Flexible optimization dispatching method, system, equipment and medium for cascaded small hydropower stations

Abstract

The present invention discloses a flexibility optimization scheduling method, system, equipment and medium for a cascade small hydropower group. The method comprises the following steps: obtaining the rainfall of the cascade small hydropower group, and quantifying the flexibility adjustment capability of the hydropower station system according to the rainfall; quantifying the flexibility demand of the hydropower station system, and quantifying the flexibility shortage of the hydropower station system in each time period according to the quantified flexibility demand and flexibility adjustment capability; performing uncertainty modeling on the rainfall and net load of the hydropower station system respectively, and obtaining a rainfall prediction model and a net load uncertainty set; constructing an optimization scheduling model of the hydropower station system based on the flexibility shortage, the rainfall prediction model and the net load uncertainty set, and solving the optimization scheduling model to obtain an optimization scheduling plan for the hydropower station system, and controlling the power grid terminals connected to the cascade small hydropower group to execute the optimization scheduling plan, so as to fully tap the flexibility of the cascade small hydropower and optimize the scheduling and operation strategy of the hydropower station system.

Description

Technical Field

[0001] The present invention relates to the technical field of power optimization dispatching, and in particular to a method, system, equipment and medium for optimizing the dispatching of cascaded small hydropower groups. Background Art

[0002] At present, the installed capacity of small hydropower in my country exceeds 30% of the total installed capacity of hydropower, and it is a flexible regulation resource that cannot be ignored. However, since most small hydropower stations are run-of-river or small-capacity water storage power stations, their power generation capacity is affected by uncertain factors such as rainfall and runoff, their regulation capacity is poor, and the phenomenon of water abandonment and water storage is serious. Existing studies mostly regard small hydropower as an uncertain factor or even a power generation load, and consider that small hydropower operates in a "water-based electricity" manner, and the reservoir capacity of cascaded small hydropower is small or even non-existent, and their regulation capacity is greatly affected by the dynamic transmission process of meteorology and hydrology. Although they have great regulation potential, they have not been fully explored and utilized. At the same time, the traditional time-delay model commonly used today can only quantify the time lag of water flow propagation between the upstream and downstream hydropower station systems in the cascaded small hydropower group through a certain mathematical model, and cannot accurately characterize the hydraulic connection between the upstream and downstream hydropower station systems of the cascaded small hydropower group, let alone make full use of this rich flexibility resource to plan and dispatch the resources of the hydropower station system.

[0003] It can be seen that how to accurately describe and fully tap the flexibility adjustment potential of cascaded small hydropower groups and thereby optimize the resource scheduling of the hydropower station system has become a technical problem that technical personnel in this field need to solve urgently. Summary of the invention

[0004] The present invention provides a method, system, device and medium for optimizing the flexibility scheduling of a cascaded small hydropower group, which solves the problem of how to accurately describe and fully tap the flexibility regulation potential of a cascaded small hydropower group, and thereby optimize the resources of the hydropower station system.

[0005] In order to solve the above technical problems, the first aspect of the present invention provides a flexibility optimization scheduling method for a cascaded small hydropower group, comprising:

[0006] Obtaining rainfall of the cascaded small hydropower group, and quantifying the flexibility adjustment capability of the hydropower station system according to the rainfall;

[0007] Quantifying the flexibility demand of the hydropower station system, and quantifying the flexibility deficit of the hydropower station system in each time period according to the quantified flexibility demand and the flexibility adjustment capacity;

[0008] uncertainty modeling is performed on the rainfall and net load of the hydropower station system respectively to obtain a rainfall prediction model and a net load uncertainty set;

[0009] Based on the flexibility deficit, the rainfall prediction model and the net load uncertainty set, an optimal scheduling model for the hydropower station system is constructed, and the optimal scheduling model is solved to obtain an optimal scheduling plan for the hydropower station system, and the power grid terminals connected to the cascade small hydropower group are controlled to execute the optimal scheduling plan.

[0010] As one of the preferred solutions, the step of obtaining the rainfall of the cascaded small hydropower station group and quantifying the flexibility adjustment capability of the hydropower station system according to the rainfall includes:

[0011] Obtaining the rainfall of the cascaded small hydropower group, and predicting the rainfall flow of each small hydropower station based on the rainfall and the Xin'an River hydrological model;

[0012] According to the upstream and downstream relationship of each small hydropower station, the Muskingum method is used to quantify the associated flow between small hydropower stations;

[0013] quantifying the flexibility capacity of the cascaded small hydropower group according to the rainfall flow of each small hydropower and the associated flow between the small hydropowers;

[0014] The flexibility regulation capability of the hydropower station system is quantified according to the flexibility capacity of the cascade small hydropower group and the ramp rate and power of the external power grid.

[0015] As one of the preferred solutions, the cascade small hydropower group includes storage-type small hydropower and runoff-type small hydropower;

[0016] The quantification of the flexibility capacity of the cascaded small hydropower group according to the rainfall flow of each small hydropower and the associated flow between the small hydropowers includes:

[0017] quantifying the flexibility capacity of each of the small storage hydropower stations according to the rainfall flow of each of the small storage hydropower stations and the associated flow of each of the small storage hydropower stations and its superior small storage hydropower station;

[0018] quantifying the flexibility capacity of each run-of-river small hydropower station according to the rainfall flow of each run-of-river small hydropower station and the associated flow of each run-of-river small hydropower station and its upstream storage small hydropower station;

[0019] The flexibility capacity of each storage-type small hydropower station and the flexibility capacity of each run-of-river small hydropower station are combined to obtain the flexibility capacity of the cascade small hydropower station group.

[0020] As one of the preferred solutions, the flexibility capacity of each of the water storage type small hydropower stations is quantified according to the rainfall flow of each of the water storage type small hydropower stations and the associated flow of each of the water storage type small hydropower stations and its upper level water storage type small hydropower station, including:

[0021] quantifying the power generation flow of each water storage type small hydropower station according to the rainfall flow of each water storage type small hydropower station and the associated flow of the water storage type small hydropower station and its superior small hydropower station;

[0022] quantifying the output data of each of the water storage type small hydropower stations according to the power generation flow of each of the water storage type small hydropower stations;

[0023] The flexibility capacity of each of the water storage type small hydropower stations is quantified based on the output data of each of the water storage type small hydropower stations and the output data of the hydropower station system.

[0024] As one of the preferred solutions, the flexibility capacity of each runoff small hydropower station is quantified according to the rainfall flow of each runoff small hydropower station and the associated flow of each runoff small hydropower station and its upstream storage small hydropower station, including:

[0025] quantifying the associated flow of each run-of-river small hydropower station according to the flexibility capacity of the target storage-type small hydropower station, wherein the target storage-type small hydropower station is a storage-type small hydropower station upstream of each run-of-river small hydropower station and has a direct hydraulic connection with each of the run-of-river small hydropower stations;

[0026] quantifying the power generation flow of each of the runoff small hydropower stations according to the associated flow and rainfall flow of each of the runoff small hydropower stations;

[0027] quantifying the output data of each of the run-of-river small hydropower stations according to the power generation flow of each of the run-of-river small hydropower stations;

[0028] The flexibility capacity of each run-of-river small hydropower station is quantified based on the output data of each run-of-river small hydropower station and the output data of the hydropower station system.

