CN114239282A - Method for implementing DMA partition of water supply pipe network in extremely-small pressure reduction space - Google Patents

Method for implementing DMA partition of water supply pipe network in extremely-small pressure reduction space Download PDF

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CN114239282A
CN114239282A CN202111557514.3A CN202111557514A CN114239282A CN 114239282 A CN114239282 A CN 114239282A CN 202111557514 A CN202111557514 A CN 202111557514A CN 114239282 A CN114239282 A CN 114239282A
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李红艳
史文韬
崔建国
马熠阳
李尚明
张翀
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Abstract

The invention discloses a method for implementing DMA partition of a water supply network under a minimal pressure reduction space. Then different minimum service water pressures are set and are respectively used as constraint conditions, the average water age of nodes after partitioning and the partitioning cost are taken as targets, equipment arrangement schemes on a plurality of boundary pipe sections are obtained by applying a function gamtobj, and the optimal arrangement scheme is screened out through three principles. And finally, finding out the optimal pipe section replacement scheme by using a simulated annealing algorithm, so that the water pressure of the partitioned pipe network can meet the specified minimum service water pressure requirement. The DMA partition method provided by the invention can not cause too large influence on the whole water quality of the partitioned pipe network on the basis of successfully completing the partition, and can provide a certain theoretical basis for tap water companies in various places to accelerate the implementation of DMA partition, reduce the leakage rate of the pipe network and construct an intelligent water supply system.

Description

Method for implementing DMA partition of water supply pipe network in extremely-small pressure reduction space
Technical Field
The application belongs to the technical field of urban water supply pipe network design, and particularly relates to a method for performing DMA partition on a water supply pipe network, in particular to a method for implementing DMA partition of the water supply pipe network under a minimum pressure reduction space.
Background
The DMA partition is that a valve is closed at a boundary pipe section and a flowmeter is additionally arranged to divide the whole pipe network into a plurality of relatively closed independent metering areas, and the purposes of controlling the leakage of the pipe network and controlling the pressure of a management system are achieved by monitoring the flow of an inlet and an outlet of each area and regulating and controlling the pressure at the inlet. Because the boundary valves are closed when the partition is carried out, the water head loss of the pipe network is inevitably increased, so that the redundancy of the pressure of each node in the pipe network is reduced, and for the nodes with extremely small pressure reduction space at the tail end of the pipe network, the water pressure after the partition hardly meets the minimum service water pressure, so that the normal operation of the pipe network is influenced.
The pressure treatment of the pipe network end node in the research of the DMA partition at present has defects. The constraint condition that the node pressure fluctuation range is within 10% is adopted in optimal arrangement of equipment in the peripheral stand and the like, which may cause the node pressure at the tail end of a pipe network not to meet the specification. The node with the water pressure exceeding 16m before the partition is restrained by the Zehn and the like to have the water pressure not lower than 16m after the partition, and the node with the water pressure lower than 16m before the partition is restrained by the Zehn and the like to have the water pressure not lower than 0m after the partition. Zhou Zhong Jian and so on should apply the pipe network tip pressure stipulated in the 'urban water supply service' specification to Italy Modena pipe network not less than 14m, increased the depressurization space of the pipe network and then accomplished DMA subregion.
Disclosure of Invention
In order to solve the partitioning problem of a pipe network under a minimum depressurization space, firstly, a spectral clustering algorithm is combined with a function gamtobj in MATLAB to determine an ideal partitioning boundary pipe section. Then, by setting a series of different minimum service water pressures and respectively using the minimum service water pressures as constraint conditions, an optimal arrangement scheme of equipment on the boundary pipe section is obtained by using a function gamtobj. And finally, finding out the pipe section with the pipe diameter needing to be replaced by using a simulated annealing algorithm, so that the pressure of all nodes in the pipe network after partitioning can meet the minimum service pressure.
The technical scheme of the invention for realizing the purpose is as follows.
