JPS6134602A - Water-delivery forecasting system of filter plant - Google Patents

Abstract

PURPOSE:To realize a management which can cope with a demand varied from day to day and scarcely generates a forecasting error, by correcting a forecasting result obtained by a Kalman filter method, by a correcting factor based on a weather change or a singular day. CONSTITUTION:Information of the primary forecasting water-delivery Qi calculated by a conventional Kalman filter method is obtained from an operation processing part 2. The information of the water-delivery Qi is inputted to the first forecasting water-delivery correcting part 3 and corrected by correcting factors DELTAQ1, DELTAQ1' based on a weather change from a weather change input part 4, and the selected secondary forecasting water-delivery Qi' is outputted. Thereafter, information of the water-delivery Qi' is sent to the second forecasting water-delivery correcting part 5 and corrected by correcting factors + or -DELTAQ2 based on a singular day from a singular day/usual day change input part 6, and information of the final forecasting water-delivery Q corresponding to the respective modes selected by switches 6a, 6b is determined.

Description

[Detailed Description of the Invention] [Field of Industrial Application] This invention relates to a technology for predicting the total daily water demand in a water treatment plant and achieving optimal operation of the water intake and distribution pumps used there. Involved.

[Conventional technology]

In general, it is preferable that water intake and water distribution plans at water treatment plants be drawn up according to the daily power consumption and water supply amount. By doing so, efficient operation of water intake and distribution pumps can be realized, and water resources savings can be made.

The water distribution amount prediction method commonly used in the past is based on mathematical methods such as the Kalman filter method, and is calculated using the following formula: Q (+)-al HQ(+-1)+ai Q(i
-2) 10-+b, 〒(i)+bg ・T (+-1)
10 ...... (11 in the above formula) d: Predicted water distribution amount (information) Q: Actual water distribution amount (past, information) 〒: Expected maximum temperature (today, information) T: Maximum temperature (the previous day, information) i : i-th day al + al ~ bI + b2 ``...'' As defined by the coefficient, it is a linear prediction based on past performance data.Therefore, changes in weather in a short period of time,
For example, the predicted water distribution amount d in a case where it was sunny yesterday and rainy today will be influenced by the past actual water distribution amount Q, and will have a large error from the actual required amount.

Figure 2 is a graph illustrating the above drawbacks in the conventional prediction method.The vertical axis shows the water distribution amount rrrZ days, and the horizontal axis shows the day.The actual water distribution amount is shown by the solid line a, and the predicted water distribution amount is shown by the dotted line. Each is shown in the following. In the figure, as can be seen from the (++3) sunny day and the (++4) rainy day, there is a fairly large difference on the (++4) day when the weather changed from sunny to rainy. In this way, in the Kalman filter method, the coefficients of the daily prediction formula are updated according to the error between the actual water distribution amount and the predicted water distribution amount, so although the prediction error is large on days when the weather changes, If there are no large changes, the prediction error will be small.

[Problem that the invention seeks to solve]

Since the Kalman filter method is based on linear prediction, it can respond to relatively long-term changes in weather, but
This means that changes over a short period of time cannot be adequately followed.

[Purpose of the invention]

Therefore, an object of the present invention is to be able to quickly respond to fluctuations in water demand due to short-term changes in weather, and to be able to respond promptly to fluctuations in water demand due to special days in the region, such as New Year, Obon, and festivals. The aim is to provide a water distribution amount forecasting method that can respond flexibly.

[Means for solving problems]

In order to achieve the above object, the present invention calculates the average value of the difference between the predicted water distribution amount and the actual water distribution amount when the weather changes from rainy to sunny or from sunny to rain throughout the year. ΔQ and 801' are tabulated in advance, for example, by date, week, or month, and for the prediction results obtained daily through the mathematical method of Kalman filter method, the above-mentioned prediction results are used only on days when the weather changes. At the same time as making corrections using ΔQ1 or ΔQ1', if necessary, regarding the singular days in the above-mentioned regions, based on past statistical data,
For example, by creating a table in advance of the average value ΔQ2 of the difference in actual water distribution amount between special days and normal days for dates or items, and using the Kalman filter method to calculate the difference between normal days and unusual days, The amendments will only be made to changes such as the transition from a singular day to an ordinary day.

[Effect]

The prediction results obtained by the conventional Kalman filter method are based on weather changes (correction factors 〇, .

By correcting with a correction factor ±ΔQ2 based on ΔQl' or a specific date, it is possible to respond to demand that fluctuates on a daily basis.
This means that management with small prediction errors can be achieved.

〔Example〕

Referring to the block diagram of FIG. 1 showing a preferred embodiment of the present invention, the water distribution amount control system 1 for a water purification plant according to the present invention includes an arithmetic processing unit 2 and a first predicted water distribution amount correction system. section 3, weather change input section 4, and second predicted water distribution amount correction section 5.
, a special day/normal day change input section 6 , a date and time generation section 7 , and a storage section 8 . It should be noted that all input parameters and outputs addressed in connection with FIG. 1 are informational since system 1 ultimately derives its electrical output to drive the intake and distribution pumps.

The water distribution amount prediction calculation processing unit 2 is a calculation processing unit using the conventional Kalman filter method.
In response to a trigger signal containing l information generated at a fixed time, the actual water distribution amount (past) Q, the predicted maximum temperature (today's )
? and the maximum temperature (the previous day) T from the storage unit 8, and perform the calculation 2). Thus, the arithmetic processing section 2
The information on the water distribution amount 00) that appears in the output of is the conventional linear prediction, and is treated here as the first predicted water distribution amount information,
It is automatically updated once a day at a scheduled time. Information on the water distribution amount d(1) calculated by the arithmetic processing section 2 is input to the first predicted water distribution amount correction section 3, and is stored in a table corresponding to the date as correction information based on the weather change from the weather change input section 4. It is corrected by ΔQ1 or 80l' which is stored as a digitized value. As shown in the figure, the weather change manpower section 4 is located at the first... The operation panel is equipped with second switches 4a and 4b, the switch 4a is a switch for inputting Q, and the switch 4b is a switch for inputting ΔQI'. By inputting a value, a predetermined numerical value is inputted from a memory having a table. And these switches 4
When a and 4b are selected manually or automatically, calculations are performed in the first predicted water distribution amount correction unit 3 to obtain information on the second child measured water distribution amount d(1)' corresponding to each. That is: i) When switch 4 is on (day of change from rainy to sunny) Q (
i)' −〇 (i) 10ΔQ.

ii) Q when switch 4' is on (i)' -〇 (+) - ΔQ1'iii) Q when switches 4 and 4' are both off (i)' -Q (i
) Any of the second measured water distribution amounts d(1) obtained in this way
The information ′ corresponds to the water distribution amount revised to take into account changes due to weather. Manual operation of the switches 4a and 4b depends on the operator's judgment, but in the case of automatic control, for example, changes in the maximum temperature are detected and automatically inputted from a control unit (not shown). Further, the switch 4a after the correction operation is completed,
4b is automatically canceled.

Thereafter, the information on the second measured water distribution amount d(1)', which is the output of the first predicted water distribution amount correction section 3, is sent to the second predicted water distribution amount correction section 5, and correction is made taking into account the special day. will receive. As can be seen from the figure, the special day/regular day change input section 6 has switches 6a and 6b, and the switch 6a is provided as an information input of the correction information +ΔQ2 stored in a table in the memory. Similar correction information - ΔQ
A switch 6b is provided as the second information input. These switches 6a and 6b are manually selected by the operator to determine the final predicted water distribution amount Q corresponding to each mode.
information is determined. That is: i) When switch 6 is on (normal day - singular day) Q = Q(i)' 1 Δ
Q2 ii) Switch 6' - when on (singular day - old days) Q
= Q(i)' - ΔQ2 iii) Switch 6, 6' - When both are off Q = Q (
1)' Note that the switches 6a and 6b are automatically released after the correction operation is completed.

As a result of the above, information on today's predicted water distribution amount is output from the second predicted water distribution amount correction section, and based on this, the water intake-distribution pump drive section 9 and the water intake-distribution pump 10 are driven. .

As explained above, the input of correction information is not limited to inputting switches for tabulated information, but it is also possible to press the numeric keypad from the keyboard and input the corresponding correction value each time. Alternatively, a configuration may be adopted in which the information is stored in a specific area of the memory and then read and calculated.

Although the first and second predicted water distribution amount correction units are shown in this embodiment, it goes without saying that only one of them may be used for correction.

Further, it goes without saying that prediction using a mathematical method is not limited to the Kalman filter method.

〔Effect of the invention〕

According to this invention, past statistical data such as the average prediction error amount due to weather changes or the average demand change amount between a specific day and a normal day is added to the water distribution amount prediction method using a conventional mathematical method (for example, the Kalman filter method). Since a correction function has been added based on □, tracking of fluctuations in predicted water distribution due to short-term weather changes and the effects of unusual days can be greatly improved.

[Brief explanation of drawings]

FIG. 1 is a block diagram of a water treatment plant water distribution control system illustrating a preferred embodiment of the present invention, and FIG. It is a graph diagram. 1: Water distribution amount control system for water purification plants 2: Arithmetic processing section 3: First predicted water distribution amount correction section 4: Weather change human power section 5: Second predicted water distribution amount correction section 6: Specific mill/normal daily change human power section 7: Date and time generation section 8: Storage section

Claims (1)

[Claims] In a water distribution forecasting method using mathematical methods, the predicted water distribution amount is corrected based on past statistical data, including the average forecast error due to changes in weather or the average demand change between unusual days and normal days. A water distribution forecasting method characterized by: