Membrane capacitance deionization module process model optimization method based on equipment production data

Abstract

The invention relates to a membrane capacitance deionization module process model optimization method based on equipment production data. The method comprises the following steps: acquiring process data; fitting the process model, extracting data, and obtaining model parameters; and determining whether the selected operation condition is applicable or not by using the process model obtained by fitting, and determining parameters in the membrane capacitance deionization process. The method has the beneficial effects that the method can be used for optimizing the optimal operation conditions for realizing the required performance under different working conditions; according to the method, any change of inflow property and / or MCDI module breakage can be considered, and collected process performance data are used in real time to periodically recalibrate the model; the method can actively predict maintenance requirements and monitor the change of fitting model parameters.

Description

Technical Field

[0001] The invention belongs to the technical field of membrane capacitor deionization, and in particular relates to a membrane capacitor deionization module process model optimization method based on equipment production data. Background Art

[0002] Currently, theoretical complex process membrane capacitive deionization (MCDI) models are mostly used to describe laboratory-scale operating systems based on idealized single-pair MCDI units. Although these MCDI models describe simple single-salt systems in detail, they cannot handle the conditions of actual processes involving multiple ions and multiple pairs of electrodes. Therefore, the control of MCDI treatment plants needs to be further optimized.

[0003] The MCDI desalination process is very flexible and can be dynamically controlled according to changes in influent or produced water requirements. This flexibility stems from the flexible operation mode of MCDI, and many operating parameters can be adjusted in real time, such as the water flow rate of the electrode module and the charge and discharge current applied to the system. However, how to assign the best settings to these parameters, achieve the desired performance, and operate at the lowest operating cost is a huge challenge for existing MCDI technology. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a membrane capacitor deionization module process model optimization method based on equipment production data.

[0005] The membrane capacitor deionization module process model optimization method based on equipment production data includes the following steps:

[0006] Step 1: Obtain process data. These process data have periodic properties and are recorded for future use. When re-parameterizing the process model to adapt to the new fitting period, there is no need to re-confirm these properties in the previous period.

[0007] Step 2: Fit the process model, extract data, and obtain model parameters;

[0008] Step 3: Use the fitted process model to determine whether the selected operating conditions are applicable and determine the parameters in the membrane capacitive deionization process.

[0009] Preferably, step 1 is specifically as follows:

[0010] Step 1.1, produce product water, integrate the product of flow rate and conductivity change; determine the total conductivity removed EC according to the following formula removed :

[0011] EC removed =F×(V charge,end -V charge,start )

[0012] In the above formula, F is the equivalent capacitance, V charge,end V is the voltage before discharge after the charge cycle is completed. charge,start To predict the starting voltage of the charging cycle;

[0013] The product of flow rate and conductivity change is integrated to determine the average conductivity EC of the product water during production. Prod,Av ;

[0014] Step 1.2: During charging, the applied current I charge,total Perform integration;

[0015] Step 1.3, in each charging cycle, obtain the discharge current of the previous charging cycle, the conductivity of the water inlet of the current charging cycle, and the voltage before charging of the current charging cycle;

[0016] Step 1.4, in each charging cycle, after charging is completed, obtain the charging current and the voltage before starting to discharge;

[0017] Step 1.5: Integrate the power applied to the battery during each charging cycle to obtain the electric energy consumed by charging E charge .

[0018] Preferably, in step 1.2: when a constant current is applied during charging, the applied constant current is integrated t charge ×I charge .

[0019] Preferably, step 2 uses a nonlinear least squares regression algorithm to fit the process model.

[0020] Preferably, step 2 specifically comprises the following steps:

[0021] Step 2.1: Determine the ratio of the total conductivity removed to the applied current f by the following linear fitting formula: Z :

[0022] EC removed =f Z ×(I charge,total );

[0023] Step 2.2: Determine the predicted charging cycle start voltage V by the following fitting function: charge,start Parameters A, B and C:

[0024] V charge,start =A+(B+C / EC in )×I discharge,prev

[0025] In the above formula, EC inis the influent conductivity, I discharge,prev is the discharge current of the previous cycle;

[0026] Step 2.3: Determine the voltage V before discharge starts after the charging cycle is completed by the following fitting formula charge,end Parameters D and E:

[0027] V charge,end =1600–I charge ×(D+E / EC Prod,Av )

[0028] In the above formula, I charge represents the constant current applied during charging, EC Prod,Av Indicates the average conductivity of product water during production;

[0029] Step 2.4: Obtain the electrical energy f required to adsorb a given number of ionic charges by fitting the following function: P :

[0030] E charge =f P ×EC removed ;

[0031] Step 2.5: Estimate the equivalent capacitance F using the following fitting function:

[0032] EC removed =F×(V charge,end -V charge,start ).

[0033] As a preferred embodiment: the voltage V before discharge after the charging cycle is completed in step 2.3 charge,end It is 1600mV. 1600mV is the final battery voltage used in operation. This value can be any desired battery voltage suitable for use in the MCDI system.

[0034] Preferably, the adsorption of a given number of ions in step 2.4 is specified by the electrical conductivity EC.

[0035] Preferably, step 3 specifically comprises the following steps:

[0036] The predicted conductivity change ΔEC is determined according to the following formula:

[0037] ΔEC=I charge ×f Z / Q

[0038] In the above formula, Q represents the flow rate;

[0039] According to the following formula, determine the conductivity EC of the product water out :

[0040] EC out＝ ΔEC–EC in

[0041] In the above formula, EC in Indicates the conductivity of influent water;

[0042] Determine the starting voltage of the charging cycle according to the following formula:

[0043] V charge,start =A+(B+C / EC in )×I discharge,prev ;

[0044] Determine the final voltage of the charge cycle according to the following formula:

[0045] V charge,end =1600–I charge ×(D+E / EC out )×I discharge,prev .

[0046] Preferably, step 3 is specifically as follows:

[0047] Check the final capacitor charging voltage V charge,end Is it greater than the initial capacitor charging voltage V charge,start ; If V charge,end ≤V charge,start , the selected operating conditions are not applicable and the selected operating conditions are discarded; if V charge,end >V charge,start , then the selected operating conditions are applicable and continue to use the selected operating conditions;

[0048] Determine the total charging time t according to the following formula charge :

[0049] t charge =EC removed / f z / I charge

[0050] In the above formula, I charge is the charging current;

[0051] The total discharge time t is determined according to the following formula discharge :

[0052] t discharge =EC removed / f z / I discharge

[0053] In the above formula, I discharge is the discharge current.

[0054] Preferably, step 2 further comprises:

[0055] Determine the product valve opening time t according to the following formula product_flow :

[0056] t product_flow =t charge +t product_flow_delay

[0057] In the above formula, t product_flow_delay delay time for any additional flow after charging;

[0058] Determine the time t that the brine valve is open brine_open ;

[0059] Determine the total time for a complete charge and discharge cycle (also called cycle time) according to the following formula: cycle :

[0060] t cycle =t product_flow +t discharge +t brine_open

[0061] In the above formula, t brine_open Refers to the time the brine valve is open;

[0062] Calculate the product water volume V generated in each cycle according to the following two formulas product and the volume of saline V brine :

[0063] V product =Q×t product_open

[0064] V brine =Q×t product_open ;

[0065] In the above formula, t product_open The time the product water valve is open;

[0066] The water recovery rate WR is determined according to the following formula:

[0067] WR=V product / (V product +V brine );

[0068] The volumetric productivity was determined according to the following formula:

[0069] Volumetric productivity = V product / t cycle ;

[0070] The energy required for each charging cycle is calculated using the following fitting function:

[0071] E charge=f P ×EC removed ;

[0072] The energy requirements of the solenoid valve are calculated based on the operating time per cycle and the known power requirements.

[0073] The beneficial effects of the present invention are:

[0074] The present invention is simple and easy to calculate, and only requires calculating the operating indicators with appropriate discretization within the entire feasible operating region; the range of the charging current of the method of the present invention is determined by the electronic equipment used to drive the process, for example, it may be 20A to 100A, so the performance of all arrangements at 5A intervals can be calculated, so that the membrane capacitor deionization process can be easily used on many devices and is useful within the time range of real-time process control (for example, a typical cycle may take 5 to 60 minutes depending on the operating conditions).

[0075] The method of the present invention can be used to optimize the best operating conditions for achieving the desired performance under different operating conditions; the method of the present invention can take into account any changes in the influent properties and / or MCDI module deterioration, and use the collected process performance data in real time to regularly recalibrate the model; the method of the present invention can actively predict maintenance needs and monitor changes in fitted model parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 is the fitted linear plot of the ratio of the total conductivity removed to the applied current fZ;

[0077] Figure 2 is the process model and the charging cycle starting voltage V charge,start Relationship diagram;

[0078] Figure 3 is the process model and the voltage V before the discharge starts charge,end Relationship diagram;

[0079] Figure 4 The electrical energy f required to adsorb a given number of ionic charges P Schematic diagram of the fitting;