The invention provides a method for implementing DMA partition of a water supply network under a minimal pressure reduction space, which comprises the following steps:
a1: calling an EPANET dynamic link library in the MATLAB, and acquiring pipe network basic data after hydraulic analysis is executed;
a2: the number of partitions is specified, and a calculation formula of the similarity between two nodes of a pipe network is defined;
a3: taking the number of the boundary pipe sections partitioned by the spectral clustering algorithm, the average flow, the pipe diameter and the length of the boundary pipe sections as target functions, optimizing parameters in a similarity calculation formula through a function gamtobj and determining the partitioned boundary pipe sections;
a4: setting a series of different minimum service water pressures as constraint conditions, taking the node average water age after partitioning and the partitioning cost as objective functions, obtaining a Pareto optimal solution set through gamtobj optimization calculation, and screening out an optimal equipment arrangement scheme through three principles;
a5: and aiming at minimizing the cost of replacing the pipe section, and finding out the optimal pipe section replacement scheme by using a simulated annealing algorithm.
According to the invention, a hydraulic model of the water supply pipe network is established in EPANET2.2, and an EPANET dynamic link library is called in MATLAB to obtain basic data of the pipe network.
The invention adopts the spectral clustering algorithm to partition the pipe network, regards the water supply pipe network as an undirected graph model consisting of nodes and pipe sections, converts the clustering problem into the graph partitioning problem by using the spectral clustering algorithm, clusters different nodes of the water supply pipe network, and ensures that the weight of boundary pipe sections among different partitions after partitioning is small, the sum of the pipe section weights in the same partition is high, and an ideal partitioning result is obtained.
In the preferred technical scheme of the invention, the similarity of two nodes in the water supply network is defined according to the formula (1), and the method mainly considers that if a valve is closed on a boundary pipe section with larger flow, energy in the pipe network is dissipated, so that the water pressure of the nodes in the pipe network is greatly reduced, and the water pressure of the tail nodes of the pipe network is easily enabled not to meet the specified minimum service water pressure. On the other hand, if the pipe diameter of the boundary pipe section is too large, the cost of zone reconstruction is increased invisibly because the price of the valve or the flowmeter is multiplied along with the increase of the pipe diameter. In addition, large pipe diameters correspond to high flow rates, so that excessive pipe diameters of the boundary pipe sections are avoided as much as possible. The risk of water quality deterioration becomes greater as the DMA cutoff pipe length increases by installing a shut-off valve on the boundary pipe section. Therefore, the pipe section with smaller flow, smaller pipe diameter and shorter length is selected as the boundary pipe section of the subarea.
The similarity value of the pipe sections between two nodes in the water supply network is shown as the formula (1):
Figure BDA0003419505340000031
in the formula: omegaij、Qij、Dij、LijAnd the similarity value, flow rate, m of the pipe sections between the nodes i and j respectively3(s), pipe diameter, mm, length, m; n is the set of all nodes in the pipe network; alpha, beta and gamma are parameters in similarity calculation formula
The selection of the three values of alpha, beta and gamma in the formula (1) can directly influence the result of the partition boundary pipe section, and the purpose of selecting the optimal boundary pipe section is achieved by optimizing the values of the three parameters.
The objective function for optimizing the three parameters of alpha, beta and gamma is
Figure BDA0003419505340000032
In the formula fnAs a boundary pipe sectionNumber of (2), bar; f. ofqThe average flow of the boundary pipe section is L/s; f. ofdIs the average pipe diameter of the boundary pipe section, mm; f. oflIs the average length of the boundary pipe segments, m; n isbIs the number of boundary pipe segments; qr、Dr、LrRespectively the flow, L/s, pipe diameter, mm, length and m of the boundary pipe section of the r-th side.
The values of the three parameters are determined by means of a self-contained function gamultiobj in MATLAB to solve the multi-objective optimization problem.
The encoding mode adopts real number encoding, decision variables are three parameters in a similarity calculation formula, and the ranges of the three parameters are limited in an interval (0, c) in the optimization process, wherein c can be determined through multiple experiments: specifically, alpha, beta and gamma are in the interval, and the normalized Laplacian matrix obtained by the method does not generate imaginary numbers when MATLAB calculates eigenvalues and eigenvectors. The selection of the c value is different when the pipe networks are different, but the determination of the c value can refer to the last water using state for different water using states of the same pipe network, and the difference between the two is small or remains unchanged.
