CN107563637B - Power station power generation scheduling near-boundary operation panoramic fuzzy risk analysis method - Google Patents
Power station power generation scheduling near-boundary operation panoramic fuzzy risk analysis method Download PDFInfo
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Abstract
The invention discloses a hydropower station power generation dispatching near-boundary operation panoramic fuzzy risk analysis method, which comprises the following steps: acquiring forecast runoff and measured runoff data of a hydropower station, grading the runoff, and counting a forecast error fuzzy membership function of each runoff grade by using runoff forecast error data; determining the near-boundary operation range of the hydropower station according to the daily operation allowable water level variation amplitude of the hydropower station; obtaining an optimal power generation dispatching scheme according to the warehousing runoff process, the dispatching initial water level and the final water level; obtaining a credibility value under each combination of the initial water level and the final water level of the dispatching period according to the forecasting error fuzzy membership function, the initial water level and the final water level of the dispatching period and the optimal power generation dispatching scheme of the N runoff levels; and obtaining a comprehensive risk value of the hydropower station with water abandon or insufficient output according to the credibility value. The method comprehensively and effectively depicts the water abandoning or undermining risks caused by runoff forecasting errors in short-term power generation dispatching of the hydropower station.
Description
Technical Field
The invention belongs to the field of hydropower station energy optimized operation and power system power generation optimized scheduling, and particularly relates to a near-boundary operation panoramic fuzzy risk analysis method for hydropower station power generation scheduling.
Background
In short-term scheduling of a hydropower station, a power generation plan is an important basis for daily production and operation of the hydropower station, time inconsistency exists between planning and implementation of the power generation plan, and when the power generation plan in the next scheduling period is planned by adopting forecast information, the planned power generation plan is often inconsistent with actual incoming flow due to uncertainty of the forecast. Generally, the influence of the deviation can be ignored due to the regulation effect of the reservoir, but when the reservoir runs near the boundary (close to a normal water storage level or a dead water level), the adjustable storage capacity of the reservoir is greatly reduced, and water abandon or insufficient output can be generated. Therefore, risk analysis of short-term power generation scheduling near-boundary operation of the hydropower station is carried out based on the runoff forecasting uncertainty, water abandonment or undergeneration risks of the hydropower station under different near-boundary operation conditions are quantified, and scientific basis and decision support can be provided for power generation planning based on runoff forecasting in actual production.
The near-boundary operation and corresponding control scheduling of the hydropower station belong to the category of risk scheduling, and in the hydropower station power generation scheduling risk analysis based on runoff prediction, the runoff prediction error is the most important one of numerous risk factors. At present, quite abundant results have been obtained in research in this respect, but research is based on random characteristics of errors, and research methods thereof are mainly risk analysis methods based on probability theory and mathematical statistics, such as a typical probability distribution function calculation method, a risk rate calculation method based on bayesian theorem, a probability combination method, and the like, while power generation scheduling risk analysis results based on the ambiguity of prediction errors are rare. In fact, due to the complexity of the objective world and the constant variation caused by the perpetual motion, when people adopt a stochastic method to deal with stochastic phenomena, the studied phenomena are not inherent or stochastic in nature, and the phenomena have a more general fuzzy uncertainty besides randomness. As is well known, the hydrologic prediction model is influenced by input uncertainty, self-structure and parameter uncertainty and a plurality of artificial uncertainty factors, is high in complexity and difficult to describe accurately, and therefore hydrologic prediction errors are random and accompanied by great ambiguity. Therefore, only the random uncertainty research of the hydrologic prediction error is carried out, the uncertainty of the prediction error cannot be accurately expressed, and the water abandon or undergeneration risk brought by the prediction error in the short-term power generation scheduling of the hydropower station cannot be comprehensively depicted.