[0080] Figure 5 It is a schematic diagram of fitting the equivalent capacitance F;

[0081] Figure 6a To generate 1m when the inlet and outlet EC are 0.8mS / cm and 2mS / cm respectively 3 The energy consumed in the charging process of desalinated water;

[0082] Figure 6b To generate 1m when the inlet and outlet EC are 0.8mS / cm and 2mS / cm respectively3 Energy consumption of solenoid valve for desalting water;

[0083] Figure 6c To generate 1m when the inlet and outlet EC are 0.8mS / cm and 2mS / cm respectively 3 The energy consumption required to mobilize standby hardware using desalinated water;

[0084] Figure 6d To generate 1m when the inlet and outlet EC are 0.8mS / cm and 2mS / cm respectively 3 Energy consumption of desalinated water pumps;

[0085] Figure 7 Based on Figures 6a to 6d Energy consumption category, generating 1m 3 Total energy consumption for desalting water;

[0086] Figure 8 Schematic diagram of the overall water production rate estimation of each electrode module according to the process model;

[0087] Fig. 9 Schematic diagram of water recovery rate model estimation;

[0088] Fig.10 A schematic diagram showing the comparison between the EC removal rate predicted by the process model of the present invention and the actually observed EC removal;

[0089] Fig.11 A schematic diagram showing the comparison between the observed water production rate and the water production rate predicted by the process model of the present invention;

[0090] Fig.12 Schematic diagram showing the comparison between the observed water production rate and the water production rate predicted by the process model of the present invention. DETAILED DESCRIPTION

[0091] The present invention is further described below in conjunction with embodiments. The description of the following embodiments is only used to help understand the present invention. It should be noted that for ordinary persons in the art, without departing from the principle of the present invention, the present invention can also be modified in some ways, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

[0092] As an embodiment, a membrane capacitor deionization module process model optimization method based on equipment production data includes the following steps:

[0093] Step 1: Obtain process data. These process data have the properties of cycles and can be recorded for future use. When re-parameterizing the process model to adapt to a new fitting cycle, there is no need to re-confirm these properties in the previous cycle. In this embodiment, a total of 814 charge and discharge cycles were collected from data of an MCDI plant operating under different conditions for one month.

[0094] Step 1.1, produce product water, integrate the product of flow rate and conductivity change; determine the total conductivity removed EC according to the following formula removed :

[0095] EC removed =F×(V charge,end -V charge,start )

[0096] In the above formula, F is the equivalent capacitance, V charge,end V is the voltage before discharge after the charge cycle is completed. charge,start To predict the starting voltage of the charging cycle;

[0097] The product of flow rate and conductivity change is integrated to determine the average conductivity EC of the product water during production. Prod,Av ;

[0098] Step 1.2: When charging with a constant current during charging, integrate the constant current applied. charge ×I charge ;

[0099] Step 1.3, in each charging cycle, obtain the discharge current of the previous charging cycle, the conductivity of the water inlet of the current charging cycle, and the voltage before charging of the current charging cycle;

[0100] Step 1.4, in each charging cycle, after charging is completed, obtain the charging current and the voltage before starting to discharge;

[0101] Step 1.5: Integrate the power applied to the battery during each charging cycle to obtain the electric energy consumed by charging E charge ;

[0102] Step 2: Use nonlinear least squares regression algorithm to fit the process model, extract data, and obtain model parameters;

[0103] Step 2.1: Figure 1 As shown, the ratio of the total conductivity removed to the applied current f is determined by the following linear fitting formula Z :

[0104] EC removed =f Z ×(I charge,total );

[0105] We get fz = 7.3 × 10 -4 L·mS·cm -1 C -1 ;

[0106] Step 2.2: Figure 2 As shown, the predicted charging cycle starting voltage V is determined by the following fitting function: charge,start Parameters A, B and C:

[0107] V charge,start =A+(B+C / EC in )×I discharge,prev

[0108] In the above formula, EC in is the influent conductivity, I discharge,prev is the discharge current of the previous cycle;

[0109] It turns out that A = 260mV, B = 2mΩ and C = 0.4mΩ·cm·L -1 mxD -1 ;

[0110] Step 2.3, if Figure 3 As shown, the voltage V before the discharge starts after the charging cycle is completed is determined by the following fitting formula charge,end Parameters D and E:

[0111] V charge,end =1600–I charge ×(D+E / EC Prod,Av )