[0029] As one preferred solution, the quantification of the flexibility demand of the hydropower station system includes:

[0030] Obtaining a wind power forecast value, a photovoltaic forecast value, and a load forecast value of the hydropower station system to quantify the net load of the hydropower station system;

[0031] A prediction error of a net load of the hydropower station system is calculated, and a flexibility demand of the hydropower station system is quantified based on the net load and its prediction error.

[0032] As one of the preferred solutions, the uncertainty modeling of the rainfall of the hydropower station system to obtain a rainfall prediction model includes:

[0033] Acquire historical rainfall data of the hydropower station system, and characterize rainfall prediction error based on the historical rainfall data and kernel density estimation;

[0034] Based on the rainfall prediction error, a rainfall prediction scenario is generated by a Monte Carlo method, and the rainfall prediction scenario is reduced by a clustering algorithm to obtain the rainfall prediction model.

[0035] As one of the preferred solutions, uncertainty modeling is performed on the net load of the hydropower station system to obtain a net load uncertainty set, including:

[0036] Obtaining prediction error sample data of the net load of the hydropower station system, and calculating the empirical distribution of the net load based on the prediction error sample data;

[0037] The payload uncertainty set is constructed according to the bulldozer distance between the empirical distribution of the payload and the true distribution of the payload.

[0038] As one of the preferred solutions, based on the flexibility shortfall, the rainfall prediction model and the net load uncertainty set, an optimal dispatching model of the hydropower station system is constructed, and the optimal dispatching model is solved to obtain an optimal dispatching scheme of the hydropower station system, and the power grid terminals connected to the cascade small hydropower group are controlled to execute the optimal dispatching scheme, including:

[0039] Based on the flexibility deficit and the net load uncertainty set, an objective function model is constructed with the goal of maximizing the operating benefit of the hydropower station system;

[0040] The objective function model is transformed according to the rainfall prediction model to obtain the optimization scheduling model;

[0041] Setting constraints for the optimization scheduling model, and converting the optimization scheduling model into a mixed integer linear programming model in combination with duality theory;

[0042] The mixed integer linear programming model is solved to obtain an optimal dispatching scheme for the hydropower station system, and the power grid terminals connected to the cascade small hydropower group are controlled to execute the optimal dispatching scheme.

[0043] The second aspect of the present invention provides a flexibility optimization scheduling system for a cascaded small hydropower group, comprising:

[0044] A flexibility regulation capacity quantification module is used to obtain the rainfall of the cascade small hydropower group and quantify the flexibility regulation capacity of the hydropower station system according to the rainfall;

[0045] A flexibility deficit quantification module, used to quantify the flexibility demand of the hydropower station system, and quantify the flexibility deficit of the hydropower station system in each time period according to the quantified flexibility demand and the flexibility adjustment capacity;

[0046] An uncertainty model building module is used to perform uncertainty modeling on the rainfall and net load of the hydropower station system respectively to obtain a rainfall prediction model and a net load uncertainty set;

[0047] An optimization scheduling scheme generation module is used to construct an optimization scheduling model for the hydropower station system based on the flexibility deficit, the rainfall prediction model and the net load uncertainty set, and solve the optimization scheduling model to obtain an optimization scheduling scheme for the hydropower station system, and control the power grid terminals connected to the cascade small hydropower group to execute the optimization scheduling scheme.

[0048] A third aspect of the present invention provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the flexibility optimization scheduling method for the cascade small hydropower group as described above is implemented.

[0049] A fourth aspect of the present invention provides a computer-readable storage medium, which includes a stored computer program, wherein when the device where the computer-readable storage medium is located executes the computer program, the flexibility optimization scheduling method for the cascade small hydropower group as described above is implemented.

[0050] Compared with the prior art, the embodiments of the present invention have the following advantages:

[0051] (1) By quantifying the rainfall of the cascaded small hydropower group and the hydraulic connection between the hydropower station systems at all levels, the flexibility regulation capacity of the storage and run-of-river power stations at different time periods can be quantified according to the rainfall and water inflow. By linking the storage and run-of-river power stations, the flexibility regulation capacity of the entire cascaded small hydropower group can be aggregated and quantified, thus breaking through the previous neglect of the regulation potential of the cascaded small hydropower group, thereby fully tapping the flexibility regulation potential of the cascaded small hydropower group, promoting the consumption of new energy such as wind and solar power, and improving the economic efficiency;

[0052] (2) By mobilizing the water storage capacity of small hydropower and river channels, the flexibility of cascaded small hydropower stations can be fully exploited, and uncertain factors such as rainfall and flexibility demand can be modeled to optimize the dispatching and operation strategy of the entire hydropower station system. This can fully tap the flexibility adjustment capacity of cascaded small hydropower stations and improve economic benefits. This is of great significance to the development of new energy and the full utilization of the flexibility of cascaded small hydropower stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the implementation mode will be briefly introduced below. Obviously, the drawings described below are only some implementation modes of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 It is a flow chart of a flexibility optimization scheduling method for a cascade small hydropower group provided by a certain embodiment of the present invention;

[0055] Figure 2 is a system structure diagram of a hydropower station system provided by a certain embodiment of the present invention;

[0056] Figure 3 is a flowchart of step S1 provided in one embodiment of the present invention;

[0057] Figure 4 It is a calculation structure diagram of the Xin'an River hydrological model provided by a certain embodiment of the present invention;

[0058] Figure 5 is a flowchart of step S13 provided by an embodiment of the present invention;

[0059] Figure 6 is a flowchart of step S131 provided by an embodiment of the present invention;

[0060] Figure 7 is a flowchart of step S132 provided by an embodiment of the present invention;

[0061] Figure 8 It is a quantitative process diagram of the flexibility demand of a hydropower station system provided by a certain embodiment of the present invention;

[0062] Fig. 9 is a diagram of a construction process of a rainfall prediction model provided by a certain embodiment of the present invention;

[0063] Fig.10 is a diagram of a process of constructing a net load uncertainty set provided by an embodiment of the present invention;

[0064] Fig.11 is a flowchart of step S4 provided by an embodiment of the present invention;

[0065] Fig.12 A watershed water system map and a small hydropower distribution map provided by an embodiment of the present invention;

[0066] Fig.13 A typical rainfall scenario curve and its probability diagram provided by an embodiment of the present invention;

[0067] Fig.14It is a rainfall flow change curve diagram provided by a certain embodiment of the present invention;

[0068] Fig.15 It is a flow evolution flow change curve diagram provided by a certain embodiment of the present invention;

[0069] Fig.16 A distribution diagram of the flexibility of increasing each flexibility resource provided by an embodiment of the present invention;

[0070] Fig.17 A distribution diagram of downward adjustment flexibility of each flexibility resource provided by an embodiment of the present invention;

[0071] Fig.18 It is a structural diagram of a flexibility optimization dispatching system for a cascaded small hydropower group provided by a certain embodiment of the present invention;

[0072] Fig.19 It is a structural diagram of an electronic device provided by a certain embodiment of the present invention. DETAILED DESCRIPTION

[0073] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0074] In the description of this application, the terms "first", "second", "third", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", "third", etc. may explicitly or implicitly include one or more of the feature. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0075] In the description of the present application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two components. The terms "vertical", "horizontal", "left", "right", "upper", "lower" and similar expressions used herein are for illustrative purposes only, and do not indicate or imply that the system or component referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0076] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those commonly understood by those skilled in the art. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood by specific circumstances.

