an example, the longitudinal section of the pipeline system is as follows Figure 2 This example selects the section from pile number 0+000° to 94+700 for calculation and analysis, with a pipeline length of 94.7 km and a design flow rate of 17.1 m 3 / s, of which the section with pile number 0+000-64+748 (length 64748m) is a DN3400 PCCP pipe with a wave velocity of 955.33m / s. The section with pile number 64+748-94+700 (length 26952m) is a DN3200 PCCP pipe with a wave velocity of 945.64m / s. The starting point is the pressure regulating pool A at the outlet of the water diversion tunnel, with a bottom plate elevation of 654.5m, a normal water level in the pool of 662.5m, and a maximum water level of 665m. A pressure regulating pool B is set at the pile number 94+700°, with a design water level of 585m;

[0089] S42: The population size is set to 50, the crossover probability is 0.8, and the mutation probability is 0.05. After 200 generations of evolution, the Pareto solution set in the target domain is obtained. The Pareto solution set in the target domain is imported into the Origin software, and the distribution diagram of the Pareto solution set can be obtained. Figure 3 , where 3a is the Pareto front of air valve + one-way pressure regulating tower + water hammer pressure relief valve, 3b is the Pareto front of air valve + two-way pressure regulating tower, and 3c is the Pareto front of air valve + air tank; F 1 is the safety index, F 2 It is an economic indicator;

[0090] S43: Figure 4This is a comparison chart of the maximum pressures of the three schemes before and after optimization. Scheme A is mainly based on the water hammer pressure relief valve, and the auxiliary air valve + one-way pressure regulating tower is a two-stage valve closing protection scheme; Scheme B is mainly based on the two-way pressure regulating tower, and the auxiliary air valve is a two-stage valve closing protection scheme; Scheme C is mainly based on the air tank, and the auxiliary air valve is a two-stage valve closing protection scheme. It can be clearly seen that the optimized scheme performs better in the overall envelope diagram of the maximum pressure, and has significant advantages over the original scheme. At the same time, the maximum water hammer pressure has also been significantly improved, which further proves the effectiveness of the optimization scheme.

[0091] Compared with the initial solution, the volume of the air tank was reduced from 7000m 3 Optimized to 5000m 3 , which is 28.6% smaller than before, and the maximum water hammer pressure is also reduced from 140.48m to 117.88m, a decrease of 16%, and the safety index and economic index are greatly improved. The results show that the optimization method proposed in this embodiment can find a better solution between safety and economy, and can select the best solution with different preferences according to specific engineering needs, which can effectively solve the water hammer protection problem of long-distance water pipelines, and can also provide reference for the multi-objective optimization design of other types of gravity flow water supply projects.

[0092] and Figure 1 Corresponding to the method described above, the embodiment of the present invention also provides a multi-objective optimization water hammer protection model establishment system based on a long-distance gravity flow water delivery system, which is used to Figure 1 The specific implementation of the method in the embodiment of the present invention is a multi-objective optimization water hammer protection model establishment system based on a long-distance gravity flow water delivery system, which can be applied to a computer terminal or various mobile devices, and specifically includes:

[0093] The characteristic line solving module is used to solve the basic equations of unsteady flow in a pressurized pipeline using the characteristic line method to obtain two pairs of characteristic line compatible equations;

[0094] The fitting module is used to optimize the size parameters of the protective equipment by adopting a multi-objective genetic algorithm, and to obtain two optimization objective functions by fitting the water hammer protection effect and engineering cost of different combined protection schemes;

[0095] The optimization calculation module is used to substitute the optimization objective function into the NSGA-Ⅱ algorithm for solution on the basis of satisfying the constraint conditions until the objective function is minimized and the Pareto optimal solution set of the protection scheme is obtained.

[0096] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0097] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system, characterized in that: The following steps are involved: S1: Based on the basic equation of unsteady flow in a pressurized pipeline, the characteristic line method is used to solve the two pairs of characteristic line compatible equations; S2: A multi-objective genetic algorithm is used to optimize the size parameters of the protective equipment, and two optimization objective functions are fitted based on the water hammer protection effect and engineering cost of different combined protection schemes; S3: On the basis of satisfying the constraints, the optimization objective function is substituted into the NSGA-Ⅱ algorithm for solution until the objective function is minimized and the Pareto optimal solution set of the protection scheme is obtained.

