An intelligent method for adaptive secondary chlorination of urban and rural integrated water supply

Abstract

The present invention discloses an intelligent method for adaptive secondary chlorination of urban and rural integrated water supply, comprising the following steps: (1) calculating the hourly average water consumption according to the factory water volume, regional pump station water volume, and village community water meter water volume in the previous 7 days; (2) calculating the hourly average water consumption according to the hourly average water volume data; (3) calculating the hourly average concentration according to the residual chlorine concentration monitoring data of the water supply network in the previous 7 days; (4) calculating the comprehensive residual chlorine attenuation coefficient of each pipe section including the pipe wall and the main water reaction according to the hourly average concentration and the water age value at the corresponding time, simulating the change of residual chlorine concentration in the pipe network after taking the average value; (5) comparing the simulated residual chlorine concentration change with the monitoring data, and calculating the Nash efficiency coefficient; (6) optimizing the comprehensive residual chlorine degradation coefficient according to historical data; the present invention ensures excellent prediction ability of residual chlorine attenuation law.

Description

Technical Field

[0001] The present invention relates to the technical field of water supply equipment, and in particular to an intelligent method for adaptive secondary chlorination of urban and rural integrated water supply. Background Art

[0002] The prominent problem in the process of urban and rural water supply integration is that rural residents are relatively scattered, and the water in the water supply network has poor fluidity, which makes it difficult to ensure the residual chlorine concentration at the end of the network, thus affecting the water quality of the end water supply. If the residual chlorine at the end of the network is too high, the risk of disinfection by-products will increase greatly. If the residual chlorine is too low, bacteria will breed and the quality of tap water will be difficult to ensure. In order to improve the scientificity and accuracy of secondary chlorination, it is very necessary to develop an intelligent decision-making system for secondary chlorination, which will provide guidance and practical experience for the water quality assurance at the end of the urban and rural water supply integration network. As the brain of the decision-making system, the mathematical model has become an important key technology in the process of promoting urban and rural water supply integration. There are many factors that affect the attenuation of residual chlorine in the network, including the organic matter content, ammonia nitrogen concentration, dissolved oxygen level, pipe wall flora, temperature and many other factors in the water body. For this reason, it is particularly urgent and important to develop an adaptive intelligent mathematical model for secondary chlorination. Summary of the invention

[0003] Purpose of the invention: The purpose of the present invention is to provide an intelligent method for adaptive secondary chlorination of urban and rural integrated water supply, which solves the problem that the residual chlorine attenuation coefficient of many models cannot change with the changes of water temperature, water quality and pipe age; adaptive to changes in water supply temperature; adaptive to changes in water supply quality (such as ammonia nitrogen, natural organic matter content, permanganate index, pH value, etc.); adaptive to changes in different pipes and pipe ages.

[0004] Technical solution: The intelligent method for adaptive secondary chlorination of urban and rural integrated water supply described in the present invention comprises the following steps:

[0005] (1) Calculate the average hourly water consumption at the hour based on the water output from the factory, the water output from the regional pumping station, and the water consumption from the village and community water meters in the previous 7 days;

[0006] (2) After balancing the water volume according to the water output and water consumption, the hourly water age value of the simulated pipe network is calculated according to the average hourly water volume data at the hour, and the simulation is repeated multiple times until the water age of the pipe network shows a very good periodic water age process.

[0007] (3) Calculate the average hourly concentration at the hour based on the residual chlorine concentration monitoring data of the water supply network in the previous 7 days;

[0008] (4) According to the average hourly concentration at the hour and the water age value at the corresponding time, the comprehensive attenuation coefficient of residual chlorine in each pipe section including the pipe wall and main water reaction is calculated, and the average value is taken to simulate the change of residual chlorine concentration in the pipe network;

[0009] (5) Compare the simulated residual chlorine concentration change with the monitoring data and calculate the Nash efficiency coefficient;

[0010] (6) The comprehensive degradation coefficient of residual chlorine was optimized based on historical data, and the water meter data of each village or community level in the past three days were calculated. The water demand pattern of each location in the next 24 hours was calculated. The residual chlorine concentration at the entrance of the village and direct supply area in winter was 0.25 mg / L, the residual chlorine concentration in summer was 0.25 mg / L, the residual chlorine concentration at the entrance of the secondary water supply area in winter was 0.35 mg / L, and the residual chlorine concentration in summer was 0.45 mg / L as the chlorination control target. The chlorine addition amount of each secondary chlorination pump station was optimized.

