CN112926164A - Multi-water-source water supply pipe network system transmission and distribution pattern optimization method - Google Patents
Multi-water-source water supply pipe network system transmission and distribution pattern optimization method Download PDFInfo
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Abstract
The invention provides a multi-water-source water supply network system transmission and distribution pattern optimization method for solving the problem that the actual water supply range of each water source in a multi-water-source water supply system possibly deviates from a preset scheme, which comprises the following steps: screening the position of a pipeline capable of being provided with a valve in the multi-water-source water supply pipe network system as a key position of the valve; constructing a transmission and distribution pattern optimization model, and setting decision variables, objective functions and constraint conditions of the transmission and distribution pattern optimization model; selecting an optimization algorithm suitable for solving a high-dimensional multi-objective optimization problem to solve the transmission and distribution pattern optimization model to obtain an optimized solution; and analyzing the relation between the optimization solutions to obtain an optimization scheme of the transmission and distribution pattern of the multi-water-source water supply network system. According to the invention, through constructing a high-dimensional multi-objective optimization model aiming at the problem of regulating the transmission and distribution pattern of the multi-water-source water supply network system, the advantages and disadvantages of each scheme are analyzed from multiple dimensions, a valve layout and regulation scheme with more comprehensive benefits and advantages can be found, and the problem of deviation of actual water supply and a preset scheme is avoided.
Description
Technical Field
The invention relates to the technical field of water supply network systems, in particular to a method for optimizing a transmission and distribution pattern of a multi-water-source water supply network system.
Background
Along with the rapid development of cities, the range of a water supply network is gradually enlarged, the total water supply amount is increased, and most of cities in China adopt a multi-water-source water supply mode at present. The mode that multiple water source supplied water can let the water consumption of whole pipe network obtain the supply from the water source of different positions, compares with single water source water supply, and multiple water source supplies water and can let the pressure distribution of whole pipe network more balanced and guarantee the reliability that the water source supplied water. If a certain water source stops supplying water, other water sources still have the guarantee water demand in the water supply system.
However, compared with the single-water-source water supply, the multi-water-source water supply method increases the difficulty of designing and managing the water supply system to some extent, for example, how to allocate the water supply scale of each water source and how to divide the water supply range of each water source. In actual operation, there may be a problem of unbalanced multi-water-source water supply pattern, for example, when the water outlet pressure of a certain water source is too high, the actual water supply amount of other water sources is lower than the designed water supply amount, so that the actual water supply range of each water source deviates from the preset scheme, and thus an ideal multi-water-source water supply pattern cannot be achieved.
Disclosure of Invention
The invention provides an optimization method for a transmission and distribution pattern of a multi-water-source water supply network system, which aims to solve the problem that the actual water supply range of each water source in the multi-water-source water supply system possibly deviates from a preset scheme.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a multi-water-source water supply network system distribution pattern optimization method comprises the following steps:
s1: screening the position of a pipeline capable of being provided with a valve in the multi-water-source water supply pipe network system as a key position of the valve;
s2: constructing a transmission and distribution pattern optimization model, and setting decision variables, objective functions and constraint conditions of the transmission and distribution pattern optimization model;
s3: selecting an optimization algorithm suitable for solving a high-dimensional multi-objective optimization problem to solve the transmission and distribution pattern optimization model to obtain an optimized solution;
s4: and analyzing the relation among the optimization solutions to obtain an optimization scheme of the transmission and distribution pattern of the multi-water-source water supply network system.
Preferably, in the step S1, the pipeline position where the valve can be installed is screened by using a priori knowledge and a graph theory analysis method.
Preferably, in the step S1, the specific steps are as follows:
s11: determining a strong water source and a weak water source of a multi-water-source water supply network system;
s12: determining all transition nodes of the multi-water-source water supply pipe network system;
s13: determining a key node in the transition nodes;
s14: finding out a water supply critical path by using a depth-first algorithm;
s15: and determining the key position of the valve according to the preset pipe diameter range of the multi-water-source water supply pipe network system.
As a preferred scheme, the strong water source comprises a water source with a water supply amount and a water supply range larger than or equal to a preset condition, and the weak water source comprises a water source with a water supply amount and a water supply range smaller than a preset condition; the transition node comprises a node with water consumption provided by a strong water source and a weak water source together.
Preferably, in the step S14, the key node is used as a search starting point, the strong water source is used as an end point, and all paths are searched along a reverse water flow direction as water supply key paths.
Preferably, in the step S15, the pipelines within the pipe diameter range of the preset multi-water-source water supply pipe network system are screened, and the pipeline closest to the forced water source is screened according to the actual flow direction as the key position of the valve.
As a preferred scheme, the decision variables in the distribution pattern optimization model comprise the critical position of the valve and the opening degree of the valve; and when the transmission and distribution pattern optimization model is optimized, simulating and controlling the opening of the valve by changing the local head loss coefficient of the pipeline.
As a preferred scheme, the target of the distribution pattern optimization model comprises the leakage quantity percentage, the pressure balance, the water age condition, the maximum water age of nodes and the number of valves of the minimum multi-water-source water supply pipe network system, and the reliability and the weak water source water quantity amplification percentage of the maximum multi-water-source water supply pipe network system; the expression formula of the objective function is as follows:
wherein LP represents the percentage of leakage, STDP represents the node pressure equalization index, WA represents the water Age of the multi-source water supply pipe network system, AgemaxExpressing the maximum water age of the node, reducing expressing the reliability of the multi-water-source water supply pipe network system, NvThe number of the valves is represented, and the IP represents the water quantity amplification percentage of the weak water source.
Preferably, the constraints include node mass conservation, pipe segment energy conservation, and minimum node pressure constraints.
Preferably, in the step S4, the optimization solution is plotted in a multi-dimensional parallel coordinates map for analysis.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that: according to the invention, through constructing a high-dimensional multi-objective optimization model aiming at the problem of regulating the transmission and distribution pattern of the multi-water-source water supply network system, the advantages and disadvantages of each scheme are analyzed from multiple dimensions, a valve layout and regulation scheme with more comprehensive benefits and advantages can be found, the problem of deviation of actual water supply and a preset scheme is avoided, and the technical defects of low efficiency and one-sidedness of a manual experience method are avoided.
Drawings
Fig. 1 is a flow chart of a method for optimizing the distribution pattern of a multiple-water-source water supply network system according to embodiment 1.
FIG. 2 is a schematic diagram of pipe networks and pipeline screening results in J City of China in example 2.
Fig. 3 is a comparison graph of evaluation results before and after the pareto pioneer solution and the valve installation obtained by the high-dimensional multi-objective optimization technique in example 2.
FIG. 4 is a schematic diagram of water supply zones before optimization of the J city pipe network in China in embodiment 2.
FIG. 5 is a schematic diagram of the water supply zones of embodiment 2 after the optimization of the J-city pipe network in China.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
The embodiment provides a method for optimizing a distribution pattern of a multi-water-source water supply network system, and is a flowchart of the method for optimizing the distribution pattern of the multi-water-source water supply network system according to the embodiment, as shown in fig. 1.
The method for optimizing the transmission and distribution pattern of the multi-water-source water supply pipe network system provided by the embodiment comprises the following steps of:
s1: and (4) screening the positions of the pipelines capable of being provided with the valves in the multi-water-source water supply pipe network system as key positions of the valves.
In the step, the pipeline position where the valve can be installed is screened by using the priori knowledge and a graph theory analysis method. The screening process is as follows:
s11: determining a strong water source and a weak water source of the multi-water-source water supply network system, wherein the strong water source is a water source with a water supply amount and a water supply range larger than or equal to a preset condition, and the weak water source is a water source with a water supply amount and a water supply range smaller than the preset condition;
s12: determining all transition nodes of the multi-water-source water supply pipe network system, wherein the transition nodes are nodes with water consumption provided by a strong water source and a weak water source together, and the rest nodes are non-transition nodes;
s13: determining a key node in the transition nodes, wherein an upstream node immediately adjacent to the key node is a non-transition node;
s14: finding out a water supply key path by using a depth-first algorithm, specifically, taking a key node as a search starting point, taking the strong water source as an end point, and searching all paths in the reverse water flow direction to be used as water supply key paths;
s15: and screening the pipelines which accord with the preset pipe diameter range of the multi-water-source water supply pipe network system according to the preset pipe diameter range of the multi-water-source water supply pipe network system, and screening the pipeline which is closest to the forced water source as a key position of the valve according to the actual flow direction.
