CN116975968A - Method for evaluating and predicting laminated water taking effect of stoplog door - Google Patents
Method for evaluating and predicting laminated water taking effect of stoplog door Download PDFInfo
- Publication number
- CN116975968A CN116975968A CN202310883395.3A CN202310883395A CN116975968A CN 116975968 A CN116975968 A CN 116975968A CN 202310883395 A CN202310883395 A CN 202310883395A CN 116975968 A CN116975968 A CN 116975968A
- Authority
- CN
- China
- Prior art keywords
- water
- water temperature
- door
- test
- tail
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 283
- 230000000694 effects Effects 0.000 title claims abstract description 49
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000000611 regression analysis Methods 0.000 claims abstract description 9
- 238000012360 testing method Methods 0.000 claims description 103
- 238000012544 monitoring process Methods 0.000 claims description 32
- 238000010248 power generation Methods 0.000 claims description 19
- 238000012806 monitoring device Methods 0.000 claims description 10
- 238000011156 evaluation Methods 0.000 claims description 8
- 238000004088 simulation Methods 0.000 claims description 8
- 230000001419 dependent effect Effects 0.000 claims description 7
- 238000013461 design Methods 0.000 claims description 5
- 238000007599 discharging Methods 0.000 claims description 4
- 238000007781 pre-processing Methods 0.000 claims description 4
- 230000002411 adverse Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000008239 natural water Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02B—HYDRAULIC ENGINEERING
- E02B9/00—Water-power plants; Layout, construction or equipment, methods of, or apparatus for, making same
- E02B9/02—Water-ways
- E02B9/04—Free-flow canals or flumes; Intakes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/27—Regression, e.g. linear or logistic regression
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Geometry (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Computer Hardware Design (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Structural Engineering (AREA)
- Civil Engineering (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Architecture (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Mechanical Engineering (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Control Of Water Turbines (AREA)
Abstract
The invention relates to the technical field of water conservancy and hydropower engineering, and provides a method for evaluating and predicting laminated water taking effects of a stoplog door, which is used for conveniently evaluating and predicting the laminated water taking effects of the stoplog door. When the prediction is carried out, a multiple regression analysis method is adopted to obtain a relational formula between related data and water taking effect, the operation is simple and convenient, the feasibility is strong, and the method can be applied to actual operation of engineering.
Description
Technical Field
The invention relates to the technical field of water conservancy and hydropower engineering, in particular to a stack gate layered water taking effect evaluation and prediction method.
Background
After the large deep reservoir stores water, the low-temperature water discharged downwards can cause adverse effects on the aquatic ecology of downstream river channels and production and life. The layered water taking measures can slow down the influence of the downstream water temperature change of the reservoir on aquatic ecology and water supply, and have important significance for protecting the ecological environment of the watershed. The stop-beam gate is used as a main layered water taking engineering measure and is widely applied to domestic large-scale hydropower engineering.
The stop log is generally started in the spawning period of fishes in 3-6 months so as to reduce the adverse effect of low-temperature water discharged from the stop log on spawning of fishes. During this period, the layered water intake effect of the stop-beam door is a main index for evaluating whether the stop-beam door is effective in operation.
In the prior art, the actual measurement data of the water temperature of the lower drainage after the stoplog door is started is compared with the numerical simulation water temperature of the lower drainage without the stoplog door or the natural water temperature of a dam site, and the temperature difference between the two is analyzed to be used as the effect of the stoplog door, but the water temperature of the lower drainage is influenced by the factors such as the vertical water temperature structure, the water taking depth, the flow and the like of a reservoir area, and the change of the water temperature is larger along with the time, so that the analysis method can not accurately reflect the layered water taking effect of the stoplog door. Secondly, the most numerical simulation method is adopted when the layered water taking effect prediction of the stoplog door is carried out, a reservoir region water temperature-hydrodynamic force coupling model is required to be constructed, the numerical simulation is carried out on the lower water discharging temperatures of different water taking elevations after the stoplog door is started, and the comparison is carried out with the lower water discharging temperature without the stoplog door. The method is strong in theory, but the numerical model construction process is complex, more basic data are needed, the operability is poor, and engineering operation is difficult to guide.