[0077] In one embodiment, if Figure 1 As shown, the first aspect of the present invention provides a flexibility optimization scheduling method for a cascade small hydropower group, comprising:

[0078] S1. Obtain the rainfall of the cascaded small hydropower group, and quantify the flexibility adjustment capacity of the hydropower station system according to the rainfall; Specifically, the present application quantifies the flexibility adjustment capacity of the hydropower station system through the rainfall of the cascaded small hydropower group, that is, the flexibility supply capacity of the hydropower station system - the flexibility capacity that can be provided by all the flexibility resources of the hydropower station system; wherein, the system structure of the hydropower station system is as follows Figure 2 As shown, it includes cascaded small hydropower groups, wind and solar energy, loads and flexibility resources of the external power grid.

[0079] In one embodiment, step S1 is as follows: Figure 3 As shown, including:

[0080] S11, obtaining the rainfall of the cascaded small hydropower group, and predicting the rainfall flow of each small hydropower according to the rainfall and the Xin'an River hydrological model;

[0081] Specifically, this application combines the hydrological process and adopts the three-water source Xin'anjiang model to describe the runoff generation and convergence process of rainfall. The Xin'anjiang model uses rainfall as input and runoff as output to describe the hydrological runoff generation and convergence process in a mathematical form. The Xin'anjiang hydrological model includes four parts: a three-layer evapotranspiration model, a full-storage runoff model, a water source model, and a convergence calculation model. The calculation structure of the model is as follows: Figure 4 As shown in the figure, by collecting the hydrological data information of the unit basin in the hydropower station system area and dividing it into units based on the catchment area of ​​each small hydropower station, the information includes the upper, lower and deep soil tension water capacity, evaporation conversion coefficient, deep evaporation coefficient, etc. required by the three-layer evapotranspiration model; the average tension water storage capacity of the basin, the power of the tension water storage capacity curve, the proportion of regional impervious area, etc. required in the full flow model; the outflow coefficient of the free water storage capacity for groundflow and soil flow, the maximum value of the free water storage capacity of the basin, the average free water storage capacity of the basin, etc. required in the water source model; the surface, underground and soil flow runoff recession coefficients required in the confluence calculation model; the inflow of each small hydropower station is used as the outflow section of each unit basin, and the Xin'anjiang hydrological model is used to predict the flow at the outlet of each unit basin through rainfall and evaporation, that is, the rainfall flow of each small hydropower station. According to the Xin'anjiang model, the rainfall flow of small hydropower stations It can be expressed as:

[0082]

[0083] In the formula, is the rainfall in the area where small hydropower station i is located at time t; The Xin'anjiang model is a mapping between rainfall and rainfall flow of small hydropower station i at time t.

[0084] S12. According to the upstream and downstream relationship of each small hydropower station, the Muskingum method is used to quantify the associated flow between each small hydropower station. Specifically, due to the regulation and storage function of the river channel, in the process of the outflow of the upstream small hydropower station flowing into the downstream small hydropower station, the flow evolution needs to consider factors such as the peak appearance time, peak value, and water wave shape. The existing simple time-lag model cannot be used for characterization. The flow evolution characteristics of the water flow during the propagation process need to be considered:

[0085]

[0086]

[0087] In the formula, is the associated flow of the upstream small hydropower station of small hydropower station i at time t; , and are the outflow, power generation and abandoned water flow of small hydropower i at time t respectively; It is the flow evolution function of the river regulation between small hydropower stations i and j.

[0088] This application uses the Muskingum (MK) method in hydrology to obtain the water flow evolution function, so as to fully consider the evolution characteristics such as flattening and deformation during the water flow propagation process:

[0089]

[0090] In the formula, For outbound traffic The coefficient of .

[0091] S13, quantifying the flexibility capacity of the cascaded small hydropower group according to the rainfall flow of each small hydropower and the associated flow between the small hydropowers;

[0092] In one embodiment, the cascade small hydropower group includes storage-type small hydropower and runoff-type small hydropower, and step S13 is as follows: Figure 5 As shown, including:

[0093] S131, quantifying the flexibility capacity of each of the water storage type small hydropower stations according to the rainfall flow of each of the water storage type small hydropower stations and the associated flow of each of the water storage type small hydropower stations and its superior water storage type small hydropower station;

[0094] In one embodiment, step S131 is as follows: Figure 6 As shown, including:

[0095] S1311, quantifying the power generation flow of each water storage type small hydropower station according to the rainfall flow of each water storage type small hydropower station and the associated flow of the water storage type small hydropower station and its superior small hydropower station;

[0096] S1312, quantifying the output data of each of the water storage type small hydropower stations according to the power generation flow of each of the water storage type small hydropower stations;

[0097] S1313. Quantify the flexibility capacity of each of the water storage type small hydropower stations according to the output data of each of the water storage type small hydropower stations and the output data of the hydropower station system.

[0098] Specifically, since the storage capacity of small hydropower is much smaller than that of large hydropower station system, its flexibility adjustment ability is significantly affected by the storage capacity and rainfall. Considering that conventional hydropower units have very good climbing ability, the flexibility adjustment ability of small hydropower is expressed as:

[0099]

[0100]

[0101] In the formula, and The time scale The upward and downward flexibility capacity of small hydropower i at time t; is the output data of small hydropower i at time t; and They are small hydropower i in Theoretical maximum and minimum output data at each moment; the output data is related to the water head of small hydropower and the maximum and minimum power generation flow in each period, and the expression is shown in the following formula:

[0102]

[0103]

[0104]

[0105] In the formula, is the generating head of small hydropower i; is the power generation efficiency of small hydropower i; and They are small hydropower i in Maximum and minimum power generation flow at the moment; is the natural water flow of small hydropower i, which can be obtained based on historical statistical data; is the ecological flow of small hydropower i; and are the storage capacity of small hydropower i and Percentile, by adjusting and The size of can adjust the conservativeness of the flexibility quantification; is the storage capacity of small hydropower i; is the time interval; and are the rated power generation flow and the minimum necessary flow of small hydropower i respectively.

