CN110991850B - Reservoir flood control forecast scheduling risk determination method - Google Patents
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Abstract
A reservoir flood control forecast scheduling risk determination method belongs to the technical field of reservoir scheduling. The method comprises the steps of firstly, identifying and selecting risk factors in reservoir flood control forecast scheduling, and defining risk events according to scheduling targets; secondly, a joint probability density function of the risk factors is calculated; thirdly, solving a risk domain corresponding to the risk event; and finally, integrating the combined probability density function in a risk domain to calculate the risk of the risk event. The reservoir flood prevention forecast scheduling risk calculation method provided by the invention introduces the concept of the risk domain, and integrates the joint probability density function in the risk domain to obtain the design risk of reservoir forecast scheduling. The risk analysis and analysis method has the advantages of simplicity and convenience in calculation, higher precision and universality, and is suitable for the complex situation of risk analysis of multiple risk factors and combined events.
Description
Technical Field
The invention belongs to the technical field of reservoir dispatching and relates to a reservoir flood control forecast dispatching risk determination method.
Background
Under the influence of extreme climates and dramatic population growth, many countries in the world, particularly developing countries, suffer from flood disasters and coexistence of water resource shortages (Re m. Topics Geo natural catagraphs 2009 analyses, associations, locations j. Munich: munch reissuance Company, 2010.). With the development of society, the functions of hydraulic engineering systems are fully exerted by advanced technical levels, and the improvement of the utilization rate of flood Resources is an important measure for relieving the problem of Water resource shortage on the premise of ensuring flood control safety (Changnon S. Research activities for flowers to solvent pollution Failure [ J ]. Journal of Water Resources Planning and Management,1985,111 (1): 54-64.).
For the reservoir, the reservoir benefit is not fully exerted by the conventional flood control scheduling without considering the forecast information, and the forecast scheduling mode utilizing the forecast information is a key technology for improving the utilization rate of flood resources. Compared with a conventional scheduling mode, actual measurement information such as dam front water level and facing moment reservoir inflow rate is used as distinguishing indexes of encountered flood magnitude and corresponding discharge, and forecast information such as accumulated net rainfall of current production forecast and inflow rate of confluence forecast is added into a forecasting scheduling mode to be used as distinguishing indexes (Wang Bende, zhou Huicheng, wang Guoli, and the like). Because the forecast information has inevitable errors, and these errors may bring risks compared with the conventional scheduling mode of planning and design, it is necessary to perform risk analysis on the forecast scheduling mode. In order to take flood control safety and benefit into consideration, the forecasting and dispatching mode should improve the flood resource utilization rate on the premise of ensuring that the flood control risk of the original design is not increased.
Risk events in the reservoir scheduling process generally comprise the conditions that the highest water level of reservoir flood regulation exceeds a characteristic water level, the lower discharge flow of a reservoir and the downstream combined flow of the reservoir exceed the bearing capacity of a protected object, and the like (enjoying fresh flowers, wang Bende. Reservoir flood control forecast scheduling mode risk analysis based on different risk source combinations [ J ]. Chinese science: technical science, 2010,40 (10): 1140-1147.), and the reservoir scheduling target is to avoid each risk event as far as possible. However, as a decision maker for reservoir scheduling, various possible risk events need to be considered to make a decision with minimum risk loss. There is a synergistic relationship between these risk events and a competitive relationship (Ding W, zhang C, peng Y, et al. An analytical frame for flow Water consistency and acceptable risk [ J ]. Water Resources Research,2015,51 (6): 4702-4726.) only one occurrence and simultaneous occurrence of risk and hazard are significantly different, and an appropriate risk event should be selected, and then risk analysis is performed according to different combinations of risk events. There is therefore a need to propose a method to address the risk analysis problem of combined events.
In recent years, some new reservoir scheduling risk analysis methods are also proposed successively by related scholars. Yan B et al (Yan B, guo S, chen L.timing of reserve volume control operations with regulating in flow errors [ J ]. Stochastic environmental forecast and risk assessment,2014,28 (2): 359-368.) analyze the scheduling risk brought by the reservoir warehousing water forecast error based on the Stochastic differential equation, the method can calculate the risk at each moment in the flood forecast period, however, because of the complexity of the differential equation, the method uses the numerical calculation method of finite difference to solve the differential equation, so the error is brought inevitably; liu P et al (Liu P, lin K, wei X.A two-stage method of qualitative flow analysis for reservoir real-time operation using estimated-based hydraulic for turbines [ J ]. Storage environmental research and risk evaluation, 2015,29 (3): 803-813) divide the risk to be faced by the reservoir into two stages: the method is characterized in that the risks and the total risks of two stages are calculated respectively by combining the MC method in the forecast period and outside the forecast period of the collective flood forecast, the method provides rich risk calculation results for decision makers, and the method has the defect that the calculation accuracy and the calculation amount of the MC method are difficult to balance; zhang Yanping (Zhang Yanping. Reservoir flood limit water level dynamic control domain research based on flood classification and risk analysis [ D ] university of great chain of thought, 2012.) reservoir scheduling risks caused by uncertainty of forecasting net rain error and flood volume are analyzed based on a total probability formula. To date, none of the above methods provides a solution that combines high accuracy, small computation, and the ability to handle multiple risk factors and combination events in complex situations.
The invention provides a reservoir flood control forecast scheduling risk calculation method. The method introduces the concept of the risk domain, and integrates the combined probability density function in the risk domain to obtain the design risk of reservoir forecast scheduling. Compared with a total probability method of risk analysis and other traditional risk analysis methods, the risk analysis method provided by the invention has the advantages of simplicity and convenience in calculation, higher precision, and suitability for complex situations of risk analysis of multiple risk factors and combined events and universality. And by taking flood control scheduling of a large-volume water depot as an example, the method is applied to carry out example calculation, and the rationality of the method is verified.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a reservoir flood control forecast and scheduling risk determination method.
The technical scheme adopted by the invention is as follows:
a reservoir flood control forecast scheduling risk determination method comprises the steps of firstly, identifying and selecting risk factors in reservoir flood control forecast scheduling, and defining risk events according to scheduling targets; secondly, a joint probability density function of the risk factors is calculated; thirdly, calculating a risk domain corresponding to the risk event; and finally, integrating the combined probability density function in a risk domain to calculate the risk of the risk event. The calculation flow chart is shown in the attached figure 1.
Step 1: and identifying and selecting risk factors in the reservoir flood control forecast scheduling process and defining risk events.
The invention aims at the reservoir which takes the forecast clear rain as a judgment index in the flood control forecast scheduling rule, and the risk factors of the reservoir are the forecast clear rain error and the actual clear rain quantity. Selecting the super-characteristic water level of the highest water level in the reservoir dispatching process as a single risk event H aiming at reservoir flood control safety 1 Wherein the highest water level in the reservoir dispatching process is recorded as Z max Super characteristic water level is recorded
Selecting super-characteristic flow of maximum flow of downstream flood control section as single risk event H aiming at downstream flood control safety 2 Wherein, the maximum flow of the downstream flood control section is recorded as Q max The super characteristic flow is recorded as->
The expression of the risk event is shown in formulas (1) and (2).
According to a single risk event H 1 、H 2 The following two combined risk events are defined:
Wherein: combined Risk event H 3 Represents H 1 And H 2 At least one occurrence, combining risk events H 4 Represents H 1 And H 2 Simultaneously.
Step 2: a joint probability density function of the risk factors is calculated.
(1) A joint probability density function of the net rain forecast error and the actual net rain is calculated. In general, the net rain forecast error and the actual net rain amount are independent, and the joint probability density function of the two is as follows:
f E,Y (e,y)＝f E (e)×f Y (y) (5)
wherein: f. of E,Y A joint probability density function, f, for the net rain forecast error and the actual net rain E Probability density function for predicting net rain error, f Y And e is the forecast clear rain error, and y is the actual clear rain amount.
(2) And determining a probability density function of the flood forecast error by adopting a maximum entropy model, and determining a forecast error domain.
