Hydropower energy drought identification and characteristic assessment method and device

Abstract

The present invention belongs to the field of energy security, and specifically relates to a method and device for identifying and evaluating characteristics of hydropower energy drought, which is conducive to ensuring the safe operation of the hydropower system and reducing the loss of hydropower energy drought. The method comprises: step 1, data collection; step 2, identifying the actual operation rules of the hydropower system based on the historical operation data of the hydropower system; step 2-1, setting the function form of the actual operation rule; step 2-2, determining the input decision information factor I of the operation rule function t ; Step 2‑3, according to I t and historical decision-making process, combined with the proposed operating rule function, the parameters of the function are determined using the optimization method; step 3, using the basin historical runoff sequence data as input, applying the identified actual operating rules of the hydropower system to perform simulation operation to obtain the long-term simulation scheduling sequence of hydropower system power generation; step 4, identifying hydropower energy drought based on the obtained long-term simulation scheduling sequence of power generation; step 5, evaluating the characteristics of hydropower energy drought.

Description

Technical Field

[0001] The present invention belongs to the field of energy security, and in particular relates to a method and device for identifying and evaluating characteristics of hydropower energy drought. Background Art

[0002] Hydropower energy has the advantages of being clean and renewable, and is an important part of my country's energy system structure in the new era. Under the background of carbon neutrality, the development of green energy such as wind power and photovoltaic power has entered a stage of rapid development. Hydropower energy can smooth the volatility and intermittency of wind power and photovoltaic power, and realize the safe absorption of wind and light energy by the power grid. It is of great significance to plan, develop, and operate hydropower energy safely and efficiently.

[0003] The production of hydropower energy mainly relies on reservoir hubs and hydropower stations to convert the gravitational potential energy of water in rivers into electrical energy. The amount of water inflow in rivers and reservoirs in the current period and in the future determines the electricity production of the hydropower energy system. When a meteorological drought occurs in the basin where the hydropower energy system is located, that is, precipitation decreases, the flow rate in the basin will decrease, and the reduction in river flow will form a hydrological drought. Furthermore, when the amount of water in rivers and reservoirs decreases in the current and future period, the amount of water used for power generation in reservoir and hydropower station hubs will decrease, and the corresponding power generation of the hydropower energy system will decrease. At this time, it can be considered that a hydropower energy drought has occurred.

[0004] However, the relationship between hydrological drought and hydropower energy drought is not a simple one-to-one correspondence. The occurrence of hydrological drought does not necessarily mean that hydropower energy drought will occur. On the contrary, hydropower energy drought may also occur during non-hydrological drought periods. ① Hydrological drought generally refers to when the amount of water in the river is less than a certain index, it can be considered that a hydrological drought has occurred, that is, the amount of water in the river at this time is much less than in previous years. But if there is water in the reservoir at this time, the water used for power generation in the hydropower station will not be greatly affected, and the power generation will not be greatly affected. This shows that hydropower energy drought does not necessarily occur when a hydrological drought occurs. ② Sometimes, due to the operation and management problems of the reservoir itself, the water level of the reservoir drops to a relatively low level. At this time, the amount of water that can be used for power generation in each period of time will not be much, and the reservoir will also be used sparingly. At this time, the power generation of the hydropower station is relatively small, and a hydropower energy drought actually occurs at this time. ③ Sometimes a hydrological drought occurs, but after a period of time, the water in the reservoir is used up and there is less water left. At this time, the power generation may be reduced, which is equivalent to a hydropower energy drought occurring after a period of time after the occurrence of a hydrological drought.

[0005] In the past, there was basically no research on hydropower energy drought, but when a large-scale hydropower system experiences a hydropower energy drought, it will have a serious impact on social economy and energy security. For example, in 2022, a basin experienced the most severe drought since records began in 1961, which caused severe hydropower energy droughts in many hydropower energy bases, resulting in a serious drop in power generation, and extreme situations in which industrial and even residential electricity consumption in the receiving provinces was restricted, causing relatively serious losses to regional economic development. Defining and identifying hydropower energy droughts, and then evaluating the various characteristics of hydropower energy droughts, assessing and warning hydropower energy droughts, and proposing response measures to ensure the safe operation of hydropower systems and reduce losses from hydropower energy droughts have important scientific and practical significance. Summary of the invention

[0006] The present invention is made to solve the above-mentioned problems, and aims to provide a method and device for identifying and evaluating the characteristics of hydropower energy drought, which can identify the actual operating rules of the hydropower system, and then accurately and effectively identify and evaluate the characteristics of hydropower energy drought.