For a node with an extremely small pressure reduction space at the end of a pipe network, once a valve is closed in the pipe network, the node pressure is easily lower than the specified minimum service water pressure, so that when equipment arrangement on a boundary pipe section is optimized, if the specified minimum service water pressure is used as a constraint, the situation that no solution exists or the solution quality is poor is likely to occur. Therefore, a series of different minimum service water pressures are set as constraint conditions for optimizing equipment arrangement, the solution conditions under each pressure constraint are observed, and an optimal arrangement scheme is determined.
When the equipment on the boundary pipe section is optimally arranged, the water quality safety of the pipe network after the partition and the economy of the partition are considered, and meanwhile, a node continuity equation, an energy conservation equation and the water pressure constraint of the node are also required to be met.
The objective function and constraint condition for optimizing equipment arrangement on the boundary pipe section are
Figure BDA0003419505340000041
In the formula: m is a tubeThe total number of nodes in the network excluding the water source; t is tiThe water age h of the node i in the pipe network is the water age of the node i; t isvThe number of valves arranged on the boundary pipe section is one; cvalve,vIs the price, dollar, of the v-th valve on the boundary pipe segment; t ismThe number of the flowmeters arranged on the boundary pipe section is set; cmeter,mThe price of the mth flowmeter on the boundary pipe section, and A is a connection matrix of the pipe network; q is the column vector of the pipe segment flow; q is the column vector of the node traffic; l is a loop matrix of the pipe network; h is the column vector of the pipe section head loss; hiThe actual water pressure m of a node i in a pipe network; hsminThe minimum water pressure m for the set pipe network; hi,maxThe maximum water pressure allowed by the node i in the pipe network, m.
And (5) utilizing a function gamultiobj in MATLAB to obtain a layout scheme of the equipment.
The decision variables are valves or flow meters arranged on the boundary pipe sections, the dimension of the decision variables is equal to the number of the boundary pipe sections, and the coding mode adopts binary coding, wherein 0 represents that the flow meters are arranged on the boundary pipe sections, and 1 represents that the valves are arranged on the boundary pipe sections.
And selecting an optimal arrangement scheme from the Pareto optimal solution set according to the following three principles.
Principle(s) is a maximum of 2 entries per DMA.
Principle II, the average water age of the nodes after the equipment is arranged is not higher than that of the nodes before the subareas.
And on the basis of meeting the requirement of the number of each DMA inlet and the limitation of the average water age of the nodes, selecting an equipment arrangement scheme which can minimize the number of the nodes which are lower than the minimum service water pressure specified by the pipe network after operation.
After the plant layout plan is determined, a hydraulic model of the water supply network under the plan is established (using EPANET2.2 software).
For the node which does not meet the minimum service water pressure specified by the pipe network, the pipe diameter flowing to the node pipe section can be enlarged to reduce the energy loss of water flow in the transferring process, so that the node pressure of the node is increased, and the node pressure meets the minimum service pressure specified by the pipe network.
The number, the length and the pipe diameter of pipe sections need to be controlled and replaced in the replacement process so as to save cost, two basic equations of the pipe network still need to be met after replacement, and the average pressure of the nodes of the pipe network after replacement is completed is not greater than the average pressure before replacement, so that the leakage loss of the pipe network is increased due to pressure increase.
The objective function and constraint condition of the pipe section replacement are
Figure BDA0003419505340000051
In the formula: di、liThe diameter, mm, length and m of the pipe section i are respectively; u is the total number of pipe sections with pipe diameters needing to be changed in the pipe network; a. b and sigma are statistical parameters in the pipe section cost formula, and a is 112.9, b is 3135, and sigma is 1.5;
Figure BDA0003419505340000052
respectively the node average pressure m of the original pipe network after the pipe diameter is replaced; hi,nowIs the actual water pressure, m, of the node i after the pipe diameter is replaced.
A simulated annealing algorithm is used for optimizing a pipe section replacement scheme, an integer coding mode is adopted for coding, decision variables are pipe diameter specifications of pipe sections which can be replaced, and dimensions are the number of the pipe sections with pipe diameters to be replaced.