The invention utilizes the maximum entropy model to identify the distribution of the forecast net rain error, and the specific maximum entropy model is as follows:
f E (e)＝exp(λ 0 +λ 1 e+λ 2 e 2 +λ 3 e 3 +…) (6)
wherein: f. of E Probability density function for predicting net rain error, e is predicted net rain error, λ 0 、λ 1 、λ 2 、λ 3 As a function f E The parameter (c) of (c). Determining a threshold [ e ] for the predicted net rain error based on the prediction error probability density function min ,e max ]。
(3) A probability density function of the actual net rainfall is calculated.
a) In general, a probability density function of the design flood can be obtained according to design data, and generally obeys P-III distribution:
wherein: f. of W To design the probability density function of the flood, α, β, a 0 As a function f W (w) parameters.
b) The relationship between the flood output and the actual net rainfall can be obtained according to the drainage basin data:
Y＝kW (8)
wherein: y is the actual net rainfall in mm and W is the flood in 10 6 m 3 . k is a linear relation coefficient between the net rainfall and the flood, and can be calculated by equation (9).
Wherein: a is the area of the drainage basin and the unit is km 2 。
c) And (3) combining the formulas (7) and (8) to obtain a probability density function of the actual net rainfall:
wherein: f. of W As a function of the probability density of the flood, f Y As a function of the probability density of the actual net rainfall.
And 3, step 3: risk domains for single risk events and combined risk events are analyzed.
With H 1 For example, a method for calculating a risk domain for a single risk event is described, comprising the steps of:
(1) At forecast net rain error threshold [ e ] min ,e max ]And (4) uniformly sampling.
(2) Selecting a design frequency p, and finding out a design net rain process (corresponding to the actual net rain total y) and a design flood process with corresponding design frequency from design data; and (2) selecting a total rain forecasting error e from the rain forecasting error samples determined in the step (1), and distributing the error to the designed rain forecasting process to obtain the rain forecasting process. The specific allocation rule takes into account the most unfavorable case: and distributing the error to a time period corresponding to the main peak flood in the design net rain process, and distributing before the drainage basin is not full. The design frequency p includes 5%,2%,1%,0.1% and 0.01%.
(3) Taking the forecast clear rain process and the corresponding designed flood process as input data, and performing flood regulation calculation to obtain the maximum flood regulation water level Z max 。
(4) Changing the input design frequency p and the forecast clear rain error e, repeating the steps (2) and (3) to obtain different e-y-Z max Combining, plotting the data points on the coordinate axes (e, y, z)), and recording as a curved surface S 1 。
(5) Drawing a horizontal plane S 2 ：
S 2 And S 1 The projection of the intersection line on the horizontal plane is the isoline L 1 ：e～y
Contour line L 1 Is the highest water level over-characteristic water level of the reservoir>
The corresponding risk domain omega.
In the same way, risk event H can be obtained 2 The risk domain of the combined event can be obtained by performing intersection or union operation according to the risk domain of the single event.
And 4, step 4: and integrating the combined probability density function in a risk domain to obtain a risk value.
Integrating the joint probability density function in the risk domain to obtain a risk value according to the following formula:
wherein: h represents any risk event, P (H) represents the risk value of the risk event H, and Ω is the risk domain.
Compared with the prior art, the invention has the following advantages and effects:
the reservoir flood prevention forecast scheduling risk calculation method provided by the invention introduces the concept of the risk domain, and integrates the joint probability density function in the risk domain to obtain the design risk of reservoir forecast scheduling. The risk analysis and analysis method has the advantages of being simple and convenient to calculate, high in precision and suitable for complex conditions and universality of risk analysis of multiple risk factors and combined events.
Drawings
FIG. 1 is a schematic flow chart of a reservoir flood control forecast scheduling risk calculation method;
FIG. 2 is a flow chart of the steps for analyzing the risk area corresponding to the highest water level of the reservoir exceeding the characteristic water level in a single risk event;
FIG. 3 is a combined risk event risk domain schematic; wherein, the graph (a) is a combined risk event H 3 The risk domain of (a), panel (b) is a combined risk event H 4 A risk domain map of (a);
FIG. 4 is a graph of the combined probability density function result of predicted net rain error and actual net rain;
FIG. 5 is a graph of the results of a risk domain corresponding to a reservoir maximum water level exceeding 136.32m in a single risk event; wherein, the diagram (a) is the highest water level Z max -accumulated net rain Y-error relationship E, plot (b) is a contour plot with a maximum water level of 136.32 m;
fig. 6 is a combined risk event risk domain result graph.