Disclosure of Invention
In order to facilitate evaluation and prediction of the laminated water taking effect of the stoplog door, the method for evaluating and predicting the laminated water taking effect of the stoplog door is provided.
The invention solves the problems by adopting the following technical scheme:
the stack beam door layered water taking effect evaluation and prediction method comprises the following steps:
step 1, setting a test group and a comparison group according to the opening and closing states of a stop log door corresponding to at least two tail water ports of a hydropower station;
step 2, setting test working conditions according to the number of layers or the height of the stop-beam door;
step 3, installing water temperature monitoring equipment in front of tail water and dams of a test group and a control group;
step 4, carrying out water taking tests according to test working conditions, obtaining tail water temperatures of a test group and a control group, and obtaining related data, wherein the related data comprise: the water temperature difference between the water temperature of the top of the stoplog door and the water temperature of the bottom plate of the water inlet and the power generation flow before the dam is formed by the height of the stoplog door, the top water head of the stoplog door and the water temperature difference between the water temperature of the top of the stoplog door and the water temperature of the bottom plate of the water inlet;
step 5, calculating the average temperature difference of the tail water temperatures of the test group and the control group in each test working condition, and taking the average temperature difference of the tail water temperatures as the laminated water taking effect of the stop-beam door under the working condition;
step 6, taking the related data as independent variables, taking the tail water temperature difference at the same time as dependent variables, and performing multiple regression analysis to obtain a quantitative relation formula of the tail water temperature difference and the related data;
and 7, predicting the water taking effect according to a quantitative relation formula.
Further, the pre-dam water temperature monitoring device adopts a pre-dam vertical water temperature monitoring device.
Further, the vertical water temperature monitoring equipment in front of the dam is arranged in a preset distance of a water inlet in front of the dam or at a midbody.
Further, the tail water temperature monitoring equipment is set to be 0.5m in depth, and the vertical water temperature monitoring equipment in front of the dam is set to be 1-Nm in depth, wherein N is greater than the depth of a water inlet bottom plate.
Further, the concrete layout mode of the vertical water temperature monitoring equipment in front of the dam is as follows: when N is less than or equal to 20m, 1 temperature sensor is arranged every 1 m; when N is more than 20m, 1 temperature sensor is arranged every 1m for the water depth of 1-20 m, and 1 temperature sensor is arranged every 2m for the water depth of 20-Nm.
Further, the step 4 specifically includes:
setting the corresponding stoplog door of the test group to the layer number designated by the design working condition, and enabling the corresponding stoplog door of the comparison group not to be started;
starting from the moment when the stop log door is dispatched to a designated position in each working condition test period, and stopping when the next working condition starts dispatching the stop log door;
during the test, the test group and the control group synchronously collect tail water temperature, vertical water temperature in front of the dam, water level in front of the dam and power generation flow of each unit;
flood discharge is avoided during the test period, and the discharging flow is discharged through the power generation tail water; the generating flow of the unit corresponding to the tail water of the test group and the generating flow of the unit corresponding to the tail water of the comparison group are in an error range;
and the duration of each working condition test is more than or equal to 24 hours, and after each working condition test is completed, the test group stop log door is scheduled to the next working condition to continue the test until all the working condition tests are completed.
Further, tail water temperature data are collected for 1 time every 15-30min, and vertical water temperature before the dam is collected for 1-2 h.
Further, the step 5 further includes preprocessing the water temperature monitoring data before calculating the average temperature difference of the tail water temperatures of the test group and the control group in each working condition.
Further, the preprocessing is as follows: deleting tail water temperature monitoring data of each period of time at the beginning and the end of the working condition; and calculating the average value of the tail water temperature difference values of the test group and the control group in the effective monitoring time.
