A reservoir dispatching scheme extraction method, system, device and storage medium

Abstract

The present invention discloses a reservoir dispatching scheme extraction method, system, device and storage medium, including: obtaining meteorological data and surface data, determining the average water withdrawal rate before dispatching of the downstream river of the reservoir according to the surface data, determining the average water withdrawal rate after dispatching, determining the probability density function of the steady-state flow of the river before dispatching according to the meteorological data and the average water withdrawal rate before dispatching, determining the probability density function of the steady-state flow of the river after dispatching according to the meteorological data and the average water withdrawal rate after dispatching, establishing a river ecological objective function according to the probability density function of the steady-state flow of the river before dispatching and the probability density function of the steady-state flow of the river after dispatching, establishing a preset objective function and constraint conditions of the reservoir, iteratively optimizing according to the river ecological objective function, the preset objective function, the constraint conditions, the preset multi-objective optimization algorithm and the dispatching function with unknown parameters, and obtaining a reservoir dispatching scheme. The present invention can reflect the random characteristics of ecological flow and reduce the "dimensionality curse" problem, and can be applied to the technical field of reservoir dispatching.

Description

Technical Field

[0001] The present invention relates to the technical field of reservoir dispatching, and in particular to a reservoir dispatching scheme extraction method, system, device and storage medium. Background Art

[0002] In order to reduce the adverse effects of reservoir operation on river ecosystems, it is necessary to consider the river ecological flow demand during reservoir operation, that is, to incorporate ecological operation targets into the formulation of reservoir operation plans. Domestic and foreign reservoir ecological operation mainly considers ecological flow indicators in objective functions or constraints. Commonly used ecological flow indicators can be obtained through Tennant method, Qp method, Hydrological Index Methods (HIM), Range Variability Approach (RVA), etc. Ecological flow calculation methods represented by the Tennant method and the Qp method target fixed ecological flow values ​​and ignore the random characteristics of river flow processes. Methods such as HIM and RVA quantify ecological flow indicators from five aspects: flow, frequency, duration, occurrence time, and rate of change, which can more comprehensively reflect the characteristics of river ecological flow. However, when calculating ecological flow, the selection and weight determination of each ecological flow indicator are subject to greater subjective influence. Taking all indicators into account in the scheduling target will cause "dimensionality disaster", which increases the difficulty in practical application. In order to avoid the "dimensionality disaster" problem, some studies only select some HIM indicators in the ecological scheduling calculation, which cannot fully reflect the random characteristics of ecological flow. Summary of the invention

[0003] In order to solve one of the above problems, the purpose of the present invention is to provide a reservoir scheduling scheme extraction method, system, device and storage medium, which can fully reflect the random characteristics of ecological flow and reduce the "dimensionality curse" problem.

[0004] In one aspect, the present invention provides a method for extracting a reservoir scheduling plan, comprising the following steps:

[0005] Obtain meteorological data and surface data, determine the average water withdrawal rate of the river downstream of the reservoir before dispatching based on the surface data, and determine the average water withdrawal rate of the river downstream of the reservoir after dispatching;

[0006] Determine the probability density function of the steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling, and determine the probability density function of the steady-state flow of the river after scheduling according to the meteorological data and the average water withdrawal rate after scheduling;

[0007] Establishing a river ecological objective function according to the probability density function of the steady-state flow of the river before the dispatch and the probability density function of the steady-state flow of the river after the dispatch;

[0008] Establish preset objective functions and constraints of the reservoir, perform iterative optimization based on the river ecological objective function, the preset objective function, the constraints, the preset multi-objective optimization algorithm and the scheduling function with unknown parameters, and obtain a reservoir scheduling plan.

[0009] Optionally, the meteorological data includes average rainfall depth and net rain event frequency, and the acquiring of meteorological data specifically includes:

[0010] Obtain observed daily rainfall, daily rainfall frequency, and evapotranspiration data;

[0011] The average rain depth is obtained according to the daily rainfall, and the net rain event frequency is obtained according to the daily rainfall frequency, evapotranspiration data and the average rain depth.

[0012] Optionally, establishing a river ecological objective function according to the probability density function of the steady-state flow of the river before the scheduling and the probability density function of the steady-state flow of the river after the scheduling specifically includes:

[0013] The pre-dispatch probability of the steady-state flow of the downstream river being within the preset flow range is obtained according to the probability density function of the steady-state flow of the river before the dispatch;

[0014] The probability of the steady-state flow of the downstream river being within the preset flow range after scheduling is obtained according to the probability density function of the steady-state flow of the river after scheduling;

[0015] A flow steady-state instability index is obtained according to the pre-scheduling probability and the post-scheduling probability, and a river ecological objective function is established with the instability index minimized.

[0016] Optionally, the preset objective function includes a water supply objective function and a power generation objective function, and the preset objective function for establishing a reservoir specifically includes:

[0017] Obtain the average water supply flow, target water supply flow, number of water supply periods, number of water supply periods that meet the target water supply flow, and total reservoir output during the preset period;

[0018] The maximum damage depth is obtained according to the average water supply flow rate and the target water supply flow rate, and the water supply guarantee rate is obtained according to the number of water supply time periods and the number of water supply satisfaction time periods;

[0019] Establishing a water supply objective function of the reservoir according to the maximum damage depth and the water supply guarantee rate;

[0020] A power generation objective function is constructed according to the total output of the reservoir during the preset time period.

[0021] Optionally, the constraint conditions include water balance constraint, water level constraint, output constraint and downstream flow constraint. Establishing the constraint conditions specifically includes:

[0022] Establish water balance constraints based on the reservoir's inflow, outflow, and initial waterway capacity;

[0023] The water level of the reservoir is constrained within a preset water level range to obtain a water level constraint;

[0024] The power generation output of the reservoir is constrained within a preset output range to obtain an output constraint;

[0025] The discharge flow constraint is obtained by making the reservoir discharge flow less than the maximum discharge capacity.

[0026] Optionally, the iterative optimization is performed according to the river ecological objective function, the preset objective function, the constraint conditions, the preset multi-objective optimization algorithm and the scheduling function with unknown parameters to obtain the reservoir scheduling plan, which specifically includes:

[0027] Taking the river ecological objective function and the preset objective function as the optimization objectives of the preset multi-objective optimization algorithm, the unknown parameters of the scheduling function with unknown parameters are iteratively optimized to obtain a multi-objective non-inferior solution set of the unknown parameters;

[0028] An optimal solution is determined from a multi-objective non-inferior solution set according to constraint conditions, and the optimal solution is substituted into the scheduling function with unknown parameters to obtain the reservoir scheduling plan.

[0029] On the other hand, the present invention provides a reservoir scheduling scheme extraction system, comprising a first module, a second module, a third module and a fourth module, wherein:

[0030] The first module is used to obtain meteorological data and surface data, determine the average water withdrawal rate of the river downstream of the reservoir before scheduling according to the surface data, and determine the average water withdrawal rate of the river downstream of the reservoir after scheduling;

[0031] The second module is used to determine the probability density function of the steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling, and to determine the probability density function of the steady-state flow of the river after scheduling according to the meteorological data and the average water withdrawal rate after scheduling;

[0032] The third module is used to establish a river ecological objective function according to the probability density function of the steady-state flow of the river before the scheduling and the probability density function of the steady-state flow of the river after the scheduling;

[0033] The fourth module is used to establish the preset objective function and constraints of the reservoir, and perform iterative optimization based on the river ecological objective function, the preset objective function, the constraints, the preset multi-objective optimization algorithm and the scheduling function with unknown parameters to obtain a reservoir scheduling plan.

[0034] In another aspect, the present invention provides a reservoir scheduling scheme extraction device, comprising:

[0035] at least one processor;

[0036] at least one memory for storing at least one program;

[0037] When the at least one program is executed by the at least one processor, the at least one processor implements the method described above.

[0038] In another aspect, the present invention provides a computer-readable storage medium storing a program executable by a processor. When the program executable by the processor is executed by the processor, it is used to perform the method as described above.

[0039] On the other hand, the present invention provides a reservoir dispatching scheme extraction system, comprising a meteorological data acquisition device, an average water withdrawal rate acquisition device, an average water withdrawal rate reasoning device, and a computer device connected to the meteorological data acquisition device, the average water withdrawal rate acquisition device, and the average water withdrawal rate reasoning device; wherein,

[0040] The meteorological data collection device is used to collect the meteorological data and upload the meteorological data to the computer device;

[0041] The average water withdrawal rate collection device is used to collect the average water withdrawal rate before scheduling, and upload the average water withdrawal rate before scheduling to the computer device;

[0042] The average water withdrawal rate inference device is used to infer the average water withdrawal rate after scheduling, and upload the average water withdrawal rate after scheduling to the computer device;

[0043] The computer device comprises:

[0044] at least one processor;

[0045] at least one memory for storing at least one program;

[0046] When the at least one program is executed by the at least one processor, the at least one processor implements the method described above.

[0047] Implementation of the present invention includes the following beneficial effects: the present invention obtains meteorological data and surface data, determines the average water withdrawal rate of the river downstream of the reservoir before scheduling according to the surface data, determines the surface number of the river downstream of the reservoir after scheduling, determines the probability density function of the steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling, determines the probability density function of the steady-state flow of the river after scheduling according to the meteorological data and the average water withdrawal rate after scheduling, establishes a river ecological objective function according to the probability density function of the steady-state flow of the river before scheduling and the probability density function of the steady-state flow of the river after scheduling, establishes a preset objective function and constraints of the reservoir, performs iterative optimization according to the river ecological objective function, the preset objective function, the constraints, the preset multi-objective optimization algorithm and the scheduling function with unknown parameters, obtains a reservoir scheduling plan, and establishes a reservoir ecological scheduling target according to maintaining the probability density function of the steady-state flow of the river. The steady-state flow probability density function characterizes the steady-state flow characteristics of a river. For a river, as the time series prolongs, the statistical characteristics of the flow will tend to be stable. Therefore, the steady-state flow probability density function of a river is a statistical description of the long-term hydrological situation of the river flow. Reservoir regulation is carried out in an ecological regulation mode that maintains the basic form of the steady-state flow of the river. In non-traditional ecological regulation, a fixed ecological flow or multiple indicators are used to determine the ecological flow in a time period as the target. Instead, the objective function of the scheduling scheme is established based on the probability of the downstream river reaching a stable ecological flow within a period of time after a certain scheduling scheme is adopted. This ensures the random characteristics of the ecological flow process and avoids the "curse of dimensionality" in ecological regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a flow chart of steps of a reservoir dispatching scheme extraction method provided by the present invention;