[0112] In the above formula, I charge represents the constant current applied during charging, EC Prod,Av Indicates the average conductivity of the product water during production; the voltage V before discharge after the charging cycle is completed charge,end 1600 mV, 1600 mV is the final battery voltage used in operation, this value can be any desired battery voltage suitable for use in the MCDI system;

[0113] It is found that D = 2mΩ and E = 0.4mΩ·cm·L -1 mxD -1 ;

[0114] Step 2.4: Figure 4 As shown, the electrical energy f required to adsorb a given number of ionic charges specified by the conductivity EC is obtained by the following fitting function: P :

[0115] E charge =fP ×EC removed ;

[0116] Get f P =0.443W·h·L·mS·cm -1 ;

[0117] Step 2.5: Figure 5 As shown, the equivalent capacitance F is estimated by the following fitting function:

[0118] EC removed =F×(V charge,end -V charge,start );

[0119] It is found that F = 0.0256 L·mS·cm -1 mV -1 ;

[0120] Step 3: Use the fitted process model to determine whether the selected operating conditions are applicable and determine the parameters in the membrane capacitive deionization process; after the necessary parameters of the model have been determined, if the model is to be used to optimize the operating parameters, if the model is to be used to optimize the operating parameters.

[0121] Check the final capacitor charging voltage V charge,end Is it greater than the initial capacitor charging voltage V charge,start ; If V charge,end ≤V charge,start , the selected operating conditions are not applicable and the selected operating conditions are discarded; if V charge,end >V charge,start , then the selected operating conditions are applicable and continue to use the selected operating conditions;

[0122] The predicted conductivity change ΔEC is determined according to the following formula:

[0123] ΔEC=I charge ×f Z / Q

[0124] In the above formula, Q represents the flow rate;

[0125] According to the following formula, determine the conductivity EC of the product water out :

[0126] EC out =ΔEC–EC in

[0127] In the above formula, EC in Indicates the conductivity of influent water;

[0128] Determine the starting voltage of the charging cycle according to the following formula:

[0129] V charge,start =A+(B+C / EC in )×I discharge,prev ;

[0130] Determine the final voltage of the charge cycle according to the following formula:

[0131] V charge,end =1600–I charge ×(D+E / EC out )×I discharge,prev ;

[0132] The total charging time t is determined according to the following formula charge :

[0133] t charge =EC removed / f z / I charge

[0134] In the above formula, I charge is the charging current;

[0135] The total discharge time t is determined according to the following formula discharge :

[0136] t discharge =EC removed / f z / I discharge

[0137] In the above formula, I discharge is the discharge current.

[0138] For this particular 8-module plant, the background energy consumption is constant at 300W, and each solenoid valve consumes 20W, which are relatively small. The line-to-water pumping efficiency of the pumps in this plant was determined to be 26%, where the pressure drop through the cartridge protection filter before the electrode module and the pressure drop through the electrode module were determined using standard hydraulic methods (both are related to the flow rate, the larger the flow rate, the greater the pressure drop, and therefore requires higher pumping energy at higher flow rates). For process optimization, the line-to-water pumping efficiency was determined to be 26%, where the pressure drop through the cartridge protection filter before the electrode module and the pressure drop through the electrode module were determined using standard hydraulic methods (both are related to the flow rate, the larger the flow rate, the greater the pressure drop, and therefore requires higher pumping energy at higher flow rates). -1 And produced water EC = 0.8mS·cm -1 In this case, the module generates 1m 3 The total energy consumption for water treatment is 40-160A for charging current, 40-160A for discharging current, and 1-8L·min for electrode flow rate. -1 was calculated within the scope of . Figures 6a to 6d shows the energy consumption of different processes, Figure 7 shows the total energy consumption of the process; Figures 8 to 12As shown in Figure 2, this type of analysis shows that from the perspective of energy consumption, the best operating conditions are 80A, a flow rate of 2.5L / min before entering the module, and a discharge current of 140A. At this time, the total energy consumption is about 1.2kW·h·m -3 .

Claims

1. A membrane capacitor deionization module process model optimization method based on equipment production data, characterized in that: The following steps are involved: Step 1: Obtain process data; Step 2: Fit the process model, extract data, and obtain model parameters; Step 3: Use the fitted process model to determine whether the selected operating conditions are applicable and determine the parameters in the membrane capacitive deionization process.

2. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 1, characterized in that: Step 1 is as follows: Step 1.1, produce product water, integrate the product of flow rate and conductivity change; determine the total conductivity removed EC according to the following formula removed : EC removed =F×(V charge,end -V charge,start ) In the above formula, F is the equivalent capacitance, V charge,end V is the voltage before discharge after the charge cycle is completed. charge,start To predict the starting voltage of the charging cycle; The product of flow rate and conductivity change is integrated to determine the average conductivity EC of the product water during production. Prod,Av ; Step 1.2: During charging, the applied current I charge,total Perform integration; Step 1.3, in each charging cycle, obtain the discharge current of the previous charging cycle, the conductivity of the water inlet of the current charging cycle, and the voltage before charging of the current charging cycle; Step 1.4, in each charging cycle, after charging is completed, obtain the charging current and the voltage before starting to discharge; Step 1.5: Integrate the power applied to the battery during each charging cycle to obtain the electric energy consumed by charging E charge .

3. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 1, characterized in that: In step 1.2: When charging by applying a constant current during charging, integrate the applied constant current t charge ×I charge .

4. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 1, characterized in that: Step 2 uses a nonlinear least squares regression algorithm to fit the process model.

5. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 2, characterized in that: Step 2 specifically includes the following steps: Step 2.1: Determine the ratio of the total conductivity removed to the applied current f by the following linear fitting formula: Z : EC removed =f Z ×(I charge,total ); Step 2.2: Determine the predicted charging cycle start voltage V by the following fitting function: charge,start Parameters A, B and C: V charge,start =A+(B+C / EC in )×I discharge,prev In the above formula, EC in is the influent conductivity, I discharge,prev is the discharge current of the previous cycle; Step 2.3: Determine the voltage V before discharge after the charging cycle is completed by the following fitting formula charge,end Parameters D and E: V charge,end =1600–I charge ×(D+E / EC Prod,Av ) In the above formula, I charge represents the constant current applied during charging, EC Prod,Av Indicates the average conductivity of product water during production; Step 2.4: Obtain the electrical energy f required to adsorb a given number of ionic charges by fitting the following function: P : E charge =f P ×EC removed ; Step 2.5: Estimate the equivalent capacitance F using the following fitting function: EC removed =F×(V charge,end -V charge,start )。 6. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 5, characterized in that: The voltage V before discharge starts after the charge cycle is completed in step 2.3 charge,end is 1600mV.

7. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 5, characterized in that: The charge of a given number of ions adsorbed in step 2.4 is specified by the electrical conductivity EC.

8. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 5, characterized in that: Step 3 specifically includes the following steps: The predicted conductivity change ΔEC is determined according to the following formula: ΔEC=I charge ×f Z / Q In the above formula, Q represents the flow rate; According to the following formula, determine the conductivity EC of the product water out : EC out＝ ΔEC–EC in In the above formula, EC in Indicates the conductivity of influent water; Determine the starting voltage of the charging cycle according to the following formula: V charge,start =A+(B+C / EC in )×I discharge,prev ; Determine the final voltage of the charge cycle according to the following formula: V charge,end =1600–I charge ×(D+E / EC out )×I discharge,prev 。 9. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 8, characterized in that: Step 3 is as follows: Check the final capacitor charging voltage V charge,end Is it greater than the initial capacitor charging voltage V charge,start ; If V charge,end ≤V charge,start , the selected operating conditions are not applicable and the selected operating conditions are discarded; if V charge,end >V charge,start , then the selected operating conditions are applicable and continue to use the selected operating conditions; The total charging time t is determined according to the following formula charge : t charge =EC removed / f z / I charge In the above formula, I charge is the charging current; The total discharge time t is determined according to the following formula discharge : t discharge =EC removed / f z / I discharge In the above formula, I discharge is the discharge current.

10. The membrane capacitor deionization module process model optimization method based on equipment production data according to claim 8, characterized in that: Step 2 also includes: Determine the product valve opening time t according to the following formula product_flow : t product_flow =t charge +t product_flow_delay In the above formula, t product_flow_delay delay time for any additional flow after charging; Determine the time t that the brine valve is open brine_open ; The total time t for a complete charge and discharge cycle is determined according to the following formula cycle : t cycle =t product_flow +t discharge +t brine_open In the above formula, t brine_open Refers to the time the brine valve is open; Calculate the product water volume V generated in each cycle according to the following two formulas product and the volume of saline V brine : In product =Q×t product_open In brine =Q×t product_open ; In the above formula, t product_open The time the product water valve is open; The water recovery rate WR is determined according to the following formula: WR=V product / (V product +V brine ); The volumetric productivity was determined according to the following formula: Volumetric productivity = V product / t cycle ; The energy required for each charging cycle is calculated using the following fitting function: E charge =f P ×EC removed ; The energy requirements of the solenoid valve are calculated based on the operating time per cycle and the known power requirements.

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