Quantitative and analytical screening method, system and storage medium for structural compression of cascade reservoir dry season regulation space
Patent Information
- Application Number
- CN202611532450.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-09-30
- Publication Date
- 2026-11-03
Smart Images
Figure CN123032122A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to reservoir group scheduling in water conservancy and hydropower projects, and in particular to a method, system, and storage medium for the structural compression quantification and analytical screening of the scheduling space of cascade reservoirs during the dry season. Background Technology
[0002] In hydropower engineering practice, in order to utilize the natural drop formed by the large bends of a river, water intake hubs are often set up upstream of the bend to impound water, and the water is then diverted to a power station downstream of the bend through a tunnel. This type of power station is called a bend-cutting hydropower station. After the water is diverted, the original bend section of the river between the water intake hub and the bend-cutting hydropower station becomes a reduced-water section because most of the water is diverted. In order to maintain the basic ecological function of the river, a certain amount of ecological flow must be released from the water intake hub to the reduced-water section, and the water cannot be completely diverted to the bend-cutting hydropower station for power generation through the tunnel.
[0003] For conventional dam-type power stations, the tailwater from power generation is directly discharged into the downstream river channel, and can be included in the ecological flow demand. However, for bend-cutting hydropower stations, the downstream flow to maintain the ecological function of the reduced-water section and the flow to be generated by power generation through the water diversion tunnel are separated at the water intake point, and the two parts of the water cannot be shared. This hydraulic pattern of separating the ecological flow path from the diversion flow path and the inability to share water is called a bend-cutting water diversion pattern.
[0004] In the cascade development of rivers in the mountainous areas of southwestern my country, a common engineering combination is a headwater reservoir with annual regulation capacity at the upstream end, and a run-of-river bend-cutting hydropower station at the downstream end. The self-regulating capacity of the run-of-river bend-cutting hydropower station is negligible. During the dry season when water inflow is low, the headwater reservoir must utilize its beneficial storage capacity to replenish water, simultaneously meeting the ecological discharge needs of the downstream water intake hub and the power generation needs of the water diversion tunnel. The bend-cutting water diversion pattern means that the two parts of the water cannot be shared, making the water supply and demand contradiction of this type of cascade reservoir more prominent during the dry season than that of conventional dam-type power station projects under the same hydrological and reservoir capacity conditions.
[0005] In existing technologies, the solutions to the aforementioned contradictions are typically implemented at the single-station level. Environmental impact assessment documents specify the minimum ecological discharge flow during the dry season for each individual bend-cutting hydropower station, and dispatching procedures follow the order of deducting the ecological flow from the inflow before determining the usable flow. These practices fail to extract the non-shareable water volume effect caused by the bend-cutting water diversion pattern into an independently quantifiable and cross-project comparable indicator. When planning departments need to conduct horizontal comparisons and prioritize the dry season dispatching capacity among multiple cascade reservoirs with similar structural characteristics, a concise quantitative basis is lacking.
[0006] On the other hand, existing reservoir system performance evaluation frameworks, such as those based on reliability, resilience, and vulnerability indicators, require long-term numerical simulations to obtain statistical indicators. While comprehensive, these frameworks necessitate modeling and simulating each reservoir individually, resulting in a large computational workload and making them unsuitable for rapid screening of a large number of cascade reservoirs during the planning phase. Numerical methods such as dynamic programming and genetic algorithms used in cascade reservoir optimization scheduling research, while embedding the bend-cutting water diversion pattern as a constraint in the model, cannot directly separate its independent contribution to the scheduling space from the solution results, nor can they be compared horizontally across different cascade reservoirs.
[0007] Therefore, there is currently no analytical method that can quickly quantify the structural compression of the dry season scheduling space of cascade reservoirs by the water diversion pattern of bend interception without relying on complex numerical simulations, and achieve direct ranking comparison among multiple cascade reservoirs. Summary of the Invention
[0008] Purpose of the invention: The purpose of this invention is to provide a method, system, and storage medium for quantifying and analyzing the structural compression of the dry season scheduling space of cascade reservoirs, which can be rapidly quantified based solely on engineering parameters and historical data without numerical simulation.
[0009] Technical Solution: The present invention provides a method for quantifying and analyzing the structural compression of the dry season scheduling space of cascade reservoirs. The cascade reservoirs include one headwater reservoir and one run-of-river bend-cutting hydroelectric power station. The headwater reservoir is an annual regulating reservoir. The method includes the following steps:
[0010] S1. Determine the available flow rate of the cascade reservoirs during the dry season based on the design parameters of the head reservoir and its hydrological characteristics during the dry season.
[0011] S2. Obtain the dry season ecological flow demand and the guaranteed power generation flow demand of the cascade reservoirs, and construct a reference reservoir. The power station in the reference reservoir is a dam-type power station, and the rest is the same as the cascade reservoirs. Determine the rigid water demand flow of the cascade reservoirs and the reference reservoir in the dry season according to the two flow demands.
[0012] S3. Calculate the difference between the available flow of the cascade reservoirs during the dry season and the rigid water demand flow of the reference reservoir and the cascade reservoirs during the dry season, and use them as the dry season scheduling space of the reference reservoir and the cascade reservoirs respectively.
[0013] S4. When the available flow rate is greater than the rigid water demand flow rate of the cascade reservoir, the dry season scheduling space ratio is obtained based on the dry season scheduling space of the cascade reservoir and the dry season scheduling space of the reference reservoir to characterize the degree of structural compression; otherwise, the cascade reservoir is treated as a special evaluation object.
[0014] S5. Calculate the elasticity coefficients of the independent variable parameters in the formula for calculating the dry season scheduling space ratio. Check the calculation results according to the identity that the elasticity coefficients should satisfy. If the corresponding identity is not satisfied, re-check and correct the previous calculation results until the corresponding identity requirements are met.
[0015] S6. For multiple cascade reservoirs, perform the above steps respectively, and sort them from small to large based on the dry season scheduling space ratio of each cascade reservoir. For special assessment objects, their dry season scheduling space ratio is regarded as the minimum value. The higher the ranking, the greater the structural compression of the cascade reservoir.
[0016] S7. For any two cascade reservoirs, calculate the probability of their ranking being reversed based on the difference in their dry season scheduling space ratio and their respective variances. When the probability exceeds a preset significance threshold, determine that their rankings are indistinguishable and rank them in parallel, thus correcting the ranking obtained in step S6.