[0011] Furthermore, step (2) is specifically as follows: using the EPANET model to simulate the change of water age in the entire water supply system.

[0012] Further, step (4) includes the following steps:

[0013] (41) Calculate the degradation rate of the main water reaction

[0014] The attenuation caused by the reaction of natural organic matter (NOM) contained in the main water body in the mainstream area, i.e. near the pipe wall, is obtained using a multi-stage attenuation kinetic model, and the formula is as follows:

[0015]

[0016] Where C is the chlorine concentration, Kb is the bulk water degradation rate and n is the reaction order to chlorine;

[0017] (42) Calculation of tube wall reaction rate coefficient

[0018] For the wall attenuation of non-metallic pipes, the first-order dynamic model is usually used, and the formula is as follows:

[0019]

[0020] Where, kw is the tube wall reaction rate coefficient, and R is the radius of the tube;

[0021] The wall reaction coefficient depends on the temperature and is also related to the age and material of the pipe;

[0022] (43) Calculation of the comprehensive attenuation coefficient The comprehensive attenuation coefficient is the sum of the above two parts, that is,

[0023]

[0024] The hourly average concentrations between any two points on the pipe network in the past 7 days are C 1,0 , C 1,1 , C 1,2 ...C 1,23 , C 2,0 , C2,1 , C 2,2 ...C 2,23 The average water age between any two points on the pipe network in the past 7 days is A 1,0 , A 1,1 , A 1,2 ...A 1,23 , A 2,0 , A 2,1 , A 2,2 ...A 2,23 . Then we have the following system of equations:

[0025]

[0026] The above system of equations has 24 equations, but the unknown quantity is only k. b , k w and n are three overdetermined equations. The least square method can be used to obtain the global optimal k of the nonlinear system. b , k w and n.

[0027] (44) Modified comprehensive attenuation coefficient simulation method

[0028] Assume a simple decay law as follows:

[0029]

[0030] The above formula can be written in difference format:

[0031] C2=C1-kC1(A2-A1)

[0032] The above formula is averaged over time and compared with the monitoring value. Assuming that the model error is caused by the error in the estimation of the attenuation coefficient, the following expression is obtained:

[0033]

[0034] in, is the average residual chlorine value at a monitoring point on the flow path, Indicates the average error of the calculated residual chlorine value at this point, is the average water age of this point, is the average water age of a monitoring point on the flow path, Δk is the attenuation coefficient correction;

[0035] After rearranging the above formula, we can get:

[0036]

[0037] Since the correction amount is small, it is assumed that the correction is made to the tube wall reaction rate coefficient:

[0038] k w =kw，0 +Δk

[0039] Among them, k w，0 is the tube wall reaction rate coefficient of the last iterative simulation.

[0040] Furthermore, step (5) is specifically as follows: if the Nash efficiency coefficient reaches 0.9 or above, the comprehensive attenuation coefficient of residual chlorine is considered to be correct; otherwise, the comprehensive degradation coefficient of residual chlorine is fine-tuned according to the difference between the calculated residual chlorine concentration and the monitored residual chlorine concentration until the number of attempts is more than 100 or the Nash efficiency coefficients of all monitoring points reach 0.9 or above; if the number of attempts reaches the maximum value, the comprehensive degradation coefficient of residual chlorine in each pipe section takes the optimal value with the highest Nash efficiency coefficient.

[0041] The present invention discloses an intelligent system for adaptive secondary chlorination of integrated urban and rural water supply, comprising:

[0042] Average hourly water consumption module at the hour: used to calculate the average hourly water consumption at the hour based on the factory water volume, regional pump station water volume, and village community water meter water volume in the previous 7 days;

[0043] Water age value module: It is used to balance the water volume according to the water output and water consumption, and then calculate the hourly water age value of the simulated pipe network according to the average hourly water volume data at the hour. The simulation is repeated multiple times until the water age of the pipe network shows a very good periodic water age process.

[0044] Average hourly concentration module at the hour: used to calculate the average hourly concentration at the hour based on the residual chlorine concentration monitoring data of the water supply network in the previous 7 days;

[0045] Attenuation coefficient module: used to calculate the comprehensive attenuation coefficient of residual chlorine in each pipe section including the pipe wall and main water reaction according to the average hourly concentration at the hour and the water age value at the corresponding time, and simulate the change of residual chlorine concentration in the pipe network after taking the average value;

[0046] Nash efficiency coefficient module: used to compare the simulated residual chlorine concentration change with the monitoring data and calculate the Nash efficiency coefficient;

[0047] Residual chlorine comprehensive degradation coefficient module: It is used to optimize the comprehensive degradation coefficient of residual chlorine based on historical data, calculate the water meter data of each village or community level in the past three days, calculate the water demand pattern of each location in the next 24 hours, and optimize the calculation of the chlorine addition amount of each secondary chlorination pump station according to the chlorine addition control target of 0.25mg / L of residual chlorine concentration at the entrance of villages and direct supply communities in winter and 0.25mg / L in summer, 0.35mg / L of residual chlorine concentration at the entrance of secondary water supply communities in winter and 0.45mg / L in summer.

[0048] Furthermore, the water age value module is specifically as follows: the EPANET model is used to simulate the change of water age in the entire water supply system.

[0049] Furthermore, the attenuation coefficient module includes the following steps:

[0050] (41) Calculate the degradation rate of the main water reaction

[0051] The attenuation caused by the reaction of natural organic matter (NOM) contained in the main water body in the mainstream area, i.e. near the pipe wall, is obtained using a multi-stage attenuation kinetic model, and the formula is as follows:

[0052]

[0053] Where C is the chlorine concentration, Kb is the bulk water degradation rate and n is the reaction order to chlorine;

[0054] (42) Calculation of tube wall reaction rate coefficient

[0055] For the wall attenuation of non-metallic pipes, the first-order dynamic model is usually used, and the formula is as follows:

[0056]

[0057] Where, kw is the tube wall reaction rate coefficient, and R is the radius of the tube;

[0058] The wall reaction coefficient depends on the temperature and is also related to the age and material of the pipe;

[0059] (43) Calculation of the comprehensive attenuation coefficient The comprehensive attenuation coefficient is the sum of the above two parts, that is,

[0060]

[0061] The hourly average concentrations between any two points on the pipe network in the past 7 days are C 1,0 , C 1,1 , C 1,2 ...C 1,23 , C 2,0 , C 2,1 , C 2,2 ...C 2,23 The average water age between any two points on the pipe network in the past 7 days is A 1,0 , A 1,1 , A 1,2 ...A 1,23 , A 2,0 , A 2,1 , A 2,2 ...A 2,23 . Then we have the following system of equations:

[0062]

[0063] The above system of equations has 24 equations, but the unknown quantity is only k. b , kw and n are three overdetermined equations. The least square method can be used to obtain the global optimal k of the nonlinear system. b , k w and n.

[0064] (44) Modified comprehensive attenuation coefficient simulation method

[0065] Assume a simple decay law as follows:

[0066]

[0067] The above formula can be written in difference format:

[0068] C2=C1-kC1(A2-A1)

[0069] The above formula is averaged over time and compared with the monitoring value. Assuming that the model error is caused by the error in the estimation of the attenuation coefficient, the following expression is obtained:

[0070]

[0071] in, is the average residual chlorine value at a monitoring point on the flow path, Indicates the average error of the calculated residual chlorine value at this point, is the average water age of this point, is the average water age of a monitoring point on the flow path, Δk is the attenuation coefficient correction;

[0072] After rearranging the above formula, we can get:

[0073]

[0074] Since the correction amount is small, it is assumed that the correction is made to the tube wall reaction rate coefficient:

[0075] k w =k w，0 +Δk

[0076] Among them, k w，0 is the tube wall reaction rate coefficient of the last iterative simulation.

[0077] Furthermore, the Nash efficiency coefficient module is as follows: if the Nash efficiency coefficient reaches 0.9 or above, the comprehensive attenuation coefficient of residual chlorine is considered correct; otherwise, the comprehensive degradation coefficient of residual chlorine is fine-tuned according to the difference between the calculated residual chlorine concentration and the monitored residual chlorine concentration until the number of attempts is more than 100 or the Nash efficiency coefficient of all monitoring points reaches 0.9 or above; if the number of attempts reaches the maximum value, the comprehensive degradation coefficient of residual chlorine in each pipe section takes the optimal value with the highest Nash efficiency coefficient.

[0078] An electronic device described in the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and is characterized in that when the computer program is loaded into the processor, it implements any one of the intelligent methods for adaptive secondary chlorination of integrated urban and rural water supply.

[0079] A storage medium described in the present invention stores a computer program, and when the computer program is executed by a processor, any one of the intelligent methods for adaptive secondary chlorination of integrated urban and rural water supply is implemented.

[0080] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: a calculation method for the residual chlorine attenuation coefficient (the main water reaction degradation rate and the tube wall reaction rate coefficient) and a calculation method based on simulation error correction are proposed, thereby ensuring excellent prediction capabilities for the residual chlorine attenuation law, and further providing a secondary chlorination plan to ensure appropriate residual chlorine concentrations for each community and village. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 is a flow chart of the present invention;

[0082] Figure 2 It is a flowchart of the intelligent mathematical model of the present invention;

[0083] Figure 3 The predicted water age distribution of the present invention;

[0084] Figure 4 The water age process of Yanzibu and Suyangshan of the present invention;

[0085] Figure 5 The water age process of Daizhuang and Daiwei of the present invention;

[0086] Figure 6 The water age process of Tiefu and Chenlou of the present invention;

[0087] Figure 7 It is the residual chlorine concentration distribution calculated in the present invention. DETAILED DESCRIPTION

[0088] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0089] like Figure 1-Figure 2 As shown, based on the Epanet 2.2 model, the Internet of Things technology, intelligent learning algorithm and other technologies are integrated to realize the intelligent push of the secondary chlorination scheme of the Pizhou pipe network. The embodiment of the present invention provides an intelligent method for adaptive secondary chlorination of urban and rural integrated water supply, including the following steps:

[0090] (1) Calculate the average hourly water consumption at the hour based on the water output from the factory, the water output from the regional pumping station, and the water consumption from the village and community water meters in the previous 7 days;

[0091] (2) After balancing the water volume according to the water output and water consumption, the hourly water age value of the simulated pipe network is calculated according to the average hourly water volume data at the hour, and the simulation is repeated many times until the water age of the pipe network shows a very good periodic water age process. The details are as follows: Use the EPANET model to simulate the changes in water age in the entire water supply system.

[0092] (3) Calculate the average hourly concentration at the hour based on the residual chlorine concentration monitoring data of the water supply network in the previous 7 days;

[0093] (4) According to the hourly average concentration and the water age value at the corresponding time, the residual chlorine comprehensive attenuation coefficient of each pipe section including the pipe wall and the main water reaction is calculated, and the average value is taken to simulate the change of residual chlorine concentration in the pipe network; including the following steps:

[0094] (41) Calculate the degradation rate of the main water reaction

[0095] The attenuation caused by the reaction of natural organic matter (NOM) contained in the main water body in the mainstream area, i.e. near the pipe wall, is obtained using a multi-stage attenuation kinetic model, and the formula is as follows:

[0096]

[0097] Where C is the chlorine concentration, Kb is the bulk water degradation rate and n is the reaction order to chlorine;

[0098] (42) Calculation of tube wall reaction rate coefficient

[0099] For the wall attenuation of non-metallic pipes, the first-order dynamic model is usually used, and the formula is as follows:

[0100]

[0101] Where, kw is the tube wall reaction rate coefficient, and R is the radius of the tube;

[0102] The wall reaction coefficient depends on the temperature and is also related to the age and material of the pipe;

[0103] (43) Calculation of the comprehensive attenuation coefficient The comprehensive attenuation coefficient is the sum of the above two parts, that is,

[0104]

[0105] The hourly average concentrations between any two points on the pipe network in the past 7 days are C 1,0 , C 1,1 , C 1,2 ...C 1,23 , C 2,0 , C2,1 , C 2,2 ...C 2,23 The average water age between any two points on the pipe network in the past 7 days is A 1,0 , A 1,1 , A 1,2 ...A 1,23 , A 2,0 , A 2,1 , A 2,2 ...A 2,23 . Then we have the following system of equations:

[0106]

[0107] The above system of equations has 24 equations, but the unknown quantity is only k. b , k w and n are three overdetermined equations. The least square method can be used to obtain the global optimal k of the nonlinear system. b , k w and n.