[0049] Figure 2 It is a structural schematic diagram of a reservoir dispatching scheme extraction system provided by the present invention;

[0050] Figure 3 It is a flow chart of steps for obtaining meteorological data provided by the present invention;

[0051] Figure 4 It is a flow chart of steps for establishing a river ecological objective function provided by the present invention;

[0052] Figure 5 It is a structural schematic diagram of another reservoir dispatching scheme extraction system provided by the present invention;

[0053] Figure 6 It is a structural schematic diagram of a reservoir scheduling scheme extraction device provided by the present invention. DETAILED DESCRIPTION

[0054] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only provided for the convenience of explanation and description, and the order between the steps is not limited in any way. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0055] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms of "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0056] When the following description relates to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims. In the description of the present application, it is necessary to understand that the terms "first / S100", "second / S200", "third / S300", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0057] like Figure 1 As shown, Figure 1 The invention provides a method for extracting a reservoir scheduling scheme, comprising the following steps:

[0058] S100, obtaining meteorological data and surface data, determining the average water withdrawal rate of the river downstream of the reservoir before dispatching according to the surface data, and determining the average water withdrawal rate of the river downstream of the reservoir after dispatching.

[0059] Among them, meteorological data include but are not limited to the average rainfall depth and net rain event frequency of the basin, and surface data include but are not limited to soil data, vegetation data and terrain data of downstream rivers.

[0060] The average drainage rate can be obtained through soil data, vegetation data and terrain data, for example, the average drainage rate = the average length of the non-ditch path / the scale velocity representing the average hydraulic conductivity of the underground environment.

[0061] Specifically, meteorological data can be obtained based on the historical rainfall data of the basin. The average rainfall depth and net rain event frequency of the basin are characteristics obtained based on the statistics of historical rainfall data, which remain unchanged before and after the scheduling.

[0062] When constructing the probability density function, the average water withdrawal rate before and after scheduling is different. The average water withdrawal rate k′ after scheduling can be determined by the following method: First, the average water withdrawal rate k′ after scheduling is taken as an unknown variable k′ 未知 Substituting into formula (1):

[0063]

[0064] Then, the historical downstream river flow data is used to fit formula (1) to determine the variable k′ 未知 The value of is taken as the average water withdrawal rate k′.

[0065] S200. Determine a probability density function of a steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling, and determine a probability density function of a steady-state flow of the river after scheduling according to the meteorological data and the average water withdrawal rate after scheduling.

[0066] Among them, for a river, before and after rainfall or reservoir regulation, as the time series is extended, the statistical characteristics of the flow will tend to be stable, and the river flow has a range of variation rather than a specific value. The present invention does not directly take a fixed ecological flow as the steady-state flow, but considers the probability of the river downstream of the reservoir reaching a certain flow range before and after the reservoir regulation, and characterizes the steady-state characteristics of the downstream river through the river steady-state flow probability density function (Probability Density Function, PDF), which represents the probability of a specific flow or a certain flow range.

[0067] Specifically, the net rainfall event frequency that can cause river flow is obtained as λ[T -1 ] and the average rainfall depth α[L], where T represents the dimension of time and L represents the dimension of length. At the same time, assuming that the basin behaves as a linear reservoir, the average water withdrawal rate is k[T -1 ], the average water withdrawal rate can be but is not limited to the average water withdrawal rate. According to formula (2), the downstream river flow Q[L 3 T -1 The probability density function p(Q) of the steady-state flow of the river before the regulation of ] is:

[0068]

[0069] where Γ(x) is the gamma function of the variable x.

[0070] The average water withdrawal rate after the scheduling is determined to be k′. According to formula (3), the flow rate Q[L 3 T -1 ]The probability density function of steady-state flow of the river after regulation p′(Q):

[0071]

[0072] S300, establishing a river ecological objective function according to the probability density function of the steady-state flow of the river before the scheduling and the probability density function of the steady-state flow of the river after the scheduling.

[0073] Specifically, the pre-scheduling probability of the steady-state flow of the downstream river within the preset flow range is obtained according to the probability density function of the steady-state flow of the river before scheduling; the post-scheduling probability of the steady-state flow of the downstream river within the preset flow range is obtained according to the probability density function of the steady-state flow of the river after scheduling; the flow steady-state instability index is obtained according to the pre-scheduling probability and the post-scheduling probability, and the river ecological objective function is established with the minimum instability index.

[0074] S400, establishing a preset objective function and constraint conditions for the reservoir, performing iterative optimization based on the river ecological objective function, the preset objective function, the constraint conditions, a preset multi-objective optimization algorithm and a scheduling function with unknown parameters, and obtaining a reservoir scheduling plan.

