CN-122010241-A - Operation parameter optimization method and system for reverse osmosis membrane water production line

CN122010241ACN 122010241 ACN122010241 ACN 122010241ACN-122010241-A

Abstract

The invention discloses an operation parameter optimization method and system for a reverse osmosis membrane water production line, and relates to the technical field of water treatment, wherein the method comprises the steps of obtaining brine characteristics of brine, and carrying out pretreatment prediction to obtain pretreated brine characteristics; obtaining desalination rate demand information, combining the pretreated brine characteristics, performing reverse osmosis operation parameter optimization to obtain optimal reverse osmosis operation parameters, wherein reverse osmosis blocking prediction, scaling prediction and desalination rate prediction of the reverse osmosis operation parameters are performed according to the pretreated brine characteristics and the desalination rate demand information, reverse osmosis fitness is calculated, an optimization cluster rule is set for optimization, and production control of a reverse osmosis membrane water production line is performed by adopting the optimal reverse osmosis operation parameters. The problems of high energy consumption, high maintenance cost and poor production efficiency of operation control due to the fact that an operation strategy cannot be adjusted in real time in the prior art, and the system operates under non-optimal working conditions for a long time are solved.

Inventors

WANG PING
XU YINDONG
XU XIAOJIN

Assignees

深圳市赛维沃科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260130

Claims (10)

1.A method for optimizing operating parameters of a reverse osmosis membrane process water production line, the method comprising: obtaining the brine characteristics of brine, and carrying out pretreatment prediction to obtain the pretreated brine characteristics; obtaining desalination rate demand information, combining the pretreated brine characteristics, performing reverse osmosis operation parameter optimization to obtain optimal reverse osmosis operation parameters, wherein reverse osmosis membrane blocking prediction, scaling prediction and desalination rate prediction of the reverse osmosis operation parameters are performed according to the pretreated brine characteristics and the desalination rate demand information, reverse osmosis fitness is calculated, and an optimization cluster rule is set for optimization; And adopting the optimal reverse osmosis operation parameters to control the production of the reverse osmosis membrane water production line.
2. The method for optimizing operating parameters of a reverse osmosis membrane process water production line of claim 1, wherein obtaining brine characteristics of brine, performing pretreatment predictions, obtaining pretreated brine characteristics, comprises: obtaining brine characteristics of the brine, wherein the brine characteristics include salt concentration and impurity characteristics; Inputting the brine characteristic into a pretreatment predictor, and outputting to obtain the pretreated brine characteristic.
3. The method for optimizing operating parameters of a reverse osmosis membrane process water production line of claim 2, wherein the training step of the pretreatment predictor comprises: Collecting a sample brine characteristic set, and collecting sample pretreatment brine characteristic sets pretreated by different sample brine characteristics; constructing a preprocessing predictor based on machine learning; And performing supervision training and testing on the pretreatment predictor by adopting the sample brine characteristic set and the sample pretreatment brine characteristic set, and iteratively optimizing network parameters until the testing converges, thereby completing training and testing.
4. The method for optimizing operating parameters of a reverse osmosis membrane process water production line according to claim 1, wherein obtaining desalination rate demand information, performing reverse osmosis operating parameter optimization in combination with the pretreated brine characteristics, obtaining optimal reverse osmosis operating parameters, comprises: Obtaining desalination rate requirement information; Acquiring a reverse osmosis operation parameter space; generating a plurality of first reverse osmosis operating parameters within the reverse osmosis operating parameter space, wherein each first reverse osmosis operating parameter comprises a pressure parameter; according to the characteristics of the pretreated brine, respectively carrying out pretreatment blocking prediction and permeation scaling prediction by combining the first reverse osmosis operation parameters to obtain a plurality of first blocking rates and a plurality of first scaling rates, and obtaining a plurality of first energy cost information and a plurality of first desalination rates; calculating a plurality of first reverse osmosis fitness based on the plurality of first blocking rates, the plurality of first fouling rates, the plurality of first energy cost information, and the plurality of first desalination rates; According to the first blocking rates and the first scaling rates, respectively carrying out optimization cluster division to obtain a plurality of blocking operation parameter clusters and a plurality of scaling operation parameter clusters, continuing iterative optimization until convergence to obtain a plurality of convergence blocking operation parameter clusters and a plurality of convergence scaling operation parameter clusters, and analyzing to obtain optimization balance; and according to the optimized balance degree, screening to obtain an optimized operation parameter set, and screening to obtain an optimal reverse osmosis operation parameter.
5. The method for optimizing operating parameters of a reverse osmosis membrane process water production line of claim 4, wherein the performing of a pretreatment block prediction and a permeation scaling prediction in combination with the plurality of first reverse osmosis operating parameters, respectively, based on the pretreatment brine characteristics, obtains a plurality of first block rates and a plurality of first scaling rates, comprising: Obtaining a reverse osmosis membrane fault predictor, wherein the reverse osmosis membrane fault predictor comprises a blocking prediction branch and a scaling prediction branch, wherein the input in the training process of the blocking prediction branch is sample pretreatment brine characteristic and sample reverse osmosis operation parameter, the label is sample blocking rate of an impurity blocking reverse osmosis membrane, the input in the training process of the scaling prediction branch is sample pretreatment brine characteristic and sample reverse osmosis operation parameter, and the label is sample scaling rate of salt scaling on the reverse osmosis membrane; and respectively combining the characteristics of the pretreated brine with the first reverse osmosis operation parameters, inputting the characteristics of the pretreated brine into the reverse osmosis membrane fault predictor, and outputting to obtain a plurality of first blocking rates and a plurality of first scaling rates.
6. The method of optimizing operating parameters for a reverse osmosis membrane process water production line of claim 4, wherein obtaining a plurality of first energy cost information and a plurality of first desalination rates comprises: Acquiring a plurality of first energy cost information of a plurality of first reverse osmosis operation parameters according to the corresponding relation of the energy consumption pressure of the reverse osmosis membrane water production line; Inputting the pretreated brine characteristic and the first reverse osmosis operation parameters into a desalination predictor, and outputting to obtain the first desalination rates, wherein the desalination predictor is constructed based on machine learning, the input characteristic of training is the sample pretreated brine characteristic and the sample reverse osmosis operation parameters, and the label is the sample desalination rate.
7. The method of optimizing operating parameters for a reverse osmosis membrane process water production line of claim 4, wherein calculating a plurality of first reverse osmosis fitness based on a plurality of first blocking rates, a plurality of first fouling rates, a plurality of first energy cost information, and a plurality of first desalination rates comprises: calculating to obtain a plurality of first fusion failure rates according to the plurality of first blocking rates and the plurality of first scaling rates; Calculating to obtain a plurality of first desalination coefficients according to the plurality of first desalination rates and the desalination rate requirement information; Calculating to obtain a plurality of first energy coefficients according to the plurality of first energy cost information and the reference energy cost information; And calculating a plurality of first reverse osmosis fitness according to the plurality of first fusion failure rates, the plurality of first desalination coefficients and the plurality of first energy coefficients, wherein the fusion failure rates and the energy coefficients are inversely related to the reverse osmosis fitness, and the desalination coefficients are positively related to the reverse osmosis fitness.
8. The method for optimizing operating parameters of a reverse osmosis membrane process water production line according to claim 4, wherein the optimizing cluster division is performed according to the plurality of first blocking rates and the plurality of first scaling rates to obtain a plurality of blocking operating parameter clusters and a plurality of scaling operating parameter clusters, respectively, and the iterative optimization is continued until convergence to obtain a plurality of converging blocking operating parameter clusters and a plurality of converging scaling operating parameter clusters, and the analyzing to obtain the optimized balance comprises: Clustering cluster division is respectively carried out on the first blocking rates and the first scaling rates to obtain a plurality of first blocking rate clusters and a plurality of first scaling rate clusters, wherein the first blocking rate clusters comprise the minimum first blocking rate and the other first following blocking rates, and the first scaling rate clusters comprise the minimum first scaling rate and the other first following scaling rates; Dividing a plurality of first reverse osmosis operation parameters according to the plurality of first blocking rate clusters and the plurality of first scaling rate clusters to obtain a plurality of blocking operation parameter clusters and a plurality of scaling operation parameter clusters; Taking the operation parameters corresponding to the first blocking rate and the first scaling rate in each operation parameter cluster as adjustment directions, adjusting the operation parameters corresponding to the first blocking rate and the first scaling rate, updating the blocking operation parameter clusters and the scaling operation parameter clusters, predicting the blocking rate and the scaling rate, and updating the adjustment directions; Continuing to perform iterative optimization until reaching convergence iteration times, and obtaining a plurality of final convergence blocking operation parameter clusters and a plurality of convergence scaling operation parameter clusters; And calculating reverse osmosis fitness averages of the plurality of converging blocking operation parameter clusters and the plurality of converging scaling operation parameter clusters, and calculating similarity to obtain optimized balance.
9. The method for optimizing operating parameters of a reverse osmosis membrane production line of claim 4, wherein the screening process to obtain an optimized operating parameter set and the screening to obtain an optimized reverse osmosis operating parameter according to the optimized balance comprises: Acquiring an operation parameter cluster with the maximum reverse osmosis fitness mean value as an optimized operation parameter set; Taking the optimized balance degree as a selection proportion, selecting reverse osmosis operation parameters of the selection proportion with the maximum reverse osmosis fitness in the optimized operation parameter set, and constructing a reverse osmosis operation parameter constraint; And extracting the reverse osmosis operation parameter with the maximum reverse osmosis fitness as the optimal reverse osmosis operation parameter.
10. An operating parameter optimization system for a reverse osmosis membrane process water production line for implementing the operating parameter optimization method for a reverse osmosis membrane process water production line according to any one of claims 1 to 9, the system comprising: The pretreatment prediction module is used for obtaining the brine characteristics of brine, and carrying out pretreatment prediction to obtain the pretreated brine characteristics; The operation parameter optimization module is used for acquiring desalination rate demand information, combining the pretreated brine characteristics, performing reverse osmosis operation parameter optimization to acquire optimal reverse osmosis operation parameters, performing reverse osmosis membrane blocking prediction, scaling prediction and desalination rate prediction of the reverse osmosis operation parameters according to the pretreated brine characteristics and the desalination rate demand information, calculating reverse osmosis fitness, setting optimization cluster rules, and performing optimization; and the production control module is used for carrying out production control on the reverse osmosis membrane water production line by adopting the optimal reverse osmosis operation parameters.

Description

Operation parameter optimization method and system for reverse osmosis membrane water production line Technical Field The invention relates to the technical field of water treatment, in particular to an operation parameter optimization method and an operation parameter optimization system for a reverse osmosis membrane water production line. Background The existing reverse osmosis membrane water production line operation control method generally uses fixed operation experience or simple water production flow and energy consumption indexes as guide setting operation parameters. Meanwhile, when the water quality fluctuates, the running strategy cannot be adjusted in real time, so that the system runs under the non-optimal working condition for a long time, and the problems of low overall energy efficiency, high running control energy consumption, high maintenance cost and poor production efficiency are caused. Disclosure of Invention The application provides an operation parameter optimization method and an operation parameter optimization system for a reverse osmosis membrane water production line, and aims to solve the problems that in the prior art, an operation strategy cannot be adjusted in real time, so that the system operates under a non-optimal working condition for a long time, the overall energy efficiency is low, the energy consumption of operation control is high, the maintenance cost is high, and the production efficiency is poor. In view of the above problems, the application provides an operating parameter optimization method and system for a reverse osmosis membrane water production line. In a first aspect, the present application provides a method for optimizing operating parameters for a reverse osmosis membrane water production line, the method comprising: obtaining the brine characteristics of brine, and carrying out pretreatment prediction to obtain the pretreated brine characteristics; obtaining desalination rate demand information, combining the pretreated brine characteristics, performing reverse osmosis operation parameter optimization to obtain optimal reverse osmosis operation parameters, wherein reverse osmosis membrane blocking prediction, scaling prediction and desalination rate prediction of the reverse osmosis operation parameters are performed according to the pretreated brine characteristics and the desalination rate demand information, reverse osmosis fitness is calculated, and an optimization cluster rule is set for optimization; And adopting the optimal reverse osmosis operation parameters to control the production of the reverse osmosis membrane water production line. In a second aspect, the present invention provides an operating parameter optimization system for a reverse osmosis membrane water production line, comprising: The pretreatment prediction module is used for obtaining the brine characteristics of brine, and carrying out pretreatment prediction to obtain the pretreated brine characteristics; The operation parameter optimization module is used for acquiring desalination rate demand information, combining the pretreated brine characteristics, performing reverse osmosis operation parameter optimization to acquire optimal reverse osmosis operation parameters, performing reverse osmosis membrane blocking prediction, scaling prediction and desalination rate prediction of the reverse osmosis operation parameters according to the pretreated brine characteristics and the desalination rate demand information, calculating reverse osmosis fitness, setting optimization cluster rules, and performing optimization; and the production control module is used for carrying out production control on the reverse osmosis membrane water production line by adopting the optimal reverse osmosis operation parameters. One or more technical schemes provided by the application have at least the following technical effects or advantages: According to the method, firstly, the salt concentration and impurity characteristics of the brine are obtained, pretreatment prediction is carried out, the water quality characteristics of the pretreated reverse osmosis membrane are mastered in real time, the prediction deviation caused by the influence of pretreatment links is overcome, and a reliable water quality data base is provided for follow-up accurate optimization. And secondly, performing reverse osmosis membrane blocking prediction, scaling prediction and desalination rate prediction of reverse osmosis operation parameters through desalination rate demand information and pretreated brine characteristics, providing a sufficient optimization space for subsequent optimization, comprehensively measuring real-time operation and long-term operation risks of parameter combination, performing double-target dynamic optimization, performing global search in a complex parameter space by combining a reverse osmosis membrane scaling prediction result and an optimization cluster rule, and outputting optimal r