For the convenience of encoding and decoding, the tube diameter specification which can be replaced is represented by natural numbers 1 to 9, and 0 represents that the tube diameter of the tube section is unchanged. For example, when x is 0,3,5,8, a total of 4 pipe sections to be replaced are shown, the pipe diameter of the first pipe section is unchanged, and the pipe diameters of the second, third and fourth pipe sections are respectively replaced by 150mm, 250mm and 400 mm.
Firstly, finding out a node set S of which the node pressure in a pipe network does not meet the specified minimum service pressure after equipment is installed1Then find the node set S adjacent to them and to which the water flows2The pipe segment set P formed by the nodes is the first pipe segment to be changed in pipe diameter, a simulated annealing algorithm is adopted to search a pipe diameter changing scheme which enables an objective function to be minimum and meets constraint conditions, and if a solution exists after optimization is completed, a comparison result is obtained at the momentFor an economical pipe diameter replacement scheme, if no solution exists, the pipe diameter is continuously searched for and compared with S2Adjacent and water flow towards their node set S3And then updating the pipe segment set P to obtain a second batch of pipe segments of the pipe diameter to be replaced, and continuously searching the optimal solution by using the simulated annealing algorithm until the algorithm is stopped when the pipe diameter replacement scheme can be found, wherein the global optimal solution can be considered to be obtained.
When the pipe diameter replacement scheme is found for the first time, the fact that the global optimal solution is obtained can be considered to be because each time of continuous downward retrieval means that elements in the set P are gradually increased, so that the search space of the algorithm is sharply enlarged, the difficulty in finding a feasible solution is greatly increased, the probability that the algorithm falls into local optimal is increased, and the algorithm is difficult to converge to the global optimal solution.
The invention has the beneficial effects that:
1. the DMA partition method for the urban water supply pipe network in the extremely-small pressure reduction space is provided, the economy of partitioning, the safety of water quality after partitioning and the effectiveness of DMA partition implementation are fully considered in the partition process, and the quality of DMA partition can be greatly improved.
2. The specific calculation method for the similarity between the nodes in the pipe network is provided, so that the influence of valve closing on the water pressure of the whole pipe network can be greatly reduced by the obtained partition boundary pipe section, the partition cost can be greatly reduced, and the water quality safety of the pipe network after partitioning is guaranteed.
Drawings
FIG. 1 is a flow chart of a method for implementing DMA partition of a water supply network in a very small pressure reduction space according to the present invention.
Fig. 2 is a case pipe network topology diagram in the present invention.
Fig. 3 is a comparison of the indexes related to the partition boundary pipe segments obtained after the case pipe network is partitioned by using the partitioning method of the present invention and the partitioning methods proposed by other studies.
FIG. 4 is a graph showing the trend of the cooling times and the optimal value of the simulated annealing algorithm of the present invention.
Fig. 5 is a final partitioning result diagram of the case pipe network according to the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples.
As shown in fig. 1, a method for implementing DMA partitioning of a water supply network in a very small pressure reduction space according to the present invention includes the following steps:
step 1, calling an EPANET dynamic link library in MATLAB, and acquiring pipe network basic data after hydraulic analysis is executed;
step 2, appointing the number of partitions, and defining a calculation formula of the similarity between two nodes of the pipe network;
step 3, taking the number of the boundary pipe sections partitioned by the spectral clustering algorithm, the average flow, the pipe diameter and the length of the boundary pipe sections as target functions, optimizing parameters in a similarity calculation formula through a function gamtobj and determining the partitioned boundary pipe sections;
step 4, setting a series of different minimum service water pressures as constraint conditions, taking the node average water age after partitioning and the partitioning cost as objective functions, obtaining a Pareto optimal solution set through gamtobj optimization calculation, and screening out an optimal equipment arrangement scheme through three principles;
step 5, aiming at the minimum cost of replacing the pipe section, finding out the optimal pipe section replacing scheme by using a simulated annealing algorithm;
an embodiment is described as an example.