Further, when the quantitative relation formula contains the temperature difference between the water temperature of the front stop-beam door top and the water temperature of the water inlet bottom plate, the predicted water temperature difference between the water temperature of the front stop-beam door top and the water temperature of the water inlet bottom plate is calculated by adopting the front vertical water temperature monitoring data or calculated by adopting a numerical simulation mode.
Compared with the prior art, the invention has the following beneficial effects:
the invention adopts a method of 'whether there is contrast', compares the measured data of the lower drain temperature after the stoplog door is started with the measured data of the lower drain temperature of the stoplog door which is not at the same time, and characterizes the layered water taking effect of the stoplog door by using the average temperature difference of the tail water temperature of the stoplog door and the tail water temperature of the stoplog door, thereby eliminating the influence of system errors and ensuring that the measured layered water taking effect of the stoplog door is more accurate.
When the prediction is carried out, a multiple regression analysis method is adopted to obtain a relational formula between related data and water taking effect, the operation is simple and convenient, the feasibility is strong, and the method can be applied to actual operation of engineering.
Drawings
FIG. 1 is a flow chart of a method for evaluating and predicting layered water intake effect of a stop log gate.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The stack-door layered water taking effect evaluation and prediction method is mainly applied to the water-electricity engineering stack-door layered water taking effect evaluation, prediction and optimal scheduling. The applied hydraulic and hydroelectric engineering needs to meet the following conditions: (1) constructing a laminated water taking facility of a stoplog door; (2) two or more tail water outlets; (3) The corresponding stoplog door of each tail water outlet can be controlled respectively. As shown in fig. 1, the method for evaluating and predicting the layered water intake effect of the stoplog gate specifically includes:
step 1, setting a test group and a comparison group according to the opening and closing states of the stop log door corresponding to at least two tail water ports of a hydropower station: before the test starts, the tail water outlet and the corresponding stoplog door which participate in the test are divided into a test group and a control group.
And 2, setting test working conditions according to the number of layers or the height of the stop log door.
Step 3, installing water temperature monitoring equipment in front of tail water and dams of a test group and a control group; and water temperature on-line monitoring devices are respectively arranged at tail water outlets of the test group and the control group to monitor the water temperature of the tail water, and the depth of the sensor is 0.5m under water. And installing a temperature chain near a water inlet in front of the dam or at a midrange, monitoring the vertical water temperature in front of the dam, and ensuring that the maximum depth of the sensor is greater than the depth of a bottom plate of the water inlet. Monitoring precision: the temperature of tail water is less than or equal to 0.1 ℃, the vertical temperature of water in front of the dam is less than or equal to 0.2 ℃, and the depth and the monitoring precision of the sensor can be set according to actual needs.
Step 4, carrying out water taking tests according to test working conditions, obtaining tail water temperatures of a test group and a control group, and obtaining related data, wherein the related data comprise: the water temperature difference between the water temperature of the top of the stoplog door and the water temperature of the bottom plate of the water inlet, the power generation flow and the like are as follows:
and setting the corresponding stoplog door of the test group at the layer number designated by the design working condition, wherein the corresponding stoplog door of the comparison group is not started. Starting from the time when the stop log door is dispatched to the designated position in each working condition test period, and stopping when the next working condition starts dispatching the stop log door. And during the test period of each working condition, the tail water temperature of the test group and the tail water temperature of the control group are compared and monitored, and during the test period, the stop log door scheduling is not carried out.
During the test, the data such as vertical water temperature in front of the dam, water level in front of the dam, warehouse-in flow, power generation flow of each unit and the like are synchronously collected. Flood discharge is avoided during the test period, and the drainage flow is discharged through the power generation tail water.
During the test, the generating flow of the unit corresponding to the tail water of the test group is similar to that of the unit corresponding to the tail water of the control group as much as possible, so that the accuracy of the comparison test result is ensured.
The duration of each working condition test is more than or equal to 24 hours. After the test of each working condition is completed, dispatching the test group stop log door to the next working condition, and continuing the test until the test of all working conditions is completed.
And 5, after all working conditions are completed, calculating the average temperature difference of the tail water temperatures of the test group and the control group in each test working condition, and taking the average temperature difference of the tail water temperatures as the laminated water taking effect of the stop log door under the working conditions. The calculation method comprises the following steps:
1) Removing tail water temperature monitoring data of 0.5-1 h at the beginning and the end of each working condition to eliminate the interference of the dispatching process of the stop-beam door on the water temperature, namely removing the beginning and the end of each working condition for 0.5-1 h at the actual monitoring time;
2) Setting the tail water temperature of test group in a certain working conditionFor t1, the tail water temperature of the control group is t2, the effective monitoring time of the working condition shares n groups of data, and the difference value between t1 and t2 in the n groups of data is t1 n -t2 n The average value of the difference values of t1 and t2 in the effective monitoring time of the working condition is the average temperature difference of the tail water temperatureWill->As the laminated water taking effect of the stop log door under the working condition. Namely:
and 6, taking the related data as independent variables, taking the tail water temperature difference at the same time as dependent variables, and performing multiple regression analysis to obtain a quantitative relation formula of the tail water temperature difference and the related data.
And (3) calculating parameters such as the height of the stoplog door, the top water head of the stoplog door (namely the distance between the top of the stoplog door and the water surface), the temperature difference between the top water temperature of the stoplog door and the water temperature of the water inlet bottom plate (for short, the temperature difference between the top and the bottom of the dam), the power generation flow and the like under all working conditions. And taking the parameters as independent variables, and taking the tail water temperature difference at the same moment as dependent variables, performing multiple regression analysis to obtain a quantitative relation empirical formula of one or more of the parameters of the water temperature difference of the tail water of the hydroelectric engineering, the height of the stop-beam door, the top water head of the stop-beam door, the temperature difference of the top and bottom of the dam, the power generation flow and the like.
And 7, predicting the water taking effect according to a quantitative relation formula. When the quantitative relation formula contains the temperature difference between the water temperature of the front stop-beam door top and the water temperature of the water inlet bottom plate, the predicted water temperature difference between the water temperature of the front stop-beam door top and the water temperature of the water inlet bottom plate is calculated by adopting the front vertical water temperature monitoring data or calculated by adopting a numerical simulation mode. When the numerical simulation method is adopted, a vertical one-dimensional or vertical two-dimensional numerical model of the vertical water temperature in front of the dam is established, then the vertical water temperature distribution in front of the dam is obtained according to the simulation result of the numerical model, and further the temperature difference between the top and the bottom of the dam is calculated.
The predicted laminated water taking effect of the stoplog gate can be applied to optimized dispatching of the stoplog gate, influence evaluation of the water discharge temperature and the like.
Examples
And 6 generating sets are arranged in a certain hydropower engineering, wherein the generating tail water of the 1# to 3# generating sets is discharged through a 1# tail water channel, and the generating tail water of the 4# to 6# generating sets is discharged through a 2# tail water channel. And each unit water inlet is provided with a stoplog door, the stoplog door leaves are divided into 3 layers, the first layer of height is 7m, the second layer of height and the third layer of height are 14m, and each unit stoplog door can be controlled respectively. The test procedure was as follows:
(1) Design test conditions
According to the number of layers and the height of the stoplog door, 3 groups of test working conditions are designed, and a 1# tail water channel and a 1# to 3# unit correspond to the stoplog door to serve as test groups, and a 2# tail water channel and a 4# to 6# unit correspond to the stoplog door to serve as comparison groups.
TABLE 1 design of test conditions
(2) Installation monitoring device
Before the test starts, the testers are respectively provided with a water temperature on-line monitoring device at tail water outlets of the No. 1 tail water channel and the No. 2 tail water channel, the tail water temperature is monitored, and the depth of the sensor is 0.5m; depending on the front dirt blocking float of the dam, a digital temperature chain is arranged in front of the dam and in the middle of the dam, the vertical water temperature in front of the dam is monitored, the depth of the sensor is 1-90 m, and the maximum depth 90m is greater than the depth of the bottom plate of the water inlet. The tail water temperature monitoring precision is 0.1 ℃. The monitoring precision of the vertical water temperature in front of the dam is 0.2 ℃. The water temperature sensor in front of the dam is arranged as follows: 1 sensor is arranged at intervals of 1m for the water depth of 1-20 m, and 1 sensor is arranged at intervals of 2m for the water depth of 22-90 m. The data acquisition frequency is: the tail water temperature data are collected 1 time every 15-30min, the vertical water temperature before the dam is collected every 1-2h, and the collection frequency of the embodiment is as follows: the tail water temperature data are acquired for 1 time every 30min, and the vertical water temperature in front of the dam is acquired for 1 hour.
(3) Performing field test
1) Before the test starts, the corresponding stopbeam gates of the No. 1 tail water channel and the No. 2 tail water channel are in a 3-layer starting state (7+2 multiplied by 14 m). And lifting all the stopcock doors corresponding to the No. 2 tail water channels, enabling the stopcock doors corresponding to the No. 1 tail water channels to be in a 3-layer starting state, and starting the working condition 1 test. During the test period, the tail water temperature of the test group and the control group is compared and monitored, and during the test period, no stop log door scheduling is carried out.
2) During the test, synchronously collecting data such as vertical water temperature in front of the dam, water level in front of the dam, warehouse-in flow, warehouse-out flow, power generation flow of each unit and the like. Flood discharge is avoided during the test period, and the drainage flow is discharged through the power generation tail water. During the test, the hydropower station makes the generating flow of the unit corresponding to the tail water of the test group and the generating flow of the unit corresponding to the tail water of the comparison group approximate to each other through scheduling as much as possible so as to ensure the accuracy of the comparison test result.
3) The duration of the condition 1 test is 112h. After the test of the working condition 1 is finished, the corresponding stoplog gate of the No. 1 tailrace is scheduled to 2 layers (2 multiplied by 14 m), the test of the working condition 2 is continued, the test duration of the working condition 2 is 64h, after the test of the working condition 2 is finished, the corresponding stoplog gate of the No. 1 tailrace is scheduled to 1 layer (14 m), the test of the working condition 3 is continued, the test duration of the working condition 3 is 64h, and after the test of the working condition 3 is finished, the field test is completely finished.
(4) Statistical calculation of laminated water intake effect of stop log door
After all working conditions are completed, the average temperature difference of the water temperatures of the No. 1 tail water and the No. 2 tail water in each working condition is counted, and the average temperature difference of the water temperatures of the tail water is used as a laminated water taking effect of the stop-beam door under the working conditions. The statistical method is as follows:
1) Removing tail water temperature monitoring data of 1h at the beginning and the end of each working condition to eliminate the interference of the dispatching process of the stop-beam door on the water temperature, namely, the effective monitoring time of the working condition 1, the working condition 2 and the working condition 3 is 110h, 62h and 62h respectively;
2) And if the water temperature of the No. 1 tail water is t1 and the water temperature of the No. 2 tail water is t2, the average value of the difference values of t1 and t2 in the effective monitoring time of each working condition is the average temperature difference of the tail water.
The results of each condition test during the test are shown in Table 2. According to the test result, the temperature difference of tail water temperature of working conditions 1,2 and 3 is 1.53 ℃, 0.78 ℃ and 0.57 ℃ respectively, namely the layered water taking effect of the stoplog doors of the hydropower station under the working conditions of 3 layers, 2 layers and 1 layers of stoplog doors is 1.53 ℃, 0.78 ℃ and 0.57 ℃ respectively.
Table 2 results of various operating conditions
(5) Laminated water taking effect prediction of stop log door
Parameters such as the height of the stoplog door, the top water head of the stoplog door (namely the distance between the top of the stoplog door and the water surface), the temperature difference between the top water temperature of the top of the stoplog door and the water temperature of a water inlet bottom plate (simply called the top-bottom temperature difference before the dam), the power generation flow and the like under each working condition are calculated in a statistics mode, the temperature difference of tail water at the same time is taken as a dependent variable, multiple regression analysis is carried out, and a quantitative relation empirical formula of one or more of the temperature difference of tail water of the hydroelectric engineering and the parameters such as the height of the stoplog door, the top water head of the stoplog door, the top-bottom temperature difference before the dam and the power generation flow is obtained, and the layered water taking effect of the stoplog door can be predicted through the empirical formula.
In this embodiment, the specific operation steps are as follows:
1) Preparing data: the data preparation works are as follows:
(1) and the height of the stop log door is the height of the stop log door started by the test group. In the embodiment, the heights of the stop-beam doors under the working conditions 1,2 and 3 are 35m, 28m and 14m respectively.
(2) The water head of the roof beam door, namely the distance between the roof beam door top and the water surface, is calculated by subtracting the elevation of the roof beam door top from the water level of the dam.
(3) The temperature difference between the water temperature of the top of the front stop log door and the water temperature of the bottom plate of the water inlet (for short, the temperature difference between the top and the bottom of the front stop log) is calculated by the following steps: in the monitoring data of vertical water temperature in front of dam during test, selecting water temperature t of the roof elevation of the stopbeam t Water temperature t at the same time as water inlet bottom plate elevation b The difference t between the two t -t b The temperature difference between the top and the bottom of the dam is obtained.
(4) The power generation flow, i.e. the total flow let down through the two tailrace channels.
2) And (3) data arrangement: the temperature difference of tail water and the data such as the height of a stop-beam door, the top water head of the stop-beam door, the temperature difference of the top and the bottom of the dam, the power generation flow and the like at the same moment are arranged into a group of data, and the monitoring data of each working condition of a test are arranged into a spreadsheet, wherein the table is as follows:
TABLE 3 temperature differential of tail water and related data analysis
3) Analysis data: statistical analysis software such as SPSS is used, the temperature difference of tail water and water is taken as a dependent variable (Y), and the height (X) of a stop log door is taken as a dependent variable (Y) 1 ) Roof head of stop beam door (X) 2 ) Temperature difference (X) between the top and bottom of dam 3 ) Flow rate of power generation (X) 4 ) And (5) taking the data as independent variables, and performing multiple regression analysis on the data in the electronic table. In the embodiment, through multiple regression analysis, two independent variables of the temperature difference between the top and the bottom of the dam and the height of the stop-beam gate pass the significance test and are reserved in a regression model; and the two independent variables of the roof head of the stoplog door and the power generation flow are not checked by significance and are removed from the regression model.
4) An empirical formula is formed: through the statistical analysis, the temperature difference (t) of the tail water temperature of the hydropower station is obtained td ) Temperature difference (t) between the dam front top and bottom sd ) The empirical formula between the stop-beam door height (H) is:
t td ＝0.622t sd +0.017H-0.021
5) And (3) predicting layered water taking effect of the stoplog door: and an empirical formula obtained by the test is adopted, so that the layered water taking effect prediction of the stop-beam door can be performed. For example, when the height of the water-electricity engineering stoplog door is 28m and the temperature difference between the top and the bottom is 0.7 ℃, according to an empirical formula, the layering water taking effect of the stoplog door under the working condition is about 0.89 ℃. And in the process of prediction, the temperature difference between the top and the bottom is calculated by adopting monitoring data of vertical water temperature in front of the dam.
The calculated laminated water taking effect of the stoplog gate can be applied to optimized dispatching of the stoplog gate, influence evaluation of the water discharge temperature and the like.
Claims (10)
1. The stack door layered water taking effect evaluation and prediction method is characterized by comprising the following steps of:
step 1, setting a test group and a comparison group according to the opening and closing states of a stop log door corresponding to at least two tail water ports of a hydropower station;
step 2, setting test working conditions according to the number of layers or the height of the stop-beam door;
step 3, installing water temperature monitoring equipment in front of tail water and dams of a test group and a control group;
step 4, carrying out water taking tests according to test working conditions, obtaining tail water temperatures of a test group and a control group, and obtaining related data, wherein the related data comprise: the water temperature difference between the water temperature of the top of the stoplog door and the water temperature of the bottom plate of the water inlet and the power generation flow before the dam is formed by the height of the stoplog door, the top water head of the stoplog door and the water temperature difference between the water temperature of the top of the stoplog door and the water temperature of the bottom plate of the water inlet;
step 5, calculating the average temperature difference of the tail water temperatures of the test group and the control group in each test working condition, and taking the average temperature difference of the tail water temperatures as the laminated water taking effect of the stop-beam door under the working condition;
step 6, taking the related data as independent variables, taking the tail water temperature difference at the same time as dependent variables, and performing multiple regression analysis to obtain a quantitative relation formula of the tail water temperature difference and the related data;
and 7, predicting the water taking effect according to a quantitative relation formula.
2. The method for evaluating and predicting the layered water intake effect of a stop log door according to claim 1, wherein the pre-dam water temperature monitoring device is a pre-dam vertical water temperature monitoring device.
3. The method for evaluating and predicting the layered water intake effect of a stop log door according to claim 2, wherein the vertical water temperature monitoring device in front of the dam is installed in a predetermined distance from a water inlet in front of the dam or at a midbody.
4. The method for evaluating and predicting layered water intake effect of stop log gate according to claim 3, wherein the tail water temperature monitoring device is set to a depth of 0.5m, the vertical water temperature monitoring device in front of the dam is set to a depth of 1-Nm, and N is larger than the depth of the water inlet bottom plate.
5. The method for evaluating and predicting the layered water intake effect of the stop log door according to claim 4, wherein the concrete layout mode of the vertical water temperature monitoring equipment in front of the dam is as follows: when N is less than or equal to 20m, 1 temperature sensor is arranged every 1 m; when N is more than 20m, 1 temperature sensor is arranged every 1m for the water depth of 1-20 m, and 1 temperature sensor is arranged every 2m for the water depth of 20-Nm.
6. The method for evaluating and predicting the layered water intake effect of the stop log gate according to claim 2, wherein the step 4 is specifically:
setting the corresponding stoplog door of the test group to the layer number designated by the design working condition, and enabling the corresponding stoplog door of the comparison group not to be started;
starting from the moment when the stop log door is dispatched to a designated position in each working condition test period, and stopping when the next working condition starts dispatching the stop log door;
during the test, the test group and the control group synchronously collect tail water temperature, vertical water temperature in front of the dam, water level in front of the dam and power generation flow of each unit;
flood discharge is avoided during the test period, and the discharging flow is discharged through the power generation tail water; the generating flow of the unit corresponding to the tail water of the test group and the generating flow of the unit corresponding to the tail water of the comparison group are in an error range;
and the duration of each working condition test is more than or equal to 24 hours, and after each working condition test is completed, the test group stop log door is scheduled to the next working condition to continue the test until all the working condition tests are completed.
7. The method for evaluating and predicting the layered water intake effect of the stop-beam gate according to claim 6, wherein the tail water temperature data is acquired 1 time every 15-30min, and the vertical water temperature before the dam is acquired every 1-2 h.
8. The method for evaluating and predicting the layered water intake effect of the stop-beam gate according to claim 1, wherein the step 5 further comprises preprocessing the water temperature monitoring data before calculating the average temperature difference of the tail water temperatures of the test group and the control group in each working condition.