[0007] In order to achieve the above object, the present invention adopts the following scheme:

[0008] <Method>

[0009] like Figure 1 As shown, the present invention provides a method for identifying and evaluating characteristics of hydropower energy drought, comprising the following steps:

[0010] Step 1, data collection: collect historical operation data of the hydropower system and historical long-sequence runoff data of the basin where the hydropower system is located;

[0011] Step 2, identification of hydropower system operation rules: identifying the actual operation rules of the hydropower system based on the historical operation data of the hydropower system;

[0012] Step 2-1, setting the functional form of the actual operation rules of the hydropower system;

[0013] Step 2-2: Determine the input decision information factor of the running rule function ;

[0014] Step 2-3: Input decision information factors based on historical operation data of hydropower system and historical decision-making process , , , combined with the proposed operation rule function , using optimization methods to determine the function Parameters ;

[0015] Step 3, long-sequence simulation operation: using the basin historical runoff sequence data as input, applying the identified actual operation rules of the hydropower system to perform simulation operation to obtain the long-term simulation scheduling sequence of the hydropower system power generation;

[0016] Taking the start time of the historical hydrological data collected by the hydropower system as the starting point, using the historical runoff data as the system driver, the operating rules identified in step 2 Calculate the dispatching decision of each reservoir in each period , through the simulation operation of the hydropower system, the power generation of the hydropower system during the period is obtained Long sequence simulation data, , is the length of the simulation period;

[0017] Step 4, hydropower energy drought identification: hydropower energy drought identification is performed based on the long-term simulated scheduling sequence of power generation, and the duration and intensity of hydropower energy drought events are extracted; hydropower energy drought identification is to identify the power generation process of the long-term simulated scheduling of the hydropower system. When the power generation is less than the set threshold within a period of time, When the event is identified as a hydropower energy drought event;

[0018] Step 5, assessment of hydropower energy drought characteristics: based on the identified hydropower energy drought events and the extracted corresponding hydropower energy drought duration and intensity, conduct an assessment of the hydropower energy drought characteristics.

[0019] In step 1, the historical operation data of the hydropower system includes the historical operation data of each hydropower station in the hydropower system and the reservoir hub where it is located. The historical operation data of the hydropower station involves the basic characteristic parameters of the hydropower station, the power generation flow process, the power generation process, and the output process of the hydropower station; the historical operation data of the reservoir where the hydropower station is located includes the basic characteristic parameters of the reservoir, the inflow flow process, the outflow flow process, the water level process in front of the reservoir dam, the downstream tailwater level process and various data related to the operation of the hydropower system. The historical runoff data of the basin where the hydropower system is located refers to the historical flow process data of each hydrological test section that can be collected in the basin where the hydropower system is located, or the historical flow process data compiled from the dam site section where the reservoir hub is located, as well as data related to the hydrological situation of the basin or basin group where the hydropower system is located.

[0020] The power generation flow of a reservoir (hydropower station), or the power generation power of a reservoir (hydropower station) (the term "output" is often used in the dispatching field to represent power generation power), the power generation, or the final water level of the reservoir can all represent the operation mode of the reservoir and can be used as "operation decisions".

[0021] Preferably, in the method for identifying and evaluating characteristics of hydropower energy drought provided by the present invention, in step 2-1, a radial basis function approximator is used to construct a function of the actual operation rule of the hydropower system. :

[0022]

[0023]

[0024] In the formula, The hydropower system Reservoir Scheduling decisions for time periods; is the number of radial basis functions; It is Reservoir radial basis function weights, and , ; is the radial basis function; represents the input decision information factor, is the number of input decision information factors (number of elements); , Respectively Radial basis function The center point and radius of the input decision information factor, ; Determine the parameters The actual operation rules of the hydropower system can be obtained by the value of .

[0025] Preferably, in the method for identifying and assessing hydropower energy drought characteristics provided by the present invention, in step 2-1, , this setting works better.

[0026] Preferably, in the method for identifying and evaluating the characteristics of hydropower energy drought provided by the present invention, in step 2-2, the rule function is run to input the decision information factor It needs to be determined based on the decision information factors actually used in the operation and management of the hydropower system. The input decision information factors are: ① The position of the current time in the year , Indicates the total number of time periods in a year when a certain time scale (day, month, ten-day period) is selected as the calculation step. When the time scale is day, ten-day period or month, the corresponding 365, 36 and 12 respectively; ② The storage capacity of each reservoir in the system ; ③ At least one of the following two data: the forecast rainfall for a certain period in the future in the basin where the hydropower system is located and the net inflow of each reservoir.