Therefore, the technical problems that uncertainty of the runoff forecasting error cannot be accurately described, and ambiguity of the runoff forecasting error cannot be effectively expressed in the hydropower station short-term power generation scheduling risk analysis, so that water abandon or undergeneration risks caused by the runoff forecasting error in the short-term power generation scheduling near-boundary operation of the hydropower station cannot be comprehensively described in the prior art are solved.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides a hydropower station power generation dispatching near-boundary operation panoramic fuzzy risk analysis method, so that the technical problems that uncertainty of a runoff forecasting error cannot be accurately described, the ambiguity of the runoff forecasting error cannot be effectively expressed in hydropower station short-term power generation dispatching risk analysis, and water abandon or underdeveloped risk caused by the runoff forecasting error in the hydropower station short-term power generation dispatching near-boundary operation cannot be comprehensively described in the prior art are solved.
In order to achieve the aim, the invention provides a power station power generation scheduling near-boundary operation panoramic fuzzy risk analysis method, which comprises the following steps:
the method comprises the steps of (1) obtaining actual measurement runoff data, forecast runoff data, runoff forecast error data and daily operation allowable water level variation amplitude of the hydropower station, grading the actual measurement runoff data to obtain N runoff grades, and counting a forecast error fuzzy membership function of each runoff grade by using the runoff forecast error data; determining the near-boundary operation range of the hydropower station according to the daily operation allowable water level variation amplitude of the hydropower station;
step (2) obtaining warehousing runoff processes corresponding to each runoff grade, dispersing water levels in a near-boundary operation range of the hydropower station to obtain M scheduling period initial water levels and M scheduling period end water levels, and combining the M scheduling period initial water levels and the M scheduling period end water levels to obtain M scheduling period end water levels2Combining the initial water level and the final water level of each dispatching period according to N warehousing runoff processes and M2Combining the initial water level and the final water level of each scheduling period to obtain N M2An optimal power generation scheduling scheme of each hydropower station;
step (3) according to the forecast runoff data of the hydropower station, grading the forecast runoff data to obtain N runoff levels, and according to the forecast error fuzzy membership function and M of the N runoff levels2The combination of the initial and final water levels of each scheduling period, N M2Obtaining M according to the optimal power generation scheduling scheme of each hydropower station2A credibility value under each combination of the scheduling initial water level and the final water level in each combination of the scheduling initial water level and the final water level;
step (4) according to M2And obtaining the credibility value of each combination of the dispatching initial water level and the final water level in each combination of the dispatching initial water level and the final water level to obtain the comprehensive risk value of the hydropower station with water abandon or insufficient output.
Further, the fuzzy membership function of the prediction error is described as: triangular distribution, trapezoidal distribution, or cauchy distribution.
Further, the step (3) comprises the following steps:
(3-1) grading the forecast runoff data according to the forecast runoff data of the hydropower station to obtain N runoff grades;
(3-2) obtaining R fuzzy errors of each runoff grade by using the forecast error fuzzy membership function of each runoff grade until obtaining N x R fuzzy errors of N runoff grades;
(3-3) obtaining N R runoff processes considering forecast errors according to the N runoff levels and corresponding fuzzy errors, and executing an optimal power generation scheduling scheme of the hydropower station for the N R runoff processes and the M scheduling initial water levels to obtain M2A credibility value under each of the scheduling onset and end level combinations.
Further, the specific implementation manner of step (4) is as follows:
according to M2Obtaining the credibility value under each combination of the dispatching initial water level and the final water level in each combination of the dispatching initial water level and the final water level to obtain a curve of the credibility value changing along with the runoff grade, wherein the area enclosed by the curve and the coordinate axis represents the risk of water abandonment or insufficient output of the hydropower station under a certain combination of the dispatching initial water level and the final water level, and the credibility value is obtained according to the requirement of the reliability valueM2And (3) obtaining a comprehensive risk value of the hydropower station with water abandon or insufficient output under the future panoramic condition by a curve of the credibility value of the combination of the initial water level and the final water level of each dispatching period along with the change of the forecast runoff volume level.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
by introducing the credibility value, the method realizes the near-boundary operation fuzzy risk analysis of the short-term power generation dispatching of the hydropower station considering the runoff forecasting error ambiguity, compared with the traditional power generation dispatching risk analysis of the hydropower station, the method provided by the invention is based on the fact that the runoff forecasting error is more universal fuzzy uncertainty, and can perfectly express the uncertainty of the runoff forecasting error in the development, thereby comprehensively and effectively depicting the water abandonment or undergeneration risk brought by the runoff forecasting error in the short-term power generation dispatching of the hydropower station, and the application prospect is wide.
Drawings
Fig. 1 is a flowchart of a method for analyzing risk of a power generation scheduling near-boundary operation panorama fuzzy of a hydropower station according to an embodiment of the present invention;
FIG. 2 is a graph of the incoming flow class distribution and corresponding empirical frequency for a West hydropower station provided in example 1 of the present invention;
FIG. 3 is a fuzzy membership function of runoff forecasting errors at different inflow frequencies according to embodiment 1 of the present invention;
FIG. 4 is a panoramic fuzzy risk space for a hydropower station operating near a high water level boundary provided in embodiment 1 of the present invention;
fig. 5 is a panoramic fuzzy risk space for operation of a hydropower station near a low water level boundary provided in embodiment 1 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, a near-boundary operation panoramic fuzzy risk analysis method for hydropower station power generation scheduling includes:
(1) acquiring actual measurement runoff data, forecast runoff data, runoff forecast error data and daily operation allowable water level variation amplitude of the hydropower station, grading the actual measurement runoff data to obtain N runoff levels, and counting a forecast error fuzzy membership function of each runoff level by using the runoff forecast error data; determining the near-boundary operation range of the hydropower station according to the daily operation allowable water level variation amplitude of the hydropower station;
(2) obtaining a warehousing runoff process corresponding to each runoff grade, dispersing water levels in a near-boundary operation range of the hydropower station to obtain M scheduling period initial water levels and M scheduling period end water levels, and combining the M scheduling period initial water levels and the M scheduling period end water levels to obtain M2Combining the initial water level and the final water level of each dispatching period according to N warehousing runoff processes and M2Combining the initial water level and the final water level of each scheduling period to obtain N M2An optimal power generation scheduling scheme of each hydropower station;
(3) classifying the forecast runoff data according to the forecast runoff data of the hydropower station to obtain N runoff levels, and obtaining a fuzzy membership function and M according to forecast errors of the N runoff levels2The combination of the initial and final water levels of each scheduling period, N M2Obtaining M according to the optimal power generation scheduling scheme of each hydropower station2A credibility value under each combination of the scheduling initial water level and the final water level in each combination of the scheduling initial water level and the final water level;
(4) according to M2And obtaining the credibility value of each combination of the dispatching initial water level and the final water level in each combination of the dispatching initial water level and the final water level to obtain the comprehensive risk value of the hydropower station with water abandon or insufficient output.
Preferably, in the embodiment of the present invention, the fuzzy membership function of the prediction error is described as follows: triangular distribution, trapezoidal distribution, or cauchy distribution.
Wherein when the prediction error fuzzy membership function is described as triangular distribution, the membership of the prediction error fuzzy variable ξ obeys triangular distribution,
assuming that s and n are the lower and upper limits of the fuzzy number of prediction errors, and m is the most probable value, the triple (s, m, n) is used to represent the fuzzy variable ξ.
When the prediction error fuzzy membership function is described as Cauchy distribution, the membership of the prediction error fuzzy variable ξ obeys the Cauchy distribution, and the prediction error fuzzy membership function μ () may be expressed as:
wherein the prediction error fuzzy number represents a specific value of the prediction error fuzzy variable ξ, Ew+、Ew-Respectively representing the statistical average values of the positive error and the negative error; σ is a weight, typically taken to be 2.333.
Preferably, in the embodiment of the present invention, step (3) includes:
(3-1) grading the forecast runoff data according to the forecast runoff data of the hydropower station to obtain N runoff grades;
(3-2) obtaining R fuzzy errors of each runoff grade by using the forecast error fuzzy membership function of each runoff grade until obtaining N x R fuzzy errors of N runoff grades;
(3-3) obtaining N R runoff processes considering forecast errors according to the N runoff levels and corresponding fuzzy errors, and executing an optimal power generation scheduling scheme of the hydropower station for the N R runoff processes and the M scheduling initial water levels to obtain M2A credibility value under each of the scheduling onset and end level combinations.
Preferably, in the embodiment of the present invention, the specific implementation manner of step (4) is as follows:
according to M2Water in the beginning of dispatching periodObtaining a curve of which the credibility value changes along with the change of runoff grade under the condition of each scheduling initial water level and final water level combination in the water level and final water level combination, wherein the area enclosed by the curve and a coordinate axis represents the risk of water abandonment or insufficient output of a hydropower station under a certain scheduling initial water level and final water level combination, and the M is used for calculating the credibility value of each scheduling initial water level and final water level combination2And (3) obtaining a comprehensive risk value of the hydropower station with water abandon or insufficient output under the future panoramic condition by a curve of the credibility value of the combination of the initial water level and the final water level of each dispatching period along with the change of the forecast runoff volume level.
Example 1
The method takes the Jinxi hydropower station of the Yangtze river basin of China as an example, takes the actual flow of long-series actual measurement, forecast runoff data and power station power generation planning and execution as the basis, calculates the short-term power generation scheduling near-boundary operation risk of the hydropower station by the provided panoramic fuzzy risk analysis method, and analyzes and refines the result to show the effect achieved by the method.
The Yashujiang is the first major tributary of the Jinshajiang, and 22-grade power stations are planned and constructed by dry flows, the hydropower development at the downstream of the Yashujiang is basically completed at present, and five established hydropower stations (Jinxi, Jindong, official places, second beaches and tung woods) are put into operation, wherein the Jinxi power station has annual regulation performance, is a leading power station at the downstream step of the Yashujiang, and the dispatching operation level directly determines the overall power generation benefit of the downstream step. Therefore, the Jinxi power station is selected as a research object in the invention. The normal impoundment level and the dead water level of the plant are 1880m and 1800m, respectively. The steps of embodiment 1 of the invention are as follows:
the method comprises the following steps: and (4) runoff grading and forecasting error uncertainty analysis. Because incoming flows with different frequencies have different error distributions, before carrying out runoff forecasting error ambiguity analysis, the incoming flows are classified on the basis of long series actual measurement and forecasting incoming flow data, the empirical frequencies of the incoming flows with different magnitudes are counted, the forecasting error series are calculated, and the forecasting error fuzzy membership function corresponding to each incoming flow frequency is calculated.
Step two: a near boundary range is determined. From the foregoing, the normal water level and the dead water level of the power station in the west and the west are 1880m and 1800m respectively, and the daily variation of the water level cannot exceed 1.5m according to the actual requirement of the short-term scheduling operation of the power station, so in the risk analysis of the near-boundary operation of the short-term power generation scheduling of the power station, the near-boundary range can be defined as [1878.5, 1880] and [1800, 1801.5], wherein the former is the boundary range when the power station operates at the near high water level, and the latter is the boundary range when the power station operates at the near low water level.
And step three, water level dispersion and combination in the near-boundary range, thinning and dispersing the water level according to the near-boundary range determined in the step two to reflect all possible near-boundary water level combination conditions as much as possible, and performing dispersion and combination on the water level in the near-boundary range by taking 0.05m as a step length, so that the total number of 31 × 31-961 scheduling period initial and final water level combinations is realized.
Step four: according to the panoramic risk analysis method and the implementation process thereof, for each water level combination, the corresponding comprehensive risk (water abandoning or undermining) can be obtained through fuzzy simulation calculation. However, in the fuzzy simulation calculation, all possible incoming water frequencies and different forecast errors thereof need to be considered in the future.
The results after the implementation of example 1 of the invention are as follows:
(1) prediction error analysis result
Through the actual measurement of runoff data, the maximum runoff of the Jinxi hydropower station is about 5500m3S, minimum runoff of about 100m3S, therefore in the example, [0, 5600m3/s]200m for incoming flow interval3The actual incoming flow is graded in discrete steps and the empirical frequency is counted, the result is shown in fig. 2.
For incoming flows with different frequencies, the error distribution rule of the incoming flows can be obtained through the statistics of the difference value of the actual measurement runoff and the prediction runoff, and the membership degree relation of different prediction errors can be more accurately reflected by Cauchy distribution compared with other membership degree functions through actual calculation. Therefore, in the embodiment, the cauchy distribution is used as a fuzzy membership function form of the runoff forecasting error. The final prediction error fuzzy membership function corresponding to different incoming flow frequencies is shown in fig. 3 (taking part of incoming flow frequencies as an example).
(2) Near high water run-time panorama blur risk
By the panoramic fuzzy analysis method provided by the invention, the water abandoning risk of the short-term power generation dispatching near-boundary operation of the Jinxi hydropower station is analyzed, and the obtained panoramic fuzzy risk three-dimensional stereogram of the hydropower station during the near-high water level operation is shown as an attached figure 4.
As can be seen from fig. 4, in the power generation planning, when the initial water level is high, the possibility of water abandonment of the power station is high, and particularly when the initial water level is close to the normal water storage level 1880m, there is a high risk that the closer the initial water level is to the normal water storage level, the smaller the adjustable storage capacity available in the reservoir scheduling period is, and when the forecast water is small and the actual water is large, the water abandonment occurs. In addition, as can be seen from fig. 4, the power station has a high risk zone of water abandonment, as shown in the right area of fig. 4. In other cases the risk of water abandonment of the plant is almost zero, as in the left-hand area of fig. 4, and the plant should therefore be located as far as possible in these areas when operating at near high water levels.
Comprehensively, when the power station in the Jinxi province runs at a boundary of a near high water level, the power generation plan is compiled to avoid the condition that the initial water level is high, particularly the condition that the power station is close to a normal water storage level; on the other hand, the banded risk zones shown in fig. 4 are to be avoided as much as possible.
(3) Near low water level runtime panorama blur risk
By the panoramic fuzzy analysis method provided by the invention, the output shortage risk of the short-term power generation scheduling near-boundary operation of the Jinxi hydropower station is analyzed, and the obtained panoramic fuzzy risk three-dimensional stereogram of the hydropower station in the near-low water level operation is shown in an attached figure 5.
As shown in fig. 5, in the power generation planning, when the initial water level is low, the power station has a high possibility of generating insufficient output, especially when the initial water level is close to the dead water level 1800m, there is a high risk that the closer the initial water level is to the dead water level, the smaller the adjustable storage capacity available in the reservoir scheduling period is, and when the forecasted incoming water is large and the actual incoming water is small, the insufficient output occurs. As can be seen from fig. 5, when the initial water level is high (about 1801 to 1801.5m) and the final water level is low (about 1800 to 1800.5m), the power plant still has a high risk zone of insufficient output, and in this zone, the risk of insufficient output of the power plant is about 0.3, because if the initial water level set at the time of generating the power generation plan is high and the final water level is low, this indicates that the reservoir is in a water discharge state, the amount of water available to the reservoir gradually decreases as the schedule progresses, and when the actual water supply is small, the power plant is likely to have insufficient output due to insufficient amount of water available in the reservoir. In other cases, the risk of underpower of the plant is small, mostly less than 0.2, so that the plant should be located as far as possible in these areas when operating at near low water levels.
Comprehensively, when the Jinxi power station runs near a low water level boundary, the power generation plan is compiled to avoid the condition that the initial water level is low, particularly the condition that the power station is close to a dead water level; on the other hand, the band-shaped risk zones in fig. 5 are avoided as much as possible when the initial water level is high and the final water level is low.
In the embodiment 1 of the invention, by taking a hydropower station of the elegant screen class I (Jinxi) in the Yangtze river basin of China as an example, the method provided by the invention is used for carrying out the panoramic fuzzy risk analysis of the short-term power generation scheduling near-boundary operation of the hydropower station, and the result shows that the method can effectively realize the coupling and conversion of the hydrologic prediction error and the scheduling risk of the hydropower station, can comprehensively analyze the water abandoning risk or the insufficient output risk of the hydropower station under different near-boundary operation conditions, more specifically provides a high-risk operation area and a recommended operation area of the hydropower station under different near-boundary operation conditions, and can provide scientific basis and decision support for the power generation planning based on runoff prediction in the actual production of the hydropower station.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (2)
1. A power station power generation scheduling near-boundary operation panoramic fuzzy risk analysis method is characterized by comprising the following steps:
the method comprises the steps of (1) obtaining actual measurement runoff data, forecast runoff data, runoff forecast error data and daily operation allowable water level variation amplitude of the hydropower station, grading the actual measurement runoff data to obtain N runoff grades, and counting a forecast error fuzzy membership function of each runoff grade by using the runoff forecast error data; determining the near-boundary operation range of the hydropower station according to the daily operation allowable water level variation amplitude of the hydropower station;
step (2) obtaining warehousing runoff processes corresponding to each runoff grade, dispersing water levels in a near-boundary operation range of the hydropower station to obtain M scheduling period initial water levels and M scheduling period end water levels, and combining the M scheduling period initial water levels and the M scheduling period end water levels to obtain M scheduling period end water levels2Combining the initial water level and the final water level of each dispatching period according to N warehousing runoff processes and M2Combining the initial water level and the final water level of each scheduling period to obtain N M2An optimal power generation scheduling scheme of each hydropower station;
step (3) according to the forecast runoff data of the hydropower station, grading the forecast runoff data to obtain N runoff levels, and according to the forecast error fuzzy membership function and M of the N runoff levels2The combination of the initial and final water levels of each scheduling period, N M2Obtaining M according to the optimal power generation scheduling scheme of each hydropower station2A credibility value under each combination of the scheduling initial water level and the final water level in each combination of the scheduling initial water level and the final water level;
step (4) according to M2Obtaining the credibility value under each combination of the dispatching initial water level and the final water level in each combination of the dispatching initial water level and the final water level to obtain a curve of the credibility value changing along with the runoff grade, wherein the area enclosed by the curve and the coordinate axis represents the risk of water abandonment or insufficient output of the hydropower station under a certain combination of the dispatching initial water level and the final water level, and the M is used for controlling the output of the hydropower station according to the M2The credibility value of the combination of the initial water level and the final water level of each dispatching period changes along with the change of the forecast runoff level, so as to obtain a comprehensive risk value of water abandonment or insufficient output of the hydropower station under the future panoramic condition;
when the prediction error fuzzy membership function is described as Cauchy distribution, the membership of the prediction error fuzzy variable ξ obeys the Cauchy distribution, and the prediction error fuzzy membership function [ mu () is expressed as:
wherein the prediction error fuzzy number represents a specific value of the prediction error fuzzy variable ξ, Ew+、Ew-Respectively representing the statistical average values of the positive error and the negative error; σ is the weight.
2. The method for analyzing the fuzzy risk of the close-boundary operation panorama of the hydropower station power generation dispatching in the claim 1, wherein the step (3) comprises the following steps:
(3-1) grading the forecast runoff data according to the forecast runoff data of the hydropower station to obtain N runoff grades;
(3-2) obtaining R fuzzy errors of each runoff grade by using the forecast error fuzzy membership function of each runoff grade until obtaining N x R fuzzy errors of N runoff grades;
(3-3) obtaining N R runoff processes considering forecast errors according to the N runoff levels and corresponding fuzzy errors, and executing an optimal power generation scheduling scheme of the hydropower station for the N R runoff processes and the M scheduling initial water levels to obtain M2A credibility value under each of the scheduling onset and end level combinations.
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