In this embodiment, the effect of "pressing" of the strong water source to the weak water source is reduced by installing the valve, so that the joint (i.e., the transition joint) for supplying water by the strong water source and the weak water source together needs to be started. In the embodiment, a valve is arranged in a pipeline from the strong water source to the transition node, the water supply quantity of the strong water source at the downstream of the valve is reduced, and the reduced water supply quantity is supplemented by the weak water source, so that the water supply pattern between the strong water source and the weak water source is adjusted. In the transition nodes, the nodes closest to the strong water source (namely key nodes) are found according to the water flow direction, and then all possible paths of the strong water source to the key nodes are found by using a depth-first algorithm. Considering that the pipe diameter of the pipe for actually installing the valve cannot be too large or too small, the pipe which meets the conditions is screened as the pipe for installing the valve according to the preset pipe diameter range on the path, namely, the key position of the valve is determined.
S2: and constructing a transmission and distribution pattern optimization model, and setting decision variables, objective functions and constraint conditions of the transmission and distribution pattern optimization model.
In the step, the layout of the valves and the opening of the valves are optimized simultaneously, so that the decision variables in the optimization model of the distribution pattern are the openings of the pipelines and the valves where the valves are installed. When the multi-water-source water supply network system is simulated, the opening degree of the regulating valve is simulated by changing the local head loss coefficient of the pipeline, and in the optimization process, the local head loss coefficients of different opening degrees of the valves under different pipe diameters are set according to parameters obtained by testing of a valve manufacturer.
The expression formula of the objective function in this step is as follows:
in the objective function, LP represents the percentage of the leakage amount, and the expression formula is as follows:
wherein, Leakage represents the total Leakage loss of the pipe network within 24 hours, DemandtotalRepresenting the total water usage within 24 hours of the network. In the optimization scheme of the pipe network transmission and distribution pattern, the smaller the obtained pipe network leakage amount is, the better the obtained pipe network leakage amount is, in this embodiment, the total leakage amount of the multi-water-source water supply pipe network system is expressed by the background leakage amount, and the calculation formula is as follows:
wherein QLiRepresenting the leakage per unit time of the pipeline, deltat representing the unit time length of the statistical leakage, npThe total number of the pipelines is,
is the pipe leakage coefficient, LiIs the length of the pipe, hiIs the average pressure head of the pipeline, nleakIs a loss pressure index, the value range of which is 0.5-2.5, Pi,1、Pi,2The pressure of the starting node and the final node of the pipeline is shown.
Objective functionIn the present embodiment, the Standard Deviation of the Pressure of the nodes is used to evaluate the Pressure balance of the nodes, so that the smaller the Standard Deviation is, the better the Pressure balance is. For a pipe network needing delay simulation, the standard deviation STDP of the node pressure of each hour is calculated firstlyhAccording to the STDP for 24 hourshAnd obtaining the standard deviation STDP of the node pressure of the pipe network, wherein the expression formula is as follows:
STDP＝median(STDPh),h＝1,2,...,24
wherein, Pi hIndicating the pressure at node i during the h hour,
the average pressure of all nodes in the pipe network in the h hour is represented, and nn represents the number of all nodes in the pipe network; the standard deviation STDP of the node pressure of the pipe network adopts the STDP of taking 24 hourshIs calculated in the manner of the median of (a).
