CN112967765A - Residual chlorine optimization model of annular water supply pipe network and pipe diameter optimization method thereof - Google Patents
Residual chlorine optimization model of annular water supply pipe network and pipe diameter optimization method thereof Download PDFInfo
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- 239000000460 chlorine Substances 0.000 title claims abstract description 81
- ZAMOUSCENKQFHK-UHFFFAOYSA-N Chlorine atom Chemical compound [Cl] ZAMOUSCENKQFHK-UHFFFAOYSA-N 0.000 title claims abstract description 69
- 229910052801 chlorine Inorganic materials 0.000 title claims abstract description 69
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 57
- 238000005457 optimization Methods 0.000 title claims abstract description 52
- 238000000034 method Methods 0.000 title claims abstract description 21
- 239000011159 matrix material Substances 0.000 claims abstract description 102
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 23
- 238000005295 random walk Methods 0.000 claims abstract description 11
- 230000006870 function Effects 0.000 claims description 9
- 238000002789 length control Methods 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims description 6
- 229910001141 Ductile iron Inorganic materials 0.000 claims description 3
- 229910000831 Steel Inorganic materials 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 3
- 239000010959 steel Substances 0.000 claims description 3
- 230000001502 supplementing effect Effects 0.000 claims description 3
- 235000020188 drinking water Nutrition 0.000 abstract description 3
- 239000003651 drinking water Substances 0.000 abstract description 3
- 239000008399 tap water Substances 0.000 description 3
- 235000020679 tap water Nutrition 0.000 description 3
- 244000000010 microbial pathogen Species 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 239000000645 desinfectant Substances 0.000 description 1
- 238000011438 discrete method Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
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Abstract
A residual chlorine optimization model of an annular water supply pipe network and a pipe diameter optimization method thereof belong to the field of municipal engineering and urban water supply pipe networks, and comprise the following steps: establishing a local dynamic pipe database; generating a pipe network system inp file based on the C language; automatically creating a pipe diameter optimization model which is mutually fed with a pipe database and aims at minimizing the total residual chlorine of a pipe network; and an ICS-GDA algorithm is provided for optimizing the model, and the specific algorithm is as follows: generating a pipe diameter matrix through a random walk mode and an approximation principle, realizing update iteration of the pipe diameter matrix through an update mode of spiral Levy flight and a abandon principle of a flood algorithm, and carrying out EPANET hydraulic judgment through mutual feedback of an inp file and a local dynamic pipe database to obtain a group of pipe diameter combinations with the minimum total residual chlorine amount of a pipe network and a set of pipe network system information. The invention effectively solves the inaccuracy of the traditional heuristic algorithm in determining the pipe diameter and reduces the safety risk caused by the pollution of drinking water.
Description
Technical Field
The invention belongs to the field of municipal engineering and urban water supply networks, and relates to a residual chlorine optimization model of an annular water supply network and a pipe diameter optimization method thereof.
Background
With the development and modernization of town water supply networks, the demands of users on quantity (flow and pressure) and quality (physical and chemical properties of water) need to be met, and the requirements of people on the quality of tap water are far higher than the quantity of tap water. Among the various disinfectants, chlorine and its derivatives are widely used because of their relatively low cost, ease of use, and suitability for treating pathogenic microorganisms in water distribution pipelines. When chlorine-containing water flows in a water supply pipe network, the chlorine-containing water reacts with various substances in the water and in the pipe wall, so that chlorine in the water is gradually reduced in the conveying process. The key of water quality management is to keep the content of residual chlorine in a water supply network within a safe range (not less than 0.05mg/L in China) so as to control the growth of pathogenic microorganisms in water and maintain the water quality of tap water. Therefore, how to develop and apply an optimization algorithm to control the residual chlorine concentration of the pipe network within a safe range as much as possible on the premise of ensuring the safety and reliability of water supply becomes a key problem that the current pipe network design needs to be researched urgently.
Disclosure of Invention
The invention aims to provide a residual chlorine optimization model of an annular water supply pipe network and a pipe diameter optimization method thereof aiming at the defects in the prior art, and the pipe diameter optimization of the pipe network can be realized by the optimization method on the premise of ensuring the safety and reliability of water supply, so that the total residual chlorine content of the pipe network is minimum.