[0027] Preferably, in the method for identifying and assessing drought characteristics of hydropower energy provided by the present invention, in step 2-3, the main goal is to determine the parameters The best estimate of Make With its analog value Closest, at this time is the actual operation rule of the identified hydropower system, that is, when the input decision information factor is given hour, The decision-making process of hydropower system operation managers can be reproduced, and the operation and management process of the hydropower system in the historical period (when the hydropower station is not in operation) or in the future can be further simulated. and The degree of closeness between them can be characterized by the Nash efficiency coefficient NSE, root mean square error RMSE, mean square error MSE or other common indicators; Solution The solution is , It can be Nash efficiency coefficient NSE, root mean square error RMSE, MSE mean square error or other indicators. Common intelligent optimization algorithms such as genetic algorithm GA can be used to solve the above formula, but are not limited to them.

[0028] Preferably, in the method for identifying and evaluating the characteristics of hydropower energy drought provided by the present invention, in step 3, a long sequence simulation operation is performed because most hydropower systems were built and operated at the end of the last century or in recent years, and the historical runoff data or hydrological situation data of the river basin where the hydropower system is located is much longer than its construction and operation time, and most of them have historical runoff data from the 1950s or earlier. To evaluate the characteristics of hydropower energy drought in a hydropower system, it is necessary to use longer runoff data to drive the simulation operation of the hydropower system to better understand and evaluate the characteristics of hydropower energy drought in the hydropower system. Length of simulation period is the length of historical runoff data, and the starting water level of each reservoir in the hydropower system The input decision information factor for each period is determined by referring to the water level of each reservoir at the corresponding time in the actual operation data of the hydropower system. It is given comprehensively based on the historical hydrological situation of the basin and the simulation results of the previous period.

[0029] Preferably, in the method for identifying and evaluating the characteristics of hydropower energy drought provided by the present invention, in step 4, a variable threshold method is used to identify hydropower energy drought events, and the variable hydropower energy drought threshold is set to the power generation corresponding to the power generation of each period minus 30% deviation from the average percentage; the power generation results of each period of the hydropower system simulation operation calculated in step 3 are Calculate the drought threshold sequence of hydropower energy at each time period of the year ; Based on the calculated hydropower energy drought threshold series , the power generation sequence obtained from the simulation operation using the run theory Hydropower energy drought events are identified in the process, and the duration and intensity of hydropower energy drought events are extracted; when the power generation in a period is less than the hydropower energy drought threshold corresponding to the period, it is considered that a hydropower energy drought has occurred; the time from the occurrence and end of the hydropower energy drought is the drought duration, and the cumulative sum of the differences between the hydropower energy drought threshold in each period during the hydropower energy drought event and the power generation corresponding to the power generation in the period is the drought intensity.

[0030] Preferably, in the method for identifying and evaluating characteristics of hydropower energy drought provided by the present invention, in step 5, the evaluation of characteristics of hydropower energy drought refers to the evaluation of the statistical characteristics of the duration of hydropower energy drought and the severity of hydropower energy drought. Specifically, according to the hydropower energy drought events and the duration and severity of hydropower energy drought extracted in step 4, a suitable distribution function is selected to characterize the distribution characteristics of drought duration and severity, and its parameters are estimated; the frequency, interannual variation and recurrence period of hydropower energy drought are analyzed and evaluated.

[0031] Preferably, the method for identifying and evaluating characteristics of hydropower energy drought provided by the present invention further includes: step 6, according to the hydropower energy drought characteristic evaluation result of step 5, performing hydropower energy drought warning and taking corresponding adjustment measures; for the situation where a serious hydropower energy drought will occur according to the established reservoir and hydropower station operation and scheduling mode, select one or adopt the following adjustment measures simultaneously: measure 1) adjust the operation and scheduling of the reservoir and hydropower station, let the reservoir generate less electricity and store more water in advance, and reduce the future power shortage as a whole; measure 2) the power grid takes measures in advance to prepare in advance from thermal power, gas, new energy and other types of energy; measure 3) before the hydropower system encounters a hydropower energy drought, use these energy sources to supplement; measure 4) before the hydropower energy drought occurs, make preparations to introduce hydropower stations in other river basins to supplement power generation.

[0032] <Device>

[0033] Furthermore, the present invention also provides a hydropower energy drought identification and feature assessment device, which can automatically implement the hydropower energy drought identification and feature assessment method described in any one of the above <methods>, including:

[0034] The data collection department collects historical operation data of the hydropower system and historical long-sequence runoff data of the basin where the hydropower system is located;

[0035] A rule identification unit, which identifies the actual operation rules of the hydropower system based on the historical operation data of the hydropower system;

[0036] The long sequence simulation department uses the historical runoff sequence data of the basin as input, and applies the identified actual operation rules of the hydropower system to simulate and operate to obtain the long-term simulation scheduling sequence of the hydropower system power generation; starting from the start time of the historical hydrological situation data collected by the hydropower system, using the historical runoff data as the system driver, the operation rules identified by the rule identification department Calculate the dispatching decision of each reservoir in each period , through the simulation operation of the hydropower system, the power generation of the hydropower system during the period is obtained Long sequence simulation data, , is the length of the simulation period;