The topological structure of the case pipe network is shown in fig. 2, and the pipe network has 272 nodes (including 4 water source nodes) and 317 pipe sections, and belongs to the medium town pipe network. The maximum pipe diameter in the pipe network is 400mm, the minimum pipe diameter is 100mm, each node has the limit of the lowest pressure of 20m and the highest pressure of 32.67-44.11 m, when the pipe network operates under the condition of single working condition, the pressure of the node in the pipe network is 20.09m at the lowest, and the pressure of 13 nodes does not exceed 20.5m,
DMA partition of the case pipe network is also completed in other researches, and the number of partitions is determined to be 4 after factors such as economy, management and the like are comprehensively considered. The partitioning schemes obtained from the other studies are referred to as scheme B and scheme C, respectively. The number of partitions adopted for implementing DMA partition to the case pipe network is also set to be 4. The scheme B is derived from the research on a water supply network DMA partition method based on node natural neighbors in the prior art (see: Zhongjian, Wangchen, Giruibo, and the like; the research on the water supply network DMA partition method based on the node natural neighbors [ J ]. water supply and drainage, 2019,55(07): 118-.
Determining a partition boundary pipe section by using a function gamultiobj, wherein the parameters are set as follows: the optimal front-end individual coefficient is 0.3, the population size is 100, the maximum evolution algebra is 600, the stopping algebra is also 600, the deviation of fitness function values is 0.01, and other parameters are default values. The value of c obtained by experiments can be 3.5, so the values of the three parameters are limited between (0, 3.5). And obtaining a Pareto optimal solution set after MATLAB calculation, determining that the values of three parameters in the similarity calculation formula are respectively 0.198, 2.41 and 0.674, obtaining boundary pipe sections and partition results according to the values, and marking the result as a scheme A.
FIG. 3 compares the related indexes of three partition schemes, and the sum of the flow, the sum of the pipe diameters and the sum of the lengths of the boundary pipe sections are respectively represented by ftq、ftdAnd ftlTo indicate.
As can be seen from fig. 3, the average flow rate and the total flow rate of the boundary pipe sections in the scheme a are both less than 50% of those of the other two schemes, while the total pipe diameter length and the average pipe diameter length are both between 55% and 86% of those of the other two schemes, and the number of the boundary pipe sections is the lowest value of the three.
After the partition boundary pipe section is determined, the equipment on the boundary pipe section is optimally arranged, namely, a valve and a flowmeter are arranged on the boundary pipe section.
Setting different minimum service water pressures of 20m, 19m, 18m and 17m respectively as constraint conditions, introducing the cost of valves and flow meters under different pipe diameter specifications into MATLAB, and optimizing the arrangement scheme of equipment on the partitioned boundary pipe section through a gamtobj function. The parameters are set as follows: the optimal front-end individual coefficient is 0.1, the population size is 100, the maximum evolution algebra is 50, the stopping algebra is also 50, the deviation of fitness function values is 0.01, and other parameters are default values.
After MATLAB calculation, the number of Pareto optimal solutions obtained under different pressure constraints is respectively 3, 4, 3 and 5, wherein 2 solutions are overlapped when the pressure constraints are 17m and 18 m. Table 1 lists two objective function values of 15 Pareto optimal solutions, the number of flow meters required for partitioning, and the number n of nodes with water pressure lower than 20m after equipment arrangementpAnd the number of water inlets of each region after partitioning.
TABLE 1 Pareto front and other related information under different pressure constraints
Figure BDA0003419505340000081
Figure BDA0003419505340000091
Note: means that the solution recurs at a minimum serving water pressure constraint of 17m
Screening Pareto optimal solution sets obtained under different pressure constraints according to the following three principles, wherein 1) the number of water inlets of a single DMA (direct memory access) is not more than two; 2) the average water age of the nodes of the pipe network is not higher than 0.72 h; 3) the number of nodes with water pressure below 20m after operation is the least.
The solution s-11 accords with the principle, and the corresponding scheme is the equipment arrangement scheme on the optimal boundary pipe section. Therefore, 8 valves and 6 flow meters are installed in the case pipe network, the equipment installation cost is 93928 yuan, the average water age of the nodes after equipment installation is 0.70h, the minimum pressure of the pipe network nodes after operation under the single-working-condition is 17.61m, and the pressure of 13 nodes in total is lower than 20 m.
The minimum service water pressure of the nodes specified by the case pipe network is 20m, and 13 nodes after partitioning do not meet the requirements, so that the pipe diameter of a part of pipe sections in the pipe network needs to be increased, the head loss of the pipe network is reduced, and the pressure of all the nodes can meet the requirements.
And (3) performing hydraulic simulation in MATLAB, finding a pipe section set with the pipe diameter to be replaced, optimizing the pipe diameter of the replaced pipe section, and obtaining an optimal solution through a simulated annealing algorithm. The algorithm parameters set the initial temperature to 200 ℃, the end temperature to 0.001 ℃, the cooling rate to 0.98, and the Mapkob chain length to 50. The number of the codes is a continuous natural number from 0 to 9, 0 represents that the pipe diameter of the pipe section is unchanged, and 1 to 9 respectively correspond to the pipe diameter change of 100mm to 450 mm.
After the set of pipe sections to be replaced is updated twice, the calculation is stopped. The operation process of the simulated annealing algorithm is shown in fig. 4, and the algorithm converges when the cooling frequency E is 290 times, namely, the global optimal scheme is obtained.
The calculation result shows that 10 pipe sections need to be replaced, which only accounts for 3.2% of the total number of the pipe sections of the pipe network, and the cost of replacing the pipe sections is 847350 yuan. After the pipe diameter of the case pipe network with the equipment arranged on the boundary pipe section is changed, the pressure of all nodes is larger than the specified minimum service water pressure when the case pipe network operates under the condition of single working condition. The result of the final partitioning is shown in fig. 5.
Table 2 is a comparison of the performance indicators before and after DMA partitioning of the Modena pipe network. In table, gwThe comprehensive water age index of the pipe network can reasonably reflect the water quality condition of the whole pipe network, particularly the water quality of large-flow users and the pipe network peripheral area.
TABLE 2DMA zoning front and back pipe network running performance index
Figure BDA0003419505340000101
As can be seen from Table 2:
compared with the node before zoning, the node water age after zoning is not changed, which shows that the case does not cause too much influence on the water quality of the pipe network after the DMA zoning is implemented by the pipe network. The comprehensive water age index of the pipe network after the subarea is reduced, and the water quality of the pipe network after the subarea, particularly the water quality of the pipe network tip and the water quality of a large-flow user are obviously improved from the angle.
On the premise of ensuring that the minimum water pressure of the pipe network is greater than the specified minimum service water pressure of the pipe network, the average water pressure of the pipe network after partitioning is reduced, the leakage loss of the pipe network is slightly reduced, although the reduction range is small, the time for finding the leakage loss and the leakage point after DMA partitioning is implemented is greatly shortened, and the leakage loss of the pipe network and the production and marketing difference of a water supply company can be further reduced.
It will be understood that modifications and variations can be made by persons skilled in the art in light of the above teachings and all such modifications and variations are intended to be included within the scope of the invention as defined in the appended claims.

Claims (8)

1. A method for implementing DMA partition of a water supply network under a minimal pressure reduction space is characterized by comprising the following steps:
a1: calling an EPANET dynamic link library in the MATLAB, and acquiring pipe network basic data after hydraulic analysis is executed;
a2: the number of partitions is specified, and a calculation formula of the similarity between two nodes of a pipe network is defined;
a3: taking the number of the boundary pipe sections partitioned by the spectral clustering algorithm, the average flow, the pipe diameter and the length of the boundary pipe sections as target functions, optimizing parameters in a similarity calculation formula through a function gamtobj and determining the partitioned boundary pipe sections;
a4: setting a series of different minimum service water pressures as constraint conditions, taking the node average water age after partitioning and the partitioning cost as objective functions, obtaining a Pareto optimal solution set through gamtobj optimization calculation, and screening out an optimal equipment arrangement scheme according to three principles;
a5: and aiming at minimizing the cost of replacing the pipe section, and finding out the optimal pipe section replacement scheme by using a simulated annealing algorithm.
2. The method for performing DMA partition of a water supply network in a space with extremely small pressure reduction as claimed in claim 1, wherein in step A2, the similarity value of the pipe sections between two nodes in the water supply network is shown in formula (1):
Figure FDA0003419505330000011
in the formula: omegaij、Qij、Dij、LijAnd respectivelyIs the similarity value, flow, m of the pipe section between the nodes i and j3(s), pipe diameter, mm, length, m; n is the set of all nodes in the pipe network; α, β, γ are parameters in the similarity calculation formula.
3. The method for implementing DMA partitioning of a water supply network in a minimal pressure drop space as recited in claim 2, wherein in step a 3: and with the minimum number of boundary pipe sections after the partition of the spectral clustering algorithm, the average flow, the pipe diameter and the length as targets, determining parameters alpha, beta and gamma in a similarity calculation formula through a multi-objective optimization function gammobj in MATLAB, and obtaining the partition boundary pipe sections corresponding to the parameters alpha, beta and gamma.
4. The method for implementing DMA partition of a water supply network under a very small pressure reduction space as claimed in claim 3, wherein in step A3: the objective function for optimizing three parameters of alpha, beta and gamma is as follows:
Figure FDA0003419505330000021
in the formula fnNumber of boundary pipe segments, bar; f. ofqThe average flow of the boundary pipe section is L/s; f. ofdIs the average pipe diameter of the boundary pipe section, mm; f. oflIs the average length of the boundary pipe segments, m; n isbIs the number of boundary pipe segments; qr、Dr、LrRespectively the flow, L/s, pipe diameter, mm, length and m of the boundary pipe section of the r-th side;
determining the values of three parameters by using a self-contained function gamultiobj for solving the multi-objective optimization problem in MATLAB;
the encoding mode adopts real number encoding, decision variables are three parameters in a similarity calculation formula, and the ranges of the three parameters are limited in an interval (0, c) in the optimization process, wherein c can be determined through multiple experiments: specifically, alpha, beta and gamma are in the interval, and the obtained normalized Laplacian matrix does not generate imaginary numbers when MATLAB calculates characteristic values and characteristic vectors; the selection of the c value is different when the pipe networks are different, but the determination of the c value can refer to the last water using state for different water using states of the same pipe network, and the difference between the two is small or remains unchanged.
5. The method for implementing DMA partitioning of a water supply network in a minimal pressure drop space as recited in claim 1, wherein in step a 4: the objective function and constraint conditions for optimizing equipment layout on the boundary pipe section are as follows:
Figure FDA0003419505330000022
in the formula: m is the total number of nodes except water sources in the pipe network; t is tiThe water age h of the node i in the pipe network is the water age of the node i; t isvThe number of valves arranged on the boundary pipe section is one; cvalve,vIs the price, dollar, of the v-th valve on the boundary pipe segment; t ismThe number of the flowmeters arranged on the boundary pipe section is set; cmeter,mIs the price, dollar, of the mth flow meter on the boundary pipe segment. A is a connection matrix of the pipe network; q is the column vector of the pipe segment flow; q is the column vector of the node traffic; l is a loop matrix of the pipe network; h is the column vector of the pipe section head loss; hiThe actual water pressure m of a node i in a pipe network; hsminThe minimum water pressure m for the set pipe network; hi,maxThe maximum water pressure allowed by a node i in a pipe network, m;
obtaining an arrangement scheme of the equipment by using a function gamultiobj in MATLAB;
the decision variables are valves or flow meters arranged on the boundary pipe sections, the dimension of the decision variables is equal to the number of the boundary pipe sections, and the coding mode adopts binary coding, wherein 0 represents that the flow meters are arranged on the boundary pipe sections, and 1 represents that the valves are arranged on the boundary pipe sections.
6. The method for implementing DMA partition of a water supply network in a very small pressure reduction space as claimed in claim 5, wherein in step A4: the three principles for screening the optimal arrangement scheme are respectively 1) the number of the water inlets of a single DMA must not exceed two; 2) the average water age of the nodes after the equipment is arranged is not higher than that of the nodes before the subareas; 3) on the basis of meeting the requirement of the number of each DMA inlet and the limitation of the average water age of the nodes, the equipment arrangement scheme which can minimize the number of the nodes which are lower than the minimum service water pressure specified by the pipe network after operation is selected.
7. The method for implementing DMA partitioning of a water supply network in a minimal pressure drop space as recited in claim 1, wherein in step a 5: the objective function and constraint conditions of the pipe section replacement are as follows:
Figure FDA0003419505330000031
in the formula: di、liThe diameter, mm, length and m of the pipe section i are respectively; u is the total number of pipe sections with pipe diameters needing to be changed in the pipe network; a. b and sigma are statistical parameters in the pipe section cost formula, and a is 112.9, b is 3135, and sigma is 1.5;
Figure FDA0003419505330000032
respectively the node average pressure m of the original pipe network after the pipe diameter is replaced; hi,nowIs the actual water pressure, m, of the node i after the pipe diameter is replaced.
8. The method for implementing DMA partition of a water supply network in a minimum depressurization space according to claim 5, wherein a simulated annealing algorithm is used for optimizing a pipe section replacement scheme, the coding mode adopts integer coding, the decision variable is the pipe diameter specification of the replaceable pipe section, and the dimension is the number of the pipe sections with pipe diameters to be replaced;
the specification of the replaceable pipe diameter is represented by natural numbers from 1 to 9, and 0 represents that the pipe diameter of the pipe section is unchanged;
firstly, finding out a node set S of which the node pressure in a pipe network does not meet the specified minimum service pressure after equipment is installed1Then find the node set S adjacent to them and to which the water flows2The pipe segment set P formed by the nodes is the pipe to be replacedAnd (3) searching the pipe diameter replacement scheme which enables the objective function to be minimum and meets the constraint condition by adopting a simulated annealing algorithm for the first pipe section, obtaining a more economic pipe diameter replacement scheme if the first pipe section is optimized and has a solution, and continuously searching the first pipe section and S if the first pipe section is not optimized2Adjacent and water flow towards their node set S3Then updating the pipe segment set P to obtain a second batch of pipe segments of the pipe diameter to be replaced, continuously searching the optimal solution by using the simulated annealing algorithm until the algorithm is stopped when the pipe diameter replacement scheme can be found, and at the moment, considering that the global optimal solution is obtained;
when the pipe diameter replacement scheme is found for the first time, the fact that the global optimal solution is obtained can be considered to be because each time of continuous downward retrieval means that elements in the set P are gradually increased, so that the search space of the algorithm is sharply enlarged, the difficulty in finding a feasible solution is greatly increased, the probability that the algorithm falls into local optimal is increased, and the algorithm is difficult to converge to the global optimal solution.
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Cited By (3)

* Cited by examiner, † Cited by third party
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CN114997751A (en) * 2022-08-03 2022-09-02 山东瀚澜水业有限公司 Direct drinking water digital water supply distribution method based on data transmission
CN115099998A (en) * 2022-06-29 2022-09-23 深圳市拓安信计控仪表有限公司 Independent metering and partitioning method for water supply network, terminal equipment and storage medium
CN116542001A (en) * 2023-05-04 2023-08-04 安徽建筑大学 Water supply network independent metering partitioning method based on improved spectral clustering and genetic algorithm

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115099998A (en) * 2022-06-29 2022-09-23 深圳市拓安信计控仪表有限公司 Independent metering and partitioning method for water supply network, terminal equipment and storage medium
CN114997751A (en) * 2022-08-03 2022-09-02 山东瀚澜水业有限公司 Direct drinking water digital water supply distribution method based on data transmission
CN114997751B (en) * 2022-08-03 2022-10-25 山东瀚澜水业有限公司 Direct drinking water digital water supply distribution method based on data transmission
CN116542001A (en) * 2023-05-04 2023-08-04 安徽建筑大学 Water supply network independent metering partitioning method based on improved spectral clustering and genetic algorithm
CN116542001B (en) * 2023-05-04 2023-11-07 安徽建筑大学 Water supply network independent metering partitioning method based on improved spectral clustering and genetic algorithm

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