JP2000107796A - Sewage water treatment process simulator system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To continuously obtain a model component output value on the basis of a model component input value by an IAWQ activated sludge model No.2. SOLUTION: An on-line measurement of quality of an inflow water is made by a UV meter 6. A measurement value from the UV meter 6 is converted from BOD to COD by using correctional equations 7, 9 respectively stored in a BOD conversion means 8 and a COD conversion means 10 of an arithmetic unit 12, and further converted into a model component input value by a COD model component input value conversion means 13. An IAWQ activated sludge model No.2 of a simulator 31 derives a model component value for each of sites of a sewage water treatment process from the model component input value.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a sewage treatment process simulator system for a sewage treatment plant.

[0002]

2. Description of the Related Art A conventional sewage treatment process simulator system 30 will be described with reference to FIG. The sewage treatment process simulator system 30 uses the IAWQ active model No. as a unit device constituting the sewage treatment process. 2
And a simulator 31 that outputs a model component output value to each component based on the model component input value.

[0003] IAWQ activity model no. No. 2 handles the model component in an amount equivalent to the chemical oxygen demand (COD), and therefore COD is used as the model component input value. Therefore, in this sewage treatment process simulator system, the user needs to collect inflow water in step 33, measure COD in step 34, and input the measured COD to the simulator 31. The simulator 31 determines a model component input value based on the input COD, performs a sewage treatment process simulation under preset conditions, and outputs a model component output value from the model component output unit 32. The user interprets and uses the output value of the model component as necessary water quality data.

[0004]

In a general sewage treatment plant, sampling of inflow water and measurement of COD are performed by staff of the sewage treatment plant. More COD
Measurement takes several hours, so measurement is performed only once per day. For this reason, with the above-described specifications and usage of the simulator 31, it is not possible to continuously or automatically supply input values required by the simulator. In addition, the user must interpret the output data, and the convenience of the simulator has been impaired. Also,
Since the data input span is at most one day,
For example, it was difficult to simulate a one-day change in water quality.

[0005] The present invention has been made in view of such a point, without impairing the simulation accuracy,
It is an object of the present invention to provide a sewage treatment process simulator that can reduce the labor required for data input, provide flexibility in handling data of the simulator, and improve the convenience and functionality of the simulator.

[0006]

SUMMARY OF THE INVENTION The present invention relates to a sewage treatment process simulator system used in a sewage treatment process. The present invention relates to an IAWQ activated sludge model no.
IAWQ activated sludge model No. 2 2 includes a simulator for obtaining a model component output value for each part based on the model component input value, a measuring means for online measuring the quality of inflow water flowing into the sewage treatment process, and a measurement value and a model component input value. A sewage treatment process simulator system comprising: conversion means using a correlation formula; and calculation means for converting a measured value from the measurement means into a model component input value using the correlation formula of the conversion means. It is.

According to the present invention, the quality of the inflow water is measured online by the measuring means. The measured value from the measuring means is converted into a model component input value using a correlation formula built in the converting means of the calculating means. This model component input value is
Simulator IAWQ activated sludge model No. 2 to determine model component values for each part of the sewage treatment process.

[0008]

DESCRIPTION OF THE PREFERRED EMBODIMENTS First Embodiment An embodiment of the present invention will be described below with reference to the drawings. As shown in FIGS. 1 and 2, the sewage treatment process includes a first settling tank 1, an aeration tank 3, and a first settling tank 4. Further, a measuring point 2 which is a water sampling point for water quality analysis is provided between the first sedimentation tank 1 and the aeration tank 3, and a UV meter 6 which is a continuous water quality automatic measuring instrument is installed at the measuring point 2. Have been. In addition, a measuring point 5 which is a water sampling point for water quality analysis is provided in a stage subsequent to the first sedimentation basin 4.

Further, the sewage treatment process simulator system 30 according to the present invention provides an IAWQ activated sludge model No. 1 that models a unit device constituting a sewage treatment process as a part. IAWQ activated sludge model No. 2 A simulator 31 for obtaining a model component output value for each part based on the model component input value by the simulator 2;
And a model component output unit 32 that outputs the model component output value obtained in step (1). The simulator 31 has UV
An operation means 12 for converting a measured value from the total 6 into a model component input value is connected.

[0010] The sewage treatment process mentioned here is an example of construction of a sewage treatment process, and the scope of the present invention is not limited to this sewage treatment process. Measurement point 2
It is not necessary to specify the continuous type automatic water quality measuring instrument installed in the UV meter 6 as long as it can grasp the organic matter of the target sample. A turbidity meter other than the UV meter 6 can be considered as a continuous water quality automatic measuring device.

Next, the operation of the embodiment having such a configuration will be described. First, UV data measured by the UV meter 6 is transmitted to the BOD conversion means 8 incorporated in the calculation means 12. In the BOD conversion means 8, U
Existing UV data measured by V meter 6 and biological oxygen demand (BOD) collected and analyzed at measurement point 2
Is stored in advance, and the UV data is converted into BOD by the correlation equation 7.

Since the BOD indicates the amount of oxygen required to decompose the organic matter in the sample, use a continuous automatic water quality measuring instrument such as a UV meter 6 or a turbidity meter capable of grasping the organic matter in the sample. Accordingly, a high correlation can be expected between the BOD and the measurement value obtained by the continuous automatic water quality measurement device. For this reason, a conversion error by the BOD conversion means 8 can be reduced, and a decrease in simulation accuracy can be prevented.

In the present embodiment, one time in the past year
BOD obtained and collected at weekly intervals
The correlation equation 7 was created by using the UV measurement value corresponding to D in time. The correlation equation 7 was created using linear approximation, exponential approximation, logarithmic approximation, or polynomial approximation as the type of approximation or regression, and the one having the highest degree of approximation was selected.
FIG. 2 shows the correlation equation 7 actually used. In FIG.
BOD = 3.913 × UV−69.314, BO
When D <0, BOD = 0.

Next, B converted by the BOD conversion means 8
The OD data is input to the COD conversion means 10 and is converted from BOD to COD by the BOD-COD correlation equation 9 between the BOD of the inflow water and the COD of the inflow water. The converted COD is converted into a model component input value by the COD / model component input value conversion means 13 and input to the simulator 31.

There are 17 types of model components of inflow water quality used in the simulator 31 (SA, SALK, SF, S
I, SN ₂ , SNH ₄ , SNO ₃ , SO ₂ , SPO ₄ ,
SS, XAUT, XH, XI, XMeOH, XMeP,
XPAO, XPHA, XPP, XS, XTSS), defined in the IAWQ Task Group: Scient
ific and Technical Report
No. 3, 1995. In the present invention, BOD
COD = 10/9 × BOD was used as COD correlation equation 9. COD is a COD / model component input value conversion means 1
3, a linear equation (each model component input value = a × COD +
b; a and b are constants) and are converted into model component input values.

Here, the COD conversion means 10 and the COD / model component input value conversion means 13 can be combined into one arithmetic means 13 and used as the conversion means 11.
Further, the conversion means 11 and the BOD conversion means 8 may be combined into one calculation means.

The simulator 31 performs a dynamic simulation of the sewage treatment process based on the continuously input model component input values, obtains model component output values for each component, and outputs the output values from the model component output unit 32. I do.

FIG. 9 shows the simulation output value from the model component output unit 32 at the measurement point 5 according to the present invention, and the water output at the measurement point 5 compared with the conventional simulation output value.
Shown with hand analysis measurements analyzed. As shown in FIG.
The simulation output value in the present invention is not different from the conventional simulation output value in terms of accuracy, and is capable of continuously outputting the simulation output value, and is excellent in function.

According to the present embodiment, the measurement value of the UV meter 6 can be continuously and automatically converted to the model component input value with high accuracy, and the data input without reducing the simulation accuracy of the simulator 31 can be performed. For the simulator 31 can be reduced, and the convenience of the simulator 31 is improved. Further, since the model component output value is continuously output from the model component output unit 32, it is easy to grasp the transition of the simulation result, and the functionality of the simulator 31 is improved.

Second Embodiment Next, a second embodiment will be described with reference to FIG. In FIG. 3, the same portions as those in the first embodiment shown in FIGS. 1 and 2 are denoted by the same reference numerals, and detailed description is omitted. In FIG. 3, the UV data measured by the UV meter 6 is transmitted to the BOD
Is converted into a BOD by the UV / BOD correlation equation 7 built in. Next, the BOD is input to the simulator 31 converted into the model component input value by the conversion means 11.
Here, some of the model component input values are determined by the following method.

During this time, the UV measured by the UV meter 6
The data may be transmitted to the SNH ₄ conversion means 15. SS
The H ₄ conversion means 15 has a UV-ammonia nitrogen correlation formula between the existing UV data measured by the UV meter 6 at the measurement point 2 and the amount of ammonia nitrogen collected and analyzed at the measurement point 2. The UV data is converted into a model component input value SNH ₄ by the correlation equation 14.
The definition of the model component SNH ₄ is ammoniacal nitrogen,
The UV data can be converted to SNH ₄ by the steps described above. By converting the UV measurement into the model component input value SNH ₄ by one conversion,
The conversion error can be reduced as compared with the case where the conversion is performed by the UV / BOD conversion means 8 and the conversion means 11, and the decrease in simulator accuracy can be suppressed.