[0037] The hydropower energy drought identification department identifies hydropower energy droughts based on the long-term simulated dispatch sequence of power generation, and extracts the duration and intensity of hydropower energy droughts;

[0038] The Assessment Department conducts a hydropower energy drought characteristic assessment based on the identified hydropower energy drought events and the extracted corresponding hydropower energy drought duration and intensity;

[0039] The Early Warning Department will issue early warnings for hydropower energy droughts based on the assessment results of the characteristics of hydropower energy droughts and provide suggestions for corresponding adjustment measures;

[0040] The input display part allows the user to input operation instructions and displays the corresponding information according to the operation instructions;

[0041] The control unit is connected to the data acquisition unit, the rule recognition unit, the long sequence simulation unit, the hydropower energy drought identification unit, the assessment unit, the early warning unit, and the input and display unit to control their operations.

[0042] Preferably, in the hydropower energy drought identification and characteristic assessment device provided by the present invention, after the user selects or inputs the corresponding adjustment measures, the control unit controls all or part of the data acquisition unit, the rule recognition unit, the long sequence simulation unit, the hydropower energy drought identification unit, the assessment unit, the early warning unit, and the input display unit based on the adjustment measures, and re-identifies, assesses and displays the results until the hydropower energy drought is controlled below the threshold allowed by the user (and will not cause hydropower energy drought in other reservoirs or hydropower stations that provide supplies), or no hydropower energy drought occurs.

[0043] Functions and Effects of the Invention

[0044] The method and device for identifying and evaluating characteristics of hydropower energy drought provided by the present invention proposes for the first time to study the problem of hydropower energy drought, and performs simulated scheduling based on the identification of hydropower system operation rules to obtain simulated values ​​of power generation, and then performs hydropower energy drought identification and characteristic evaluation. The method is scientific and reasonable, and fits the actual operation of the project. It can provide reference data and decision-making support for the safe operation of the hydropower energy system, hydropower energy drought risk assessment, hydropower energy drought early warning, and scientific formulation of measures to mitigate hydropower energy drought losses, which is of great significance for ensuring the safe operation of the hydropower system and reducing hydropower energy drought losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] FIG1 is a flow chart of a method for identifying and assessing characteristics of hydropower energy drought according to the present invention;

[0046] FIG2 is a diagram showing a process of simulated operation and power generation of a hydropower system according to the first embodiment of the present invention;

[0047] FIG3 is a diagram of a storage capacity process of a hydropower system simulation operation involved in the first embodiment of the present invention;

[0048] FIG4 is a diagram of the drought threshold values ​​of hydropower energy in each decade of the year involved in the first embodiment of the present invention;

[0049] FIG5 is a diagram of hydropower energy drought events from 1951 to 1980 involved in the first embodiment of the present invention;

[0050] FIG6 is a diagram of hydropower energy drought events from 1981 to 2016 involved in the first embodiment of the present invention;

[0051] FIG. 7 is a frequency fitting curve of the drought duration D of the hydropower energy drought identified in the first embodiment of the present invention;

[0052] FIG. 8 is a frequency fitting curve of the drought severity S of the hydropower energy drought identified in the first embodiment of the present invention. DETAILED DESCRIPTION

[0053] The specific implementation scheme of the method and device for identifying and evaluating characteristics of hydropower energy drought according to the present invention will be described in detail below with reference to the accompanying drawings.

[0054] <Example 1>

[0055] This embodiment is described by taking a hydropower station as an example.

[0056] (1) Collect historical operation data of the hydropower system and historical long-sequence runoff data of the basin where the hydropower system is located. The historical operation data include the historical power generation flow process, power generation process, and output process of each hydropower station in the hydropower system, as well as the historical operation data of the reservoir where each hydropower station is located, including the historical inflow process, outflow process, water level process in front of the reservoir dam, and downstream tailwater level process.

[0057] The historical runoff data of the river basin where the hydropower system is located refers to the historical flow process data of each hydrological test section that can be collected in the river basin where the hydropower system is located, or the compiled historical flow process data of the dam site section where the reservoir is located, as well as data related to the hydrological situation in the river basin where the hydropower system is located.

[0058] In this embodiment, the time span of historical operation data is from January 2014 to August 2018, and the time span of historical long-series runoff data is from 1951 to 2016. The time scale of the collected data is ten-day scale data, and the subsequent calculation time step is ten-day scale.