[0106] By considering the rainfall flow and the associated flow with the upper-level small hydropower, this application can accurately calculate the power generation flow of each water-storage small hydropower under current conditions, which helps to optimize the allocation and utilization of water resources in the region and ensure that each small hydropower can operate efficiently; converting the power generation flow into output data (i.e., power generation) can more intuitively understand the power generation capacity of each small hydropower to support scheduling decisions; and quantifying the flexibility capacity based on the power generation capacity assessment to formulate a more flexible and efficient scheduling strategy.

[0107] S132, quantifying the flexibility capacity of each run-of-river small hydropower station according to the rainfall flow of each run-of-river small hydropower station and the associated flow of each run-of-river small hydropower station and its upstream storage-type small hydropower station;

[0108] In one embodiment, step S132 is as follows: Figure 7 As shown, including:

[0109] S1321. quantifying the associated flow of each run-of-river small hydropower station according to the flexibility capacity of the target storage-type small hydropower station, wherein the target storage-type small hydropower station is a storage-type small hydropower station that is upstream of each run-of-river small hydropower station and has a direct hydraulic connection with each of the run-of-river small hydropower stations;

[0110] S1322, quantifying the power generation flow of each of the runoff small hydropower stations according to the associated flow and rainfall flow of each of the runoff small hydropower stations;

[0111] S1323, quantifying the output data of each of the runoff-type small hydropower stations according to the power generation flow of each of the runoff-type small hydropower stations;

[0112] S1324. Quantify the flexibility capacity of each run-of-river small hydropower station based on the output data of each run-of-river small hydropower station and the output data of the hydropower station system.

[0113] Specifically, because run-of-river small hydropower has no storage capacity, its flexibility regulation capability is often overlooked. However, run-of-river small hydropower can be linked with its upstream storage hydropower station system and exert its flexibility regulation capability by regulating the storage capacity of the upstream storage power station. In the cascade small hydropower group, run-of-river small hydropower accounts for a large proportion, and its flexibility regulation potential cannot be ignored. The upward and downward flexibility capacity that run-of-river small hydropower i can provide at time t can be expressed as:

[0114]

[0115]

[0116] In the formula, and The time scale Under the above equation, the upward and downward flexibility capacity of run-of-river small hydropower i at time t. Since run-of-river small hydropower has no storage capacity, its power generation flow depends entirely on its water inflow, which can be expressed by the following formula:

[0117]

[0118]

[0119] In the formula, is the total water inflow of run-of-river small hydropower station i at time t. According to the quantification of hydraulic connections between hydropower stations at all levels and the flexibility adjustment capacity of target storage small hydropower stations, it can be obtained:

[0120]

[0121]

[0122]

[0123]

[0124] In the formula, It is the set of storage-type small hydropower stations that have direct hydraulic connection with the upstream of run-of-river small hydropower station i, that is, the set of target storage-type small hydropower stations.

[0125] This application helps to predict and plan the power generation capacity of downstream power stations by determining the hydraulic connection between the target storage-type small hydropower and the downstream runoff-type small hydropower, namely the associated flow; combines the associated flow with the rainfall flow, considers the impact of natural rainfall and human scheduling on runoff, and more accurately estimates the power generation flow of each runoff-type small hydropower; converts the power generation flow into specific output data, which helps to achieve the optimal operation of the entire hydropower generation system; quantifies the flexibility capacity based on the power generation capacity assessment, so as to reasonably allocate resources, cope with uncertain factors such as rainfall and demand, and reduce losses caused by supply and demand mismatch.

[0126] S133, combining the flexibility capacity of each storage-type small hydropower station and the flexibility capacity of each run-of-river small hydropower station to obtain the flexibility capacity of the cascade small hydropower station group;

[0127] Specifically, the cascaded small hydropower group consists of several storage-type small hydropower stations and multiple run-of-river small hydropower stations. The upward and downward flexibility capacity of the cascaded small hydropower group is:

[0128]

[0129]

[0130] In the formula, and The time scale The upward and downward flexibility capacity of the lower cascade small hydropower group at time t; X and Y are the collections of storage small hydropower and run-of-river small hydropower in the cascade small hydropower group, respectively.

[0131] This application reflects the spatiotemporal coupling relationship of hydraulic connections between small hydropower stations at all levels within a cascade small hydropower station group through associated flow rates, so as to describe the characteristics of water flow flattening and deformation during the evolution of water flow, and serves as a key linkage and aggregation of upstream and downstream small hydropower stations, so that the flexibility capacity of the cascade small hydropower station group obtained by final quantification is more accurate.

[0132] S14, quantifying the flexibility regulation capability of the hydropower station system according to the flexibility capacity of the cascade small hydropower group and the ramp rate and power of the external power grid;

[0133] Specifically, the hydropower station system can adjust the purchase and sale of electricity with the external power grid to reflect the upward and downward flexibility of the power grid:

[0134]

[0135]

[0136] In the formula, and The time scale The upward and downward flexibility capacity of the external power grid at time t; , and are the power transmitted by the external power grid at time t and its upper and lower limits respectively; and They are the upward and downward climbing rates of the external power grid respectively.

[0137] Then, the total flexibility supply capacity of the hydropower station system in each period can be expressed as:

[0138]

[0139]

[0140] In the formula, and The time scale The upward and downward flexibility capacity that all flexibility resources in the hydropower station system can provide at time t.

[0141] This application quantifies the rainfall flow of small hydropower and the hydraulic connection between small hydropower at all levels through the distributed Xin'anjiang model and Muskingum method, so as to quantify the flexibility regulation capacity of storage and run-of-river power stations in different time periods according to rainfall and water inflow; through the linkage between storage power stations and run-of-river power stations, the flexibility regulation capacity of the entire cascade small hydropower group is aggregated and quantified; taking into account the flexibility of external resources of the power grid, the flexibility regulation capacity that can be provided by all flexibility resources in the system is quantified, which helps to optimize scheduling decisions and enhance system flexibility.

[0142] S2. quantifying the flexibility demand of the hydropower station system, and quantifying the flexibility shortage of the hydropower station system in each time period according to the quantified flexibility demand and the flexibility adjustment capacity;

[0143] In one embodiment, the quantification process of the hydropower station system flexibility demand is as follows: Figure 8 As shown, including:

[0144] S211. Obtain wind power prediction value, photovoltaic prediction value and load prediction value of the hydropower station system to quantify the net load of the hydropower station system; wherein the quantification formula of the net load prediction value is:

[0145]

[0146] In the formula, is the net load forecast value at time t; is the load forecast value at time t; is the wind power forecast value at time t; is the photovoltaic prediction value at time t.