The technical scheme of the invention is as follows: a residual chlorine optimization model of an annular water supply pipe network and a pipe diameter optimization method thereof are characterized by comprising the following steps:
(1) acquiring the commercial information of the water supply pipes of different pipes, continuously updating the information content according to market change, forming a dynamic scattered point line graph by monthly information, selecting the average value of images as current real-time data according to nearly 6 months, and establishing a local dynamic pipe database;
(2) based on a hydraulic analysis engine EPANET, the initial conditions and the set arrangement mode of the town annular water supply pipe network system are perfected, and a net file of the town annular water supply pipe network system is output; reading a pipe network system and a net file through C language, adding attribute categories in each data layer of the initial condition and the established arrangement mode of the pipe network system, creating inp files, and writing the attribute categories and the corresponding pipe network information in the inp files;
(3) reading an inp file of a pipe network system in a binary mode, automatically extracting data information required by a pipe diameter optimization model in the inp file according to attribute types, and automatically generating mutual feedback with a local dynamic pipe database by combining the local dynamic pipe database so as to obtain the pipe diameter (D) of each pipe sectioni) For discrete decision variables, the total residual chlorine (Cl) of the pipe network is minimizedmin) The pipe diameter optimization model is a target, and the specific optimization model is as follows:
an objective function:
constraint 1 (node continuity equation):
constraint 2 (ring energy equation):
constraint 3 (node minimum head):
constraint 4 (nodal minimum residual chlorine content):
in the formula: n is the number of pipe sections, m is the number of nodes, and q is the number of closed loops; ciTaking the average value of the concentrations of two nodes at the beginning and the end of the pipe section as the concentration (mg/L) of the residual chlorine in the ith pipe section in the water body, wherein the calculation formula of the node concentration is as follows: dc/dt-kc, t is the time(s) taken from the source node to a certain node, and the pipe diameter (D)i) There is an inverse relationship, the pipe diameter is obtained by comparing the pipe database, DiE { D (1), D (2),.., D (np) }, np is the number of selectable commercial pipe diameters; k is the reaction rate constant, i.e., the overall attenuation coefficient, which can be calculated by the following equation: k is kb+kf·kw/rh·(kf+kw)，rhIs the hydraulic radius (m), k of the pipe sectionbIs the attenuation coefficient (min) of water body-1)，kfIs the mass transfer coefficient (m/min), kwThe attenuation coefficient (m/min) of the tube wall; liThe tube length of the ith tube section; qj,in、Qj,outThe respective flows (l/s), Q flowing into and out of the node jjThe traffic (l/s) that needs to be satisfied for node j; Δ HkHead loss (m) for a closed loop k in an annular water supply network, wherein head loss (H) can be calculated by: h ═ ω · Qβ·L/(CW β·Dγ) Wherein ω, β, γ are constants; cWThe coefficient is a Hazen-William coefficient and is obtained by comparing a pipe database; hj、Hj,max、Hj,minA free head (m), a maximum allowable head (m) and a minimum allowable head (m) at node j, respectively; cj、Cj,minRespectively meeting the residual chlorine concentration and the minimum residual chlorine content requirement of the node j;
(4) the pipe diameter matrix U of the water supply pipe network system is coupled with a flood algorithm program (ICS-GDA) through improving a valley distribution bird algorithm, automatic iterative optimization of mutual information feedback of the pipe diameter matrix U of the pipe network system and a local dynamic pipe database is completed, EPANET hydraulic judgment is carried out through mutual information feedback of an inp file and the local dynamic pipe database, and a pipe diameter combination with the minimum total residual chlorine of the pipe network is determined, wherein the specific ICS-GDA algorithm comprises the following steps:
(4.1) initializing ICS-GDA algorithm parameters: setting the number of lines (N) of the pipe diameter matrix U and the maximum step length control factor (alpha)max) And maximum number of iterations (t)max)；
(4.2) t is 1, and an initial Nxn pipe diameter matrix U is generated through a random walk mode and an approximation principle (d)ij)N×n；
(4.3) in the t-th iteration, iterative update and discard of U using ICS-GDA and EPANET:
the updating mode of the spiral levy flight is as follows:
in the formula:
respectively representing the ith matrix row in the t generation and the t +1 generation of the pipeline matrix U; alpha is a step length control factor and is calculated by an equation (7); levy (lambda) is a random search path matrix and obeys Levy distribution: levy (λ) ═ μ · Φ/| ν1/βMu and v follow a standard normal distribution, phi ═ Γ (1+ β) · sin (pi · β/2)]/[Γ(1+β)·β·2(β-1)/2/2]Γ (1+ β) is a Γ function, i.e.
