A run-of-river power station active power regulation intelligent control method and system

Abstract

The present invention discloses an intelligent control method and system for active power regulation of a runoff power station, including: obtaining the initial storage capacity of the current reservoir within a specified period, the final storage capacity of the current reservoir, the outflow of the upstream power station, the outflow of the current reservoir, and calculating the interval inflow between the upstream reservoir and the current reservoir; judging whether the power station meets the start-up and shutdown conditions of the unit, and performing corresponding start-up and shutdown operations if the start-up and shutdown conditions are met; setting a flow reference value according to the historical data of coordinated operation of the power station; when the interval inflow is greater than the flow reference value, adopting a large flow active power preprocessing algorithm; otherwise, the active power prediction algorithm based on the negative feedback regulation of the water level on the dam predicts the active power setting value of the unit, and realizes the automatic optimization distribution of the active power of the unit. The present invention realizes the intelligent control of active power regulation of the runoff power station, realizes the automatic optimization distribution of the active power of the unit, and ensures the safe operation of the power station.

Description

Technical Field

[0001] The present invention relates to the technical field of optimized dispatching of cascade hydropower stations, and in particular to an intelligent control method and system for active power regulation of a run-of-river power station. Background Art

[0002] In recent years, the water level of daily-regulated run-of-river power stations has been greatly affected by the hydrological characteristics of the upstream and within the basin. The power station output and water level safety control are very sensitive to water level information. Water level fluctuations exceeding 10 cm may lead to flooding of gates and dams.

[0003] At present, the coordinated operation between hydropower stations still relies on historical data and dispatchers' manual estimation based on experience, which cannot realize automatic power generation control, and there are human judgment deviations or errors. Therefore, it is of great practical significance to study how to combine the complex hydraulic and power connection constraints of the cascade basin to conduct water level control research on runoff daily regulation power stations, realize load optimization distribution, ensure the safe operation of power stations, and improve the water energy utilization rate and comprehensive benefits of cascade power stations in the basin. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides an intelligent control method and system for active power regulation of a runoff power station to solve the problems of low efficiency and judgment deviation in manual estimation of active power regulation of existing power stations.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides an intelligent control method for active power regulation of a run-of-river power station, comprising:

[0009] Get the initial storage capacity of the reservoir in the specified period, the final storage capacity of the reservoir in the specified period, and the outflow of the upstream power station as the outflow of the reservoir, and calculate the interval inflow between the upstream reservoir and the reservoir;

[0010] Determine whether the power station meets the unit start-up and shutdown conditions, and if so, perform the corresponding start-up and shutdown operations;

[0011] The flow rate reference value is set according to the historical data of coordinated operation of the power station. When the interval inflow flow is greater than the flow rate reference value, the large flow active power preprocessing algorithm is adopted. Otherwise, the active power prediction algorithm based on the negative feedback regulation of the water level on the dam predicts the active power setting value of the unit to realize the automatic optimization distribution of the active power of the unit.

[0012] As a preferred solution of the intelligent control method for active power regulation of run-of-river power station described in the present invention, the formula for calculating the interval inflow flow between the upstream reservoir and the reservoir is specifically:

[0013] V1-V0=(Q s +qQ c )*t

[0014] Among them, V0 represents the initial storage capacity of this period, V1 represents the final storage capacity of this period, Q s represents the outflow from the upstream power station, Q c It represents the outbound flow of this warehouse, t represents the time interval, and q represents the actual inbound flow of this warehouse.

[0015] As a preferred solution of the intelligent control method for active power regulation of a radial power station according to the present invention, the specific rules for judging whether the power station meets the start-stop conditions of the unit and performing corresponding start-stop operations if the start-stop conditions are met are as follows:

[0016] Calculate the power generation flow of the unit in this warehouse when it is fully powered. When the interval inflow flow is greater than the power generation flow of the unit in the power generation state when it is fully powered, and there are units that can be started, increase the unit operation;

[0017] If there is no unit that can be started, all units will run at full capacity;

[0018] When one or several units are reduced from generating electricity, and the current interval inflow flow is less than the generating flow of the remaining units at full power, the units will be shut down.