In the objective function, WA represents the Water Age (Water Age) of a multi-source Water supply pipe network systemmaxRepresenting the maximum water age of the node. In the optimization scheme of the pipe network transmission and distribution pattern, the water age of each node of the pipe network is required to be small, so that the water age of the node needs to be minimized. In this embodiment, the node water ages of the entire pipe network are evaluated by using the weighted average water age and the maximum water age. For the weighted average age, the weighted average age of each hour in the pipe network is calculated
Then according to the time of the pipe network having the maximum weighted average water age within 24 hoursThe water age condition WA of the whole pipe network is characterized by the following expression formula:
wherein the content of the first and second substances,
representing the water usage of node i during the h hour,
indicating the age of node i at h. In order to avoid the situation that nodes with smaller water demand and larger water Age are weighted and backup nodes with larger water demand and smaller water Age are covered, the maximum water Age of the nodes appearing in 24 hours of the pipe network is counted in the objective function at the same timemaxThe overall measurement of the water age condition of the whole pipe network is expressed by the following formula:
in the objective function, Reduncy represents the reliability of the multi-water-source water supply pipe network system, and the higher the reliability of the pipe network is, the higher the probability that the pipe network still can normally supply water under the operation accident is, so that in the optimization scheme of the pipe network transmission and distribution pattern, the Reduncy is required to maximize the reliability of the multi-water-source water supply pipe network system. When the pipe network is subjected to delay simulation, the node pressure Redundancy of each hour pipe networkhThe calculation formula of (a) is as follows:
wherein, Pi minRepresents the minimum pressure allowed by node i, Pi maxRepresenting the maximum pressure allowed at node i. According to the time period with the minimum node pressure Redundancy within 24 hours of the pipe network, the reliability condition of the whole pipe network is represented, and an expression formula of the reliability Redunnancy of the multi-water-source water supply pipe network system is obtained:
Redundancy＝min(Redundancyh),h＝1,2,...,24。
the node pressure balance index STDP and the average water age of the nodes of the pipe network
And the calculation expressions of the reliability index Redunnancy of the pipe network system aim at the multi-water-source water supply pipe network system needing time delay simulation, and for the multi-water-source water supply pipe network system only needing instantaneous simulation, only the corresponding index STDP under a certain instantaneous state needs to be calculatedh、Ageh、RedundancyhAnd the corresponding numerical value can be obtained by one-step calculation directly according to the corresponding formula.
In the objective function, NvThe number of the valves is represented, and in the optimization scheme of the pipe network transmission and distribution pattern, the number of the installed valves needs to be minimized in consideration of the same influence on the pipe network (leakage quantity, water age, reliability and the like).
In the objective function, IP represents the percentage of Increase of water quantity of a weak water source (Increase Percent), and the expression formula is as follows:
wherein Q isvRepresents the total water yield, Q, of the weak water source within 24 hours after the valve is installed0Representing the total water output within 24 hours of the disadvantaged water source prior to valve installation.
Therefore, in the embodiment, the high-dimensional multi-objective optimization model is used for optimizing the valve layout and the opening scheme, and the optimization indexes comprise background leakage quantity, node pressure balance, average water age of nodes of the pipe network, reliability of the pipe network system, the amplification percentage of weak water source water quantity and the number of valves.
Further, the constraints in this embodiment include node mass conservation, pipe segment energy conservation, and minimum node pressure constraints.
S3: and selecting an optimization algorithm suitable for solving a high-dimensional multi-objective optimization problem to solve the distribution pattern optimization model to obtain an optimized solution.
S4: and analyzing the relation among the optimization solutions to obtain an optimization scheme of the transmission and distribution pattern of the multi-water-source water supply network system.
Furthermore, all the optimization solutions obtained through the optimization algorithm are drawn in a multi-dimensional parallel coordinate graph, the relation among all the optimization solutions is analyzed, and selection is carried out according to actual requirements, so that the optimization scheme of the transmission and distribution pattern of the multi-water-source water supply network system is obtained.