1+ beta > 0, beta is a constant, beta belongs to [0,2 ]]；xbest tFor optimal pipe diameter combination of the t-th generation, DtIs xi tTo xbest tDistance of (D)t＝|xbest t-xi tI, b is a spiral constant, p, l are [0,1 ]]A random number in between;
the abandoning steps are as follows: calculating and sequencing all matrix rows (x) in the pipe diameter matrix U before and after the iteration of the formula (6) through EPANET and an objective function after the pipe diameter matrix U which is subjected to the updating stepi t、xi t+1) Total residual chlorine (F) of pipe networki t、Fi t +1) Will Fi t+1And Fi tBy comparison, if Fi t+1Preferably, x is usedi t+1Replace xi tOtherwise, the result is not changed;
(4.4) abandoning the optimized pipe diameter matrix U through a flood algorithm (GDA) if the total residual chlorine content is higher than CllevelX ofi t+1All are discarded, and the specific discarding formula is as follows:
Cllevel＝Cllevel-UP (8)
in the formula: cllevelThe initial value of the initial pipe diameter matrix is the average value of the total residual chlorine of N pipe networks corresponding to the initial pipe diameter matrix U; UP is the standard deviation of the total residual chlorine of N pipe networks.
Then, the new matrix row is supplemented by the random walk and approximation principle of step (4.2), but the update formula is improved to the following formula:
in the formula: ε is [0,2]Random number between, xminAnd xmaxMinimum and maximum commercial pipe diameters, respectively; xi is [ -1,1]A random number in between; pa < 0.2 indicates that the generation of the new matrix row is completed by the formula (9) in the first 20% of the better matrix rows cut in the t generation, and Pa > 0.2 indicates that the generation of the new matrix row is completed by the formula (9) in the second 80% of the worse matrix rows;
(4.5) through the approximation principle discrete value of the step (4.4), covering each matrix row of a new pipe diameter matrix U, mutually feeding the 'pipe diameter' attribute category in the inp file and the local pipe database information, adjusting a Haizhen-Weilian coefficient in the inp file, carrying out EPANET hydraulic judgment, and discarding the matrix rows which do not meet the constraint; then supplementing a new matrix row by the random walk mode and the approximation principle of the step 4.4, and judging EPANET hydraulic power by the new matrix row again until all the matrix rows of the pipe diameter matrix U meet the constraint, and calculating and sequencing the total residual chlorine amount of the pipe network of all the matrix rows in the pipe diameter matrix U, wherein t is t + 1;
(4.6)t＞tmaxterminating iteration to obtain an optimal pipe diameter matrix row;
(5) and after the ICS-GDA optimization of the pipe diameter of the pipe network system is finished, outputting all attribute categories and corresponding pipe network information in the inp file corresponding to the optimal pipe diameter matrix row.
The tubing database described in step (1) comprising: the inner diameters of the pipelines of the ductile cast iron pipe, the PE pipe, the welded steel pipe and the concrete pipe, and the corresponding price and Haizhong-Weiliang coefficient.
The initial conditions and the established arrangement mode of the town annular water supply pipe network system in the step (2) comprise: the preset number of each node, the preset elevation of each node, the preset outflow of each node, the residual chlorine amount of the factory water, the preset number of each pipe section, the preset pipe length of each pipe section, the initial pipe diameter of each pipe section, the initial Hazevrai coefficient of each pipe section, the selectable commercial pipe diameter and the corresponding price and the Hazevrai coefficient thereof.
The attribute type of the data information in the step (2) includes: pipe section number, pipe diameter, pipe length, Haizhen-Weilian coefficient, node number and node demand.
The mode for generating the initial pipe diameter matrix U through the approximation principle in the step (4) is as follows: first, a tube diameter matrix U ═ N (d) of N × N is randomly generated by equation (10)ij)N×n(ii) a Then, carry out data standardization to this pipe diameter matrix, namely: using selectable commercial pipe diameter values (D) approximating said combination of pipe diametersi) Elements in the matrix are replaced one by one to realize discretization of pipe diameter combination, so that each pipe diameter value belongs to a set of selectable commercial pipe diameters;
xp＝xmin+ξ(xmax-xmin) (10)
in the formula: x is the number ofpIs the p-th pipe diameter; x is the number ofminAnd xmaxMinimum and maximum commercial pipe diameters, respectively; xi is in the middle of 0,1]。
The pipe network information in the step (5) comprises: the residual chlorine amount of each node, the total residual chlorine amount of a pipe network, the total cost of investment and construction, the optimal design pipe diameter of each pipe section and the corresponding Haizhong-Weilian coefficient thereof, the node pressure of each node, the head loss of each pipe section and the conveying flow of each pipe section.