The UV data measured by the UV meter 6 may be transmitted to the SNO ₃ conversion means 17. SNO ₃
In the conversion means 17, a UV / nitrate nitrogen correlation equation 16 between the existing UV data measured by the UV meter 6 at the measurement point 2 and the amount of nitrate nitrogen collected and analyzed at the measurement point 2 is stored. UV data is converted into a model component input value SNO _{3 according} to the correlation equation 16. Model component SNO
The definition of ₃ is nitrate nitrogen, and the UV data can be converted to SNO ₃ by the above-mentioned process.
Model component input value SN by converting UV measurement value once
By converting to O ₃ , a conversion error can be reduced as compared with the case where conversion is performed by the BOD conversion means 8 and the conversion means 11, and a decrease in simulator accuracy can be suppressed.

Further, UV data measured by the UV meter 6 may be transmitted to the SPO ₄ conversion means 19. SPO
_{4 In the} conversion means 19, a UV-phosphorus correlation equation 18 between the existing UV data measured by the UV meter 6 at the measurement point 2 and the phosphorus amount sampled and analyzed at the measurement point 2 is previously stored. The UV data is converted into the model component input value SPO ₄ by the correlation equation 18. The definition of the model component SPO ₄ is phosphorus, and UV data is converted to S
It can be converted to PO _4. By converting the model component input value SPO ₄ by conversion once UV measurements, reduces the conversion error compared with the case in which the converted BOD converting means 8 by the conversion means 11, it is possible to suppress the deterioration of the simulator accuracy.

The UV data measured by the UV meter 6 may be transmitted to the XTSS conversion means 21. XTSS
The conversion means 21 previously incorporates a UV / SS correlation equation 20 between the existing UV data measured by the UV meter 6 at the measurement point 2 and the SS sampled and analyzed at the measurement point 2,
According to this correlation equation 20, the UV data is converted to the model component input value X.
Converted to TSS. The definition of the model component XTSS is the total suspended matter, and the UV data can be converted into the XTSS by the above-described process. 1 UV measurement
By performing the conversion to the model component input value XTSS by the second conversion, the conversion error can be reduced as compared with the case where the conversion is performed by the BOD conversion unit 8 and the conversion unit 11, and a decrease in simulator accuracy can be suppressed.

The UV data measured by the UV meter 6 may be transmitted to the SO ₂ conversion means 23. In the SO ₂ conversion means 23, the existing UV data measured by the UV meter 6 at the measurement point 2 and the D data collected and analyzed at the measurement point 2
UV · DO correlation equation 22 between the O is incorporated in advance, UV data by the correlation equation 22 is the model component inputs SO ₂
Is converted to The definition of the model component SO ₂ is dissolved oxygen, and the UV data can be converted to SO ₂ by the above-described steps. By converting the UV measurement into the model component input value SO ₂ by one conversion,
The conversion error can be reduced as compared with the case where the conversion is performed by the BOD conversion unit 8 and the conversion unit 11, and a decrease in simulator accuracy can be suppressed.

In FIG. 3, SNH ₄ conversion means 1
5, SNO ₃ conversion means 17, SPO ₄ conversion means 19, X
As for the TSS converter 21 and the SO ₂ converter 23, any one of these converters 15, 17, 19, 21, and 23 can be provided.

Third Embodiment In the first embodiment, the correlation equation shown in FIG. 2 is used as the UV / BOD correlation equation 7 built in the BOD conversion means 8, but the correlation increases with time. It is also conceivable that it will decrease.

FIG. 4 is a graph showing the relationship between the UVs after two years from the correlation shown in FIG.
9 shows a correlation equation between a measured value and a BOD. 2 and 4
The correlation formula shown in FIG. 2 is significantly different. Using the correlation formula shown in FIG. 2 and FIG. 4, a simulation of the amount of ammonia nitrogen was performed using the UV measurement value two years later as an input value. A result was obtained that the simulation output value (see FIG. 6) using the correlation formula shown in FIG. 4 was closer to the analyzed hand analysis measured value than the simulation output value using the correlation formula (see FIG. 5). In view of this result, the following improvements were made.