[0108] (44) Modified comprehensive attenuation coefficient simulation method

[0109] Assume a simple decay law as follows:

[0110]

[0111] The above formula can be written in difference format:

[0112] C2=C1-kC1(A2-A1)

[0113] The above formula is averaged over time and compared with the monitoring value. Assuming that the model error is caused by the error in the estimation of the attenuation coefficient, the following expression is obtained:

[0114]

[0115] in, is the average residual chlorine value at a monitoring point on the flow path, Indicates the average error of the calculated residual chlorine value at this point, is the average water age of this point, is the average water age of a monitoring point on the flow path, Δk is the attenuation coefficient correction;

[0116] After rearranging the above formula, we can get:

[0117]

[0118] Since the correction amount is small, it is assumed that the correction is made to the tube wall reaction rate coefficient:

[0119] k w =kw，0 +Δk

[0120] Among them, k w，0 is the tube wall reaction rate coefficient of the last iterative simulation.

[0121] (5) The simulated residual chlorine concentration change is compared with the monitoring data to calculate the Nash efficiency coefficient; the details are as follows: if the Nash efficiency coefficient reaches 0.9 or above, the comprehensive attenuation coefficient of residual chlorine is considered correct; otherwise, the comprehensive degradation coefficient of residual chlorine is fine-tuned according to the difference between the calculated residual chlorine concentration and the monitored residual chlorine concentration until the number of attempts is more than 100 or the Nash efficiency coefficient of all monitoring points reaches 0.9 or above; if the number of attempts reaches the maximum value, the comprehensive degradation coefficient of residual chlorine in each pipe section takes the optimal value with the highest Nash efficiency coefficient.

[0122] (6) The comprehensive degradation coefficient of residual chlorine was optimized based on historical data, and the water meter data of each village or community level in the past three days were calculated. The water demand pattern of each location in the next 24 hours was calculated. The residual chlorine concentration at the entrance of the village and direct supply area in winter was 0.25 mg / L, the residual chlorine concentration in summer was 0.25 mg / L, the residual chlorine concentration at the entrance of the secondary water supply area in winter was 0.35 mg / L, and the residual chlorine concentration in summer was 0.45 mg / L as the chlorination control target. The chlorine addition amount of each secondary chlorination pump station was optimized.

[0123] When the model was applied in a city in Jiangsu, the simulation predicted the water age distribution on November 5, 2023. Figure 3 As shown in Figure 2, the water age process of pumping stations in important areas is as follows: Figures 4 to 6 The residual chlorine concentration distribution is shown in Figure 7 As shown. The predicted 24-hour average water ages are 30h for Suyangshan, 44h for Yanzibu, 26h for Daixu, 60h for Daizhuang, 15h for Chenlou, and 25h for Tiefu, which are close to the water ages measured by the reduction of residual chlorine concentration during the hypochlorous acid-chloramine disinfection process. The error between the hourly average value of residual chlorine concentration predicted by the model and the measured value can be controlled above the Nash efficiency coefficient of 0.9.

[0124] The embodiment of the present invention provides an urban-rural integrated water supply adaptive secondary chlorination intelligent system, comprising:

[0125] Average hourly water consumption module at the hour: used to calculate the average hourly water consumption at the hour based on the factory water volume, regional pump station water volume, and village community water meter water volume in the previous 7 days;

[0126] Water age value module: It is used to balance the water volume according to the water output and water consumption, and then calculate the hourly water age value of the simulated pipe network according to the average hourly water volume data at the hour. The simulation is repeated many times until the water age of the pipe network shows a very good periodic water age process. The details are as follows: Use the EPANET model to simulate the changes in water age in the entire water supply system.

[0127] Average hourly concentration module at the hour: used to calculate the average hourly concentration at the hour based on the residual chlorine concentration monitoring data of the water supply network in the previous 7 days;

[0128] Attenuation coefficient module: used to calculate the comprehensive attenuation coefficient of residual chlorine in each pipe section including the pipe wall and main water reaction according to the average hourly concentration at the hour and the water age value at the corresponding time, and simulate the change of residual chlorine concentration in the pipe network after taking the average value; including the following steps:

[0129] (41) Calculate the degradation rate of the main water reaction

[0130] The attenuation caused by the reaction of natural organic matter (NOM) contained in the main water body in the mainstream area, i.e. near the pipe wall, is obtained using a multi-stage attenuation kinetic model, and the formula is as follows:

[0131]

[0132] Where C is the chlorine concentration, Kb is the bulk water degradation rate and n is the reaction order to chlorine;

[0133] (42) Calculation of tube wall reaction rate coefficient

[0134] For the wall attenuation of non-metallic pipes, the first-order dynamic model is usually used, and the formula is as follows:

[0135]

[0136] Where, kw is the tube wall reaction rate coefficient, and R is the radius of the tube;

[0137] The wall reaction coefficient depends on the temperature and is also related to the age and material of the pipe;