The invention has the beneficial effects that: the invention provides a residual chlorine optimization model of an annular water supply pipe network and a pipe diameter optimization method thereof, wherein the model comprises the following steps: establishing a local dynamic pipe database; generating a pipe network system inp file based on the C language; automatically creating a pipe diameter optimization model which is mutually fed with a pipe database and takes the minimum total residual chlorine amount of a pipe network as a target; an ICS-GDA algorithm is provided for optimizing the model, the flood algorithm only depends on one parameter, and the optimal solution can be found at a higher operation speed, and the specific algorithm is as follows: the pipe diameter matrix is generated through a random walk mode and an approximation principle, the pipe diameter fluctuation amplitude can be reduced by an improved matrix row generation formula in the later iteration stage, and the optimal pipe diameter combination of the tth generation is close to the optimal solution which can be found in the later iteration stage, so that the later-stage optimization is more rapid and accurate by the improved formula; meanwhile, an irregular updating formula is still reserved, the optimization process cannot be trapped in a local optimal solution, and the global and local optimization processes are balanced. Updating iteration of the pipe diameter matrix is realized through the updating mode of spiral levy flight and the abandoning principle of a flood algorithm, EPANET hydraulic judgment is carried out through mutual feedback of inp files and a local dynamic pipe database, and a group of pipe diameter combinations and a set of pipe network system information with the minimum total residual chlorine amount of a pipe network are obtained. The invention effectively solves the inaccuracy of the traditional heuristic algorithm in determining the pipe diameter and reduces the safety risk caused by the pollution of drinking water.
Drawings
FIG. 1 is a flow chart of a residual chlorine optimization model and a pipe diameter optimization method thereof for an annular water supply pipe network.
Detailed Description
The invention will be further described with reference to the accompanying drawings in which:
as shown in FIG. 1, the method of the present invention comprises the following steps:
(1) acquiring the commercial information of the water supply pipes of different pipes, continuously updating the information content according to market change, forming a dynamic scatter broken line graph by monthly information, selecting the average value of the images according to nearly 6 months as current real-time data, and establishing a local dynamic pipe database, wherein the local dynamic pipe database comprises the selectable commercial pipe inner diameters of common pipes such as ductile cast iron pipes, PE pipes, welded steel pipes, concrete pipes and the like, and the corresponding local commercial prices and Haizhong-Weiliang coefficients.
(2) Based on a hydraulic analysis engine EPANET, the initial conditions and the established arrangement mode of the town annular water supply pipe network system are perfected, namely: the method comprises the following steps of setting the number of each node, the elevation of each node, the flow rate of each node, the residual chlorine amount of factory water, the number of each pipe section, the length of each pipe section, the initial pipe diameter of each pipe section, the initial Hazewaii coefficient of each pipe section, the available commercial pipe diameter and the corresponding price and Hazewaii coefficient; outputting a net file of the urban annular water supply pipe network system; net files are read through C language, and attribute categories are added in each data layer of the initial conditions and the established arrangement mode of the pipe network system, namely: creating an inp file and writing in attribute categories and corresponding pipe network information of the inp file;
(3) reading an inp file of a pipe network system in a binary mode, automatically extracting data information required by a pipe diameter optimization model in the inp file according to attribute types, and automatically generating mutual feedback with a local dynamic pipe database by combining the local dynamic pipe database so as to obtain the pipe diameter (D) of each pipe sectioni) For discrete decision variables, the total residual chlorine (Cl) of the pipe network is minimizedmin) The pipe diameter optimization model is a target, and the specific optimization model is as follows:
an objective function:
constraint 1 (node to node)Continuity equation):
constraint 2 (ring energy equation):
constraint 3 (node minimum head):
constraint 4 (nodal minimum residual chlorine content):
in the formula: n is the number of pipe sections, m is the number of nodes, and q is the number of closed loops; ciTaking the average value of the concentrations of two nodes at the beginning and the end of the pipe section as the concentration (mg/L) of the residual chlorine in the ith pipe section in the water body, wherein the calculation formula of the node concentration is as follows: dc/dt-kc, t is the time(s) taken from the source node to a certain node, and the pipe diameter (D)i) There is an inverse relationship, the pipe diameter is obtained by comparing the pipe database, DiE { D (1), D (2),.., D (np) }, np is the number of selectable commercial pipe diameters; k is the reaction rate constant, i.e., the overall attenuation coefficient, which can be calculated by the following equation: k is kb+kf·kw/rh(kf+kw)，rhIs the hydraulic radius (m), k of the pipe sectionbIs the attenuation coefficient (min) of water body-1)，kfIs the mass transfer coefficient (m/min), kwThe attenuation coefficient (m/min) of the tube wall; liThe tube length of the ith tube section; qj,in、Qj,outThe respective flows (l/s), Q flowing into and out of the node jjThe traffic (l/s) that needs to be satisfied for node j; Δ HkHead loss (m) for a closed loop k in an annular water supply network, wherein head loss (H) can be calculated by: h ═ ω · Qβ·L/(CW β·Dγ) Wherein ω, β, γ are constants; cWThe coefficient is a Hazen-William coefficient and is obtained by comparing a pipe database; hj、Hj,max、Hj,minA free head (m), a maximum allowable head (m) and a minimum allowable head (m) at node j, respectively; cj、Cj,minRespectively the residual chlorine concentration and the minimum residual chlorine content requirement of the node j.
(4) The pipe diameter matrix U of the water supply pipe network system is coupled with a flood algorithm program (ICS-GDA) through improving a valley distribution bird algorithm, automatic iterative optimization of mutual information feedback of the pipe diameter matrix U of the pipe network system and a local dynamic pipe database is completed, EPANET hydraulic judgment is carried out through mutual information feedback of an inp file and the local dynamic pipe database, and a pipe diameter combination with the minimum total residual chlorine of the pipe network is determined, wherein the specific ICS-GDA algorithm comprises the following steps:
(4.1) initializing ICS-GDA algorithm parameters: setting the number of lines (N) of the pipe diameter matrix U and the maximum step length control factor (alpha)max) And maximum number of iterations (t)max)；
(4.2) t is 1, and an initial Nxn pipe diameter matrix U is generated by a random walk mode and an approximation principle (a discrete method) (d)ij)N×nThe method comprises the following specific steps: first, a tube diameter matrix U ═ N (d) of N × N is randomly generated by equation (8)ij)N×n(ii) a Then, carry out data standardization to this pipe diameter matrix, namely: using selectable commercial pipe diameter values (D) approximating said combination of pipe diametersi) Elements in the matrix are replaced one by one, discretization of pipe diameter combination is achieved, and all pipe diameter values belong to a set of selectable commercial pipe diameters.
xp＝xmin+ξ(xmax-xmin) (10)
In the formula: x is the number ofpIs the p-th pipe diameter; x is the number ofminAnd xmaxMinimum and maximum commercial pipe diameters, respectively; xi is in the middle of 0,1]；
(4.3) in the t-th iteration, iterative update and discard of U using ICS-GDA and EPANET:
the updating mode of the spiral levy flight is as follows:
in the formula: x is the number ofi t、xi t+1Respectively representing the ith matrix row in the t generation and the t +1 generation of the pipeline matrix U; alpha is a step length control factor and is calculated by an equation (7); levy (lambda) is a random search path matrix and obeys Levy distribution: levy (λ) ═ μ · Φ/| ν1/βMu and v follow a standard normal distribution, phi ═ Γ (1+ β) · sin (pi · β/2)]/[Γ(1+β)·β·2(β-1)/2/2]Γ (1+ β) is a Γ function, i.e.
1+ beta > 0, beta is a constant, beta belongs to [0,2 ]]；xbest tFor optimal pipe diameter combination of the t-th generation, DtIs xi tTo xbest tDistance of (D)t＝|xbest t-xi tI, b is a spiral constant, p, l are [0,1 ]]A random number in between;
the abandoning steps are as follows: calculating and sequencing all matrix rows (x) in the pipe diameter matrix U before and after the iteration of the formula (7) through EPANET and an objective function after the pipe diameter matrix U which is subjected to the updating stepi t、xi t+1) Total residual chlorine (F) of pipe networki t、Fi t +1) Will Fi t+1And Fi tBy comparison, if Fi t+1Preferably, x is usedi t+1Replace xi tOtherwise, the result is not changed;
(4.4) abandoning the optimized pipe diameter matrix U through a flood algorithm (GDA) if the total residual chlorine content is higher than CllevelX ofi t+1All are discarded, and the specific discarding formula is as follows:
Cllevel＝Cllevel-UP (8)
in the formula: cllevelThe initial value of (1) is N pipe network total remainders corresponding to the initial pipe diameter matrix UAverage value of chlorine amount; UP is the standard deviation of the total residual chlorine of N pipe networks.
Then, the new matrix row is supplemented by the random walk and approximation principle of step (4.2), but the update formula is improved to the following formula:
in the formula: ε is [0,2]Random number between, xminAnd xmaxMinimum and maximum commercial pipe diameters, respectively; when epsilon is less than 1, plus or minus is taken out, and when epsilon is more than or equal to 1, plus or minus is taken out; xi is [0,1 ]]A random number in between; pa < 0.2 indicates that the generation of the new matrix row is completed by the formula (9) in the first 20% of the better matrix rows cut in the t generation, and Pa > 0.2 indicates that the generation of the new matrix row is completed by the formula (9) in the second 80% of the worse matrix rows;
(4.5) discretely taking values again according to the approximation principle of the step (4.4), covering each matrix row of a new pipe diameter matrix U, mutually feeding the attribute type of the pipe diameter in the inp file and the information of a local pipe database, adjusting a Haizhong-Wei-Ni coefficient in the inp file, performing EPANET hydraulic judgment, and discarding the matrix rows which do not meet the constraint; then supplementing a new matrix row by the random walk mode and the approximation principle of the step 4.4, and judging EPANET hydraulic power by the new matrix row again until all the matrix rows of the pipe diameter matrix U meet the constraint, and calculating and sequencing the total residual chlorine amount of the pipe network of all the matrix rows in the pipe diameter matrix U, wherein t is t + 1;
(4.6)t＞tmaxterminating iteration to obtain an optimal pipe diameter matrix row;
(5) after the ICS-GDA optimization of the pipe diameter of the pipe network system is finished, all attribute categories and corresponding pipe network information in the inp file corresponding to the optimal pipe diameter matrix row are output, and the attribute categories and the corresponding pipe network information comprise: the residual chlorine amount of each node, the total residual chlorine amount of a pipe network, the total cost of investment and construction, the optimal design pipe diameter of each pipe section and the corresponding Haizhong-Weilian coefficient thereof, the node pressure of each node, the head loss of each pipe section and the conveying flow of each pipe section.
The key point of the invention is to provide a pipe diameter optimization model which is mutually fed with a pipe database and takes the minimum total residual chlorine amount of a pipe network as a target; meanwhile, an ICS-GDA algorithm is provided for optimizing the model. The safety risk caused by pollution of drinking water is effectively reduced, and the safety and reliability of the water quality of the pipe network are guaranteed.
Claims (6)
1. A residual chlorine optimization model of an annular water supply pipe network and a pipe diameter optimization method thereof are characterized by comprising the following steps:
(1) acquiring the commercial information of the water supply pipes of different pipes, continuously updating the information content according to market change, forming a dynamic scattered point line graph by monthly information, selecting the average value of images as current real-time data according to nearly 6 months, and establishing a local dynamic pipe database;
(2) based on a hydraulic analysis engine EPANET, the initial conditions and the set arrangement mode of the town annular water supply pipe network system are perfected, and a net file of the town annular water supply pipe network system is output; reading a pipe network system and a net file through C language, adding attribute categories in each data layer of the initial condition and the established arrangement mode of the pipe network system, creating inp files, and writing the attribute categories and the corresponding pipe network information in the inp files;
(3) reading an inp file of a pipe network system in a binary mode, automatically extracting data information required by a pipe diameter optimization model in the inp file according to attribute types, and automatically generating mutual feedback with a local dynamic pipe database by combining the local dynamic pipe database so as to obtain the pipe diameter (D) of each pipe sectioni) For discrete decision variables, the total residual chlorine (Cl) of the pipe network is minimizedmin) The pipe diameter optimization model is a target, and the specific optimization model is as follows:
an objective function:
constraint 1 (node continuity equation):
constraint 2 (ring energy equation):
constraint 3 (node minimum head):
constraint 4 (nodal minimum residual chlorine content):
in the formula: n is the number of pipe sections, m is the number of nodes, and q is the number of closed loops; ciTaking the average value of the concentrations of two nodes at the beginning and the end of the pipe section as the concentration (mg/L) of the residual chlorine in the ith pipe section in the water body, wherein the calculation formula of the node concentration is as follows: dc/dt-kc, t is the time(s) taken from the source node to a certain node, and the pipe diameter (D)i) There is an inverse relationship, the pipe diameter is obtained by comparing the pipe database, DiE { D (1), D (2),.., D (np) }, np is the number of selectable commercial pipe diameters; k is the reaction rate constant, i.e., the overall attenuation coefficient, which can be calculated by the following equation: k is kb+kf·kw/rh·(kf+kw)，rhIs the hydraulic radius (m), k of the pipe sectionbIs the attenuation coefficient (min) of water body-1)，kfIs the mass transfer coefficient (m/min), kwThe attenuation coefficient (m/min) of the tube wall; liThe tube length of the ith tube section; qj,in、Qj,outThe respective flows (l/s), Q flowing into and out of the node jjThe traffic (l/s) that needs to be satisfied for node j; Δ HkHead loss (m) for a closed loop k in an annular water supply network, wherein head loss (H) can be calculated by: h ═ ω · Qβ·L/(CW β·Dγ) Wherein ω, β, γ are constants; cWThe coefficient is a Hazen-William coefficient and is obtained by comparing a pipe database; hj、Hj,max、Hj,minA free head (m), a maximum allowable head (m) and a minimum allowable head (m) at node j, respectively; cj、Cj,minThe residual chlorine concentration and the maximum chlorine concentration of the node j respectivelyThe requirement of small residual chlorine content;
(4) the pipe diameter matrix U of the water supply pipe network system is coupled with a flood algorithm program (ICS-GDA) through improving a valley distribution bird algorithm, automatic iterative optimization of mutual information feedback of the pipe diameter matrix U of the pipe network system and a local dynamic pipe database is completed, EPANET hydraulic judgment is carried out through mutual information feedback of an inp file and the local dynamic pipe database, and a pipe diameter combination with the minimum total residual chlorine of the pipe network is determined, wherein the specific ICS-GDA algorithm comprises the following steps:
(4.1) initializing ICS-GDA algorithm parameters: setting the number of lines (N) of the pipe diameter matrix U and the maximum step length control factor (alpha)max) And maximum number of iterations (t)max)；
(4.2) t is 1, and an initial Nxn pipe diameter matrix U is generated through a random walk mode and an approximation principle (d)ij)N×n；
(4.3) in the t-th iteration, iterative update and discard of U using ICS-GDA and EPANET:
the updating mode of the spiral levy flight is as follows:
in the formula: x is the number ofi t、xi t+1Respectively representing the ith matrix row in the t generation and the t +1 generation of the pipeline matrix U; alpha is a step length control factor and is calculated by an equation (7); levy (lambda) is a random search path matrix and obeys Levy distribution: levy (λ) ═ μ · Φ/| ν1/βMu and v follow a standard normal distribution, phi ═ Γ (1+ β) · sin (pi · β/2)]/[Γ(1+β)·β·2(β-1)/2/2]Γ (1+ β) is a Γ function, i.e.
Beta is a constant, beta belongs to [0,2 ]]；xbest tFor optimal pipe diameter combination of the t-th generation, DtIs xi tTo xbest tDistance of (D)t＝|xbest t-xi tI, b is a spiral constant, p, l are[0,1]A random number in between;
the abandoning steps are as follows: calculating and sequencing all matrix rows (x) in the pipe diameter matrix U before and after the iteration of the formula (6) through EPANET and an objective function after the pipe diameter matrix U which is subjected to the updating stepi t、xi t+1) Total residual chlorine (F) of pipe networki t、Fi t+1) Will Fi t+1And Fi tBy comparison, if Fi t+1Preferably, x is usedi t+1Replace xi tOtherwise, the result is not changed;
(4.4) abandoning the optimized pipe diameter matrix U through a flood algorithm (GDA) if the total residual chlorine content is higher than CllevelX ofi t+1All are discarded, and the specific discarding formula is as follows:
Cllevel＝Cllevel-UP (8)
in the formula: cllevelThe initial value of the initial pipe diameter matrix is the average value of the total residual chlorine of N pipe networks corresponding to the initial pipe diameter matrix U; UP is the standard deviation of the total residual chlorine of N pipe networks.