[0019] As a preferred solution of the intelligent control method for active power regulation of run-of-river power station described in the present invention, the active power prediction algorithm based on negative feedback regulation of water level on the dam has the following specific steps:

[0020] Obtain the real-time active power of each unit in the reservoir, the real-time water level on the dam, and the reference water level range on the dam;

[0021] Determine whether the current water level on the dam is within the dam reference water level range. If the water level on the dam is within the dam reference water level range, it is in a balanced state and directly enters AGC regulation; if it is not in a balanced state, calculate the active power adjustment of the power station according to the water level negative feedback regulation control algorithm.

[0022] As a preferred solution of the intelligent control method for active power regulation of runoff power station described in the present invention, the specific steps of calculating the active power regulation of the power station are as follows:

[0023] Calculate the real-time power generation flow of this pool based on the initial value of the power generation head, the head-output-flow relationship curve of each unit and the real-time active power of the unit;

[0024] Calculate the expected power generation flow using a negative feedback control algorithm. According to the dam water level-reservoir capacity relationship function curve, calculate the optimal reference water level and the current dam front water level to adjust the reservoir tolerance. Divide by the time period to get the adjusted flow. Calculate the expected power generation flow through the current power generation flow and the adjusted flow.

[0025] Based on the head-output-flow relationship curve of each unit, the active power setting value is determined by interpolating the head value H and the expected power generation flow.

[0026] As a preferred solution of the intelligent control method for active power regulation of runoff power station described in the present invention, the storage capacity adjustment algorithm is expressed as:

[0027]

[0028] Among them, u(t) represents the adjusted storage capacity, K p Represents the proportionality coefficient, K i represents the integral coefficient, e(t) represents the control deviation between the storage capacity required to be adjusted at the previous time point and the storage capacity adjusted at the current time point, Indicates the adjusted reservoir capacity required for the optimal benchmark water level and the current water level in front of the dam.

[0029] As a preferred solution of the intelligent control method for active power regulation of runoff power station described in the present invention, wherein: the active power setting value is determined by interpolation of the head value H and the expected power generation flow, and the specific steps are as follows:

[0030] Calculate the initial value of the generating head, and interpolate the output-flow function curve according to the head-output-flow relationship curve of each unit;

[0031] Determine whether the expected power generation flow q exceeds the maximum flow corresponding to the maximum output of a single machine. If the expected power generation flow is less than the maximum power generation flow of a single machine, the operation curve is the output-flow function curve; if it is greater than the maximum power generation flow of a single machine, the multi-machine operation curve is obtained according to the unit operation characteristics;

[0032] According to the obtained head-flow curve, the corresponding active power setting value is obtained by interpolation.

[0033] In a second aspect, the present invention provides an intelligent control system for active power regulation of a runoff power station, comprising:

[0034] The calculation module obtains the initial storage capacity of the reservoir in the specified period, the final storage capacity of the reservoir in the specified period, and the outflow of the upstream power station as the outflow of the reservoir, and calculates the interval inflow between the upstream reservoir and the reservoir;

[0035] The judgment module judges whether the power station meets the start-up and shutdown conditions of the unit, and performs corresponding start-up and shutdown operations if the start-up and shutdown conditions are met;

[0036] The setting module sets the flow reference value according to the historical data of coordinated operation of the power station; when the interval inflow flow is greater than the flow reference value, the large flow active power preprocessing algorithm is adopted; otherwise, the active power prediction algorithm based on the negative feedback regulation of the water level on the dam predicts the active power setting value of the unit to realize the automatic optimization distribution of the active power of the unit.

[0037] In a third aspect, the present invention provides a computing device, comprising:

[0038] Memory, used to store programs;

[0039] The processor is used to execute the computer executable instructions, which, when executed by the processor, implement the steps of the intelligent control method for active power regulation of the run-of-river power station.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium, comprising: when the program is executed by a processor, the steps of implementing the intelligent control method for active power regulation of a run-of-river power station are implemented.

[0041] The beneficial effects of the present invention are as follows: the manual estimation of the active power of cascade hydropower stations is replaced by automated intelligent control, which can realize the automation and digitization of load adjustment, increase the robustness of the water level control effect in front of the dam, thereby reducing the workload of water regulators and saving human resources. At the same time, the regulation advantages of hydropower units are fully utilized to ensure safe and efficient operation of the units. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0043] Figure 1 A basic flow chart of an intelligent control method for active power regulation of a run-of-river power station provided by an embodiment of the present invention;

[0044] Figure 2 A schematic diagram of the overall process of an intelligent control method for active power regulation of a run-of-river power station provided by an embodiment of the present invention;

[0045] Figure 3A diagram of the active power regulation process when the water inflow upstream of the west gate increases slowly, according to an intelligent control method for active power regulation of a run-of-river power station provided by an embodiment of the present invention;

[0046] Figure 4 A diagram of the active power regulation process when the water inflow upstream of the west gate is large, provided by an embodiment of the present invention, of an intelligent control method for active power regulation of a run-of-river power station; DETAILED DESCRIPTION

[0047] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0048] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0049] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0050] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0051] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0052] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0053] Example 1

[0054] Reference Figure 1-2 , is an embodiment of the present invention, which provides an intelligent control method for active power regulation of a runoff power station, such as Figure 1 , as shown in 2, comprising the following steps:

[0055] S1: Obtain the initial storage capacity of the reservoir in the specified period, the final storage capacity of the reservoir in the specified period, and the outflow of the upstream power station as the outflow of the reservoir, and calculate the interval inflow between the upstream reservoir and the reservoir;

[0056] Furthermore, by substituting the following formula, we can obtain the interval inflow flow q of this library:

[0057] V1-V0=(Q s +qQ c )*t

[0058] Among them, V0 represents the initial storage capacity of this period, V1 represents the final storage capacity of this period, Q s represents the outflow from the upstream power station, Q c It represents the outbound flow of this warehouse, t represents the time interval, and q represents the actual inbound flow of this warehouse.

[0059] S2: Determine whether the power station meets the start-up and shutdown conditions of the unit. If the start-up and shutdown conditions are met, perform corresponding start-up and shutdown operations;

[0060] Furthermore, it is determined whether the power station meets the start-up and shutdown conditions of the unit. If the start-up and shutdown conditions are met, the corresponding start-up and shutdown operations are performed. The specific rules are as follows:

[0061] Calculate the power generation flow of the unit in this warehouse when it is fully powered. When the interval inflow flow is greater than the power generation flow of the unit in the power generation state when it is fully powered, and there are units that can be started, increase the unit operation;

[0062] If there is no unit that can be started, all units will run at full capacity;

[0063] When one or several units are reduced from generating electricity, and the current interval inflow flow is less than the generating flow of the remaining units at full power, the units will be shut down.

[0064] Furthermore, the power generation flow of the unit in this library is calculated when it is fully powered. The specific steps are as follows:

[0065] A1: Calculate the initial value of the turbine generating head, the formula is: H = Z t -Z0;

[0066] Among them, H is the generating head, Z t is the water level above the dam, and Z0 is the water level below the dam.

[0067] A2: Draw the head-output-flow relationship curve (NHQ curve) of each unit. The head value H is known, and the output-flow function curve can be interpolated according to the NHQ curve. The maximum active power that the unit can generate is known, so the maximum power generation flow of the power station can be calculated by interpolation.

[0068] S3: Set the flow reference value according to the historical data of coordinated operation of the power station; when the interval inflow flow is greater than the flow reference value, adopt the large flow active power preprocessing algorithm; otherwise, the negative feedback regulation active power prediction algorithm based on the water level on the dam predicts the active power setting value of the unit to achieve automatic optimization distribution of the active power of the unit.

[0069] Furthermore, the specific method of the large-flow active power preprocessing algorithm is: when the interval inflow flow exceeds the flow baseline value, the baseline water level interval range of the reservoir is reduced to make the reservoir have a relatively large water storage space, and the execution rate of the active power adjustment algorithm is increased to cope with the sudden rise in water level.

[0070] Furthermore, according to the historical data of the coordinated operation of the power station, the range of the base water level of the reservoir is reduced, for example, the upper and lower limits are reduced by 60 cm each, so that the reservoir has a relatively large water storage space; secondly, the execution speed of the active power adjustment algorithm is accelerated, from the original adjustment every 100 seconds to every 30 seconds, in order to cope with the sudden rise of the water level. After the adjustment of the base water level range and the execution speed of the active power adjustment algorithm is completed, the negative feedback adjustment active power prediction algorithm based on the water level on the dam is executed.

[0071] Furthermore, the active power prediction algorithm based on the negative feedback regulation of the water level on the dam adopts negative feedback regulation control on the water level output in front of the dam, and the active power of the unit is adjusted to maintain the water level on the dam within the reference water level range. The specific steps of the negative feedback regulation active power prediction algorithm based on the water level on the dam are:

[0072] B1: Obtain the real-time active power of each unit in this reservoir, the real-time water level on the dam and the reference water level range on the dam. The reference water level range on the dam is obtained based on historical data.

[0073] B2: Determine whether the current water level on the dam is within the dam reference water level range. If the water level on the dam is within the dam reference water level range, it is in a balanced state and directly enters AGC regulation; if it is not in a balanced state, calculate the active power adjustment of the power station according to the water level negative feedback regulation control algorithm.

[0074] Furthermore, the steps to calculate the active power of the power station are as follows:

[0075] C1: Calculate the real-time power generation flow of the reservoir based on the initial value of the power generation head, NHQ curve and the real-time active power of the unit. Obtain the water level above the dam and the water level below the dam, and calculate the initial value of the turbine power generation head H=Z t -Z0, the output-flow function curve can be interpolated according to the NHQ curve. The actual active power generated by the current unit is known, so the real-time power generation flow of the unit can be interpolated and calculated. Finally, the real-time power generation flow of each unit is added together to obtain the real-time power generation flow of the power station.

[0076] C2: Calculate the expected power generation flow using a negative feedback regulation control algorithm.

[0077] Given the water level on the dam, the current reservoir capacity is obtained by interpolation based on the dam water level-reservoir capacity relationship function curve; then the reservoir capacity corresponding to the optimal reference water level is calculated (the optimal reference water level is the average of the upper and lower limits of the reference water level range), thereby obtaining the reservoir capacity that needs to be adjusted. In order to suppress the serious overshoot caused by excessive adjustment speed, it is necessary to calculate the control deviation between the required adjustment reservoir capacity in the previous time period and the adjustment reservoir capacity in the current time period. The algorithm for adjusting the reservoir capacity is as follows:

[0078]

[0079] where u(t) is the adjusted storage capacity, K p is the proportionality coefficient, K i is the integral coefficient, e(t) is the control deviation between the storage capacity required to be adjusted in the previous time period and the storage capacity adjusted in the current time period, It is the adjusted reservoir capacity required for the optimal benchmark water level and the current water level in front of the dam.

[0080] The optimal reference water level and the current dam front water level adjustment reservoir tolerance are obtained, and then divided by the time period to obtain the adjustment flow. The current power generation flow and the adjustment flow are added to obtain the expected power generation flow.

[0081] C3: Based on the NHQ curve, the active power setting value is determined by interpolation of the known current head value H and the expected power generation flow.

[0082] C31: Calculate the initial value of the generating head H = Z t -Z0, the output-flow function curve can be interpolated according to the NHQ curve.

[0083] C32: Determine whether the expected power generation flow q exceeds the maximum flow corresponding to the maximum output of a single machine. If the expected power generation flow is less than the maximum power generation flow of a single machine, the operating curve is the curve obtained by C31; if it is greater than the maximum power generation flow of a single machine, and the unit operating characteristics are the same, then multiply the NQ coordinate value corresponding to the curve obtained by C31 by the required number of generator sets. If the unit operating characteristics are different, then add the NQ curves of different units to obtain the multi-machine operating curve. Finally, interpolate the corresponding active power setting value based on the obtained NQ curve.

[0084] C33: Based on the NQ curve obtained in the above steps, interpolate and obtain the corresponding active power setting value.

[0085] This embodiment also provides an intelligent control system for active power regulation of a runoff power station, comprising:

[0086] The calculation module obtains the initial storage capacity of the reservoir in the specified period, the final storage capacity of the reservoir in the specified period, and the outflow of the upstream power station as the outflow of the reservoir, and calculates the interval inflow between the upstream reservoir and the reservoir;

[0087] The judgment module judges whether the power station meets the start-up and shutdown conditions of the unit, and performs corresponding start-up and shutdown operations if the start-up and shutdown conditions are met;

[0088] The setting module sets the flow reference value according to the historical data of coordinated operation of the power station; when the interval inflow flow is greater than the flow reference value, the large flow active power preprocessing algorithm is adopted; otherwise, the active power prediction algorithm based on the negative feedback regulation of the water level on the dam predicts the active power setting value of the unit to realize the automatic optimization distribution of the active power of the unit.

[0089] Furthermore, it also includes:

[0090] Memory, used to store programs;

[0091] A processor is used for loading the program to execute the progressive image recognition method based on sub-modular optimization constraints.

[0092] This embodiment also provides a computer-readable storage medium storing a program, which, when executed by a processor, implements the progressive image recognition method based on sub-modular optimization constraints.

[0093] The storage medium proposed in this embodiment and the progressive image recognition method based on sub-module optimization constraints proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0094] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0095] Example 2

[0096] Reference Figure 2-3 , which is an embodiment of the present invention, provides an intelligent control method for active power regulation of a run-of-river power station. In order to verify its beneficial effects, scientific demonstration is carried out through specific implementation methods and implementation effects.

[0097] The present embodiment is as follows:

[0098] The actual operation process of the West Gate on June 2, 2023 was selected for analysis. The benchmark water level range was set to 165.90-165.93 meters, the proportional coefficient was 0.05, the integral coefficient was 2, and it was adjusted every 100 seconds.

[0099] 1. When the interval inflow is less than the flow reference value, the active power regulation intelligent control process is as follows Figure 3 As shown in the figure: when the upstream water increases slowly, the active setting value increases slowly; when the upstream water is rapid but the interval inflow is less than the flow reference value of 200m 3 / s, the active setting step size is increased each time, so that the water level in front of the dam is always maintained within the reference water level range of 165.9-165.93m.

[0100] 2. When the interval inflow is greater than the flow reference value, the active power regulation intelligent control process is as follows Figure 4 As shown: It is judged that the upstream water exceeds the flow reference value. At around 14:43 in the figure, the reference water level range is lowered to 165.84-165.87m. After the water level drops, it is restored to the original reference water level of 165.9-165.93m. Since it takes about 15 minutes for the upstream water to reach the west gate, the speed is set to 15 minutes later. At around 14:57 in the figure, the adjustment speed is changed from 100 seconds to once every 30 seconds.

[0101] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent control method for active power regulation of a runoff power station, characterized in that: include: Get the initial storage capacity of the reservoir within the specified time period, the final storage capacity of the reservoir, the outflow of the upstream power station as the outflow of the reservoir, and calculate the interval inflow between the upstream reservoir and the reservoir; Determine whether the power station meets the unit start-up and shutdown conditions, and if so, perform the corresponding start-up and shutdown operations; Set the flow rate benchmark value based on the historical data of the coordinated operation of the power station; When the interval inflow flow is greater than the flow reference value, a large flow active power preprocessing algorithm is used; Otherwise, the active power prediction algorithm based on the negative feedback regulation of the water level on the dam predicts the active power setting value of the unit to achieve automatic optimization of the active power distribution of the unit; The formula for calculating the interval inflow between the upstream reservoir and the reservoir is specifically: V1-V0=(Q s +q-Q c )*t Among them, V0 represents the initial storage capacity of this period, V1 represents the final storage capacity of this period, Q s represents the outflow from the upstream power station, Q c represents the outbound flow of this warehouse, t represents the time interval, and q represents the actual inbound flow of this warehouse; The negative feedback regulation active power prediction algorithm based on the water level on the dam has the following specific steps: Obtain the real-time active power of each unit in the reservoir, the real-time water level on the dam, and the reference water level range on the dam; Determine whether the current water level on the dam is within the dam reference water level interval. If the water level on the dam is within the dam reference water level interval, it is in a balanced state and directly enters AGC regulation; if it is not in a balanced state, calculate the active power adjustment of the power station according to the water level negative feedback regulation control algorithm; The specific steps of calculating the power station adjustment active power are as follows: Calculate the real-time power generation flow of the database based on the initial value of the power generation head, the head-output-flow relationship curve of each unit and the real-time active power of the unit; Calculate the expected power generation flow using a negative feedback control algorithm. According to the dam water level-reservoir capacity relationship function curve, calculate the optimal reference water level and the current dam front water level to adjust the reservoir tolerance. Divide by the time period to get the adjusted flow. Calculate the expected power generation flow through the current power generation flow and the adjusted flow. Based on the head-output-flow relationship curve of each unit, the active power setting value is determined by interpolating the head value H and the expected power generation flow; The adjusted flow rate is expressed as: Among them, u(t) represents the adjusted storage capacity, K p Represents the proportionality coefficient, K i represents the integral coefficient, e(t) represents the control deviation between the storage capacity required to be adjusted at the previous time point and the storage capacity adjusted at the current time point, Indicates the adjusted storage capacity required for the optimal reference water level and the current water level in front of the dam; The active power setting value is determined by interpolating the water head value H and the expected power generation flow, and the specific steps are as follows: Calculate the initial value of the generating head, and interpolate the output-flow function curve according to the head-output-flow relationship curve of each unit; Determine whether the expected power generation flow q exceeds the maximum flow corresponding to the maximum output of a single machine. If the expected power generation flow is less than the maximum power generation flow of a single machine, the operation curve is the output-flow function curve; if it is greater than the maximum power generation flow of a single machine, the multi-machine operation curve is obtained according to the unit operation characteristics; According to the obtained head-flow curve, the corresponding active power setting value is obtained by interpolation.

2. The intelligent control method for active power regulation of a runoff power station according to claim 1, characterized in that: The power station is judged whether it meets the start-up and shutdown conditions of the unit. If the start-up and shutdown conditions are met, the corresponding start-up and shutdown operations are performed. The specific rules are as follows: Calculate the power generation flow of the unit in this warehouse when it is fully powered. When the interval inflow flow is greater than the power generation flow of the unit in the power generation state when it is fully powered, and there are units that can be started, increase the unit operation; If there is no unit that can be started, all units will run at full capacity; When one or several units are reduced from generating electricity, and the current interval inflow flow is less than the generating flow of the remaining units at full power, the units will be shut down.

3. A system based on the intelligent control method for active power regulation of a runoff power station according to claim 1, characterized in that: include: The calculation module obtains the initial storage capacity of the reservoir in the specified period, the final storage capacity of the reservoir in the specified period, and the outflow of the upstream power station as the outflow of the reservoir, and calculates the interval inflow between the upstream reservoir and the reservoir; The judgment module judges whether the power station meets the start-up and shutdown conditions of the unit, and performs corresponding start-up and shutdown operations if the start-up and shutdown conditions are met; Setting module, setting flow reference value according to the historical data of coordinated operation of power station; When the interval inflow flow is greater than the flow reference value, a large flow active power preprocessing algorithm is used; Otherwise, the active power prediction algorithm based on the negative feedback regulation of the water level on the dam predicts the active power setting value of the unit to achieve automatic optimization of the active power distribution of the unit.

4. An electronic device, characterized in that: include: Memory, used to store programs; A processor is used to load the program to execute the intelligent control method for active power regulation of a run-of-river power station as described in any one of claims 1-2.

5. A computer-readable storage medium storing a program, characterized in that: When the program is executed by the processor, the intelligent control method for active power regulation of a run-of-river power station as described in any one of claims 1-2 is implemented.

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