In the embodiment, the high-dimensional multi-target optimization model aiming at the regulation problem of the transmission and distribution pattern of the multi-water-source water supply network system is constructed, the advantages and disadvantages of all schemes are analyzed from multiple dimensions, the valve layout and the regulation scheme with more comprehensive benefits can be found, and the technical defects of low efficiency and one-sided manual experience method are overcome. In addition, in the embodiment, before the optimization algorithm is used for solving the problems of valve layout and opening combination, the key nodes on the partition boundaries of the multi-water-source water supply network system are determined by using the priori knowledge, the key paths are searched by using the depth-first algorithm, and the pipelines capable of being provided with the valves are screened out, so that the solution space of the optimization problem is greatly reduced.
Example 2
The embodiment is a specific implementation process of applying the method for optimizing the transmission and distribution pattern of the multi-water-source water supply pipe network system provided in embodiment 1 to the pipe network of the J city in China.
As shown in fig. 2, a schematic diagram of a pipe network in the J city of our country and a result of pipeline screening in this embodiment are shown, which show the distribution of the node water consumption source when the water consumption is the highest. The analysis of the J city pipe network in China is based on the highest time condition.
(1) Screening pipeline position capable of installing valve in multi-water-source water supply pipe network system as valve key position
The J city pipe network in China is supplied with water by two water sources, namely a water source 68 (a left water reservoir in the figure) and a water source 1 (a right water reservoir in the figure). Wherein the total head of the water source 68 is 50m and the total head of the water source 1 is 45 m. The high outlet pressure of the water source 68 stresses the water supply range of the water source 1, so most of the water demand of the pipe network in J city of China is provided by the water source 68, and the water supply pattern of the whole pipe network is not balanced. As can be seen, the strong water source in this embodiment is the water source 68, and the weak water source is the water source 1.
As can be seen from fig. 2, there are nodes that are commonly supplied by the water source 68 and by the water source 1, these nodes being transition nodes, with the nodes identified by the triangular icons being key nodes in the transition nodes.
The critical path of water supply is found by using a depth-first algorithm, as shown in fig. 2, the pipeline corresponding to the thick line with lighter gray scale is represented as an installable valve pipeline.
For the pipe network in J city of China, a valve is supposed to be installed in a pipeline with the diameter of DN400-6000, as shown in figure 2, the pipeline corresponding to the thick line with the deep gray scale is represented as the pipeline which is further screened according to the pipe diameter in the key path, and the pipeline is taken as the key position of the valve.
(2) Constructing a transportation and distribution pattern optimization model
The local head loss coefficient settings of the valve in this example are shown in table 1:
TABLE 1 local head loss coefficient settings for different opening of valve under different pipe diameters
The optimization of the embodiment considers 100%, 80%, 60%, 40% and 20% of opening, wherein 100% of opening means that no valve is installed on the pipeline.
Optimizing by adopting the objective function provided in embodiment 1, wherein in the calculation of the leakage loss, the value of the pipeline leakage loss coefficient is CL＝10-8m0.82S, the value of the loss pressure index is nleak1.18. In the reliability evaluation, the maximum pressure allowed by the node is Pmax48.5m, the minimum pressure allowed at the node is Pmin＝15m。
(3) Optimization solution
For the J city pipe network in China, each optimized solution has 7 decision variables (7 optional pipelines are obtained by screening in total), and each decision variable has 5 optional values (5 valve opening selections), so that the solution space of the objective function is 57＝78125。
In this embodiment, a Borg optimization algorithm is selected to perform optimization solution on the transmission and distribution layout optimization model. Borg is a multi-objective evolutionary algorithm developed specifically for solving high-dimensional multi-objective models. Therefore, for a high-dimensional multi-objective optimization problem, the Borg algorithm has good solving capacity. According to the problem scale, the Borg algorithm parameters are set as follows: the population size was 100 and the total number of evaluations was 10000.
(4) Analyzing the optimization solution to obtain an optimization scheme
As shown in fig. 3, a comparison graph of the evaluation results before and after the pareto pioneer solution and the valve installation obtained by the high-dimensional multi-objective optimization technique is shown. In addition to the two representative solutions, the other solutions are presented in a low-grayscale polyline manner.
As shown in fig. 3, the present embodiment has 7 targets, and the index corresponding to each solution is represented by a numerical value on the 7-column ordinate axis. The color of each polyline is assigned with the leakage size of the first column. For example, the solution corresponding to the maximum value of the total Leakage loss amount Leakage is connected with the index values by a lighter gray broken line.
It can be seen from the figure that as the total Leakage decreases, the reduction decreases while the percentage increase in the water output of the water source 1 increases. As can be seen from the calculation formula of the Leakage loss amount leak, a decrease in the Leakage loss amount leak means that the pressure of the entire pipe network also decreases, and therefore the pressure redundancy decreases. The more the pressure drops, the greater the resistance to the passage of water from the source 68 after the valve is installed, thus increasing the output of the source 1. Other indexes do not show obvious rules.
After the optimization solution is carried out on the transmission and distribution pattern optimization model, the rationality of the scheme can be evaluated in multiple dimensions, and therefore a solution which best meets the actual requirement is found out. In particular, fig. 3 shows 2 broken lines, where the lower gray line represents the index distribution without valves and the higher gray line represents the index distribution with one of the representative optimization solutions. After 5 valves are added according to the optimized scheme of the transmission and distribution pattern of the multi-water-source water supply network system, the leakage loss of the network is reduced from 5.04% to 4.75%, and the increase of the water yield of the water source 1 is 7.49%. The node pressure balance index STDP is increased to 3.17 from the original 2.88, the average water age of the pipe network is unchanged, the maximum water age maxApe of the pipe network is increased to 12.8 from 10.98, and the pressure Redundancy rednancy is reduced to 0.33 from 0.44. As can be seen from FIG. 3, the addition of the valve to the optimized solution (broken line with higher gray scale) does not have too much negative effect on the multi-source water supply pipe network system after the water output of the water source 1 is adjusted upwards.
Fig. 4 and 5 are water supply subarea conditions before and after optimization, respectively, wherein fig. 4 is the water supply subarea condition before valve installation (before optimization), and fig. 5 is the optimized water supply subarea condition obtained after optimization solution is substituted into pipe network simulation operation. Wherein, the water consumption of the node marked as the medium gray is 100% provided by the water source 68, the water consumption of the node marked as the deep gray is 100% provided by the water source 1, the water consumption of the node marked as the shallow node is provided by the water sources 68 and 1, and the position of the pipeline marked by the thick high gray line on the right graph of fig. 4 is the position for installing the valve. After optimization, the water supply pattern of the water supply pipe network system is changed, the water supply scale of the strong water source 68 is reduced, the water supply scale of the weak water source 1 is increased, and meanwhile, the dividing line of the water supply subareas moves towards the direction of the water source 68, so that the water supply layout of the pipe network system is obviously improved.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. A multi-water-source water supply network system distribution pattern optimization method is characterized by comprising the following steps:
s1: screening the position of a pipeline capable of being provided with a valve in the multi-water-source water supply pipe network system as a key position of the valve;
s2: constructing a transmission and distribution pattern optimization model, and setting decision variables, objective functions and constraint conditions of the transmission and distribution pattern optimization model;
s3: selecting an optimization algorithm suitable for solving a high-dimensional multi-objective optimization problem to solve the transmission and distribution pattern optimization model to obtain an optimized solution;
s4: and analyzing the relation among the optimization solutions to obtain an optimization scheme of the transmission and distribution pattern of the multi-water-source water supply network system.
2. The method for optimizing the distribution pattern of the multi-water-source water supply pipe network system according to claim 1, wherein in the step S1, the positions of the pipes where the valves can be installed are screened by using a priori knowledge and a graph theory analysis method.
3. The method for optimizing the transportation and distribution pattern of a multi-water source water supply pipe network system according to claim 1, wherein the step of S1 comprises the following specific steps:
s11: determining a strong water source and a weak water source of a multi-water-source water supply network system;
s12: determining all transition nodes of the multi-water-source water supply pipe network system;
s13: determining a key node in the transition nodes;
s14: finding out a water supply critical path by using a depth-first algorithm;
s15: and determining the key position of the valve according to the preset pipe diameter range of the multi-water-source water supply pipe network system.