Detailed Description
The invention takes a large-room reservoir as an example, and the specific implementation mode is described in detail by combining the technical scheme and the attached drawings, and the method specifically comprises the following steps:
step 1: and identifying and selecting risk factors in the reservoir flood control forecast scheduling process and defining risk events.
The invention selects the forecast clear rain error and the actual clear rain amount as risk factors according to the forecast information adopted in the flood control forecast scheduling rule. The regional flood combination condition is considered when flood regulation calculation is carried out, and the method takes the same frequency of a control area of a large-volume house reservoir and a control area of a sinking section as an example for research. The flood control planning design result of the large-volume house reservoir is that the maximum water level obtained by regulating the design flood of each frequency by adopting a conventional scheduling mode (the flood limit water level is 126.4 m)
The results are shown in table 1, and the water level is used as a limiting condition of the highest water level of each frequency in the forecast scheduling rule studied by the invention.
TABLE 1 highest water level of flood of each design frequency under conventional scheduling mode of large-scale houses and water reservoir
(1) Single risk event
Selecting the highest water level (recorded as Z) in the reservoir dispatching process aiming at the flood control safety of the reservoir max ) Super characteristic water level (note as
) As a single risk event H 1 Wherein the characteristic water level->
I.e. the maximum water level corresponding to the 5 design frequencies in table 1>
Selecting the maximum flow (denoted as Q) of the flood control section of the downstream Shenyang with respect to the flood control safety of the section of the downstream Shenyang max ) Super characteristic flow (marked as +>
) As a single risk event H 2 Wherein the characteristic flow->
For safe discharge 6260m 3 /s。
Thus for a single risk event:
H 2 :Q max ＞6260m 3 /s (13)
the sinking section flood control standard is 300 years, so the risk event analysis is combined to design the frequency P 0 0.33% is exemplified. Design frequency P 0 At 0.33%, the downstream safety discharge of the large-volume aqueous humor reservoir is 6260m 3 S, maximum flood level of
The combined risk events are therefore:
H 3 :Z max 136.32m or Q max ＞6260m 3 /s (14)
H 4 :Z max 136.32m and Q max ＞6260m 3 /s (15)
Step 2: a joint probability density function of the risk factors is calculated.
A joint probability density function of the net rain forecast error and the actual net rain is calculated. The net rain forecast error and actual net rain are generally independent (Zhou R, lu D, wang B, et al. Risk analysis of rain responding rain flow limited water level base on Bayes the item and flow for example error [ J ]. Transformations of the Chinese Society of Agricultural Engineering, 2016.) and their joint probability density function is shown in equation (5).
The parameters in the formula (6) are estimated by curve fitting by using the historical forecast error data of the reservoir, and the results are shown in table 2:
TABLE 2 forecast clear rain error density function f E (e) Parameter (d) of
Error density function f according to forecast net rain E (e) And analyzing to obtain a threshold value of the forecast net rain error [ -48,48]mm。
Fitting the design flood according to flood design data to obtain a probability density function f of the design flood W (w) parameters shown in Table 3.
Table 3 design flood density function f W (w) related parameters
Large-daily-use-house reservoir controlled watershed area 5437km 2 If k =0.174 is calculated according to equation (9), the actual net rain is always clearDensity function f of quantity Y (y) is
f Y (y)＝0.0041×y 0.384 ×exp(-0.0172y) (16)
Finally, a joint probability density function of the net rain forecast error and the actual net rain is obtained, as shown in equation (17) and FIG. 4
f E,Y (e,y)＝0.0041×y 0.384 ×exp(-3.645-0.017e-0.002e 2 -2×10 -5 e 3 -0.0172y) (17)
And 3, step 3: risk domains for single risk events and combined risk events are analyzed.