[0059] (2) Identify the actual operating rules of the hydropower system based on the historical operating data of the hydropower system;

[0060] When the hydropower system is actually in operation, the operation decision is made by the hydropower station operation management personnel in the hydropower system based on the actual working conditions of the hydropower station and reservoir in the current period and other decision support information (such as the reservoir inflow forecast information in the future period) through comprehensive consideration of various factors after multiple rounds of consultation. The process of hydropower system managers making hydropower system operation decisions can be described by the dispatching rules, and its essence can be expressed by the following function:

[0061] In the formula, The first Reservoir Operational decisions made during the period; is the number of reservoirs in the hydropower system; is the length of the operation period; For the Decision information factors (including M elements), function Characterization Reservoir operation rules, For function Parameters.

[0062] The specific steps include the following:

[0063] a. Assuming the hydropower system actually operates in a rule function form. Preferably, assuming the hydropower system actually operates in a rule function form for: ,in,

[0064] In the formula, is the number of radial basis functions; It is Reservoir radial basis function weights, and , ; is the radial basis function; is the number of input decision information factors, that is The number of elements; , Respectively Radial basis function The center point and radius of the input decision information factor. Determine the parameters The actual operation rules of the hydropower system can be obtained by the value of .

[0065] b. Determine the input decision information factor of the above operation rule function In this embodiment, the decision information factor input when making a decision on the operation of the hydropower system is preferably the position of the current period in the year. , reservoir capacity at the beginning of the period , and the forecast inflow for the next period, that is, , that is, the number of input decision information factors .

[0066] c. Input decision information factors based on historical operation data of hydropower system and historical decision-making process , combined with the proposed operation rule function , use optimization methods (for example, various intelligent algorithms of evolutionary computing, this embodiment uses genetic algorithm GA) to determine the function Parameters This example uses the Nash efficiency coefficient NSE to characterize and The closeness between them is determined by using genetic algorithm to solve the parameters The best estimate of The objective function is ,in for and The Nash efficiency coefficient NSE. is the actual operation rule of the identified hydropower system, that is, when the input decision information factor is given hour, The decision-making process of hydropower system operation managers can be reproduced. sequence, and the actual operation The sequences are closer, indicating that this set of parameters Better.

[0067] In this embodiment, the number of reservoirs , input the number of decision information factors (ie, the number of elements is 3), the number of radial basis functions According to the formula Determine, that is Use historical operation data from January 2014 to August 2018 to run the rule function Parameters To rate, The number of elements contained is The optimal parameters are shown in Table 1. The NSE coefficient corresponding to the optimal parameters is 0.7728, which shows that the calibrated operation rule function can well restore the operation process of the hydropower system, providing a basis for further using long-sequence runoff data for long-sequence simulation operation of the hydropower system.

[0068] Table 1 Optimal parameters of running rule functions

[0069]

[0070] (3) Simulation of hydropower system operation. First, a basin hydrological (water-power coupling) model including various hydropower stations and reservoir nodes is constructed. The historical runoff data of the basin is used as input to drive the various hydropower stations and reservoirs in the hydropower system to perform simulation operations according to the dispatching rules identified in step (2), thereby obtaining long-sequence data of the simulated dispatching power generation of the hydropower system.

[0071] Taking the start time of the historical runoff data collected by the hydropower system as the starting point, using the historical runoff data as input, the operation rules identified by step (2) Calculate the dispatching decision of each reservoir in each period , further drive the simulation operation of the hydropower system, and then obtain the power generation of the hydropower system during the period The simulation period length is the length of historical runoff data, such as Figure 2~3 As shown in the figure, in this example, the simulation period is from 1951 to 2016, with a total of 2376 days of data. The starting water level of each reservoir in the hydropower system is It can be determined based on the average water level of each reservoir at the corresponding time in the actual operation data of the hydropower system. The normal water level is 400m, and the input decision information factors for each period are It is given comprehensively based on the historical hydrological situation of the basin, the simulated runoff forecast results of the corresponding historical period, and the simulation results of the hydropower system in the previous period.

[0072] (4) Identification of hydropower energy drought based on the run theory. The variable threshold method is used to identify hydropower energy drought events. The variable hydropower energy drought threshold is set as the power generation corresponding to the power generation of each period minus 30% deviation percentage; the power generation results of each period of the hydropower system simulation operation calculated in step (3) are Calculate the drought threshold sequence of hydropower energy at each time period of the year Based on the calculated hydropower energy drought threshold series , the power generation sequence obtained from the simulation operation using the run theory Hydropower drought events are identified in the process, and the duration and severity of the hydropower drought events are extracted. When the power generation in a period is less than the power generation threshold corresponding to the period, it is considered that a hydropower drought has occurred. The time between the occurrence and end of the hydropower drought is the drought duration, and the cumulative sum of the difference between the hydropower drought threshold in each period and the power generation corresponding to the power generation in the period during the hydropower drought event is the drought severity. In this embodiment, the sequence of hydropower drought thresholds for each decade in each year is shown in Figure 4 .