[0075] The preset objective function may include but is not limited to a water supply objective function and a power generation objective function.

[0076] Constraints include, but are not limited to, water balance constraints, water level constraints, output constraints, and downstream flow constraints.

[0077] The preset multi-objective optimization algorithm may be, but is not limited to, a NSGAII multi-objective optimization algorithm, a particle swarm optimization algorithm, a taboo search algorithm, and the like.

[0078] The determination of the reservoir outflow depends on the inflow, reservoir storage and time period information during the period. The scheduling function with unknown parameters is shown in formula (4):

[0079] Q out (t) = f(Q in (t),V(t),t;θ) (4)

[0080] Among them, Q in (t) is the inflow of the reservoir during period t, Q out (t) is the outflow of the reservoir during period t, and its dimension is [L 3 T -1 ]; V(t) is the reservoir water storage at the beginning of period t, and its dimension is [L 3 ]; θ is the parameter of the scheduling function, which is related to the ecological flow of the downstream rivers.

[0081] Specifically, the dispatching plan includes but is not limited to the outflow flow Q of the reservoir during period t out (t), the parameter θ of the dispatching function is related to the flow received by each downstream river, the reservoir output and other parameters.

[0082] In some embodiments, considering the periodic variation of precipitation and temperature within a year, the historical rainfall data can be divided into annual periods based on the characteristics of precipitation and temperature in the basin, and the steady-state PDF of river flow in each period can be studied separately. For example, according to the four seasons of the year, for each season, the probability density function p of the steady-state flow of the river before scheduling is i (Q) is shown in formula (5):

[0083]

[0084] Among them, i represents the i-th period. For example, if the year is divided into installments according to seasons, i represents the season, then i∈[1,4].

[0085] Correspondingly, the probability density function of the steady-state flow of the river after regulation is i ′(Q) is shown in formula (6):

[0086]

[0087] It is worth noting that k i ′ is the average water withdrawal rate after the operation of the i-th period according to the fitted curve and the predicted reservoir operation plan. It is necessary to ensure that the core characteristics of the river flow morphology after the reservoir operation will not change, that is, the relative relationship between λ and k in formulas (5) and (6) remains unchanged. For example, in p i (Q) has λ i >k i , then in p i ′(Q) still maintains λ i >k i ′(Reservoir operation only changes the value of parameter k).

[0088] In some embodiments, Figure 2 As shown, Figure 2 The step S100 of obtaining meteorological data specifically includes:

[0089] S110. Obtain observed daily rainfall, daily rainfall frequency, and evapotranspiration data.

[0090] The observed daily rainfall includes the daily rainfall of the river on the same day in several years.

[0091] Evapotranspiration data may be, but are not limited to, soil moisture cross-talk characteristics of climate / soil / vegetation parameters such as mean evapotranspiration rate.

[0092] S120. Obtain an average rain depth according to the daily rainfall, and obtain a net rain event frequency according to the daily rainfall frequency, evapotranspiration data and the average rain depth.

[0093] Among them, evapotranspiration data includes but is not limited to meteorological data such as temperature, wind speed, air pressure, and land surface data such as soil and vegetation.

[0094] Specifically, the average evapotranspiration rate η is obtained based on meteorological data such as temperature, wind speed, and air pressure, and land surface data such as soil and vegetation. The average rain depth is calculated based on the daily rainfall, and the net rain event frequency λ is obtained through formula (7):

[0095]

[0096] where γ(a, b) represents the incomplete gamma function with parameters a and b, η is the average evapotranspiration rate, β is the average rainfall depth after normalization to the available water depth in the plant root zone, and λ is p The frequency of rainfall on this day.

[0097] In some embodiments, Figure 3 As shown, Figure 3 The invention is a flow chart of steps for establishing a river ecological objective function. The step S300 of establishing a river ecological objective function according to the probability density function of the steady-state flow of the river before the scheduling and the probability density function of the steady-state flow of the river after the scheduling specifically includes:

[0098] S310. Obtain the pre-scheduling probability of the steady-state flow of the downstream river within a preset flow range according to the probability density function of the steady-state flow of the river before scheduling.

[0099] Specifically, taking the case of annual phases as an example, by integrating the probability density function of the steady-state flow of the river before scheduling in the preset flow range, the probability of the river in the i-th phase before scheduling in the preset flow range is obtained.

[0100] S320. Obtain the post-scheduling probability that the steady-state flow of the downstream river is within a preset flow range according to the probability density function of the steady-state flow of the river after scheduling.

[0101] Specifically, taking the case of annual phases as an example, by integrating the probability density function of the steady-state flow of the river after scheduling in the preset flow range, the probability of the river in the i-th phase after scheduling in the preset flow range is obtained.

[0102] S330. Obtain a flow steady-state instability index according to the pre-schedule probability and the post-schedule probability, and establish a river ecological objective function with the instability index minimized.