With H 1 For example, single Risk event H 1 The risk domain analysis result is shown in fig. 5, the risk domain calculation flow chart is shown in fig. 2, and the calculation process is as follows:
(1) Sampling was performed in steps of 2mm within the threshold of the forecast net rain error [ -48,48] mm, for a total of 49 samples.
(2) Selecting one design frequency p from the 5 design frequencies (0.01%, 0.1%,0.33%,1%, 2%) in table 1, and finding out the design clear rain process (corresponding to the actual clear rain total y) and the design flood process with corresponding frequencies from the flood design data; selecting a total error e of the forecasted clear rain from the samples of the errors of the forecast clear rain in the step (1), and distributing the error to the designed clear rain process to obtain the process of the forecast clear rain.
(3) Taking the forecast clear rain process and the corresponding designed flood process as input data, and performing flood regulation calculation to obtain the maximum flood regulation water level Z max 。
(4) Changing the input design frequency p and the forecast clear rain error e, repeating the steps (2) and (3) to obtain different e-y-Z max Combined, as curved surface S 1 。
(5) Drawing a horizontal plane S 2 ：Z max ＝136.32m，S 2 And S 1 The projection of the intersection line on the horizontal plane is the isoline L 1 ：e～y(Z max ＝136.32m)。
In the same way, risk event H can be obtained 2 The risk domains of (2) can be operated by intersection or union set operation according to the risk domains of the single eventObtaining a risk domain of the combined event, wherein Ω in FIG. 3 (a) 3 To combine risk events H 3 Corresponding risk domain, Ω in FIG. 3 (b) 4 To combine risk events H 4 The corresponding risk domain.
L 1 、L 2 Respectively when the design frequency is 0.33%, the highest water level Z max =136.32m and downstream peak flow Q max ＝6260m 3 The iso-line of/s as shown in figure 6. L is 1 At the upper side is event H 1 (namely the reservoir water level exceeds 300 years-water level 136.32 m); l is 2 At the upper side is event H 2 (i.e. the downstream flow rate exceeds 30 years and the safe discharge amount is 6260m 3 /s) corresponding risk domain; due to L 1 Is completely at L 2 So as to combine the events H 3 Risk domain and H 2 Same, H 4 Risk domain and H 1 The same is true.
And 4, step 4: and integrating the combined probability density function in a risk domain to obtain a risk value.
And substituting the calculated joint probability density function and the risk domain into a formula (18) to calculate the risks of the single risk event and the combined risk event.
The risk calculation for a single event is as follows:
TABLE 4 Risk of Single Risk event
The combined risk event calculation is as follows:
table 5 risks of Combined Risk events (%)
The above-mentioned embodiments only express the embodiments of the present invention, but not should be understood as the limitation of the scope of the invention patent, it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the concept of the present invention, and these all fall into the protection scope of the present invention.
Claims (3)
1. A reservoir flood control forecast scheduling risk determination method is characterized by comprising the following steps:
step 1: identifying and selecting risk factors in a reservoir flood control forecast scheduling process and defining risk events;
aiming at the reservoir with forecast clear rain as a judgment index in the flood control forecast scheduling rule, the risk factors are forecast clear rain error and actual clear rain amount; selecting the super-characteristic water level of the highest water level in the reservoir dispatching process as a single risk event H aiming at reservoir flood control safety 1 Wherein the highest water level in the reservoir dispatching process is recorded as Z max Super characteristic water level is recorded
Selecting the super-characteristic flow of the maximum flow of the downstream flood control section as a single risk event H aiming at the downstream flood control safety 2 Wherein, the maximum flow of the downstream flood control section is recorded as Q max The super characteristic flow is recorded as->
The expression of the risk event is shown as formulas (1) and (2);
according to a single risk event H 1 、H 2 The following two combined risk events are defined:
Wherein: combined Risk event H 3 Represents H 1 And H 2 At least one occurrence, combined risk event H 4 Represents H 1 And H 2 Simultaneously;
and 2, step: calculating a joint probability density function of the risk factors;
(1) Calculating a joint probability density function of the net rain forecast error and the actual net rainfall; the joint probability density function for both net rain forecast error and actual net rainfall is:
f E,Y (e,y)＝f E (e)×f Y (y) (5)