4. The method as claimed in claim 3, wherein the strong water source includes water sources with water supply amount and water supply range larger than the preset condition, and the weak water source includes water sources with water supply amount and water supply range smaller than the preset condition; the transition node comprises a node with water consumption provided by a strong water source and a weak water source together.
5. The method for optimizing the distribution pattern of a multi-water-source water supply pipe network system according to claim 3, wherein in the step S14, all the paths are searched in the reverse water flow direction as the critical paths for water supply by using the critical nodes as the search starting points and the strong water sources as the end points.
6. The method for optimizing the distribution pattern of a multi-source water supply pipe network system according to claim 3, wherein in the step S15, the pipelines within the preset pipe diameter range of the multi-source water supply pipe network system are screened, and the pipeline closest to the strong water source is screened according to the actual flow direction as the key position of the valve.
7. The method for optimizing the distribution pattern of the multiple water source water supply pipe network system according to claim 1, wherein the decision variables in the distribution pattern optimization model include critical positions of valves and opening degrees of the valves; and when the transmission and distribution pattern optimization model is optimized, simulating and controlling the opening of the valve by changing the local head loss coefficient of the pipeline.
8. The method for optimizing the distribution pattern of the multi-water-source water supply pipe network system according to claim 1, wherein the goal of the distribution pattern optimization model comprises minimizing the percentage of leakage, pressure equalization, water age condition, maximum node water age, number of valves, and maximizing the reliability of the multi-water-source water supply pipe network system and the percentage of increase of water quantity of a weak water source; the expression formula of the objective function is as follows:
wherein LP represents the percentage of leakage, STDP represents the nodal pressure equalization index, WA represents the water in the multiple water source water supply piping network systemAge condition, AgemaxExpressing the maximum water age of the node, reducing expressing the reliability of the multi-water-source water supply pipe network system, NvThe number of the valves is represented, and the IP represents the water quantity amplification percentage of the weak water source.
9. The method for optimizing the distribution pattern of a multiple water source water supply piping system of claim 1, wherein the constraints include conservation of mass of nodes, conservation of energy of pipe segments, and minimum node pressure constraints.
10. The method for optimizing the transportation and distribution pattern of a multi-water source water supply pipe network system according to claim 1, wherein in the step S4, the optimization solution is plotted in a multi-dimensional parallel coordinate graph for analysis.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012246684A (en) * | 2011-05-27 | 2012-12-13 | Meidensha Corp | Water operation system and water operation method |
| US20160103452A1 (en) * | 2014-10-14 | 2016-04-14 | Lsis Co., Ltd. | System and method for managing water in water pipe network |
| WO2016167453A1 (en) * | 2015-04-14 | 2016-10-20 | 고려대학교 산학협력단 | Metaheuristic method for designing pipe network on basis of water source tracing |
| JP2017045222A (en) * | 2015-08-26 | 2017-03-02 | 株式会社日立製作所 | Update planning apparatus and update planning method |
| CN106886156A (en) * | 2017-05-03 | 2017-06-23 | 杭州电子科技大学 | Feed pipe gateway valve method based on binary system multi-objective particle swarm algorithm |
| US20180068038A1 (en) * | 2015-05-22 | 2018-03-08 | Dong-A University Research Foundation For Industry Academy Cooperation | Method for optimal design of aquifer injection-pumping system |
| CN108876066A (en) * | 2018-09-04 | 2018-11-23 | 常州英集动力科技有限公司 | Heat supply network off-the-line operating scheme real-time optimization method and its system |
| CN110334850A (en) * | 2019-05-30 | 2019-10-15 | 中国地质大学（武汉） | A kind of water supply network valve layout designs and optimization method |
| CN110425427A (en) * | 2019-08-19 | 2019-11-08 | 吉林建筑大学 | A kind of control method of water supply network leakage |
| CN110782366A (en) * | 2019-10-12 | 2020-02-11 | 大连理工大学 | Water supply pipe network multi-objective optimization regulation and control method based on scene uncertainty |
| CN111080483A (en) * | 2019-12-17 | 2020-04-28 | 上海市城市建设设计研究总院（集团）有限公司 | DMA automatic partitioning method for water supply network based on graph division |
-
2021
- 2021-02-22 CN CN202110197021.7A patent/CN112926164B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012246684A (en) * | 2011-05-27 | 2012-12-13 | Meidensha Corp | Water operation system and water operation method |
| US20160103452A1 (en) * | 2014-10-14 | 2016-04-14 | Lsis Co., Ltd. | System and method for managing water in water pipe network |
| WO2016167453A1 (en) * | 2015-04-14 | 2016-10-20 | 고려대학교 산학협력단 | Metaheuristic method for designing pipe network on basis of water source tracing |
| US20180068038A1 (en) * | 2015-05-22 | 2018-03-08 | Dong-A University Research Foundation For Industry Academy Cooperation | Method for optimal design of aquifer injection-pumping system |
| JP2017045222A (en) * | 2015-08-26 | 2017-03-02 | 株式会社日立製作所 | Update planning apparatus and update planning method |
| CN106886156A (en) * | 2017-05-03 | 2017-06-23 | 杭州电子科技大学 | Feed pipe gateway valve method based on binary system multi-objective particle swarm algorithm |
| CN108876066A (en) * | 2018-09-04 | 2018-11-23 | 常州英集动力科技有限公司 | Heat supply network off-the-line operating scheme real-time optimization method and its system |
| CN110334850A (en) * | 2019-05-30 | 2019-10-15 | 中国地质大学（武汉） | A kind of water supply network valve layout designs and optimization method |
| CN110425427A (en) * | 2019-08-19 | 2019-11-08 | 吉林建筑大学 | A kind of control method of water supply network leakage |
| CN110782366A (en) * | 2019-10-12 | 2020-02-11 | 大连理工大学 | Water supply pipe network multi-objective optimization regulation and control method based on scene uncertainty |
| CN111080483A (en) * | 2019-12-17 | 2020-04-28 | 上海市城市建设设计研究总院（集团）有限公司 | DMA automatic partitioning method for water supply network based on graph division |
Non-Patent Citations (10)
| Title |
|---|
| CHENGSHA LIANG ET AL: "Research on multi-source collaborative simulation and operation optimization of regional centralized supply system", 《2020 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS)》 * |
| WANG QI ET AL: "Impact of problem formulations, pipe selection methods,and optimization algorithms on the rehabilitation of water distribution systems", 《JOURNAL OF WATER SUPPLY: RESEARCH AND TECHNOLOGY—AQUA》 * |
| YANG JIANJUN ET AL: "Simultaneous optimization of start up scheme and pipe network for multi-source water injection system based on improved genetic particle swarm optimization algorithm", 《PROC. 2015 INT. CONF. MATERIALS ENGINEERING AND INFORMATION TECHNOLOGY APPLICATIONS (MEITA 2015), COMPUTER SCIENCE AND ELECTRONIC TECHNOLOGY INTERNATIONAL SOCIETY》 * |
| 付强 等: "基于Flowmaster的不同阀门开度对供水管网优化", 《排灌机械工程学报》 * |
| 戴雪峰: "多水源供水系统优化调度及管网铁释放研究", 《中国优秀硕士学位论文全文数据库 (工程科技Ⅱ辑)》 * |
| 方海恩: "大规模供水管网多水源优化调配运行研究", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 曹平 等: "管网模型在多水源供水优化调度中的应用研究", 《中国给水排水》 * |
| 王礼炳 等: "基于高维多目标优化的供水管网背景漏失控制优化模型", 《给水排水》 * |
| 耿为民: "给水管网压力调节阀门优化控制", 《计算机技术》 * |
| 陈晨: "多水源供水系统泵组优化控制漏失", 《中国优秀硕士学位论文全文数据库 (工程科技Ⅱ辑)》 * |
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