[0017] By constructing a reference reservoir with identical hydrological, storage capacity, and water demand conditions to the cascade reservoirs under evaluation, except that the bend-cutting diversion power station is replaced with a conventional dam power station, a standardized index reflecting only the structural pattern can be obtained. Since the reference reservoir and the cascade reservoirs under evaluation are identical in five aspects—dry season inflow, beneficial storage capacity, dry season duration, ecological flow demand, and guaranteed power generation flow demand—the only difference lies in the power station type. The reference reservoir uses a conventional dam power station, allowing tailwater to directly return to the river channel and share ecological flow; while the cascade reservoirs use bend-cutting diversion power stations, separating ecological discharge from power generation water diversion. Therefore, the difference in dry season dispatch space is entirely due to the different power station types, unrelated to the specific hydrological conditions and storage capacity of each project. Based on this premise, calculating the dry season dispatch space of the reference reservoir and the cascade reservoirs separately and taking their ratio yields a standardized index reflecting only the impact of structural patterns. The calculated dry season scheduling space ratio is then self-checked using the homogeneous identity that is always satisfied between the elasticity coefficients of the independent variable parameters in its calculation formula. This allows for the immediate detection of calculation or coding errors without relying on external verification data, preventing erroneous results from propagating downstream. For multiple cascade reservoirs to be evaluated, sorting them according to this ratio from smallest to largest allows for the rapid identification of the individual reservoirs with the most severe structural compression. Furthermore, considering the impact of parameter uncertainty on the sorting conclusion, the inversion probability of any two cascade pairs is calculated to correct for any pseudo-precision parts in the sorting obtained in step S6. Cascade reservoirs that are indistinguishable in the sorting are then grouped together for further ensuring the accuracy of the sorting. This method clearly separates the structural compression of the dry season scheduling space by the bend-cutting hydropower station into a comparable independent indicator, and can quickly determine the degree of structural compression without complex simulation calculations, significantly improving efficiency.
[0018] Preferably, in step S1, the design parameters of the headwater reservoir are the beneficial storage capacity, and the hydrological characteristic parameters include the multi-year average inflow during the dry season and the duration of the dry season.
[0019] The beneficial storage capacity is directly derived from the normal storage level and dead storage level settings in the reservoir design documents. The multi-year average inflow during the dry season can be obtained from historical observation data of the watershed hydrological stations, while the duration of the dry season is determined based on hydrological periodization results. These three parameters are readily available and fixed values based on the existing design and observation data of the reservoir. Subsequent calculations based on these parameters can avoid deviations caused by unclear parameter sources or the need for estimation.
[0020] Preferably, the available flow rate of the cascade reservoirs during the dry season is calculated according to the following formula.
[0021]
[0022] Where W represents the available flow rate of the cascade reservoirs during the dry season. V represents the multi-year average inflow to the Longtou Reservoir during the dry season, and V represents the beneficial storage capacity of the Longtou Reservoir. This refers to the dry season.
[0023] The available flow during the dry season consists of two superimposed parts, the first part The second part is the multi-year average inflow of the Longtou Reservoir during the dry season. This formula represents the additional flow that the leading reservoir can provide when it uniformly releases its beneficial storage capacity during the dry season. Based on the principle of water balance, it assumes that the leading reservoir fills to its normal storage level at the end of the flood season and drops to its dead storage level at the end of the dry season, neglecting inflow and water consumption within the same area. This represents a reasonable simplification of the dry season operation of the annual regulating reservoir. This formula concisely calculates the available flow of the cascade reservoirs during the dry season, providing a foundation for subsequent rapid calculations.
[0024] Preferably, in step S4, the dry season scheduling space ratio is the ratio of the dry season scheduling space of the cascade reservoirs to the dry season scheduling space of the reference reservoir, specifically expressed as follows:
[0025]
[0026] Where R is the dry season scheduling space ratio. and These are the dry season ecological flow requirements of the cascade reservoirs and the flow requirements to ensure power generation.
[0027] This expression only contains , , V and Five parameters are used, which can be directly obtained from environmental impact assessment approvals, power plant design documents, hydrological station data, reservoir design documents, and hydrological phasing results. The R value ranges from 0 to 1, and its engineering meaning is the proportion of dry season scheduling space retained by the cascade reservoirs relative to the reference reservoir. The closer the R value is to 0, the more severe the structural compression and the more limited the remaining scheduling space; the closer the R value is to 1, the smaller the impact of structural compression. This analytical formula completely eliminates the dependence on numerical simulation of reservoir scheduling, allowing horizontal comparisons between multiple cascade reservoirs to be completed immediately after obtaining the above five parameters.
[0028] Preferably, the dry season ecological flow demand and the guaranteed power generation flow demand are both based on their preset flow values during the dry season, without considering the changes in each month during the dry season.
[0029] In practical engineering, ecological flow demand may vary with the month and the growth and activity of aquatic organisms, and the power generation flow corresponding to the guaranteed output may also vary monthly due to seasonal differences in power system load. However, the purpose of this method is to quickly screen and identify the individual reservoirs that pose the most significant pressure on the shunting space structure from among numerous candidate cascade reservoirs, rather than to provide precise scheduling and operation plans. Using preset flow values instead of monthly sequence data can significantly reduce the workload of data preparation, and it has been verified (see Table 4 for specific implementation methods) that it does not affect the correctness of the relative ordering between the cascade reservoirs.
[0030] Preferably, the cascade reservoir has a water intake hub below the headwater reservoir. The outflow from the headwater reservoir is equal to the inflow from the water intake hub. The outflow from the water intake hub is diverted to the reduced-water section as ecological flow supply and to the bend-cutting hydropower station as power generation flow supply.
[0031] This limitation defines the applicable boundary conditions of this method: First, it ignores the inflow and water use between the headwater reservoir and the intake hub, assuming no significant increase or decrease in water volume in the river channel between them; second, the intake hub is the only diversion node in the cascade reservoir, and the allocation of ecological flow and power generation flow is completed at this point. This limitation clarifies the hydraulic assumptions on which this method is based, avoiding misuse of the method or distortion of results due to incompatible applicable conditions.
[0032] Preferably, the elastic coefficient in step S5 should satisfy the following identity:
[0033] ,
[0034] ,
[0035] in, , , , and V, respectively , , and The elastic modulus;
[0036] The elastic coefficients corresponding to each parameter are calculated using the following formula.
[0037] ,
[0038] Where x is V, , , and In any of them, Ex is the elastic coefficient corresponding to x.
[0039] First identity This indicates that the elasticity coefficients of the beneficial storage capacity and the dry season duration are opposites, reflecting the inherent law that their relative influences on the dry season scheduling space ratio are equal in magnitude and opposite in direction; the second identity This study reveals the homogeneity of the sum of the elasticity coefficients of four parameters—ecological flow demand, guaranteed power generation flow demand, dry season inflow, and beneficial storage capacity—which is always zero. The two identities are independent of the specific values of each parameter and serve as a self-checking rule for the elasticity coefficient calculation results. A deviation exceeding the floating-point precision level is considered a calculation error, preventing numerical errors from being imperceptibly transmitted to downstream results.
[0040] Preferably, the probability of the order of the two cascade reservoirs being reversed in step S7 is calculated according to the following formula:
[0041] ,
[0042] Among them, P rev Let Φ be the probability of a reversal in the ranking of two cascade reservoirs, Φ be the standard normal cumulative distribution function, and R be the probability of a reversal. i and R j These are the dry season scheduling space ratios for the i-th and j-th cascade reservoirs, respectively; and denoted as , respectively, are the standard deviations of the dry season scheduling space ratios for the i-th and j-th cascade reservoirs.
[0043] This formula uses the difference in the dry season scheduling space ratio of the two reservoirs as the numerator and the square root of the sum of their variances as the denominator. It is then converted into a reversal probability using a standard normal cumulative distribution function. When the R-values of the two reservoirs are very similar but their respective standard deviations are large, it indicates that their R-values are quite close. Furthermore, their R-values are prone to fluctuation, thus increasing the probability of reversal in the ranking. The corresponding P... revThe smaller the value, the higher the probability of the two cascade reservoirs being reversed in order. By using this quantitative calculation formula and the preset significance threshold, the ordering results can be corrected quickly and accurately, thereby avoiding the output of ordering conclusions with pseudo-precision due to parameter disturbances.
[0044] The present invention discloses a structural compression quantification and analytical screening system for the dry season scheduling space of cascade reservoirs. The cascade reservoirs include one headwater reservoir and one run-of-river bend-cutting hydroelectric power station. The headwater reservoir is an annual regulating reservoir, comprising:
[0045] Available flow determination module: used to determine the available flow of cascade reservoirs during the dry season based on the design parameters of the head reservoir and its hydrological characteristics during the dry season;
[0046] Rigid water demand determination module: used to obtain the dry season ecological flow demand and the flow demand to ensure power generation of cascade reservoirs, and to construct a reference reservoir. The power station in the reference reservoir is a dam-type power station, and the rest is the same as the cascade reservoir. The rigid water demand of the cascade reservoir and the reference reservoir in the dry season is determined according to the two flow demands.
[0047] Dry season scheduling space confirmation module: used to calculate the difference between the available flow of the cascade reservoir in the dry season and the rigid water demand flow of the reference reservoir and the cascade reservoir in the dry season, which are respectively used as the dry season scheduling space of the reference reservoir and the cascade reservoir.
[0048] Dry season scheduling space ratio confirmation module: When the available flow is greater than the rigid water demand of the cascade reservoir, it obtains the dry season scheduling space ratio, which is used to characterize the degree of structural compression, based on the dry season scheduling space of the cascade reservoir and the dry season scheduling space of the reference reservoir; otherwise, the cascade reservoir is treated as a special evaluation object.
[0049] Self-checking module: Used to calculate the elasticity coefficients of the independent variable parameters in the formula for calculating the dry season scheduling space ratio, and to self-check the calculation results according to the identity that the elasticity coefficients should satisfy. If the corresponding identity is not satisfied, the previous calculation results are re-checked and corrected until the corresponding identity requirements are met.
[0050] Screening module: This module is used to execute the above modules for multiple cascade reservoirs. It sorts the reservoirs from smallest to largest based on their dry season scheduling space ratio. For special assessment objects, their dry season scheduling space ratio is considered to be the minimum value. The higher the ranking, the greater the structural compression of the cascade reservoir.
[0051] Correction module: For any two cascade reservoirs, based on the difference in their dry season scheduling space ratio and their respective variances, calculate the probability that their rankings will be reversed; when the probability exceeds a preset significance threshold, determine that their rankings are indistinguishable and sort them in parallel, thus correcting the ranking obtained by the screening module.
[0052] The present invention provides a computer-readable storage medium for storing one or more programs, wherein the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods described above.
[0053] Beneficial Effects: By constructing a reference reservoir and deriving analytical formulas, the structural compression effect of the bend-cutting water diversion pattern on the dry season scheduling space was successfully isolated from traditional numerical models and quantified independently. This method eliminates the need for complex reservoir scheduling numerical simulations. Using only basic parameters obtainable from environmental impact assessment approvals, design documents, and conventional hydrological data, it can quickly compare and rank the degree of structural compression of the dry season scheduling space for multiple cascade reservoirs, significantly improving efficiency. Furthermore, this method performs self-checking based on elasticity coefficients and sorts based on the difference and variance between two cascade reservoirs, ensuring the accuracy of the final screening and ranking results. Both of these processes involve minimal computation, ensuring the overall efficiency of the technical solution. Attached Figure Description
[0054] Figure 1 This is a flowchart of the method of the present invention;
[0055] Figure 2 This is a schematic diagram comparing the dry season water distribution of cascade reservoir A under two different patterns in the embodiment.
[0056] Figure 3 This is a schematic diagram comparing the dry season water distribution of cascade reservoir B under two different patterns in the embodiment.
[0057] Figure 4 This is a schematic diagram illustrating the supply and demand imbalance of cascade reservoir C during the dry season in the embodiment.
[0058] Figure 5 This is a schematic diagram illustrating the ranking and simulation verification of the dry season scheduling space ratio of the five cascade reservoirs in the embodiment. Detailed Implementation
[0059] It should be noted that, unless otherwise specified, the term "cascade reservoir" in this application refers specifically to the aforementioned structural form, namely, an independent hydraulic engineering unit consisting of a single annual regulating head reservoir and a single downstream bend-diversion hydropower station, rather than a group of cascade reservoirs consisting of multiple reservoirs connected in series on the same river. In other words, the term "cascade reservoir" in this application refers to "bend-diversion cascade reservoir".
[0060] like Figure 1 As shown, the structural compression quantification and analytical screening method for the dry season scheduling space of cascade reservoirs described in this invention includes the following steps:
[0061] S1. Determine the available flow rate of the cascade reservoirs during the dry season based on the design parameters of the head reservoir and its hydrological characteristics during the dry season.
[0062] The design parameters for the Longtou Reservoir are its beneficial storage capacity, and its hydrological characteristics include the multi-year average inflow during the dry season and the duration of the dry season. This method assumes that the outflow from the Longtou Reservoir is equal to the inflow at the intake, i.e., it ignores the intermediate inflow and water consumption between the two. The Longtou Reservoir is filled to its normal storage level at the end of the flood season and lowered to its dead storage level at the end of the dry season. The amount of water that can be released during the dry season is equal to the beneficial storage capacity. The water intake hub has weak regulation and storage capacity, and the available flow during the dry season is determined solely by the inflow of the headwater reservoir, the beneficial storage capacity, and the duration of the dry season.
[0063] Cascade Dry Season Available Flow (m³ / s) is defined as the total usable water volume during the dry season (the sum of inflow and storage water volume) divided by the duration of the dry season. The calculation formula is as follows:
[0064]
[0065] Where W represents the available flow rate of the cascade reservoirs during the dry season. V represents the multi-year average inflow to the Longtou Reservoir during the dry season, and V represents the beneficial storage capacity of the Longtou Reservoir. This refers to the dry season.
[0066] S2. Obtain the dry season ecological flow demand and the guaranteed power generation flow demand of the cascade reservoirs, and construct a reference reservoir. The power station in the reference reservoir is a dam-type power station, and the rest is the same as the cascade reservoirs. Determine the rigid water demand flow of the cascade reservoirs and the reference reservoir during the dry season based on the two flow demands. Specifically:
[0067] Set the dry season ecological flow requirement as follows: (m³ / s, Let the power generation flow rate corresponding to the guaranteed output be... (m³ / s, In cascade reservoirs, The minimum dry season flow that must be maintained for the corresponding river section with reduced water flow. The minimum flow rate that the corresponding water diversion tunnel must maintain. This method uses the preset flow rate value during the dry season as... and Without considering the variations in each month during the dry season, the preset flow rate is determined by the preliminary engineering design.
[0068] A reference reservoir is introduced as a comparison reference, and the reference reservoir maintains... , , , and Similar to cascade reservoirs, the only difference is that the bend-cutting hydropower station is replaced with a conventional dam-type power station.
[0069] The dry season rigid water demand (m³ / s) is defined as the minimum water supply flow that the headwater reservoir must maintain during the dry season. The dry season rigid water demand for the two types of reservoirs is determined as follows:
[0070] Referring to the case of a reservoir where the tailwater from power generation is directly discharged into the downstream river channel, it can be included in the ecological flow. Therefore, the discharge flow only needs to be no less than [amount missing]. and The larger value in the middle can simultaneously meet the needs of both ecological flow and power generation flow. The rigid water demand during the dry season is .
[0071] In a cascade reservoir system, under the assumptions made in step S1, the outflow from the headwater reservoir equals the inflow from the intake hub. This is used to satisfy... The water volume is discharged through the water intake hub to the reduced-water section of the river to meet the needs of... The water is diverted to the power station via two independent routes, and the water volume cannot be shared. Therefore, the rigid water demand during the dry season is... .
[0072] When a cascade includes two or more bend-cutting hydropower stations, the water distribution relationship of each power station's intake hub becomes more complex, making this method unsuitable.
[0073] S3. Calculate the difference between the available flow of the cascade reservoirs during the dry season and the rigid water demand flow of the reference reservoir and the cascade reservoirs during the dry season, and use them as the dry season scheduling space of the reference reservoir and the cascade reservoirs respectively.
[0074] The dry season dispatch space (m³ / s) is the dry season available flow minus the dry season rigid water demand. The dry season dispatch spaces for the reference reservoir and cascade reservoirs are as follows:
[0075]
[0076]
[0077] in To reference the reservoir's dry season scheduling capacity, This provides room for the dry season scheduling of cascade reservoirs.
[0078] minus This refers to the loss of scheduling space caused by the bend-cutting water diversion pattern, denoted as... , The expression can be simplified to:
[0079] .
[0080] S4. When the available flow rate is greater than the rigid water demand flow rate of the cascade reservoir, the dry season scheduling space ratio is obtained based on the dry season scheduling space of the cascade reservoir and the dry season scheduling space of the reference reservoir to characterize the degree of structural compression; otherwise, the cascade reservoir is treated as a special evaluation object.
[0081] when hour, and Define the dry season scheduling space ratio. for and The ratio. After simplification, This can be expressed as an analytical formula containing only the following five parameters:
[0082]
[0083] exist Under the conditions, Established. The engineering meaning refers to the proportion of dry season scheduling space reserved by cascade reservoirs relative to a reference reservoir. The smaller the value, the more significant the structural compression of the dry season scheduling space by the water diversion pattern.
[0084] The calculation requires only the following five parameters, which are detailed in Table 1.
[0085] Table 1. Meaning and Source of the Five Parameters
[0086]
[0087] If a certain level ,but This indicates that the off-season scheduling space for this tier is insufficient, and it is directly listed as a special assessment object, in which case it is not calculated. .
[0088] S5. Based on the first-order partial derivatives of the independent variable parameters in the calculation formula according to the dry season scheduling space comparison, calculate the elasticity coefficients of the independent variable parameters, and perform self-checking on the calculation results according to the identity that the elasticity coefficients should satisfy. If the corresponding identity is not satisfied, re-check and correct the previous calculation results until the corresponding identity requirements are met.
[0089] The specific process is as follows:
[0090] Based on the first-order partial derivatives of the dry season scheduling space ratio R obtained in step S4 with respect to each parameter (that is, each independent variable parameter in the calculation formula of R), calculate the elasticity coefficient of each parameter, and self-check the results according to the identity that the elasticity coefficient should satisfy.
[0091] In step S4, the applicable domain W>Q eco +Q firmAnd Q eco ≠Q firm Within, the dry season scheduling space ratio R is adjusted according to the elasticity coefficients corresponding to each parameter. Calculate, where x is any one of the five parameters, E x Let R be the elastic coefficient corresponding to x, representing the relative change of R when x undergoes a relative change; it is dimensionless. From R with respect to (V,T) dry ) and about (Q) eco Q firm , The homogeneity of order 0 for V yields five elastic coefficients that always satisfy:
[0092] ,
[0093] ,
[0094] The two identities are independent of the specific values of each parameter and are used as self-checking rules for the calculation results of the elasticity coefficient of this method: when the self-check deviates beyond the floating-point precision level, it is judged as a calculation or coding error (if this method is implemented by programming, there may be calculation errors caused by coding errors).
[0095] After calculating the first-order partial derivative, the variance of the dry season scheduling space ratio R can be calculated according to the propagation formula of the variance of each parameter, and its robustness interval can be constructed.
[0096] The standard deviation of each parameter during the planning phase , , , and Characterizing parameter uncertainty, under the conservative assumption that the parameters are independent, the variance of the dry season scheduling space ratio is calculated by the first-order partial derivatives of the standard deviations of each parameter using the following formula:
[0097] ,
[0098] Where σ R Let i be the standard deviation of the dry season scheduling space ratio, i = 1, 2, 3, 4, 5; when i takes the values 1, 2, 3, 4, and 5 respectively, the corresponding... (That is, x1, x2, x3, x4, and x5) take respectively , , , and , for The variance of the corresponding parameter, for example Pick hour, That is That is, the variance of the multi-year average inflow of the headwater reservoir during the dry season. The meanings for other values are analogous and will not be elaborated further. For example, [R-2σ] R ,R+2σ R As the robustness interval of R, its width reflects the degree of dispersion of parameter uncertainty in the planning stage after propagation to the dry season scheduling space ratio. The narrower the robustness interval, the less the value of the dry season scheduling space ratio is affected by parameter uncertainty.
[0099] S6. For multiple cascade reservoirs, perform the above steps respectively, and sort them from smallest to largest based on the dry season scheduling space ratio of each cascade reservoir. For special evaluation objects, their dry season scheduling space ratio is regarded as the minimum value (when there are multiple special evaluation objects, their dry season scheduling space ratios are treated as the minimum values in parallel). The higher the ranking, the greater the structural compression of the cascade reservoir, and the more likely it is to be evaluated by refined numerical simulation.
[0100] S7. For any two cascade reservoirs, calculate the probability of their ranking being reversed based on the difference in their dry season scheduling space ratio and their respective standard deviations. When the probability exceeds a preset significance threshold, determine that their rankings are indistinguishable and rank them in parallel, thus correcting the ranking obtained in step S6.
[0101] For any two cascade reservoirs i and j, when their dry season scheduling space ratio satisfies R i <R j When i is ranked before j in the order obtained in step S6; under the assumption that the difference between the dry season scheduling space ratios of the two reservoirs approximately follows a normal distribution, the probability that the rankings of the two reservoirs will be reversed (i.e., the actual dry season scheduling space ratio of i is greater than that of j) is calculated by the following formula:
[0102] .
[0103] Where Φ is the standard normal cumulative distribution function. and These are the standard deviations of the dry season scheduling space ratios for cascade reservoirs i and j, calculated in step S6. Under normal circumstances, the five input parameters ( , , , and The errors come from different independent sources, and their sources are diverse and independent of each other. As a nonlinear combination of five parameters, the distribution of the estimation error of R can usually be approximated well by a normal distribution.
[0104] Given a significance threshold α (taken as 0.10 in engineering implementation), when P revWhen the value is greater than α, it is determined that the ranking of cascade reservoirs i and j is indistinguishable, and they should be merged into the same priority group for evaluation; otherwise, their rankings are strictly distinguishable. Therefore, the ranking obtained in step S6 based solely on the dry season scheduling space ratio is corrected to avoid pseudo-precision rankings that may occur under parameter disturbances.
[0105] The present invention discloses a structural compression quantification and analytical screening system for the dry season scheduling space of cascade reservoirs. The cascade reservoirs include one headwater reservoir and one run-of-river bend-cutting hydroelectric power station. The headwater reservoir is an annual regulating reservoir, comprising:
[0106] Available flow determination module: used to determine the available flow of cascade reservoirs during the dry season based on the design parameters of the head reservoir and its hydrological characteristics during the dry season;
[0107] Rigid water demand determination module: used to obtain the dry season ecological flow demand and the flow demand to ensure power generation of cascade reservoirs, and to construct a reference reservoir. The power station in the reference reservoir is a dam-type power station, and the rest is the same as the cascade reservoir. The rigid water demand of the cascade reservoir and the reference reservoir in the dry season is determined according to the two flow demands.
[0108] Dry season scheduling space confirmation module: used to calculate the difference between the available flow of the cascade reservoir in the dry season and the rigid water demand flow of the reference reservoir and the cascade reservoir in the dry season, which are respectively used as the dry season scheduling space of the reference reservoir and the cascade reservoir.
[0109] Dry season scheduling space ratio confirmation module: When the available flow is greater than the rigid water demand of the cascade reservoir, it obtains the dry season scheduling space ratio, which is used to characterize the degree of structural compression, based on the dry season scheduling space of the cascade reservoir and the dry season scheduling space of the reference reservoir; otherwise, the cascade reservoir is treated as a special evaluation object.
[0110] Self-checking module: Used to calculate the elasticity coefficients of the independent variable parameters in the formula for calculating the dry season scheduling space ratio, and to self-check the calculation results according to the identity that the elasticity coefficients should satisfy. If the corresponding identity is not satisfied, the previous calculation results are re-checked and corrected until the corresponding identity requirements are met.
[0111] Screening module: This module is used to execute the above modules for multiple cascade reservoirs. It sorts the reservoirs from smallest to largest based on their dry season scheduling space ratio. For special assessment objects, their dry season scheduling space ratio is considered to be the minimum value. The higher the ranking, the greater the structural compression of the cascade reservoir.
[0112] Correction module: For any two cascade reservoirs, based on the difference in their dry season scheduling space ratio and their respective variances, calculate the probability that their rankings will be reversed; when the probability exceeds a preset significance threshold, determine that their rankings are indistinguishable and sort them in parallel, thus correcting the ranking obtained in step S6.
[0113] The present invention provides a computer-readable storage medium for storing one or more programs, wherein the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods described above.
[0114] To better illustrate this method, a specific example will be used below for further explanation:
[0115] Five cascade reservoirs distributed in different river basins were selected as examples, denoted as Cascade Reservoir A to Cascade Reservoir E. The leading reservoir in each of the five cascade reservoirs is an annual regulating reservoir, and each downstream includes a bend-cutting hydroelectric power station. All five water intakes are run-of-river type. The five cascade reservoirs exhibit significant differences in river scale, reservoir capacity, dry season inflow and outflow, dry season ecological flow requirements, and guaranteed power output levels, covering the typical application scenarios of this method.
[0116] Basic parameters of cascade reservoirs:
[0117] The basic parameters of each cascade reservoir are shown in Table 2.
[0118] Table 2 Basic parameters of the five cascade reservoirs
[0119]
[0120] In Table 2, This refers to the available flow during the dry season. The multi-year average inflow during the dry season for each cascade reservoir. Xingli Storage Capacity And the dry season duration (When substituting into the formula, it needs to be converted to seconds) Data are taken from hydrological stations, reservoir design documents, and hydrological phased results for the corresponding watersheds; dry season ecological flow requirements. Taken from the environmental impact assessment approval; ensuring the power generation flow corresponding to the output. Taken from power plant design documents.
[0121] Cascade Reservoir A is located in the middle reaches of a medium-sized river. The headwater reservoir has a beneficial storage capacity of 520 million m³, a dry season of 182 days, and an average annual inflow of 55.0 m³ / s during the dry season. The bend-cutting hydropower station utilizes a bend in the river, straightening the bend through a water diversion tunnel. The required ecological flow in the reduced-flow section during the dry season is 19.0 m³ / s, ensuring a power generation flow of 40.0 m³ / s to match the output. < .
[0122] Cascade Reservoir B is located in a high mountain canyon section upstream, where the river channel has a high meander rate. The basin is rich in fish resources, and the environmental impact assessment approval requires a high ecological flow during the dry season, reaching 35.0 m³ / s, while the corresponding power generation flow to guarantee output is only 26.0 m³ / s. > .
[0123] Cascade Reservoir C is located in the middle reaches of a small river, where water inflow is low during the dry season. The average annual inflow during the dry season is only 20.0 m³ / s, while the reservoir's beneficial storage capacity is 160 million m³, and the dry season lasts for a relatively long period of 212 days. + =12.0+22.0=34.0m³ / s, which exceeds the dry season's available flow of 28.74m³ / s. The dry season's water inflow cannot simultaneously meet both ecological and power generation needs.
[0124] Cascade Reservoir D is located in the middle reaches of a large river with abundant water inflow. The average inflow during the dry season is 145.0 m³ / s, and the head reservoir has a usable storage capacity of 1.55 billion m³, providing ample regulation capacity. Although the guaranteed power generation flow is as high as 55.0 m³ / s, the available flow during the dry season is still 243.57 m³ / s, indicating that the water supply and demand imbalance is not significant.
[0125] Cascade Reservoir E is located in the middle and upper reaches of a medium-sized river. The inflow during the dry season is 30.0 m³ / s, the effective storage capacity of the headwater reservoir is 220 million m³, and the dry season lasts 185 days. + =36.0m³ / s, and the available flow rate during the dry season is 43.76m³ / s, which is greater than the rigid water demand. However, the dry season scheduling space of the cascade reservoirs is only 7.76m³ / s, which is very small.
[0126] The following describes the specific treatment process for three typical scenarios: cascade reservoirs A and C. The treatment processes for cascade reservoirs D and E are the same as these three scenarios, and will not be repeated here.
[0127] Using cascade reservoir A as an example, the demonstration... < The calculation process for each step.
[0128] Following step one, based on =55.0m³ / s =5.20×10 8 m³ =182 days, available flow during the dry season =88.07m³ / s.
[0129] Following step two, determine the rigid water demand during the dry season for the two types of reservoirs. For the reference reservoir, the tailwater from power generation is directly discharged into the downstream river channel and can be included in the ecological flow; the rigid water demand is max(19.0, 40.0) = 40.0 m³ / s. For the cascade reservoir, the ecological flow is discharged downstream to the reduced-flow section via the intake hub, while the power generation flow is diverted to the power station via the diversion tunnel. These two paths are independent, and the water volume cannot be shared; the rigid water demand is 19.0 + 40.0 = 59.0 m³ / s. The difference between the two is 19.0 m³ / s, which is exactly equal to the dry season ecological flow requirement. This difference of 19.0 m³ / s represents the additional water demand caused by the bend-cutting diversion pattern, which transforms the ecological flow from a shared item to an independent consumption item.
[0130] Following step three, refer to the reservoir's dry season scheduling capacity. =88.07-40.0=48.07m³ / s, the dry season scheduling space of cascade reservoirs =88.07 - 59.0 = 29.07 m³ / s. Scheduling space loss. =min(19.0,40.0)=19.0m³ / s.
[0131] Follow step four. > + The calculation conditions are met, and the dry season scheduling space ratio is calculated. ,at this time The water diversion pattern of the bend-cutting design allows the dry season scheduling space of cascade reservoir A to retain 60.5% of that of the reference reservoir, while 39.5% of the space is lost due to the inability to share water volume.
[0132] A comparison of dry season water distribution under the two types of cascade reservoir patterns (see below) Figure 2 .
[0133] Using cascade reservoir B as an example, the demonstration... > The calculation process is explained in detail, focusing on the value rule of scheduling space loss.
[0134] Dry season available flow of cascade reservoir B =98.71 m³ / s. The rigid water demand of the reference reservoir is max(35.0,26.0) = 35.0 m³ / s, and the rigid water demand of the cascade reservoirs is 35.0 + 26.0 = 61.0 m³ / s.
[0135] Scheduling space loss =min(35.0,26.0)=26.0m³ / s, which equals the power generation flow rate corresponding to the guaranteed output, rather than the ecological flow requirement during the dry season. The reason is that, in the reference reservoir, the rigid water demand flow rate is relatively large. =35.0 m³ / s control, =26.0 m³ / s is included; in the cascade reservoirs, the power generation flow must be diverted independently through the water diversion tunnel, and the water volume no longer shares the ecological flow path, with the additional consumption exactly equal to =26.0m³ / s.
[0136] Therefore, it can be seen that the scheduling space loss is always equal to and The smaller value in the middle means that the scheduling space loss is entirely determined by the water distribution relationship under the bend-cutting water diversion pattern, and is not affected by the inflow conditions and reservoir size.
[0137] calculate Compared with cascade reservoir A, =0.592 is slightly lower than 0.605, indicating a slightly higher degree of structural compression. A comparison of dry season water distribution under the two types of cascade reservoir patterns (see...) Figure 3 .
[0138] Taking cascade reservoir C as an example, this paper demonstrates the determination process when the dry season scheduling space is insufficient (the available flow in the dry season is not greater than the rigid water demand flow of the cascade reservoir in the dry season).
[0139] Dry season available flow of cascade reservoir C =28.74 m³ / s, the rigid water demand during the dry season of the cascade reservoirs + =12.0+22.0=34.0m³ / s. < + During the dry season, the available flow is insufficient to simultaneously meet the minimum requirements of ecological flow in the reduced-water section and power generation flow in the water diversion tunnel, with a shortfall of 5.26 m³ / s.
[0140] Dry season scheduling space =28.74-34.0=-5.26m³ / s≤0, directly listed as a special evaluation object, the dry season scheduling space ratio is not calculated. .
[0141] In comparison, the reference reservoir, under the same inflow and storage capacity conditions, has a spatial density of 28.74 - 22.0 = 6.74 m³ / s, which is still positive. It is precisely the non-shared water volume effect caused by the bend-cutting water diversion pattern that pushes the cascade reservoir C from a barely positive spatial density to a state of insufficient spatial density, with the consequences of structural compression being particularly pronounced. The dry season supply-demand imbalance of cascade reservoir C is shown in [reference needed]. Figure 4 .
[0142] The above process was performed on five cascade reservoirs to demonstrate the function of quickly sorting the degree of structural compression caused by the water diversion pattern between multiple cascade reservoirs. The calculation results for each cascade reservoir are summarized in Table 3.
[0143] Table 3. Analytical Calculation Results and Screening Ranking of Five-Tier Reservoirs
[0144]
[0145] In Table 3, all columns representing flow rates are in m³ / s. and These are the dry season rigid water demand flows for the reference reservoir and the cascade reservoirs, respectively.
[0146] The dry season available flow of cascade reservoir C is insufficient to cover the rigid water demand of the cascade reservoirs, and it is directly listed as the highest priority. The dry season scheduling space ratio of cascade reservoir E is only 0.327, retaining only about one-third of the space of the reference reservoir, indicating significant structural compression, and it is listed as the second priority. The space ratios of cascade reservoirs B and A are 0.592 and 0.605 respectively, with moderate structural compression, and they are ranked third and fourth respectively. Cascade reservoir D has abundant inflow and ample storage capacity, with a space ratio of 0.852, and its structural compression has limited impact, so it is ranked last.
[0147] The above sorting requires only five parameters that can be directly obtained from existing engineering data, and all calculations are completed within milliseconds, eliminating the need to establish scheduling models or run numerical simulations for any cascade reservoirs. The sorting and simulation verification results of the five cascade reservoirs are shown below. Figure 5 .
[0148] To verify the rationality of the ranking conclusions, a separate comparison was conducted using traditional long-sequence numerical simulation methods. The Thomas-Fiering autoregressive model is a commonly used method in hydrological synthetic runoff generation, generating synthetic sequences with similar statistical characteristics based on historical runoff statistical parameters. The simulation used the Thomas-Fiering autoregressive model to generate a 1000-year dry season daily synthetic runoff sequence, with a sequence length of 1000 years to ensure the stability of statistical indicators. For each cascade reservoir, the dry season rigid water demand of both types of reservoirs was used as the water demand target, and the storage and release process of the leading reservoir was simulated daily. Reliability indicators... Defined as the proportion of days during the simulation period where the water demand during the dry season is met out of the total number of days in the dry season, representing the difference in reliability between the two types of reservoirs. The simulation results reflect the impact of the bend-cutting water diversion pattern on water supply security. Table 4 shows the simulation results.
[0149] Table 4 Comparison and verification of analytical method and traditional simulation method
[0150]
[0151] Arranged from highest to lowest reliability, the five cascade reservoirs are in the order of C, E, B, A, D. This order corresponds to the spatial ratio of the reservoirs scheduled during the dry season as described in this method. The order from smallest to largest is consistent.
[0152] The simulation results are consistent with the analytical method's assessment of the severely compressed cascade reservoirs. The reliability of the bend-cutting water diversion in cascade reservoir C is only 0.6209, far lower than the reference reservoir's 0.9922, with a reliability difference of 0.3713. This fully verifies the rationality of the analytical method's assessment of it as having insufficient space and classifying it as the highest level of special evaluation object. The reliability of the bend-cutting water diversion in cascade reservoir E drops to 0.9824, with a reliability difference of 0.0175, ranking second among the five cascade reservoirs, consistent with the strained state reflected by the space ratio of 0.327.
[0153] For the cascade reservoirs B, A, and D with relatively ample space, the reliability of both types of configurations is close to 1.0, and the difference in reliability is close to zero (0.0010, 0.0007, and 0.0000, respectively). Simulation methods can hardly provide effective differentiation in this range. However, the dry season scheduling space ratio provided by this method still maintains a clear gradient (0.592, 0.605, and 0.852) in the same range, which can directly reflect the relative differences in the degree of structural compression of each cascade reservoir. This characteristic allows this method to still play a screening role in the range with ample scheduling space: even in the range with ample scheduling space where the differentiation of simulation methods is insufficient, it can still provide meaningful ranking criteria.
[0154] In terms of computational efficiency and complexity, the analytical method completes all calculations for the five cascade reservoirs within milliseconds. Traditional simulation methods require generating runoff sequences for each cascade reservoir and simulating them daily. The computational efficiency for the five cascade reservoirs is significantly lower than that of the analytical method, differing by more than three orders of magnitude. The efficiency advantage of this method is prominent.
[0155] The five cascade reservoirs (cascade reservoirs A to E) underwent self-inspection and sorting correction in steps S5 and S7 respectively. The parameter standard deviation values are shown in Table 5. During the evaluation process, the parameters were mutually independent, that is, the covariance matrix was diagonalized, and all off-diagonal elements σ xi,xj Set to zero; the significance threshold in step S7 is set to α=0.10.
[0156] Table 5 Standard deviation values of parameters for cascade reservoirs
[0157]
[0158] Of the above values, σ Qeco / Q eco =15% is the maximum, which corresponds to the objective reality that ecological flow varies greatly among different calculation methods; σ V / V=2% minimum reflects the high-precision attribute of the beneficial storage capacity as a core indicator of reservoir design.
[0159] Following step S5, calculate the five first-order partial derivatives and corresponding elasticity coefficients for each of the cascade reservoirs A, B, D, and E. The output of the elasticity coefficients for each cascade reservoir is within floating-point precision (10⁻⁶). -16Within the order of magnitude, two self-checking identities are used. and ;according to Calculate the variance of the dry season scheduling space ratio and construct ±2σ. R Robustness intervals, results are shown in Table 6.
[0160] Table 6. Sensitivity-robustness assessment results of the five-stage reservoirs.
[0161]
[0162] Cascade reservoir C is a special object identified in the original step S5 and is not included in the sensitivity and robustness assessment.
[0163] σ of cascade reservoirs A, B and D R The / R values are approximately 11.9%, 9.2%, and 2.9%, respectively, indicating that the dry season scheduling space ratio of these three cascade reservoirs is limited by parameter uncertainty, and the value ranking given by this method has high stability; the σ of E for the cascade reservoirs R The R value is approximately 38.5%, and the robustness interval [0.075, 0.578] has exceeded its R value, indicating that this cascade reservoir is most sensitive to parameter disturbances.
[0164] The order reversal probability of key cascade reservoir pairings was calculated in step S7, and the results are shown in Table 7.
[0165] Table 7. Order reversal probability of cascade reservoir pairings
[0166]
[0167] At a significance threshold of α = 0.10, the P-values of steps A and B are... rev ≈0.4434 significantly exceeds α, indicating that the two are indistinguishable in ranking and should be merged into the same priority group; the P of tier E relative to A and B rev All are no more than 0.0276 and are strictly distinguishable; the P of step A relative to D is... rev Even at 0.0006, it is strictly distinguishable. The final screening priority order after step S7 is C→E→{A,B}→D, which is different from the order C→E→B→A→D obtained by only taking the value of the dry season scheduling space ratio in step S6, which merges A and B into the same priority level, and the overall priority is reduced from five levels to four levels.
[0168] The above conclusions cross-validate with the traditional long-sequence simulation results in Table 4 of the original manual: the reliability difference between the bend-cutting water diversion conditions of cascades A and B in Table 4 is only 0.0003. Traditional methods require a complete simulation run to identify such a small difference, while this method only uses the analytical gradient and parameter standard deviation as inputs and simultaneously provides the order reversal probability during the planning stage, avoiding the potentially accuracy-affected ranking conclusion of B being ranked third and A fourth based solely on the dry season scheduling space ratio. Meanwhile, in Table 7, the P of cascade D relative to A... rev Only 0.0006, the distance between step E and A and B is P rev The conclusion that all values are strictly distinguishable (less than 0.03) is also in complete agreement with the relative magnitude of the corresponding reliability differences in Table 4, verifying the reliability of the method for screening and ranking structural compression levels.
[0169] In this embodiment, all calculations in steps S5 and S7 are completed within milliseconds, maintaining an efficiency advantage of more than three orders of magnitude compared to the original traditional simulation scheme, while also providing additional sorting reliability information.
Claims
1. A method for quantifying and analyzing the structural compression of the dry season scheduling space of cascade reservoirs, wherein the cascade reservoirs include one headwater reservoir and one run-of-river bend-cutting hydroelectric power station, the headwater reservoir being an annual regulating reservoir, characterized in that, Includes the following steps: S1. Determine the available flow rate of the cascade reservoirs during the dry season based on the design parameters of the head reservoir and its hydrological characteristics during the dry season. S2. Obtain the dry season ecological flow demand and the guaranteed power generation flow demand of the cascade reservoirs, and construct a reference reservoir. The power station in the reference reservoir is a dam-type power station, and the rest is the same as the cascade reservoirs. Determine the rigid water demand flow of the cascade reservoirs and the reference reservoir in the dry season according to the two flow demands. S3. Calculate the difference between the available flow of the cascade reservoirs during the dry season and the rigid water demand flow of the reference reservoir and the cascade reservoirs during the dry season, and use them as the dry season scheduling space of the reference reservoir and the cascade reservoirs respectively. S4. When the available flow rate is greater than the rigid water demand flow rate of the cascade reservoir, the dry season scheduling space ratio is obtained based on the dry season scheduling space of the cascade reservoir and the dry season scheduling space of the reference reservoir to characterize the degree of structural compression; otherwise, the cascade reservoir is treated as a special evaluation object. S5. Calculate the elasticity coefficients of the independent variable parameters in the formula for calculating the dry season scheduling space ratio. Check the calculation results according to the identity that the elasticity coefficients should satisfy. If the corresponding identity is not satisfied, re-check and correct the previous calculation results until the corresponding identity requirements are met. S6. For multiple cascade reservoirs, perform the above steps respectively, and sort them from small to large based on the dry season scheduling space ratio of each cascade reservoir. For special assessment objects, their dry season scheduling space ratio is regarded as the minimum value. The higher the ranking, the greater the structural compression of the cascade reservoir. S7. For any two cascade reservoirs, calculate the probability of their ranking being reversed based on the difference in their dry season scheduling space ratio and their respective variances. When the probability exceeds a preset significance threshold, determine that their rankings are indistinguishable and rank them in parallel, thus correcting the ranking obtained in step S6.
2. The method according to claim 1, characterized in that: In step S1, the design parameters of the headwater reservoir are the beneficial storage capacity, and the hydrological characteristic parameters include the multi-year average inflow during the dry season and the duration of the dry season.
3. The method according to claim 2, characterized in that: The available flow rate of the cascade reservoirs during the dry season is calculated according to the following formula. ， Where W represents the available flow rate of the cascade reservoirs during the dry season. V represents the multi-year average inflow to the Longtou Reservoir during the dry season, and V represents the beneficial storage capacity of the Longtou Reservoir. This refers to the dry season.
4. The method according to claim 3, characterized in that: In step S4, the dry season scheduling space ratio is the ratio of the dry season scheduling space of the cascade reservoirs to the dry season scheduling space of the reference reservoir, and the specific expression is as follows: ， Where R is the dry season scheduling space ratio. and These are the dry season ecological flow requirements of the cascade reservoirs and the flow requirements to ensure power generation.
5. The method according to claim 1, characterized in that: The dry season ecological flow demand and the guaranteed power generation flow demand are both based on their preset flow values during the dry season, without considering the changes in each month during the dry season.
6. The method according to claim 1, characterized in that: The cascade reservoirs have a water intake hub below the headwater reservoir. The outflow from the headwater reservoir is equal to the inflow from the water intake hub. The outflow from the water intake hub is diverted to the reduced-water section as ecological flow supply and to the bend-cutting hydropower station as power generation flow supply.
7. The method according to claim 4, characterized in that, The identity that the elastic coefficient should satisfy in step S5 is: ， ， in, , , , and V, respectively , , and The elastic modulus; The elastic coefficients corresponding to each parameter are calculated using the following formula. ， Where x is V, , , and In any of them, Ex is the elastic coefficient corresponding to x.
8. The method according to claim 7, characterized in that: The probability of the order of the two cascade reservoirs being reversed in step S7 is calculated according to the following formula: ， Among them, P rev Let Φ be the probability of a reversal in the ranking of two cascade reservoirs, Φ be the standard normal cumulative distribution function, and R be the probability of a reversal. i and R j These are the dry season scheduling space ratios for the i-th and j-th cascade reservoirs, respectively; and denoted as , respectively, are the standard deviations of the dry season scheduling space ratios for the i-th and j-th cascade reservoirs.
9. A structural compression quantification and analytical screening system for the dry season scheduling space of cascade reservoirs, wherein the cascade reservoirs include one headwater reservoir and one run-of-river bend-cutting hydroelectric power station, the headwater reservoir being an annual regulating reservoir, characterized in that, include: Available flow determination module: used to determine the available flow of cascade reservoirs during the dry season based on the design parameters of the head reservoir and its hydrological characteristics during the dry season; Rigid water demand determination module: used to obtain the dry season ecological flow demand and the flow demand to ensure power generation of cascade reservoirs, and to construct a reference reservoir. The power station in the reference reservoir is a dam-type power station, and the rest is the same as the cascade reservoir. The rigid water demand of cascade reservoirs and reference reservoirs in the dry season is determined according to the two flow demands. Dry season scheduling space confirmation module: used to calculate the difference between the available flow of the cascade reservoir in the dry season and the rigid water demand flow of the reference reservoir and the cascade reservoir in the dry season, which are respectively used as the dry season scheduling space of the reference reservoir and the cascade reservoir. Dry season scheduling space ratio confirmation module: When the available flow is greater than the rigid water demand of the cascade reservoir, it obtains the dry season scheduling space ratio, which is used to characterize the degree of structural compression, based on the dry season scheduling space of the cascade reservoir and the dry season scheduling space of the reference reservoir; otherwise, the cascade reservoir is treated as a special evaluation object. Self-checking module: Used to calculate the elasticity coefficients of the independent variable parameters in the formula for calculating the dry season scheduling space ratio, and to self-check the calculation results according to the identity that the elasticity coefficients should satisfy. If the corresponding identity is not satisfied, the previous calculation results are re-checked and corrected until the corresponding identity requirements are met. Screening module: This module is used to execute the above modules for multiple cascade reservoirs. Based on the dry season scheduling space ratio of each cascade reservoir, the reservoirs are sorted from smallest to largest. For special assessment objects, their dry season scheduling space ratio is regarded as the minimum value. The higher the ranking, the greater the structural compression of the cascade reservoir. Correction module: For any two cascade reservoirs, based on the difference in their dry season scheduling space ratio and their respective variances, calculate the probability that their rankings will be reversed; when the probability exceeds a preset significance threshold, determine that their rankings are indistinguishable and sort them in parallel, thus correcting the ranking obtained by the screening module.
10. A computer-readable storage medium for storing one or more programs, characterized in that: The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods according to claims 1 to 8.