2. The method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system according to claim 1 is characterized in that: The S1 comprises the following steps: S11: The basic mathematical equations for establishing the pressurized water pipeline system model are as follows: Where: H is the water head of the pressure tube, t is time, V is flow velocity, x is the node coordinate, α is the pipe inclination, a is the water hammer wave velocity, g is the gravity acceleration, f is the resistance coefficient along the way, and D is the pipe diameter; S12: Use the characteristic line method to solve formulas (1) and (2) and obtain the characteristic line compatibility equation as follows: C P =H i-1 +BQ i-1 -RQ i-1 |Q i-1 | (5); C M =H i+1 -BQ i+1 +RQ i+1 |Q i+1 | (6); In the formula: B=a / gA, R=fΔx / 2gDA 2 ; C p , C M , B, R are all calculation constants; H pi represents the water head of the calculated section i in the pipe at time t, Q pi represents the flow rate of the calculated section i in the pipe at time t, A represents the cross-sectional area; H i-1 represents the water head of the calculated section i-1 in the pipe, Q i-1 represents the flow rate of the calculated section i-1 in the pipe, Δx represents the length of the characteristic line grid pipe section; H i+1 represents the water head of the calculated section i+1 in the pipe, Q i+1 Represents the flow rate at the calculated section i+1 in the pipe.

3. The method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system according to claim 1 is characterized in that: The S2 comprises the following steps: S21: Select decision variables based on air valve, water surge relief valve, one-way surge tower, two-way surge tower and air tank; S22: Design three water hammer protection schemes: air valve + one-way pressure regulating tower + water hammer pressure relief valve, air valve + two-way pressure regulating tower, and air valve + air tank. Optimize the water hammer protection effect and engineering cost of different protection schemes to obtain safety and economic indicators.

4. The method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system according to claim 3 is characterized in that: The decision variables include: Three-action air valve diameter D q1 , D q2 , D q3 , Water hammer relief valve diameter D s , the diameter of the one-way pressure regulating tower is D t , initial effective water head H t , water supply pipe diameter D b , the diameter of the bidirectional pressure regulating tower is D j , water supply pipe diameter D a and the volume V of the air tank k , connecting pipe diameter D k , initial internal pressure P k ; The expression of the objective function is: Where: F1 represents the average value of the water hammer pressure difference of each node, that is, the safety index; F2 represents the engineering cost index of the linear superposition of each sub-element after being assigned weights, that is, the economic index; i is the node number, n is the number of nodes, i = 1, 2, ..., n; H max (i) represents the maximum water hammer pressure at each node, H max (i') represents the maximum allowable pressure of the pipeline at each node; I is the protection type, I = 1, 2, 3 represent the protection of various protective equipment respectively; k I represents the weight of each protection type sub-goal, and the sum of the weights of each sub-goal is 1; f I represents the normalized value of the I-th sub-goal; N I Indicates the number of devices used for protection type I, W I Indicates the unit price of the equipment used for protection type I, W z Represents the total investment in pipeline projects.

5. The method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system according to claim 4, characterized in that: The S3 comprises the following steps: S31: Under the premise of ensuring the safe operation of the water delivery system, determine the various constraints of water hammer protection parameters and decision variables based on the inherent characteristics of the protection equipment; S32: Fit the relationship between the objective function and each decision variable and substitute it into the NSGA-Ⅱ algorithm. Through the methods of selection, crossover, and mutation, the optimal performance of the parent line is transferred to the offspring until the engineering safety index F1 and the engineering economic index F2 reach the minimum and converge to the Pareto solution set.

6. The method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system according to claim 4, characterized in that: The constraints include: a. System constraints: basic equations of transient flow, system upstream boundary conditions, air valve boundary conditions, water hammer relief valve boundary conditions, one-way surge tower boundary conditions, two-way surge tower boundary conditions, air tank boundary conditions, system downstream boundary conditions; b. Maximum water hammer pressure rise constraint meets: H max (i)<(1.5~2.0)H(i) L,max ; Among them, H max (i) represents the maximum water hammer pressure at each node, H(i) L,max Indicates the maximum static pressure at the lowest point of the pipeline; c. Input variable upper and lower limit constraints: The value of each decision variable is within the specified range, that is: d. Pressure upper and lower limit constraints: The maximum and minimum water hammer pressures at each point in the pipeline system are within the allowable range, that is: H max (i)-H max (i')<0H min (i)-H min (i')<0 e. The investment in water hammer protection equipment shall not exceed 30% of the total investment in the pipeline project, namely: <h2 style=";text-align:left;direction:ltr">N1W1+N2W2+N3W3<0.3W<h2 style=";text-align:left;direction:ltr"> z Where: W I Indicates the unit price of the equipment used for protection type I, where I is the protection type and I=1,2,3 represent the protection of various protective equipment respectively; W z Represents the total investment in pipeline projects.

7. A system for implementing the method for establishing a multi-objective optimization water hammer protection model based on a long-distance gravity flow water delivery system as described in any one of claims 1 to 6, characterized in that: include: The characteristic line solving module is used to solve the basic equations of unsteady flow in a pressurized pipeline using the characteristic line method to obtain two pairs of characteristic line compatible equations; The fitting module is used to optimize the size parameters of the protective equipment by adopting a multi-objective genetic algorithm, and to obtain two optimization objective functions by fitting the water hammer protection effect and engineering cost of different combined protection schemes; The optimization calculation module is used to substitute the optimization objective function into the NSGA-Ⅱ algorithm for solution on the basis of satisfying the constraint conditions until the objective function is minimized and the Pareto optimal solution set of the protection scheme is obtained.

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