[0073] In this embodiment, according to the 66-year historical simulation operation process from 1951 to 2016, 89 hydropower energy droughts were identified, and the 10 longest hydropower energy drought events were selected and listed in the following Table 2. Compared with the actual situation during the operation period, the hydropower energy drought events during this period can be accurately identified, and the consistency is very good.

[0074] Table 2 The 10 longest drought events for hydropower energy

[0075]

[0076] (5) Evaluation of hydropower energy drought characteristics Based on the hydropower energy drought events and the duration and intensity of hydropower energy drought extracted in the previous step, select appropriate distribution functions to characterize the distribution characteristics of drought duration and intensity, and estimate their parameters. Analyze and evaluate the frequency, interannual variation and recurrence period of the extracted hydropower energy drought events.

[0077] (5-1) In this example, a total of 89 hydropower drought events were identified for the 66-year long-series historical simulation process. Figures 5 and 6 The event distribution and drought intensity of each hydropower energy drought event are listed. It can be seen from the figure that since the 20th century, hydropower energy droughts have occurred more frequently and the corresponding drought intensity is also greater.

[0078] (5-2) The 89 hydropower energy drought events identified in the previous step are recorded as: ), the drought duration of each drought event is recorded as , the drought intensity is recorded as ;

[0079] (5-3) Select a suitable distribution function and use the linear fitting method to analyze the drought duration sample series. Fitting; In this embodiment, the fitting of the person-III distribution and the exponential distribution to the empirical frequency points of the drought duration samples is compared, and the person-III distribution function with better fitting effect is finally selected as the distribution function of the drought duration. Its distribution function parameters are: the mean is 6.9 ten days, , .

[0080] (5-4) Select an appropriate distribution function and use the drought intensity sample series The distribution function is fitted. After comparing the fitting of the person-III distribution and the exponential distribution to the empirical frequency points of the drought intensity samples, it is also found that the person-III distribution has a better fitting effect on the empirical frequency, and the person-III distribution function is selected as the distribution function of the drought intensity. Its distribution function parameters are: the mean is 337.23 million kWh, , .

[0081] The empirical frequency points of drought duration and drought intensity and the distribution functions adjusted by line fitting are as follows: Figure 7-8 shown.

[0082] (5-5) Based on the distribution functions of drought duration and drought severity, the drought duration and drought severity recurrence periods of each hydropower energy drought event can be calculated. Tables 3 and 4 list the recurrence periods of the drought event with the longest duration and the recurrence periods of the top 10 droughts with the highest severity.

[0083] Table 3 The 10 longest drought events for hydropower energy and their return periods

[0084]

[0085] Table 4 The 10 most severe hydropower drought events and their recurrence periods

[0086]

[0087] <Example 2>

[0088] The second embodiment provides a hydropower energy drought identification and feature assessment device that can automatically implement the method of the first embodiment. The device includes a data acquisition unit, a rule recognition unit, a long sequence simulation unit, a hydropower energy drought identification unit, an assessment unit, an early warning unit, an input display unit, and a control unit.

[0089] The data collection unit performs the collection of historical operation data of the hydropower system and historical long-sequence runoff data of the watershed where the hydropower system is located as described in step (1) above.

[0090] The rule identification unit executes the contents described in step (2) above and identifies the actual operation rules of the hydropower system based on the historical operation data of the hydropower system.

[0091] The long sequence simulation part executes the contents described in step (3) above, taking the historical runoff sequence data of the basin as input, and applying the identified actual operation rules of the hydropower system to perform simulation operation to obtain the long-term simulation scheduling sequence of the hydropower system's power generation.

[0092] The hydropower energy drought identification unit executes the contents described in step (4) above, identifies the hydropower energy drought according to the obtained long-term simulated dispatch sequence of power generation, and extracts the duration and intensity of the hydropower energy drought;

[0093] The assessment department performs the contents described in step (5) above, and conducts a hydropower energy drought characteristic assessment based on the identified hydropower energy drought events and the extracted corresponding hydropower energy drought duration and intensity;

[0094] The Early Warning Department will issue early warnings for hydropower energy drought based on the assessment results of hydropower energy drought characteristics and early warning thresholds, and give corresponding adjustment measures (select one or more measures to be adopted at the same time):

[0095] Measure 1) Adjust the operation and dispatch of reservoirs and hydropower stations, so that reservoirs can generate less electricity and store more water in advance, thus reducing the overall power shortage in the future;

[0096] Measure 2) The power grid should take measures in advance and make preparations in advance from thermal power, gas, new energy and other types of energy;

[0097] Measure 3) Use these energies to supplement the hydropower system before it runs out of hydropower;

[0098] Measure 4) Hydropower energy Before a drought occurs, be prepared to introduce hydropower stations in other river basins to supplement power generation.

[0099] The input display unit allows the user to input operation instructions and displays accordingly according to the operation instructions. For example, the input display unit can display the data collected by the data acquisition unit according to the operation instructions, display the identification situation of the rule identification unit, display the data simulated by the long sequence simulation unit, display the identification results of the hydropower energy drought identification unit, display the evaluation results of the evaluation unit, and display the warning information and measures of the warning unit. The display method can be text (including data), graphs, tables, or static or dynamic model diagrams.

[0100] The control unit is connected to the data acquisition unit, the rule recognition unit, the long sequence simulation unit, the hydropower energy drought identification unit, the evaluation unit, the early warning unit, and the input display unit to control their operation. Further, when the user selects or inputs the corresponding adjustment measures, the control unit also controls all or part of the data acquisition unit, the rule recognition unit, the long sequence simulation unit, the hydropower energy drought identification unit, the evaluation unit, the early warning unit, and the input display unit based on the adjustment measures, and re-identifies, evaluates, and displays the results until the hydropower energy drought is controlled below the threshold allowed by the user (and will not cause hydropower energy drought in other reservoirs or hydropower stations that provide replenishment), or no hydropower energy drought occurs.

[0101] The above embodiments are merely examples of the technical solutions of the present invention. The method and device for identifying and evaluating the characteristics of hydropower energy drought involved in the present invention are not limited to the contents described in the above embodiments, but are subject to the scope defined by the claims. Any modification, supplement or equivalent replacement made by a technician in the field of the present invention based on the embodiment is within the scope of protection required by the claims of the present invention.

Claims

1. A method for identifying and evaluating the characteristics of hydropower energy drought, characterized in that: The following steps are involved: Step 1, data collection: collect historical operation data of the hydropower system and historical long-sequence runoff data of the basin where the hydropower system is located; Step 2, identification of hydropower system operation rules: identifying the actual operation rules of the hydropower system based on the historical operation data of the hydropower system; Step 2-1, setting the functional form of the actual operation rules of the hydropower system; Step 2-2: Determine the input decision information factor of the running rule function ; Step 2-3: Input decision information factors based on historical operation data of hydropower system and historical decision-making process , , , combined with the proposed operation rule function , using optimization methods to determine the function Parameters ; Step 3, long-sequence simulation operation: using the basin historical runoff sequence data as input, applying the identified actual operation rules of the hydropower system to perform simulation operation to obtain the long-term simulation scheduling sequence of the hydropower system power generation; Taking the start time of the historical hydrological data collected by the hydropower system as the starting point, using the historical runoff data as the system driver, the operating rules identified in step 2 Calculate the dispatching decision of each reservoir in each period , through the simulation operation of the hydropower system, the power generation of the hydropower system during the period is obtained Long sequence simulation data, , is the length of the simulation period; Step 4, hydropower energy drought identification: hydropower energy drought identification is performed based on the long-term simulated scheduling sequence of power generation. When the power generation is less than the set threshold for a period of time, this event is identified as a hydropower energy drought event; the duration and intensity of the hydropower energy drought event are extracted; Step 5, hydropower energy drought characteristics assessment: based on the identified hydropower energy drought events and the corresponding hydropower energy drought duration and intensity, conduct a hydropower energy drought characteristics assessment; Among them, in step 2-1, the radial basis function approximator is used to construct the actual operation rule function of the hydropower system : In the formula, The hydropower system Reservoir Scheduling decisions for time periods; is the number of radial basis functions; It is Reservoir radial basis function weights, and , ; is the radial basis function; represents the input decision information factor, is the number of input decision information factors; , Respectively Radial basis function The center point and radius of the input decision information factor, ; Determine the parameters The actual operation rules of the hydropower system can be obtained by the value of ; In step 2-2, run the rule function to input the decision information factor Determined according to the decision information factors actually used in the operation and management of the hydropower system, the input decision information factors are: ① The position of the current time in the year , Indicates the total number of time periods in a year when a certain time scale is selected as the calculation step. When the time scale is day, ten days or month, the corresponding 365, 36 and 12 respectively; ② The storage capacity of each reservoir in the system ; ③ At least one of the following two data: the forecast rainfall for a certain period in the future in the basin where the hydropower system is located and the net inflow of each reservoir.

2. The method for identifying and evaluating hydropower energy drought according to claim 1, characterized in that: in, In step 2-3, the main goal is to determine the parameters The best estimate of Make With its analog value Closest, at this time To identify the actual operating rules of the hydropower system; The solution is , is the Nash efficiency coefficient NSE or other error indicators.

3. The method for identifying and evaluating hydropower energy drought according to claim 1, characterized in that: in, In step 3, the simulation period length is the length of historical runoff data, and the starting water level of each reservoir in the hydropower system The input decision information factor for each period is determined by referring to the water level of each reservoir at the corresponding time in the actual operation data of the hydropower system. It is given comprehensively based on the historical hydrological situation of the basin and the simulation results of the previous period.

4. The method for identifying and evaluating hydropower energy drought according to claim 1, characterized in that: in, In step 4, the variable threshold method is used to identify hydropower energy drought events, and the variable hydropower energy drought threshold is set as the power generation corresponding to the power generation of each period minus 30% deviation percentage; according to the power generation results of each period of the hydropower system simulation operation calculated in step 3 Calculate the drought threshold sequence of hydropower energy at each time period of the year ; Based on the calculated hydropower energy drought threshold series , the power generation sequence obtained from the simulation operation using the run theory Hydropower energy drought events are identified in the process, and the duration and intensity of hydropower energy drought events are extracted; when the power generation in a period is less than the hydropower energy drought threshold corresponding to the period, it is considered that a hydropower energy drought has occurred; the time from the occurrence and end of the hydropower energy drought is the drought duration, and the cumulative sum of the differences between the hydropower energy drought threshold in each period during the hydropower energy drought event and the power generation corresponding to the power generation in the period is the drought intensity.

5. The method for identifying and evaluating the characteristics of hydropower energy drought according to claim 1, Features: Wherein, in step 5, according to the hydropower energy drought events and the duration and severity of the hydropower energy drought extracted in step 4, a suitable distribution function is selected to characterize the distribution characteristics of the drought duration and severity, and its parameters are estimated; Analyze and evaluate the frequency, interannual variation and recurrence period of hydropower energy drought.

6. The method for identifying and evaluating hydropower energy drought according to claim 1, characterized in that: Also includes: Step 6: Based on the evaluation results of the hydropower energy drought characteristics in step 5, a hydropower energy drought warning is carried out and corresponding adjustment measures are taken; for situations where a severe hydropower energy drought will occur according to the established reservoir and hydropower station operation and dispatching mode, one or both of the following adjustment measures are adopted: Adjust the operation and dispatch of reservoirs and hydropower stations, so that reservoirs can generate less electricity and store more water in advance, thus reducing the overall power shortage in the future; The power grid takes measures in advance to prepare for thermal power, gas, new energy and other types of energy; when the hydropower system encounters a drought, these energy sources will be used to supplement it; Before a hydropower energy drought occurs, preparations should be made to introduce hydropower stations in other river basins to supplement power generation.

7. A device for identifying and evaluating drought characteristics of hydropower energy, capable of automatically implementing the method for identifying and evaluating drought characteristics of hydropower energy as claimed in any one of claims 1 to 6, characterized in that: include: The data collection department collects historical operation data of the hydropower system and historical long-sequence runoff data of the basin where the hydropower system is located; A rule identification unit, which identifies the actual operation rules of the hydropower system based on the historical operation data of the hydropower system; The long-sequence simulation department uses the historical runoff sequence data of the basin as input, applies the identified actual operation rules of the hydropower system to perform simulation operations to obtain the long-term simulation scheduling sequence of the hydropower system's power generation; The hydropower energy drought identification department identifies hydropower energy drought based on the long-term simulated scheduling sequence of power generation. When the power generation is less than the set threshold for a period of time, the event is identified as a hydropower energy drought event; the duration and intensity of the hydropower energy drought are extracted; The Assessment Department conducts a hydropower energy drought characteristic assessment based on the identified hydropower energy drought events and the extracted corresponding hydropower energy drought duration and intensity; The Early Warning Department will issue early warnings for hydropower energy droughts based on the assessment results of the characteristics of hydropower energy droughts and provide suggestions for corresponding adjustment measures; The input display part allows the user to input operation instructions and displays the corresponding information according to the operation instructions; The control unit is connected to the data acquisition unit, the rule recognition unit, the long sequence simulation unit, the hydropower energy drought identification unit, the evaluation unit, the early warning unit, and the input display unit to control their operations.

8. The hydropower energy drought identification and characteristic assessment device according to claim 7, characterized in that: in, After the user selects or inputs corresponding adjustment measures, the control unit controls the operation of the data acquisition unit, the rule recognition unit, the long sequence simulation unit, the hydropower energy drought identification unit, the evaluation unit, the early warning unit, and the input and display unit based on the adjustment measures, thereby re-identifying, evaluating, and displaying the adjusted results until the hydropower energy drought is controlled below the threshold level allowed by the user.

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