[0147] S212, calculating the prediction error of the net load of the hydropower station system, and quantifying the flexibility demand of the hydropower station system according to the net load and its prediction error, wherein the quantification formula is:

[0148]

[0149]

[0150] In the formula, and The time scale The system's upward and downward flexibility requirements at the next time t; is a random variable, representing the net load forecast error at time t; and The time scale The system's upward and downward flexibility requirements at time t.

[0151] Flexibility balance refers to the ability of the flexibility supply provided by the flexibility resources in the hydropower station system to meet the net load flexibility demand. This application seeks the flexibility deficit based on the system flexibility supply capacity and the net load flexibility demand:

[0152]

[0153]

[0154]

[0155] In the formula, , The time scale The flexibility of the hydropower station system at time t is adjusted upward and downward to meet the shortfall; For time scale The flexibility deficit of the hydropower station system at time t.

[0156] This application takes into account the volatility and uncertainty of the load and wind and solar power output within the hydropower station system, and uses net load to better represent the superimposed effect of wind and solar power generation power and load power, thereby reflecting the dual fluctuations of source and load, and sets the flexibility demand according to the fluctuation of net load and its prediction error, and combines the flexibility adjustment capability of the hydropower station system to accurately quantify the flexibility deficit in each time period.

[0157] S3, performing uncertainty modeling on the rainfall and net load of the hydropower station system respectively, to obtain a rainfall prediction model and a net load uncertainty set;

[0158] In one embodiment, the construction process of the rainfall prediction model is as follows: Fig. 9 As shown, including:

[0159] S311, obtaining historical rainfall data of the hydropower station system, and characterizing rainfall prediction errors based on the historical rainfall data and kernel density estimation;

[0160] S312. Based on the rainfall prediction error, generate a rainfall prediction scenario by using a Monte Carlo method, and reduce the rainfall prediction scenario by using a clustering algorithm to obtain the rainfall prediction model.

[0161] Specifically, this application uses kernel density estimation to characterize rainfall prediction errors based on historical rainfall data samples:

[0162]

[0163] In the formula, is the rainfall prediction error distribution function; is the rainfall prediction error data of the ith numerical weather forecast; n is the historical rainfall data; H is the wide window; As the kernel density function, this application selects the Gaussian kernel function.

[0164] Based on the rainfall prediction error distribution, this application adopts the Monte Carlo method to generate rainfall prediction scenario data, uses methods such as k-means clustering to reduce the scenarios, and expresses the probability information of rainfall prediction error distribution through limited scenarios, that is, the rainfall prediction model.

[0165] In one embodiment, the process of constructing the net load uncertainty set is as follows: Fig.10 As shown, including:

[0166] S321, obtaining prediction error sample data of the net load of the hydropower station system, and calculating the empirical distribution of the net load according to the prediction error sample data;

[0167] S322. Construct the net load uncertainty set according to the bulldozer distance between the empirical distribution of the net load and the true distribution of the net load.

[0168] Specifically, the present application constructs a net load uncertainty set by using a distributed robust method: first, a sample set consisting of N net load prediction error sample data is obtained. , and obtain the empirical distribution P * , using Wasserstein distance to measure the empirical distribution P * With the true distribution The "distance" of is used to construct an uncertain set; the calculation process is expressed by the following formula:

[0169]

[0170]

[0171]

[0172]

[0173] In the formula, and They are respectively distributed as P * and A random variable of for and Joint distribution; is the 1-norm; is the net load uncertainty set; For the support set The total probability distribution on ; is the radius of the Wasserstein sphere; is the confidence level, is the sample mean.

[0174] Through uncertainty modeling, this application can more comprehensively consider the randomness and volatility of rainfall, thereby improving the accuracy of rainfall forecasts, helping to more accurately estimate the inflow of reservoirs, and providing more reliable data support for scheduling decisions; net load uncertainty modeling can help dispatchers better understand the fluctuations in system loads, thereby formulating more flexible scheduling plans. By adjusting the output of the hydropower station system, the system load can be balanced to ensure the stable operation of the power grid, thereby improving the risk resistance of the hydropower station system and promoting sustainable development.

[0175] S4. Based on the flexibility shortfall, the rainfall prediction model and the net load uncertainty set, an optimal dispatching model of the hydropower station system is constructed, and the optimal dispatching model is solved to obtain an optimal dispatching scheme of the hydropower station system, and the power grid terminals connected to the cascade small hydropower group are controlled to execute the optimal dispatching scheme;

[0176] In one embodiment, step S4 is as follows: Fig.11 As shown, including:

[0177] S41. Based on the flexibility deficit and the net load uncertainty set, an objective function model is constructed with the goal of maximizing the operating benefit of the hydropower station system. This application takes the maximization of the operating benefit of the hydropower station system as the objective function to construct a cascade small hydropower group flexibility aggregation distribution robust optimization scheduling model considering the hydrological process, which mainly includes: wind, solar and water power generation benefits, power grid purchase costs, regulation costs, power abandonment costs, load shedding costs and flexibility deficit costs. The objective function model is expressed by the following formula:

[0178]

[0179]

[0180]

[0181]

[0182]

[0183]

[0184] In the formula, It is the opposite of the total system revenue; is the total number of time periods; Cost of purchasing electricity from the grid; , and They are hydropower, wind power and photovoltaic income respectively; , and are the power purchase cost coefficients of the power grid respectively; , and They are the revenue per unit power generated by hydropower, wind power and photovoltaic power respectively; is the total number of small hydropower; , are the adjustment costs of the power grid and hydropower to cope with the uncertainty of net load at time t; , They are the adjusted power abandonment cost and load shedding cost respectively; To adjust the time scale The flexibility deficit of the system at the next time t; The unit flexibility deficit cost.

[0185] S42, transforming the objective function model according to the rainfall prediction model to obtain the optimization scheduling model; specifically, due to There are many random variables in the algorithm. This application uses the distributed robust stochastic optimization method to reduce the difficulty of solving. Based on the rainfall prediction error scenario in the rainfall prediction model, the optimization problem is transformed into a distributed robust stochastic optimization problem, namely:

[0186]

[0187] In the formula, is the number of rainfall error scenarios; is the scenario probability; For the The rainfall prediction error vector for each scenario.

[0188] S43. Setting constraints for the optimization scheduling model, and converting the optimization scheduling model into a mixed integer linear programming model in combination with the duality theory; specifically, since the net load prediction has uncertainty, there may be a deviation between the actual net load value and the predicted value in the real-time stage. In order to balance the power, it is necessary to further adjust the flexibility resources in the system, so as to smooth the impact of the net load prediction error. Therefore, the constraints set for the optimization scheduling model in this application are all adjusted for the prediction error, including:

[0189] The hydropower regulation constraint is expressed as follows:

[0190]

[0191]

[0192]

[0193] In the formula, is the adjusted output of small hydropower station i at time t; is the adjustment factor of small hydropower i at time t; is the adjusted power generation flow of small hydropower i at time t.

[0194] The adjustment constraint of cascade relationship of small hydropower projects is expressed by the following formula:

[0195]

[0196]

[0197] In the formula, is a 0-1 variable for the small hydropower type, =0 means that the water small hydropower i is a run-of-river small hydropower, =1 means that small hydropower i is a storage type small hydropower; is the adjusted storage capacity of small hydropower station i at time t; , are the adjusted total inflow and abandoned water flow of small hydropower station i at time t respectively.

[0198] The operation constraints of the hydropower station system including cascaded small hydropower stations are expressed by the following formula:

[0199]

[0200]

[0201] In the formula, , are the normal storage capacity and dead storage capacity of small hydropower i respectively.

[0202] Constraints on abandoned water flow of small hydropower stations with water storage: ,Because in addition to the mandatory ecological flow, the excess water abandonment means loss of benefits, this application regards the abandoned water flow of storage-type small hydropower as ecological flow.

[0203] The grid purchase adjustment constraint is expressed by the following formula:

[0204]

[0205]

[0206]

[0207] In the formula, is the adjusted transmission power of the upper power grid at time t; is the adjustment factor of the upper power grid at time t.

[0208] The load shedding adjustment constraint is expressed by the following formula:

[0209]

[0210]

[0211]

[0212]

[0213] In the formula, , are the power abandonment and load shedding adjusted at time t respectively; , are the adjustment factors for power abandonment and load shedding at time t respectively.

[0214] The power balance adjustment constraint is expressed by the following formula:

[0215] .

[0216] The flexibility adjustment constraint is expressed as follows:

[0217]

[0218]

[0219]

[0220]

[0221]

[0222] In the formula, , They are the upper and lower flexibility regulation capabilities adjusted at time t under the time scale τ; , are the adjusted upper and lower flexibility deficits at time t under the time scale τ; is the total flexibility deficit after adjustment at time t under the time scale τ.

[0223] Since the optimization scheduling model is a nonlinear programming problem, it can be transformed into a mixed integer linear programming problem by combining the duality theory.

[0224] S44. Solve the mixed integer linear programming model to obtain an optimal scheduling plan for the hydropower station system, and control the power grid terminals connected to the cascade small hydropower group to execute the optimal scheduling plan; wherein the solution includes but is not limited to solving the model by a gurobi solver.

[0225] In one embodiment, this application uses 15 small hydropower stations in a river basin in southern my country as an example for calculation analysis. The total installed capacity of small hydropower stations is 12.22MW, of which 7.73MW is storage-type small hydropower and 4.49MW is run-of-river small hydropower. Based on the digital elevation model (DEM) of the river basin, the river system of the river basin is extracted. The extracted river system map and small hydropower distribution are shown in Fig.12 As shown, the example is solved by Gurobi solver. In this application, the time scale of flexibility is 1h, the scheduling cycle T is 24h, the time interval is 1h, the confidence level of Wasserstein ball is 0.95, and the storage capacity quantile is Take 0.2, Taking 0.8, the number of rainfall prediction error samples generated by the Monte Carlo method is 5000, and the number of scenarios reduced by the k-means clustering algorithm is 5. The typical scenario curves and their probabilities are shown in Fig.13 .

[0226] by Fig.12 Taking the No. 1 and No. 3 small hydropower stations in the basin as examples, the hydrological process of the basin is analyzed. The No. 1 small hydropower station is located upstream of the No. 3 small hydropower station. Fig.13 Under the rainfall curve, the rainfall flow curves of No. 1 and No. 3 small hydropower stations over time are as follows Fig.14 As shown in the figure, the outflow curve of No. 1 small hydropower station and the curve of the flow when it flows to the entrance section of No. 3 small hydropower station are as follows: Fig.15 As shown, it can be seen that the model is effective in expressing the time lag and flattening characteristics in the process of water flow propagation. Three schemes are set up: the entire cascade small hydropower group does not participate in flexibility regulation (Scheme 1), only storage small hydropower participates in flexibility regulation (Scheme 2), and both storage and run-of-river small hydropower participate in flexibility regulation (Scheme 3), and their respective operating costs and benefits are compared. The results are as follows:

[0227]

[0228] Fig.16 Adjust the flexibility capacity distribution of each flexibility resource under the third option. Fig.17 To adjust the flexibility capacity distribution of each flexibility resource under the third option, the above table is combined with Fig.16 , Fig.17 It can be seen that the benefits of the hydropower station system dispatched by the scheme described in this application are significantly improved, most costs are significantly reduced, and the increased costs are added as flexibility resources of the external power grid in the optimization scheduling process of the hydropower station system, promoting the development of the hydropower station system and saving other costs or resources for it.

[0229] In the embodiments of the present application, based on the problem of how to accurately describe and fully tap the flexibility adjustment potential of cascade small hydropower groups, and thereby optimize the resource scheduling of the hydropower station system, the hydrological model and the water flow evolution process are taken into account, the rainfall flow generation of small hydropower and the hydraulic connection between the hydropower station systems at all levels are described respectively, the flexibility adjustment capacity of the storage and runoff power stations in each period is quantified according to rainfall and water inflow, and the flexibility adjustment capacity of the entire cascade small hydropower group is aggregated and quantified through linkage between the storage and runoff power stations; the small hydropower group and other flexibility resources are coordinated to participate in the power system scheduling, and on the basis of improving the overall economy of the system, the flexibility adjustment capacity of the aggregated cascade small hydropower group is fully utilized; a flexibility aggregation optimization operation strategy for cascade small hydropower groups considering distributed hydrological models is provided to improve the utilization rate of small hydropower and wind and solar new energy, promote the consumption of new energy, and effectively promote energy transformation, which is of great significance to promoting the sustainable development of energy and building a more flexible new power system.

[0230] It should be noted that although the steps in the above flowchart are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders.

[0231] In another embodiment, if Fig.18 As shown, the second aspect of the present invention provides a flexibility optimization scheduling system for a cascade small hydropower group, comprising:

[0232] The flexibility regulation capacity quantification module 10 is used to obtain the rainfall of the cascade small hydropower group and quantify the flexibility regulation capacity of the hydropower station system according to the rainfall;

[0233] A flexibility deficit quantification module 20 is used to quantify the flexibility demand of the hydropower station system, and quantify the flexibility deficit of the hydropower station system in each time period according to the quantified flexibility demand and the flexibility adjustment capacity;

[0234] The uncertainty model building module 30 is used to perform uncertainty modeling on the rainfall and net load of the hydropower station system respectively to obtain a rainfall prediction model and a net load uncertainty set;

[0235] The optimization scheduling scheme generation module 40 is used to construct an optimization scheduling model for the hydropower station system based on the flexibility deficit, the rainfall prediction model and the net load uncertainty set, and solve the optimization scheduling model to obtain the optimization scheduling scheme for the hydropower station system, and control the power grid terminals connected to the cascade small hydropower group to execute the optimization scheduling scheme.