[0138] (43) Calculation of the comprehensive attenuation coefficient The comprehensive attenuation coefficient is the sum of the above two parts, that is,

[0139]

[0140] The hourly average concentrations between any two points on the pipe network in the past 7 days are C 1,0 , C 1,1 , C 1,2 ...C 1,23 , C 2,0 , C 2,1 , C 2,2 ...C 2,23 The average water age between any two points on the pipe network in the past 7 days is A 1,0 , A 1,1 , A 1,2 ...A 1,23 , A 2,0 , A 2,1 , A 2,2 ...A2,23 . Then we have the following system of equations:

[0141]

[0142] The above system of equations has 24 equations, but the unknown quantity is only k. b , k w and n are three overdetermined equations. The least square method can be used to obtain the global optimal k of the nonlinear system. b , k w and n.

[0143] (44) Modified comprehensive attenuation coefficient simulation method

[0144] Assume a simple decay law as follows:

[0145]

[0146] The above formula can be written in difference format:

[0147] C2=C1-kC1(A2-A1)

[0148] The above formula is averaged over time and compared with the monitoring value. Assuming that the model error is caused by the error in the estimation of the attenuation coefficient, the following expression is obtained:

[0149]

[0150] in, is the average residual chlorine value at a monitoring point on the flow path, Indicates the average error of the calculated residual chlorine value at this point, is the average water age of this point, is the average water age of a monitoring point on the flow path, Δk is the attenuation coefficient correction;

[0151] After rearranging the above formula, we can get:

[0152]

[0153] Since the correction amount is small, it is assumed that the correction is made to the tube wall reaction rate coefficient:

[0154] k w =k w，0 +Δk

[0155] Among them, k w，0 is the tube wall reaction rate coefficient of the last iterative simulation.

[0156] Nash efficiency coefficient module: used to compare the simulated residual chlorine concentration changes with the monitoring data and calculate the Nash efficiency coefficient; the details are as follows: if the Nash efficiency coefficient reaches 0.9 or above, the comprehensive attenuation coefficient of residual chlorine is considered correct; otherwise, the comprehensive degradation coefficient of residual chlorine is fine-tuned according to the difference between the calculated residual chlorine concentration and the monitored residual chlorine concentration until the number of attempts is more than 100 or the Nash efficiency coefficient of all monitoring points reaches 0.9 or above; if the number of attempts reaches the maximum value, the comprehensive degradation coefficient of residual chlorine in each pipe section takes the optimal value with the highest Nash efficiency coefficient.

[0157] Residual chlorine comprehensive degradation coefficient module: It is used to optimize the comprehensive degradation coefficient of residual chlorine based on historical data, calculate the water meter data of each village or community level in the past three days, calculate the water demand pattern of each location in the next 24 hours, and optimize the calculation of the chlorine addition amount of each secondary chlorination pump station according to the chlorine addition control target of 0.25mg / L of residual chlorine concentration at the entrance of villages and direct supply communities in winter and 0.25mg / L in summer, 0.35mg / L of residual chlorine concentration at the entrance of secondary water supply communities in winter and 0.45mg / L in summer.

[0158] An embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is loaded into the processor, any one of the intelligent methods for adaptive secondary chlorination of integrated urban and rural water supply is implemented.

[0159] An embodiment of the present invention further provides a storage medium storing a computer program, wherein the computer program, when executed by a processor, implements any one of the intelligent methods for adaptive secondary chlorination of integrated urban and rural water supply.

Claims

1. An intelligent method for adaptive secondary chlorination of urban and rural integrated water supply, characterized in that: The following steps are involved: (1) Calculate the average hourly water consumption at the hour based on the water output from the factory, the water output from the regional pumping station, and the water consumption from the village and community water meters in the previous 7 days; (2) After balancing the water volume according to the water output and water consumption, the hourly water age value of the simulated pipe network is calculated according to the average hourly water volume data at the hour, and the simulation is repeated many times until the water age of the pipe network shows a very good periodic water age process; the details are as follows: the EPANET model is used to simulate the water age changes in the entire water supply system; (3) Calculate the average hourly concentration at the hour based on the residual chlorine concentration monitoring data of the water supply network in the previous 7 days; (4) According to the hourly average concentration and the water age value at the corresponding time, the residual chlorine comprehensive attenuation coefficient of each pipe section including the pipe wall and the main water reaction is calculated, and the average value is taken to simulate the change of residual chlorine concentration in the pipe network; including the following steps: (41) Calculate the degradation rate of the main water reaction The attenuation caused by the reaction of natural organic matter (NOM) contained in the main water body in the mainstream area, i.e. near the pipe wall, is obtained using a multi-stage attenuation kinetic model, and the formula is as follows: Where C is the chlorine concentration, Kb is the bulk water degradation rate and n is the reaction order to chlorine; (42) Calculation of tube wall reaction rate coefficient For the wall attenuation of non-metallic pipes, the first-order dynamic model is usually used, and the formula is as follows: Where, kw is the tube wall reaction rate coefficient, and R is the radius of the tube; The wall reaction coefficient depends on the temperature and is also related to the age and material of the pipe; (43) Calculation of comprehensive attenuation coefficient The comprehensive attenuation coefficient is the sum of the above two parts, that is, The hourly average concentrations between any two points on the pipe network in the past 7 days are C 1,0 , C 1,1 , C 1,2 ...C 1,23 , C 2,0 , C 2,1 , C 2,2 ...C 2,23 The average water age between any two points on the pipe network in the past 7 days is A 1,0 , A 1,1 , A 1,2 ...A 1,23 , A 2,0 , A 2,1 , A 2,2 ...A 2,23， Then we have the following system of equations: The above system of equations has 24 equations, but the unknown quantity is only k. b , k w and n are three overdetermined equations. The least square method can be used to obtain the global optimal k of the nonlinear system. b , k w and n; (44) Modified comprehensive attenuation coefficient simulation method Assume a simple decay law as follows: The above formula can be written in difference format: C2=C1-kC1(A2-A1) The above formula is compared with the monitoring value after taking the time average, and assuming that the model error is caused by the error in the estimation of the attenuation coefficient, the following expression is obtained: in, is the average residual chlorine value at a monitoring point on the flow path, Indicates the average error of the calculated residual chlorine value at this point, is the average water age of this point, is the average water age of a monitoring point on the flow path, Δk is the attenuation coefficient correction; After rearranging the above formula, we can get: Since the correction amount is small, it is assumed that the correction is made to the tube wall reaction rate coefficient: k w =k w，0 +Δk Among them, k w，0 is the tube wall reaction rate coefficient of the last iteration simulation; (5) Compare the simulated residual chlorine concentration change with the monitoring data and calculate the Nash efficiency coefficient; the details are as follows: if the Nash efficiency coefficient reaches 0.9 or above, the comprehensive attenuation coefficient of residual chlorine is considered correct; otherwise, the comprehensive degradation coefficient of residual chlorine is fine-tuned according to the difference between the calculated residual chlorine concentration and the monitored residual chlorine concentration until the number of attempts is more than 100 or the Nash efficiency coefficient of all monitoring points reaches 0.9 or above; if the number of attempts reaches the maximum value, the comprehensive degradation coefficient of residual chlorine in each pipe section takes the optimal value with the highest Nash efficiency coefficient; (6) The comprehensive degradation coefficient of residual chlorine was optimized based on historical data, and the water meter data of each village or community level in the past three days were calculated. The water demand pattern of each location in the next 24 hours was calculated. The residual chlorine concentration at the entrance of the village and direct supply area in winter was 0.25 mg / L, the residual chlorine concentration in summer was 0.25 mg / L, the residual chlorine concentration at the entrance of the secondary water supply area in winter was 0.35 mg / L, and the residual chlorine concentration in summer was 0.45 mg / L as the chlorination control target. The chlorine addition amount of each secondary chlorination pump station was optimized.

2. An intelligent system for adaptive secondary chlorination of integrated urban and rural water supply, characterized in that: include: Average hourly water consumption module at the hour: used to calculate the average hourly water consumption at the hour based on the factory water volume, regional pump station water volume, and village community water meter water volume in the previous 7 days; Water age value module: It is used to balance the water volume according to the water output and water consumption, and then calculate the hourly water age value of the simulated pipe network according to the average hourly water volume data at the hour. The simulation is repeated many times until the water age of the pipe network shows a very good periodic water age process. Average hourly concentration module at the hour: used to calculate the average hourly concentration at the hour based on the residual chlorine concentration monitoring data of the water supply network in the previous 7 days; Attenuation coefficient module: used to calculate the comprehensive attenuation coefficient of residual chlorine in each pipe section including the pipe wall and main water reaction according to the average hourly concentration at the hour and the water age value at the corresponding time, and simulate the change of residual chlorine concentration in the pipe network after taking the average value; Nash efficiency coefficient module: used to compare the simulated residual chlorine concentration change with the monitoring data and calculate the Nash efficiency coefficient; Residual chlorine comprehensive degradation coefficient module: It is used to optimize the comprehensive degradation coefficient of residual chlorine based on historical data, calculate the water meter data of each village or community level in the past three days, calculate the water demand pattern of each location in the next 24 hours, and optimize the calculation of the chlorine addition amount of each secondary chlorination pump station according to the chlorine addition control target of 0.25mg / L of residual chlorine concentration at the entrance of villages and direct supply communities in winter and 0.25mg / L in summer, 0.35mg / L of residual chlorine concentration at the entrance of secondary water supply communities in winter and 0.45mg / L in summer.

3. The intelligent system for adaptive secondary chlorination of urban and rural integrated water supply according to claim 2, characterized in that: The water age value module is as follows: Use the EPANET model to simulate the changes in water age in the entire water supply system.

4. The intelligent system for adaptive secondary chlorination of urban and rural integrated water supply according to claim 2, characterized in that: The attenuation coefficient module includes the following steps: (41) Calculate the degradation rate of the main water reaction The attenuation caused by the reaction of natural organic matter (NOM) contained in the main water body in the mainstream area, i.e. near the pipe wall, is obtained using a multi-stage attenuation kinetic model, and the formula is as follows: Where C is the chlorine concentration, Kb is the bulk water degradation rate and n is the reaction order to chlorine; (42) Calculation of tube wall reaction rate coefficient For the wall attenuation of non-metallic pipes, the first-order dynamic model is usually used, and the formula is as follows: Where, kw is the tube wall reaction rate coefficient, and R is the radius of the tube; The wall reaction coefficient depends on the temperature and is also related to the age and material of the pipe; (43) Calculation of comprehensive attenuation coefficient The comprehensive attenuation coefficient is the sum of the above two parts, that is, The hourly average concentrations between any two points on the pipe network in the past 7 days are C 1,0 , C 1,1 , C 1,2 ...C 1,23 , C 2,0 , C 2,1 , C 2,2 ...C 2,23 The average water age between any two points on the pipe network in the past 7 days is A 1,0 , A 1,1 , A 1,2 ...A 1,23 , A 2,0 , A 2,1 , A 2,2 ...A 2,23， Then we have the following system of equations: The above system of equations has 24 equations, but the unknown quantity is only k. b , k w and n are three overdetermined equations. The least square method can be used to obtain the global optimal k of the nonlinear system. b , k w and n; (44) Modified comprehensive attenuation coefficient simulation method Assume a simple decay law as follows: The above formula can be written in difference format: C2=C1-kC1(A2-A1) The above formula is compared with the monitoring value after taking the time average, and assuming that the model error is caused by the error in the estimation of the attenuation coefficient, the following expression is obtained: in, is the average residual chlorine value at a monitoring point on the flow path, Indicates the average error of the calculated residual chlorine value at this point, is the average water age of this point, is the average water age of a monitoring point on the flow path, Δk is the attenuation coefficient correction; After rearranging the above formula, we can get: Since the correction amount is small, it is assumed that the correction is made to the tube wall reaction rate coefficient: k w =k w，0 +Δk Among them, k w，0 is the tube wall reaction rate coefficient of the last iterative simulation.

5. The intelligent system for adaptive secondary chlorination of urban and rural integrated water supply according to claim 2, characterized in that: The Nash efficiency coefficient module is as follows: if the Nash efficiency coefficient reaches 0.9 or above, the comprehensive attenuation coefficient of residual chlorine is considered correct; otherwise, the comprehensive degradation coefficient of residual chlorine is fine-tuned according to the difference between the calculated residual chlorine concentration and the monitored residual chlorine concentration until the number of attempts is more than 100 or the Nash efficiency coefficient of all monitoring points reaches 0.9 or above; if the number of attempts reaches the maximum value, the comprehensive degradation coefficient of residual chlorine in each pipe section takes the optimal value with the highest Nash efficiency coefficient.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is loaded into the processor, the intelligent method for adaptive secondary chlorination of integrated urban and rural water supply according to claim 1 is implemented.

7. A storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the intelligent method for adaptive secondary chlorination of urban and rural integrated water supply according to claim 1 is implemented.

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