Conversion means 8, 10, 15, 17, 19, for converting any time-series data A into any time-series data B,
Reference numerals 21 and 23 allow the user to change the correlation equation between the arbitrary time series data A and the arbitrary time series data B to be used in accordance with the passage of time by setting the set value by the user. Here, the items that can be set by the user are the data range and the setting of the approximate curve. This allows the user to create a correlation formula with the highest correlation, and suppresses a decrease in simulation accuracy.

Alternatively, conversion means 8, 10, 15, 1
Prior to the step of converting any time-series data A into any time-series data B using a correlation equation according to 7, 19, 21, 23, a correlation equation that is valid for a predetermined period, specifically, one year, There may be provided a time-change correlation expression creating means for creating while changing. As a result, since the conversion is always performed using the latest correlation expression without the user's recognition, a decrease in simulation accuracy is suppressed and the convenience of the simulator is improved.

Fourth Embodiment A fourth embodiment will be described with reference to FIG. In FIG. 2, a flow meter 24 is provided at the measurement point 2 together with the UV meter 6.

If the inflow rate measured by the flow meter 24 exceeds the predetermined value, the flow rate change correlation formula creation means 25 determines that the mode is the rainfall mode, and calculates the correlation formula a as the correlation formula of the BOD of the UV measurement value.
Create In this case, a correlation equation a is created based on the BOD obtained by collecting and analyzing water in the rainfall mode for the past year and the UV measurement value temporally corresponding to the BOD.

On the other hand, when the flow rate amount is equal to or less than the predetermined value, the flow rate change correlation formula creating means 25 determines that the mode is the fine weather mode and creates a correlation formula b as a correlation formula between the UV measurement value and the BOD. In this case, a correlation equation b is created based on the BOD obtained by collecting and analyzing water in the fine weather mode for the past year and the UV measurement value corresponding to the BOD in time.

In the rainfall mode, the pollutants stored in the sewer pipe and the surface of the ground flow at a dash due to an increase in the amount of inflow.
This is generally called first flash. By switching between rain / sunny mode according to the inflow amount and creating correlation equations a and b using the measured values in each mode, the correlation between UV and BOD in each mode is improved, and as a result, the data The conversion accuracy is improved, and a decrease in the accuracy of the simulator can be suppressed.

The correlation equations a and b obtained by the flow rate change correlation equation creating means 25 are sent to the BOD conversion means 8 and
In the BOD conversion means 8, a and b are used as the correlation equation 7. Similarly, other conversion means 10, 15, 17, 1
The correlation equations a and b may be sent from the flow rate change correlation equation creating means 25 to 9, 21, and 23 and used.

Fifth Embodiment Water quality hand analysis measured and measured at measurement point 5 in FIG.
When the parameter fitting of the simulator is performed between the model component output value obtained by the simulator 31 corresponding to the hand analysis measured value and the model component output unit 32, the parameters are adjusted one by one to obtain the hand analysis measured value. As a result of enhancing the consistency between the model component output value and the simulator 31
IAWQ active ingredient model no. KH, K used in 2
X, μH, qfe, bH, qPHA, qPP, μPA
O, bPAO, bPP, bPHA, μAUT, bAU
T, the kinetic parameter is varied proportionally with the inflow water temperature,
In addition, it was found that by specifying the μAUT, it was possible to easily fit ammonia nitrogen and nitrate nitrogen. FIG. 8 shows an example in which parameter fitting was performed for ammoniacal nitrogen. By performing the parameter fitting, the simulator can follow the change of ammonia nitrogen particularly from April to July. Regarding the change from October to January, this can be determined to be a change due to factors other than the inflow water quality.

By matching the parameters used by the model with the target sewage treatment process, an improvement in simulation accuracy as shown in FIG. 8 can be expected.

Sixth Embodiment In FIG. 1, a model component output value obtained by a simulator 31 and output from a model component output unit 32 is converted by a conversion correlation equation according to the correspondence table of Table 1. When the notation of the correlation equation is “=”, there is a 1: 1 correspondence between the model component output value and the conversion value. In other cases, a correlation equation between the model component output value and the hand analysis measurement actual measurement value corresponding to the model component output value is used.

By the above conversion, the simulation output value can have various meanings, and the simulator data can be handled flexibly.

[0040]

[Table 1]

[0041]

As described above, according to the present invention, the quality of the inflow water is measured online by the measuring means, and based on the measured value, the IAWQ activated sludge model N of the simulator is used.
o. Since the simulation is performed according to 2, the model component output value can be continuously obtained based on the model component input value.

[Brief description of the drawings]

FIG. 1 is a diagram showing a first embodiment of a sewage treatment process simulator system according to the present invention.

FIG. 2 is a diagram showing a correlation equation between UV and BOD.

FIG. 3 is a diagram showing a second embodiment of the sewage treatment process simulator system according to the present invention.

FIG. 4 is a diagram showing a correlation equation between UV and BOD in a third embodiment of the sewage treatment process simulator system according to the present invention.

FIG. 5 is a diagram showing a simulation result using the correlation equation of FIG. 2;

FIG. 6 is a view showing a simulation result using the correlation equation of FIG. 4;

FIG. 7 is a diagram showing a fourth embodiment of the sewage treatment process simulator system according to the present invention.

FIG. 8 is a view showing a state of parameter fitting showing a fifth embodiment of the sewage treatment process simulator system according to the present invention.

FIG. 9 is a diagram showing a simulation result according to the present invention.

FIG. 10 is a diagram showing a general form of a conventional sewage treatment process simulator system.

[Explanation of symbols]

Reference Signs List 6 UV meter 8 BOD conversion means 10 COD conversion means 11 Conversion means 12 Operation means 15 SNH ₄ conversion means 17 SNO ₃ conversion means 19 SPO ₄ conversion means 21 XTSS conversion means 23 SO ₂ conversion means 30 Sewage treatment process simulator system 31 Simulator 32 Model component output section

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Shozaburo Furube 1 Toshiba-cho, Fuchu-shi, Tokyo Inside the Toshiba Fuchu plant (72) Inventor Manabu Matsumae 1 Toshiba-cho, Fuchu-shi, Tokyo (72) Inventor Tsuyoshi Takizawa 1 Toshiba-cho, Fuchu-shi, Tokyo Inside the Fuchu Plant, Toshiba Corporation (72) Inventor Tetsuya Shinohara 1-1-30 Oyodonaka, Kita-ku, Osaka-shi, Osaka Toshiba Kansai Co., Ltd. Branch office (72) Inventor Masahiko Tsutsumi 1 Toshiba-cho, Fuchu-shi, Tokyo F-term in the Fuchu factory of Toshiba Corporation 4D040 BB02 BB32 BB91

Claims (9)

[Claims] 1. A sewage treatment process simulator system used for a sewage treatment process, comprising: an IAWQ activated sludge model No. 1 that models a unit device constituting the sewage treatment process as a part. 2 and IA
WQ activated sludge model No. 2 includes a simulator for obtaining a model component output value for each component based on the model component input value, a measuring means for online measuring the quality of the inflow water flowing into the sewage treatment process, and a measurement value and a model component input value. A sewage treatment process simulator system comprising: conversion means using a correlation formula; and calculation means for converting a measurement value from the measurement means into a model component input value using the correlation formula of the conversion means. . 2. A simulator according to claim 1, wherein the model component input value is C
The sewage treatment process simulator system according to claim 1, wherein a value obtained by converting the OD is used. An arithmetic unit configured to convert a measured value from the measuring unit into a corresponding BOD; a COD converting unit converting the BOD into a corresponding COD; and a COD model converting the COD into a model component input value. 3. A sewage treatment process simulator system according to claim 2, further comprising component conversion means. 4. The simulator according to claim 1, wherein said model component input value is S.
_{NH 4, SNO 3, SPO 4} , XTSS or sewage treatment process simulator system of claim 1, wherein the use of any of SO _2. 5. The calculating means calculates the measured value from the measuring means as SNH
SNH ₄ converting means for converting the _4, SNO ₃ conversion means for converting the measured values from the measuring means to SNO _3, SPO ₄ conversion means for converting the measured values from the measuring means to the SPO _4, the measured values from the measuring means XTSS conversion means for converting into XTSS, sewage treatment process simulator system according to claim 4, wherein a measured value from the measuring means one one of the SO ₂ conversion means for converting the SO _2. 6. A time-varying correlation equation means for obtaining a correlation equation that changes with the passage of time is provided, and the conversion means of the arithmetic means uses a correlation equation from the time-variation correlation equation creating means. The sewage treatment process simulator system according to claim 1. 7. A flow rate change correlation formula creating means for obtaining a correlation equation that changes in response to a change in the flow rate of inflow water is provided, and the conversion means of the arithmetic means has a correlation formula from the flow rate change correlation formula creation means. The sewage treatment process simulator system according to claim 1, wherein: 8. The sewage treatment process simulator system according to claim 1, wherein the measuring means is a UV meter. 9. The sewage treatment process simulator system according to claim 1, wherein the measuring means is a turbidity meter.