[0236] It should be noted that each module in the above-mentioned flexibility optimization scheduling system based on cascade small hydropower groups can be fully or partially implemented by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. For the specific definition of a flexibility optimization scheduling system for a cascade small hydropower group, please refer to the definition of a flexibility optimization scheduling method for a cascade small hydropower group in the above text. The two have the same functions and effects and will not be repeated here.

[0237] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0238] processor, memory, and bus;

[0239] The bus is used to connect the processor and the memory;

[0240] The memory is used to store operation instructions;

[0241] The processor is used to call the operation instruction, and the executable instruction enables the processor to perform operations corresponding to the flexibility optimization scheduling method of a cascade small hydropower group as shown in the first aspect of the present application.

[0242] In an alternative embodiment, an electronic device is provided, such as Fig.19 As shown, Fig.19 The electronic device 5000 shown includes: a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are connected, such as through a bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. It should be noted that in actual applications, the transceiver 5004 is not limited to one, and the structure of the electronic device 5000 does not constitute a limitation on the embodiments of the present application.

[0243] Processor 5001 may be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 5001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0244] The bus 5002 may include a path to transmit information between the above components. The bus 5002 may be a PCI bus or an EISA bus, etc. The bus 5002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.19 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0245] The memory 5003 may be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, or an EEPROM, a CD-ROM or other optical disk storage, an optical disk storage (including a compressed optical disk, a laser disk, an optical disk, a digital versatile disk, a Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0246] The memory 5003 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 5001. The processor 5001 is used to execute the application code stored in the memory 5003 to implement the content shown in any of the above method embodiments.

[0247] Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.

[0248] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a flexibility optimization scheduling method for a cascade small hydropower group as shown in the first aspect of the present application.

[0249] Another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0250] In addition, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented.

[0251] In summary, the present invention relates to the technical field of power optimization and scheduling, and discloses a flexibility optimization and scheduling method, system, equipment and medium for a cascade small hydropower group, the method comprising obtaining the rainfall of the cascade small hydropower group, and quantifying the flexibility adjustment capability of the hydropower station system according to the rainfall; quantifying the flexibility demand of the hydropower station system, and quantifying the flexibility shortage of the hydropower station system in each time period according to the quantified flexibility demand and the flexibility adjustment capability; performing uncertainty modeling on the rainfall and net load of the hydropower station system respectively to obtain a rainfall prediction model and a net load uncertainty set; constructing an optimization scheduling model of the hydropower station system based on the flexibility shortage, the rainfall prediction model and the net load uncertainty set, and solving the optimization scheduling model to obtain an optimization scheduling plan for the hydropower station system, and controlling the power grid terminal connected to the cascade small hydropower group to execute the optimization scheduling plan, so as to fully tap the flexibility of cascade small hydropower, further optimize the scheduling and operation strategy of the hydropower station system, and improve economic benefits.

[0252] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0253] The above-mentioned embodiments only express several preferred implementation modes of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in the technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be based on the protection scope of the claims.

Claims

1. A flexibility optimization scheduling method for cascaded small hydropower groups, characterized in that: include: Obtaining rainfall of the cascaded small hydropower group, and quantifying the flexibility adjustment capability of the hydropower station system according to the rainfall; Quantifying the flexibility demand of the hydropower station system, and quantifying the flexibility deficit of the hydropower station system in each time period according to the quantified flexibility demand and the flexibility adjustment capacity; uncertainty modeling is performed on the rainfall and net load of the hydropower station system respectively to obtain a rainfall prediction model and a net load uncertainty set; Based on the flexibility shortfall, the rainfall prediction model and the net load uncertainty set, an optimal dispatching model of the hydropower station system is constructed, and the optimal dispatching model is solved to obtain an optimal dispatching scheme of the hydropower station system, and the power grid terminals connected to the cascade small hydropower group are controlled to execute the optimal dispatching scheme; The step of obtaining the rainfall of the cascaded small hydropower station group and quantifying the flexibility adjustment capability of the hydropower station system according to the rainfall includes: Obtaining the rainfall of the cascaded small hydropower group, and predicting the rainfall flow of each small hydropower station based on the rainfall and the Xin'an River hydrological model; According to the upstream and downstream relationship of each small hydropower station, the Muskingum method is used to quantify the associated flow between small hydropower stations; quantifying the flexibility capacity of the cascaded small hydropower group according to the rainfall flow of each small hydropower and the associated flow between the small hydropowers; Quantify the flexibility regulation capability of the hydropower station system according to the flexibility capacity of the cascaded small hydropower group and the ramp rate and power of the external power grid; The cascade small hydropower group includes storage-type small hydropower and run-of-river small hydropower; The quantification of the flexibility capacity of the cascaded small hydropower group according to the rainfall flow of each small hydropower and the associated flow between the small hydropowers includes: quantifying the flexibility capacity of each of the small storage hydropower stations according to the rainfall flow of each of the small storage hydropower stations and the associated flow of each of the small storage hydropower stations and its superior small storage hydropower station; quantifying the flexibility capacity of each run-of-river small hydropower station according to the rainfall flow of each run-of-river small hydropower station and the associated flow of each run-of-river small hydropower station and its upstream storage small hydropower station; Combining the flexibility capacity of each storage-type small hydropower station and the flexibility capacity of each run-of-river small hydropower station to obtain the flexibility capacity of the cascade small hydropower station group; The quantification of the flexibility capacity of each of the water storage type small hydropower stations according to the rainfall flow of each of the water storage type small hydropower stations and the associated flow of each of the water storage type small hydropower stations and its superior water storage type small hydropower station includes: quantifying the power generation flow of each water storage type small hydropower station according to the rainfall flow of each water storage type small hydropower station and the associated flow of the water storage type small hydropower station and its superior small hydropower station; quantifying the output data of each of the water storage type small hydropower stations according to the power generation flow of each of the water storage type small hydropower stations; quantifying the flexibility capacity of each of the water storage type small hydropower stations according to the output data of each of the water storage type small hydropower stations and the output data of the hydropower station system; The quantification of the flexibility capacity of each run-of-river small hydropower station according to the rainfall flow of each run-of-river small hydropower station and the associated flow of each run-of-river small hydropower station and its upstream storage-type small hydropower station includes: quantifying the associated flow of each run-of-river small hydropower station according to the flexibility capacity of the target storage-type small hydropower station, wherein the target storage-type small hydropower station is a storage-type small hydropower station upstream of each run-of-river small hydropower station and has a direct hydraulic connection with each of the run-of-river small hydropower stations; quantifying the power generation flow of each of the runoff small hydropower stations according to the associated flow and rainfall flow of each of the runoff small hydropower stations; quantifying the output data of each of the run-of-river small hydropower stations according to the power generation flow of each of the run-of-river small hydropower stations; The flexibility capacity of each run-of-river small hydropower station is quantified based on the output data of each run-of-river small hydropower station and the output data of the hydropower station system.

2. The flexibility optimization scheduling method for cascaded small hydropower groups according to claim 1 is characterized in that: The quantification of the flexibility requirements of the hydropower station system includes: Obtaining a wind power forecast value, a photovoltaic forecast value, and a load forecast value of the hydropower station system to quantify the net load of the hydropower station system; A prediction error of a net load of the hydropower station system is calculated, and a flexibility demand of the hydropower station system is quantified based on the net load and its prediction error.

3. The flexibility optimization scheduling method for cascaded small hydropower groups according to claim 1 is characterized in that: The uncertainty modeling of the rainfall of the hydropower station system to obtain a rainfall prediction model includes: Acquire historical rainfall data of the hydropower station system, and characterize rainfall prediction error based on the historical rainfall data and kernel density estimation; Based on the rainfall prediction error, a rainfall prediction scenario is generated by a Monte Carlo method, and the rainfall prediction scenario is reduced by a clustering algorithm to obtain the rainfall prediction model.

4. The flexibility optimization scheduling method for cascaded small hydropower groups according to claim 1 is characterized in that: The net load of the hydropower station system is subjected to uncertainty modeling to obtain a net load uncertainty set, including: Obtaining prediction error sample data of the net load of the hydropower station system, and calculating the empirical distribution of the net load based on the prediction error sample data; The payload uncertainty set is constructed according to the bulldozer distance between the empirical distribution of the payload and the true distribution of the payload.

5. The flexibility optimization scheduling method for cascaded small hydropower groups according to claim 1 is characterized in that: The method of constructing an optimal dispatching model of the hydropower station system based on the flexibility shortfall, the rainfall prediction model and the net load uncertainty set, solving the optimal dispatching model to obtain an optimal dispatching scheme of the hydropower station system, and controlling the power grid terminals connected to the cascade small hydropower group to execute the optimal dispatching scheme includes: Based on the flexibility deficit and the net load uncertainty set, an objective function model is constructed with the goal of maximizing the operating benefit of the hydropower station system; The objective function model is transformed according to the rainfall prediction model to obtain the optimization scheduling model; Setting constraints for the optimization scheduling model, and transforming the optimization scheduling model into a mixed integer linear programming model in combination with duality theory; The mixed integer linear programming model is solved to obtain an optimal dispatching scheme for the hydropower station system, and the power grid terminals connected to the cascade small hydropower group are controlled to execute the optimal dispatching scheme.

6. A flexible optimization dispatching system for cascaded small hydropower groups, characterized in that: include: A flexibility regulation capacity quantification module is used to obtain the rainfall of the cascade small hydropower group and quantify the flexibility regulation capacity of the hydropower station system according to the rainfall; A flexibility deficit quantification module, used to quantify the flexibility demand of the hydropower station system, and quantify the flexibility deficit of the hydropower station system in each time period according to the quantified flexibility demand and the flexibility adjustment capacity; An uncertainty model building module is used to perform uncertainty modeling on the rainfall and net load of the hydropower station system respectively to obtain a rainfall prediction model and a net load uncertainty set; An optimization scheduling scheme generating module is used to construct an optimization scheduling model of the hydropower station system based on the flexibility shortage, the rainfall prediction model and the net load uncertainty set, solve the optimization scheduling model, obtain an optimization scheduling scheme of the hydropower station system, and control the power grid terminals connected to the cascade small hydropower group to execute the optimization scheduling scheme; The step of obtaining the rainfall of the cascaded small hydropower station group and quantifying the flexibility adjustment capability of the hydropower station system according to the rainfall includes: Obtaining the rainfall of the cascaded small hydropower group, and predicting the rainfall flow of each small hydropower station based on the rainfall and the Xin'an River hydrological model; According to the upstream and downstream relationship of each small hydropower station, the Muskingum method is used to quantify the associated flow between small hydropower stations; quantifying the flexibility capacity of the cascaded small hydropower group according to the rainfall flow of each small hydropower and the associated flow between the small hydropowers; Quantify the flexibility regulation capability of the hydropower station system according to the flexibility capacity of the cascaded small hydropower group and the ramp rate and power of the external power grid; The cascade small hydropower group includes storage-type small hydropower and run-of-river small hydropower; The quantification of the flexibility capacity of the cascaded small hydropower group according to the rainfall flow of each small hydropower and the associated flow between the small hydropowers includes: quantifying the flexibility capacity of each of the small storage hydropower stations according to the rainfall flow of each of the small storage hydropower stations and the associated flow of each of the small storage hydropower stations and its superior small storage hydropower station; quantifying the flexibility capacity of each run-of-river small hydropower station according to the rainfall flow of each run-of-river small hydropower station and the associated flow of each run-of-river small hydropower station and its upstream storage small hydropower station; Combining the flexibility capacity of each storage-type small hydropower station and the flexibility capacity of each run-of-river small hydropower station to obtain the flexibility capacity of the cascade small hydropower station group; The quantification of the flexibility capacity of each of the water storage type small hydropower stations according to the rainfall flow of each of the water storage type small hydropower stations and the associated flow of each of the water storage type small hydropower stations and its superior water storage type small hydropower station includes: quantifying the power generation flow of each water storage type small hydropower station according to the rainfall flow of each water storage type small hydropower station and the associated flow of the water storage type small hydropower station and its superior small hydropower station; quantifying the output data of each of the water storage type small hydropower stations according to the power generation flow of each of the water storage type small hydropower stations; quantifying the flexibility capacity of each of the water storage type small hydropower stations according to the output data of each of the water storage type small hydropower stations and the output data of the hydropower station system; The quantification of the flexibility capacity of each run-of-river small hydropower station according to the rainfall flow of each run-of-river small hydropower station and the associated flow of each run-of-river small hydropower station and its upstream storage-type small hydropower station includes: quantifying the associated flow of each run-of-river small hydropower station according to the flexibility capacity of the target storage-type small hydropower station, wherein the target storage-type small hydropower station is a storage-type small hydropower station upstream of each run-of-river small hydropower station and has a direct hydraulic connection with each of the run-of-river small hydropower stations; quantifying the power generation flow of each of the runoff small hydropower stations according to the associated flow and rainfall flow of each of the runoff small hydropower stations; quantifying the output data of each of the run-of-river small hydropower stations according to the power generation flow of each of the run-of-river small hydropower stations; The flexibility capacity of each run-of-river small hydropower station is quantified based on the output data of each run-of-river small hydropower station and the output data of the hydropower station system.

7. An electronic device, characterized in that: It comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements the flexibility optimization scheduling method of the cascade small hydropower group as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the device where the computer-readable storage medium is located executes the computer program, the flexibility optimization scheduling method for the cascade small hydropower group as described in any one of claims 1 to 5 is implemented.

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