[0103] Specifically, the flow steady-state instability index is shown in formula (8):

[0104]

[0105] Among them, FRI iis the flow steady-state instability index, p i (Q) and p i ′(Q) represents the steady-state flow PDF before and after the impact of reservoir operation in the i-th period of the year.

[0106] In some embodiments, the preset objective function of step S400 includes a water supply objective function and a power generation objective function, wherein the water supply objective function is established by the following method:

[0107] S410, obtaining an average water supply flow rate, a target water supply flow rate, the number of water supply time periods, and the number of water supply time periods required to reach the target water supply flow rate.

[0108] The average water supply flow rate refers to the average water supply flow rate of the river during the water supply period t.

[0109] The target water supply flow rate indicates the flow rate that the river needs to provide during the water supply period t.

[0110] In the i-th period divided into years, the river needs to supply water in a number of time periods, and the total number of water supply time periods is the number of water supply time periods.

[0111] S420. Obtain a maximum damage depth according to the average water supply flow and the target water supply flow, and obtain a water supply guarantee rate according to the number of water supply time periods and the number of water supply satisfaction time periods.

[0112] Specifically, the maximum damage depth represents the ratio of the maximum water shortage to the target water supply flow rate in all water supply periods, as shown in formula (9):

[0113]

[0114] Where Dmax is the maximum damage depth, W(t) is the average water flow rate during period t, and the dimension is [L 3 T -1 ]; W obj is the target water supply flow, the dimension is [L 3 T -1 ].

[0115] The water supply guarantee rate indicates the proportion of time periods that meet the target water supply flow rate in all water supply time periods, as shown in formula (10):

[0116]

[0117] Among them, R is the water supply guarantee rate, N s is the number of time periods during which water supply is sufficient, and its dimension is [T]; T is the total number of time periods, and its dimension is [T].

[0118] S430: Establishing a water supply objective function of the reservoir according to the maximum damage depth and the water supply guarantee rate.

[0119] Specifically, the water supply objective function is established by minimizing the maximum damage depth and maximizing the water supply guarantee rate, as shown in formula (11):

[0120]

[0121]

[0122] Among them, min(x) means taking the minimum value, and max(x) means taking the maximum value.

[0123] The method for establishing the power generation objective function is as follows:

[0124] The total output of the reservoir in each water supply period t is superimposed to obtain the total power generation of the reservoir in all periods T. The power generation objective function is established with the maximum total power generation of the reservoir, as shown in formula (12):

[0125]

[0126] Where E is the total power generation of the reservoir during the dispatch period T, and its dimension is [M·L 2 / T 2 ]; N(t) is the total output of the reservoir in period t (the total output of the reservoir in the preset period), and its dimension is [M·L 2 / T 3 ]; ΔT(t) is the time step of period t (the time step of the preset period), and its dimension is [T].

[0127] In some embodiments, the constraint conditions in step S400 include water balance constraint, water level constraint, output constraint and downstream flow constraint. Establishing the constraint conditions specifically includes:

[0128] S440. Establish a water balance constraint according to the reservoir's inflow, outflow, and initial waterway capacity.

[0129] Specifically, the water balance constraint is shown in formula (13):

[0130] V j (t+1)=V j (t)+(I j (t)-Q j (t))Δt (13)

[0131] Among them, V j (t) is the water demand of reservoir j at the beginning of period t, V j (t+1) is the reservoir water storage at the end of period t, and its dimension is [L 3 ];I j (t) and Q j(t) are the inflow and outflow of reservoir j in period t, respectively, and the dimension is [L 3 T -1 ].

[0132] S450: constraining the water level of the reservoir within a preset water level range to obtain a water level constraint.

[0133] Specifically, the minimum water level and the maximum water level are set, and the water level of the reservoir after scheduling is limited between the minimum water level and the maximum water level to obtain the water level constraint, as shown in formula (14):

[0134] Z j，min ≤Z j (t)≤Z j，max (14)

[0135] Among them, Z j (t) is the water level of reservoir j in period t, with the dimension [L]; Z j，min is the minimum water level allowed in reservoir j during the dispatch period, Z j，max is the maximum water level allowed in reservoir j during the dispatch period.

[0136] S460: Constrain the power generation output of the reservoir within a preset output range to obtain an output constraint.

[0137] Specifically, the minimum output and maximum output are set, and the power generation of the reservoir after scheduling is limited to between the minimum output and the maximum output to obtain the output constraint, as shown in formula (15):

[0138] P j,min ≤P j (t)≤P j,max (15)

[0139] Among them, P j (t) is the output of reservoir j in period t, with the dimension of [M·L2 / T3]; P j,min is the minimum output of reservoir j during the dispatch period, P j,max is the maximum output of reservoir j during the dispatch period, with the dimension of [M·L2 / T3].

[0140] S470, making the outflow of the reservoir less than the maximum outflow capacity to obtain an outflow constraint.

[0141] Specifically, the maximum discharge capacity is set so that the discharge flow of the reservoir is less than the maximum discharge capacity to obtain the discharge flow constraint, as shown in formula (16):

[0142] q j (t)≤q max (Z j (t)) (16)

[0143] Among them, q j (t) is the discharge flow of reservoir j in period t, and its dimension is [L 3 T -1 ];q max (Z j (t)) is the water level of reservoir j at time period t, Z j The maximum discharge capacity at (t).

[0144] In some embodiments, in step S400, the iterative optimization is performed according to the river ecological objective function, the preset objective function, the constraint condition, the preset objective optimization algorithm and the scheduling function with unknown parameters to obtain a reservoir scheduling plan, which specifically includes:

[0145] S480, taking the river ecological objective function and the preset objective function as the optimization objectives of the preset multi-objective optimization algorithm, iteratively optimizing the unknown parameters of the scheduling function with unknown parameters, and obtaining a multi-objective non-inferior solution set of the unknown parameters.

[0146] Among them, the multi-objective non-inferior solution set includes several groups of specific values ​​of unknown parameters.

[0147] Specifically, the river ecological objective function, water supply objective function and power generation objective function are used as optimization objectives of the preset multi-objective optimization algorithm. The preset multi-objective optimization algorithm is used to iterate the parameters of the scheduling function several times to obtain a multi-objective non-inferior solution set that meets the objective function.

[0148] S490. Determine an optimal solution from a multi-objective non-inferior solution set according to constraint conditions, and substitute the optimal solution into the scheduling function with unknown parameters to obtain the reservoir scheduling plan.

[0149] Specifically, combining the competitive relationship and constraints between different scheduling objectives, an optimal solution is selected from the non-inferior solution set, and the numerical value corresponding to the optimal solution is substituted into the parameters of the reservoir scheduling function to obtain a reservoir scheduling plan that considers the steady state of ecological flow.

[0150] The implementation of the present invention includes the following beneficial effects:

[0151] The present invention establishes a reservoir dispatching scheme with the goal of maintaining the basic form of the steady-state probability density function of the ecological flow, thereby ensuring the random characteristics of the ecological flow process and avoiding the "curse of dimensionality" in ecological dispatching.

[0152] like Figure 4 As shown, Figure 4 The present invention is a schematic diagram of a reservoir dispatching scheme extraction system. The present invention also provides a reservoir dispatching scheme extraction system, including a first module, a second module, a third module and a fourth module, wherein:

[0153] The first module is used to obtain meteorological data and surface data, determine the average water withdrawal rate of the river downstream of the reservoir before scheduling according to the surface data, and determine the average water withdrawal rate of the river downstream of the reservoir after scheduling;

[0154] The second module is used to determine the probability density function of the steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling, and to determine the probability density function of the steady-state flow of the river after scheduling according to the meteorological data and the average water withdrawal rate after scheduling;

[0155] The third module is used to establish a river ecological objective function according to the probability density function of the steady-state flow of the river before the scheduling and the probability density function of the steady-state flow of the river after the scheduling;

[0156] The fourth module is used to establish the preset objective function and constraints of the reservoir, and perform iterative optimization based on the river ecological objective function, the preset objective function, the constraints, the preset objective optimization algorithm and the scheduling function with unknown parameters to obtain a reservoir scheduling plan.

[0157] It can be seen that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0158] like Figure 5 As shown, Figure 5 The present invention also provides a structural schematic diagram of a reservoir dispatching scheme extraction system, including a meteorological data acquisition device, an average water withdrawal rate acquisition device and an average water withdrawal rate reasoning device, and a computer device connected to the meteorological data acquisition device, the average water withdrawal rate acquisition device and the average water withdrawal rate reasoning device; wherein,

[0159] The meteorological data collection device is used to collect the meteorological data and upload the meteorological data to the computer device;

[0160] The average water withdrawal rate collection device is used to collect the average water withdrawal rate before scheduling, and upload the average water withdrawal rate before scheduling to the computer device;

[0161] The average water withdrawal rate inference device is used to infer the average water withdrawal rate after scheduling, and upload the average water withdrawal rate after scheduling to the computer device;

[0162] The computer device comprises:

[0163] at least one processor;

[0164] at least one memory for storing at least one program;

[0165] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned method.

[0166] Specifically, computer equipment may be different types of electronic devices, including but not limited to desktop computers, laptops and other terminals.

[0167] It can be seen that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0168] like Figure 6 As shown, Figure 6 The present invention is a schematic diagram of a structure of a reservoir dispatching scheme extraction device. The present invention also provides a reservoir dispatching scheme extraction device, comprising:

[0169] at least one processor;

[0170] at least one memory for storing at least one program;

[0171] When the at least one program is executed by the at least one processor, the at least one processor implements the steps of a reservoir scheduling scheme extraction method described in the above method embodiment.

[0172] Among them, the memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. The memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a remote memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0173] It can be seen that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0174] In addition, the embodiment of the present application also discloses a computer program product or a computer program, and the computer program product or the computer program is stored in a computer-readable storage medium. The processor of the computer device can read the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device performs the above method. Similarly, the contents in the above method embodiment are all applicable to the storage medium embodiment, and the functions specifically implemented by the storage medium embodiment are the same as those in the above method embodiment, and the beneficial effects achieved are also the same as those achieved by the above method embodiment.

[0175] The present invention also provides a computer-readable storage medium, which stores a program executable by a processor. The program executable by the processor is used to implement the above method when executed by the processor.

[0176] It is understood that all or some steps and systems in the disclosed method above can be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, disk storage or other magnetic storage device, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0177] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0178] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A reservoir dispatching scheme extraction method, characterized in that: The following steps are involved: Obtain meteorological data and surface data, determine the average water withdrawal rate of the river downstream of the reservoir before dispatching based on the surface data, and determine the average water withdrawal rate of the river downstream of the reservoir after dispatching; Determine the probability density function of the steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling, and determine the probability density function of the steady-state flow of the river after scheduling according to the meteorological data and the average water withdrawal rate after scheduling; Establishing a river ecological objective function according to the probability density function of the steady-state flow of the river before the dispatch and the probability density function of the steady-state flow of the river after the dispatch; Establishing a preset objective function and constraint conditions of the reservoir, performing iterative optimization according to the river ecological objective function, the preset objective function, the constraint conditions, a preset multi-objective optimization algorithm and a scheduling function with unknown parameters, and obtaining a reservoir scheduling plan; Wherein, determining the probability density function of the steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling includes: The historical rainfall data is divided into periods within the year, and the probability density function of the steady-state flow of the river before dispatching is determined for each period; The expression of the probability density function of the steady-state flow of the river before the dispatch is: In the formula, p i (Q) is the probability density function of the steady-state flow of the river before the regulation of the i-th period; i is the i-th period; Γ(x) is the gamma function of the variable x; λ i is the frequency of net rain events in period i; k i is the average water withdrawal rate before dispatch in the i-th period; α i is the average rainfall depth in period i; Q is the downstream river flow in period i; The expression of the probability density function of the steady-state flow of the river after the dispatch is: In the formula, p i ′ (Q) is the probability density function of the steady-state flow of the river after the regulation in the i-th period; k i ′ is the average water withdrawal rate after scheduling in the i-th period; The establishing of the river ecological objective function according to the probability density function of the steady-state flow of the river before the scheduling and the probability density function of the steady-state flow of the river after the scheduling specifically includes: The pre-dispatch probability of the steady-state flow of the downstream river being within the preset flow range is obtained according to the probability density function of the steady-state flow of the river before the dispatch; The probability of the steady-state flow of the downstream river being within the preset flow range after scheduling is obtained according to the probability density function of the steady-state flow of the river after scheduling; Obtaining a flow steady-state instability index according to the pre-dispatching probability and the post-dispatching probability, and establishing a river ecological objective function with the instability index minimized; The expression of the flow steady-state instability index is: Where FRI i It is the indicator of flow steady-state instability; The preset objective function includes a water supply objective function and a power generation objective function. The preset objective function for establishing a reservoir specifically includes: Obtain the average water supply flow, target water supply flow, number of water supply periods, number of water supply periods that meet the target water supply flow, and total reservoir output during the preset period; The maximum damage depth is obtained according to the average water supply flow rate and the target water supply flow rate, and the water supply guarantee rate is obtained according to the number of water supply time periods and the number of water supply satisfaction time periods; Establishing a water supply objective function of the reservoir according to the maximum damage depth and the water supply guarantee rate; Constructing a power generation objective function according to the total output of the reservoir during the preset period; The expression of the water supply objective function is: Where D max is the maximum damage depth; W(t) is the average water flow rate during period t; W obj is the target water supply flow; R is the water supply guarantee rate; N s is the number of time periods required for water supply to be satisfied; T is the total number of time periods; min(x) means taking the minimum value; max(x) means taking the maximum value; The expression of the power generation objective function is: Where, E is the total power generation of the reservoir in the dispatch period T; N(t) is the total output of the reservoir in the t period; ΔT(t) is the time step of the t period; The constraints include water balance constraints, water level constraints, output constraints and downstream flow constraints. The constraints are established, specifically including: Establish water balance constraints based on the reservoir's inflow, outflow, and initial waterway capacity; The water level of the reservoir is constrained within a preset water level range to obtain a water level constraint; The power generation output of the reservoir is constrained within a preset output range to obtain an output constraint; The discharge flow constraint is obtained by making the reservoir discharge flow less than the maximum discharge capacity.

2. The method according to claim 1, characterized in that The meteorological data includes average rainfall depth and net rain event frequency, and the obtaining of meteorological data specifically includes: Obtain observed daily rainfall, daily rainfall frequency, and evapotranspiration data; The average rain depth is obtained according to the daily rainfall, and the net rain event frequency is obtained according to the daily rainfall frequency, evapotranspiration data and the average rain depth.

3. The method according to any one of claims 1 to 2, characterized in that: The iterative optimization is performed according to the river ecological objective function, the preset objective function, the constraint conditions, the preset multi-objective optimization algorithm and the scheduling function with unknown parameters to obtain the reservoir scheduling plan, which specifically includes: Taking the river ecological objective function and the preset objective function as the optimization objectives of the preset multi-objective optimization algorithm, the unknown parameters of the scheduling function with unknown parameters are iteratively optimized to obtain a multi-objective non-inferior solution set of the unknown parameters; An optimal solution is determined from a multi-objective non-inferior solution set according to constraint conditions, and the optimal solution is substituted into the scheduling function with unknown parameters to obtain the reservoir scheduling plan.

4. A reservoir dispatching scheme extraction system, characterized in that: It includes a first module, a second module, a third module and a fourth module, wherein: The first module is used to obtain meteorological data and surface data, determine the average water withdrawal rate of the river downstream of the reservoir before scheduling according to the surface data, and determine the average water withdrawal rate of the river downstream of the reservoir after scheduling; The second module is used to determine the probability density function of the steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling, and to determine the probability density function of the steady-state flow of the river after scheduling according to the meteorological data and the average water withdrawal rate after scheduling; The third module is used to establish a river ecological objective function according to the probability density function of the steady-state flow of the river before the scheduling and the probability density function of the steady-state flow of the river after the scheduling; The fourth module is used to establish a preset objective function and constraint conditions for the reservoir, and perform iterative optimization according to the river ecological objective function, the preset objective function, the constraint conditions, the preset multi-objective optimization algorithm and the scheduling function with unknown parameters to obtain a reservoir scheduling plan; Wherein, determining the probability density function of the steady-state flow of the river before scheduling according to the meteorological data and the average water withdrawal rate before scheduling includes: The historical rainfall data is divided into periods within the year, and the probability density function of the steady-state flow of the river before dispatching is determined for each period; The expression of the probability density function of the steady-state flow of the river before the dispatch is: In the formula, p i (Q) is the probability density function of the steady-state flow of the river before the regulation of the i-th period; i is the i-th period; Γ(x) is the gamma function of the variable x; λ i is the frequency of net rain events in period i; k i is the average water withdrawal rate before dispatch in the i-th period; α i is the average rainfall depth in period i; Q is the downstream river flow in period i; The expression of the probability density function of the steady-state flow of the river after the dispatch is: Where p′ i (Q) is the probability density function of the steady-state flow of the river after the regulation in the i-th period; k′ i is the average water withdrawal rate after scheduling in the i-th period; The third module is specifically used for: The pre-dispatch probability of the steady-state flow of the downstream river being within the preset flow range is obtained according to the probability density function of the steady-state flow of the river before the dispatch; The probability of the steady-state flow of the downstream river being within the preset flow range after scheduling is obtained according to the probability density function of the steady-state flow of the river after scheduling; Obtaining a flow steady-state instability index according to the pre-dispatching probability and the post-dispatching probability, and establishing a river ecological objective function with the instability index minimized; The expression of the flow steady-state instability index is: Where FRI i It is the indicator of flow steady-state instability; The preset objective function includes a water supply objective function and a power generation objective function. The preset objective function for establishing a reservoir specifically includes: Obtain the average water supply flow, target water supply flow, number of water supply periods, number of water supply periods that meet the target water supply flow, and total reservoir output during the preset period; The maximum damage depth is obtained according to the average water supply flow rate and the target water supply flow rate, and the water supply guarantee rate is obtained according to the number of water supply time periods and the number of water supply satisfaction time periods; Establishing a water supply objective function of the reservoir according to the maximum damage depth and the water supply guarantee rate; Constructing a power generation objective function according to the total output of the reservoir during the preset period; The expression of the water supply objective function is: Where D max is the maximum damage depth; W(t) is the average water flow rate during period t; W obj is the target water supply flow; R is the water supply guarantee rate; N s is the number of time periods required for water supply to be satisfied; T is the total number of time periods; min(x) means taking the minimum value; max(x) means taking the maximum value; The expression of the power generation objective function is: Where, E is the total power generation of the reservoir in the dispatch period T; N(t) is the total output of the reservoir in the t period; ΔT(t) is the time step of the t period; The constraints include water balance constraints, water level constraints, output constraints and downstream flow constraints. The constraints are established, specifically including: Establish water balance constraints based on the reservoir's inflow, outflow, and initial waterway capacity; The water level of the reservoir is constrained within a preset water level range to obtain a water level constraint; The power generation output of the reservoir is constrained within a preset output range to obtain an output constraint; The discharge flow constraint is obtained by making the reservoir discharge flow less than the maximum discharge capacity.

5. A reservoir dispatching scheme extraction device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 3.

6. A computer-readable storage medium storing a program executable by a processor, characterized in that: The processor-executable program is used to perform the method according to any one of claims 1 to 3 when executed by the processor.

7. A reservoir dispatching scheme extraction system, characterized in that: It includes meteorological data collection equipment, average water retreat rate collection equipment and average water retreat rate reasoning equipment, and computer equipment connected to the meteorological data collection equipment, average water retreat rate collection equipment and average water retreat rate reasoning equipment; wherein, The meteorological data collection device is used to collect the meteorological data and upload the meteorological data to the computer device; The average water withdrawal rate collection device is used to collect the average water withdrawal rate before scheduling, and upload the average water withdrawal rate before scheduling to the computer device; The average water withdrawal rate inference device is used to infer the average water withdrawal rate after scheduling, and upload the average water withdrawal rate after scheduling to the computer device; The computer device comprises: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 3.

Images