wherein: f. of E,Y Combined probability density function for net rain forecast error and actual net rain amount, f E Probability density function for predicting net rain error, f Y The probability density function of the actual net rainfall is obtained, e is the forecast net rainfall error, and y is the actual net rainfall amount;
(2) Determining a probability density function of a flood forecast error by adopting a maximum entropy model, and determining a forecast error domain;
the distribution of the forecast net rain error is identified by using a maximum entropy model as follows:
f E (e)＝exp(λ 0 +λ 1 e+λ 2 e 2 +λ 3 e 3 +…) (6)
wherein: f. of E Probability density function for predicting net rain errorNumber, e is the predicted clear rain error, λ 0 、λ 1 、λ 2 、λ 3 As a function f E The parameters of (1);
determining a threshold [ e ] for the predicted net rain error based on the prediction error probability density function min ,e max ]；
(3) Calculating a probability density function of actual net rainfall:
wherein: f. of W As a function of the probability density of the flood, f Y K is a linear relation coefficient between the net rainfall and the flood, and is a probability density function of the actual net rainfall;
and step 3: analyzing risk domains for single and combined risk events;
with H 1 For example, a method for calculating a risk domain for a single risk event is described, comprising the steps of:
(1) At forecast net rain error threshold [ e ] min ,e max ]Uniformly sampling;
(2) Selecting a design frequency p, and finding out a design clear rain process and a design flood process of corresponding design frequency from design data; selecting a total forecast clear rain error e from the samples of the errors of the forecast clear rain determined in the step (1), and distributing the error to the design clear rain process to obtain the process of the forecast clear rain; the specific allocation rule takes into account the most unfavorable case: distributing the error to a time period corresponding to the main peak flood in the design net rain process, and distributing before the drainage basin is not fully stored;
(3) Taking the forecast clear rain process and the corresponding designed flood process as input data, and performing flood regulation calculation to obtain the maximum flood regulation water level Z max ；
(4) Changing the input design frequency p and the forecast clear rain error e, repeating the steps (2) and (3) to obtain different e-y-Z max Combining, plotting the data points on the coordinate axes (e, y, z)), and recording as a curved surface S 1 ；
(5) Drawing a horizontal plane S 2 ：
S 2 And S 1 The projection of the intersection line on the horizontal plane is the isoline L 1 : e to y; contour line L 1 Is the highest water level over-characteristic water level of the reservoir>
A corresponding risk domain Ω;
similarly, a risk event H can be obtained 2 The risk domain of the combined event can be obtained by performing intersection or union operation according to the risk domain of the single event;
and 4, step 4: integrating the combined probability density function in a risk domain to obtain a risk value;
integrating the joint probability density function in the risk domain to obtain a risk value according to the following formula:
wherein: h represents any risk event, P (H) represents the risk value of the risk event H, and omega is the risk domain.
2. The method for determining the risk of dispatching for flood prevention of reservoir according to claim 1, wherein the probability density function for calculating the actual net rainfall in step 2 (3) is as follows:
a) Obtaining a probability density function of the design flood according to the design data, wherein the probability density function generally obeys P-III distribution:
wherein: f. of W To design the probability density function of the flood, α, β, a 0 As a function f W (w) a parameter;
b) Obtaining the relation between the flood output and the actual net rainfall according to the drainage basin data:
Y＝kW (10)
wherein: y is actual net rainfall in mm, W is flood volume in 10 6 m 3 (ii) a k is a linear relation coefficient between net rainfall and flood, and can be calculated by the formula (9);
wherein: a is the area of the drainage basin and the unit is km 2 ；
c) And (3) combining the formulas (7) and (8) to obtain a probability density function of the actual net rainfall:
wherein: f. of W As a function of the probability density of the flood, f Y As a function of the probability density of the actual net rainfall.
3. The method for determining risk of forecasting and dispatching flood in reservoir according to claim 1 or 2, wherein the design frequency p in step (2) in step 3 is 5%,2%,1%,0.1%,0.01%.
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| CN107992989A (en) * | 2017-11-03 | 2018-05-04 | 河海大学 | A kind of multi-reservoir utilization of flood resources stores in advance lets out Application of risk decision method in advance |
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