Then, the new matrix row is supplemented by the random walk and approximation principle of step (4.2), but the update formula is improved to the following formula:
in the formula: ε is [0,2]Random number between, xminAnd xmaxMinimum and maximum commercial pipe diameters, respectively; xi is [ -1,1]A random number in between; pa < 0.2 indicates that the generation of the new matrix row is completed by the formula (9) in the first 20% of the better matrix rows cut in the t generation, and Pa > 0.2 indicates that the generation of the new matrix row is completed by the formula (9) in the second 80% of the worse matrix rows;
(4.5) through the approximation principle discrete value of the step (4.4), covering each matrix row of a new pipe diameter matrix U, mutually feeding the 'pipe diameter' attribute category in the inp file and the local pipe database information, adjusting a Haizhen-Weilian coefficient in the inp file, carrying out EPANET hydraulic judgment, and discarding the matrix rows which do not meet the constraint; then supplementing a new matrix row by the random walk mode and the approximation principle of the step 4.4, and judging EPANET hydraulic power by the new matrix row again until all the matrix rows of the pipe diameter matrix U meet the constraint, and calculating and sequencing the total residual chlorine amount of the pipe network of all the matrix rows in the pipe diameter matrix U, wherein t is t + 1;
(4.6)t＞tmaxterminating iteration to obtain an optimal pipe diameter matrix row;
(5) and after the ICS-GDA optimization of the pipe diameter of the pipe network system is finished, outputting all attribute categories and corresponding pipe network information in the inp file corresponding to the optimal pipe diameter matrix row.
2. The residual chlorine optimization model of the annular water supply pipe network and the pipe diameter optimization method thereof according to claim 1 are characterized in that: the tubing database described in step (1) comprising: the inner diameters of the pipelines of the ductile cast iron pipe, the PE pipe, the welded steel pipe and the concrete pipe, and the corresponding price and Haizhong-Weiliang coefficient.
3. The residual chlorine optimization model of the annular water supply pipe network and the pipe diameter optimization method thereof according to claim 1 are characterized in that: the initial conditions and the established arrangement mode of the town annular water supply pipe network system in the step (2) comprise: the preset number of each node, the preset elevation of each node, the preset outflow of each node, the residual chlorine amount of the factory water, the preset number of each pipe section, the preset pipe length of each pipe section, the initial pipe diameter of each pipe section, the initial Hazevrai coefficient of each pipe section, the selectable commercial pipe diameter and the corresponding price and the Hazevrai coefficient thereof.
4. The residual chlorine optimization model of the annular water supply pipe network and the pipe diameter optimization method thereof according to claim 1 are characterized in that: the attribute type of the data information in the step (2) includes: pipe section number, pipe diameter, pipe length, Haizhen-Weilian coefficient, node number and node demand.
5. The residual chlorine optimization model of the annular water supply pipe network and the pipe diameter optimization method thereof according to claim 1 are characterized in that: the mode for generating the initial pipe diameter matrix U through the approximation principle in the step (4) is as follows: first, a tube diameter matrix U ═ N (d) of N × N is randomly generated by equation (10)ij)N×n(ii) a Then, carry out data standardization to this pipe diameter matrix, namely: using selectable commercial pipe diameter values (D) approximating said combination of pipe diametersi) Elements in the matrix are replaced one by one to realize discretization of pipe diameter combination, so that each pipe diameter value belongs to a set of selectable commercial pipe diameters;
xp＝xmin+ξ(xmax-xmin) (10)
in the formula: x is the number ofpIs the p-th pipe diameter; x is the number ofminAnd xmaxMinimum and maximum commercial pipe diameters, respectively; xi is in the middle of 0,1]。
6. The residual chlorine optimization model of the annular water supply pipe network and the pipe diameter optimization method thereof according to claim 1 are characterized in that: the pipe network information in the step (5) comprises: the residual chlorine amount of each node, the total residual chlorine amount of a pipe network, the total cost of investment and construction, the optimal design pipe diameter of each pipe section and the corresponding Haizhong-Weilian coefficient thereof, the node pressure of each node, the head loss of each pipe section and the conveying flow of each pipe section.
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