9. The method for evaluating and predicting the layered water intake effect of the stop log gate according to claim 8, wherein the preprocessing is: deleting tail water temperature monitoring data of each period of time at the beginning and the end of the working condition; and calculating the average value of the tail water temperature difference values of the test group and the control group in the effective monitoring time.
10. The method for evaluating and predicting the layered water intake effect of the stoplog door according to any one of claims 1 to 9, wherein when the quantitative relation formula contains a temperature difference between the water temperature of the front stoplog door top and the water temperature of the water inlet bottom plate, the temperature difference between the water temperature of the front stoplog door top and the water temperature of the water inlet bottom plate is calculated by using the front vertical water temperature monitoring data or calculated by using a numerical simulation mode.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310883395.3A CN116975968A (en) | 2023-07-18 | 2023-07-18 | Method for evaluating and predicting laminated water taking effect of stoplog door |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310883395.3A CN116975968A (en) | 2023-07-18 | 2023-07-18 | Method for evaluating and predicting laminated water taking effect of stoplog door |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116975968A true CN116975968A (en) | 2023-10-31 |
Family
ID=88477691
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310883395.3A Pending CN116975968A (en) | 2023-07-18 | 2023-07-18 | Method for evaluating and predicting laminated water taking effect of stoplog door |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116975968A (en) |
-
2023
- 2023-07-18 CN CN202310883395.3A patent/CN116975968A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104792945B (en) | A kind of rockfill washes away analogue experiment installation and experimental data acquisition method | |
| CN113222296B (en) | Flood control scheduling method based on digital twinning | |
| CN101807045B (en) | Data-based urban sewage pumping station system modeling method | |
| CN105550943A (en) | Method for identifying abnormity of state parameters of wind turbine generator based on fuzzy comprehensive evaluation | |
| CN103886187A (en) | River channel water and sediment real-time prediction method based on data assimilation | |
| CN110849580B (en) | Laminated beam door water intake monitoring method based on far dam region vertical temperature chain | |
| CN112187932A (en) | Intelligent monitoring and early warning method for small and medium reservoir dam based on edge calculation | |
| CN116595327B (en) | Sluice deformation monitoring data preprocessing system and method | |
| CN111581828A (en) | Calculation method for water level flow relation under tidal river reach gate | |
| CN108088694B (en) | The field in-situ monitoring device and diagnostic method of scale farmland drip irrigation system performance | |
| CN115909662A (en) | Check dam flood control early warning method and system | |
| CN109902267B (en) | River channel safety discharge amount calculation method influenced by downstream lake jacking | |
| CN114861279A (en) | Method and system for testing temperature simulation consistency of hydraulic concrete structure | |
| CN113128098B (en) | Concrete dam singular value detection method and equipment based on DE-LOF | |
| CN116975968A (en) | Method for evaluating and predicting laminated water taking effect of stoplog door | |
| CN105303264A (en) | Flood forecasting method under influences of human activities | |
| CN104614144A (en) | Method for predicting soil vibration caused by flood discharge and energy dissipation | |
| CN210013197U (en) | Water temperature monitoring system with laminated beam door hydropower station | |
| CN115493659A (en) | Hydraulic engineering safety monitoring method and system | |
| CN112284682B (en) | Experimental device and method for simulating gully head falling acupoint development | |
| Gunawan et al. | Measuring and modeling flow structures in a small river | |
| Li et al. | Experimental study of overtopping on sea dikes and coastal flooding under the coupled processes of tides and waves | |
| CN103093113B (en) | A kind of concrete dam damage field harmfulness diagnostic method | |
| CN112267418A (en) | Novel method for calculating water inflow and outflow of tidal channel | |
| Ding et al. | Binomial-bivariate log-normal compound model and its application on probability estimation of extreme sea state |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |