Method and device for determining economic operation of power plant under dynamic control of reservoir water level during flood season

Abstract

The application discloses a method and device for determining economic operation of a power plant under dynamic control of reservoir flood season operation water level. The method comprises the following steps: determining flood control risk based on a dynamic control strategy of reservoir flood season operation water level; determining reservoir hydropower station water quantity according to reservoir water storage and release quantity for resisting secondary rain flood, and constructing an economic operation model of the power plant, wherein the economic operation model of the power plant comprises a target function of maximizing total power generation of the hydropower station in a foreseeable period and at least a constraint condition of reservoir hydropower station water quantity; and adopting a particle swarm algorithm to optimize the economic operation model of the power plant, and determining optimal dispatching conditions of the generator set. In the method, the economic operation model of the power plant under the mode of determining electricity according to water is constructed, optimal output of the hydropower station, number, combination and output of each operating unit of the power plant are determined; and re-optimization dispatching of the economic operation of the power plant under control of risk-controllable reservoir flood control dispatching and total water consumption is considered, so that not only the accuracy of the economic operation analysis of the power plant is improved, but also the calculation granularity is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of reservoir regulation, and in particular to a method and device for determining economic operation of a power plant under dynamic control of a flood season operation water level of a reservoir. BACKGROUND

[0002] The "dynamic control of a flood season operation water level" of a reservoir in real-time regulation refers to a method for determining a specific value of a dynamically controlled flood season operation water level in a prediction period within an upper and lower limit domain value of a designed flood season operation water level, according to meteorological and hydrological forecast information of a reservoir basin, water regime information at a moment, working condition information and disaster condition information, under the premise of meeting the requirements of reservoir water storage, reservoir water discharge capacity and flood control and water utilization, and is one of effective methods for improving the utilization level of water resources in a basin and the water supply guarantee capacity.

[0003] In related technologies, especially the technologies represented by CN117592876A and CN117791737A, economic operation data analysis of a power plant is usually committed to starting from factors affecting cost and benefit, but these methods are difficult to comprehensively reflect the evaluation results of economic operation of the power plant, and reduce the accuracy of evaluation of economic operation of the power plant. SUMMARY

[0004] Therefore, the application provides a method and device for determining economic operation of a power plant under dynamic control of a flood season operation water level of a reservoir, which can improve the accuracy of economic operation analysis.

[0005] In a first aspect, the application provides a method for determining economic operation of a power plant under dynamic control of a flood season operation water level of a reservoir, comprising:

[0006] Based on a dynamic control strategy of a flood season operation water level of a reservoir according to a pre-storage, pre-discharge and recharge method, a flood control risk is determined, and the water storage and discharge amount of the reservoir against secondary rain floods is determined according to the flood control risk;

[0007] The water amount of a reservoir hydropower station is determined according to the water storage and discharge amount of the reservoir against secondary rain floods, and an economic operation model of the power plant is constructed, the economic operation model of the power plant including a target function of maximizing total power generation of the hydropower station in a prediction period and at least a constraint condition of a generator set parameter, a hydropower station output limit and the water amount of the reservoir hydropower station;

[0008] A particle swarm algorithm is used to perform optimization calculation on the economic operation model of the power plant to determine an optimal dispatching condition of the generator set.

[0009] Optionally, the dynamic control strategy of the flood season operation water level of the reservoir comprises:

[0010] A water level range of dynamic control of the flood season operation water level is predefined, and the water level of the reservoir at the moment is located in the water level range;

[0011] If a super flood is predicted to occur within a certain forecast period, the pre-storage, pre-discharge and recharge method is adopted. The water level at the end of the forecast period is calculated from the allowable discharge flow within the forecast period, and the discharge scheme is optimized based on the water level at the end of the forecast period and the water level range.

[0012] If a major flood is predicted to occur within a certain forecast period, the reservoir water level will be established as the reservoir water level at that time.

[0013] If a small to medium-sized flood is predicted to occur within a certain forecast period, the reservoir water level will be set as the upper limit of the aforementioned water level range.

[0014] Optionally, the water level at the end of the forecast period can be estimated from the allowable discharge flow within the forecast period using the following formula.

[0015] ;

[0016] ;

[0017] ;

[0018] In the formula: for t Allow flow to be released at any time; The safe flow rate for flood control targets; The inflow is the section between the reservoir dam section and the flood control section. In preparation for the moment, For flood forecast period, This refers to the amount of water that can be pre-discharged within the forecast period. To predict the inbound flow during the forecast period, To calculate the length of the time period, To anticipate the end of the period The water level is constantly dropping. This is a function that converts water level into reservoir capacity.

[0019] Optionally, the discharge scheme is optimized based on the predicted drawdown level and the predicted water level range, including:

[0020] If the predicted drawdown level at the end of the period is lower than the dynamic control range of the flood season operating water level, the reservoir capacity difference is determined, and the amount of water that can be replenished is determined using a simplified water balance formula that generalizes the receding water line to a straight line. The simplified water balance formula is expressed by the following formula.

[0021]

[0022] In the formula, This refers to the amount of water that can be refilled. To anticipate the end of the period Inbound traffic at any given time Qmin Qmin tmin tmin Qmin

[0023] Qmin Qmin

[0024] Qmin Qmin

[0025] Qmin Qmin Qmin

[0026] Qmin Qmin Qmin

[0027] Qmin Qmin Qmin

[0028] Qmin Qmin Qmin Qmin Qmin Qmin Qmin Qmin Qmin

[0029] Qmin Qmin Qmin

[0030] Qmin Qmin Qmin

[0031] Qmin Qmin Qmin

[0032] Qmin Qmin Qmin

[0033] Qmin Qmin Qmin Qmin Qmin Qmin Qmin Qmin Qmin QminFor the moment, For the flood forecasting period.

[0034] Optionally, the determination of the flood control risk is performed by the following formula,

[0035] ;

[0036] ;

[0037] In the formula, is the design frequency of the reservoir The maximum allowable water level of the flood; is the design frequency of the reservoir The maximum allowable discharge of the flood; is the nth n flood control water level The flood control risk rate after flood regulation exceeding the maximum allowable water level; is the nth n flood control water level The flood control risk rate after flood regulation exceeding the maximum allowable discharge; is the design frequency of the reservoir The flood control risk rate of the flood; is the design frequency of the reservoir When the flood occurs, the nth n flood control water level is used to regulate the flood to obtain the maximum water level of flood regulation; is the design frequency of the reservoir When the flood occurs, the nth n flood control water level is used to regulate the flood to obtain the maximum water level of flood regulation.

[0038] Optionally, the objective function is in the form of the following formula,

[0039] ;

[0040] In the formula, is the number of units that can be put into operation at the moment, which is less than or equal to the total number of units; t is the number of units put into operation and less than or equal to w ; is the number of the nth unit that can be put into operation at the moment; t is the number of the nth w unit that can be put into operation at the moment; is the output of the nth g unit of the power plant;

[0041] The constraint conditions of the generator set parameters include unit head constraint, unit output limit and unit water consumption characteristics, and the constraint conditions of the reservoir hydropower station water quantity include total water quantity constraint, reservoir hydropower station water quantity balance constraint, reservoir water level constraint and initial reservoir water level constraint.

[0042] The constraint conditions of the power plant economic operation model further include minimum discharge flow of downstream comprehensive utilization requirement and reservoir hydropower station characteristic curve constraint.

[0043] Optionally, in the process of performing the optimization calculation by using the particle swarm algorithm, the population size takes the reservoir water level at the end of the period as the decision variable.

[0044] In a second aspect, the present application provides a device for determining power plant economic operation under reservoir flood season operation water level dynamic control, comprising:

[0045] A first determining module is configured to determine a flood control risk based on a reservoir flood season operation water level dynamic control strategy based on the pre-accumulation and pre-discharge recharging method, and determine reservoir water storage and discharge amount for resisting secondary rain flood based on the flood control risk.

[0046] A second determining module is configured to determine reservoir hydropower station water quantity according to the reservoir water storage and discharge amount for resisting secondary rain flood, and construct a power plant economic operation model, wherein the power plant economic operation model includes a target function of maximizing total power generation of the hydropower station within a foreseeable period and constraint conditions of at least generator set parameters, hydropower station output limit and reservoir hydropower station water quantity.

[0047] A third determining module is configured to perform optimization calculation on the power plant economic operation model by using a particle swarm algorithm to determine optimal dispatching conditions of the generator set.

[0048] In a third aspect, the present application provides an execution device, comprising a processor and a memory, wherein the processor is coupled with the memory;

[0049] The memory is configured to store a program.

[0050] The processor is configured to execute the program in the memory, so that the execution device executes the method as described above.

[0051] In the method disclosed in the present application, a general model for determining power plant economic operation under reservoir water power mode is constructed and efficiently solved, not only the optimal output of the hydropower station is determined, but also the number, combination and output of each operating generator set of the power plant are determined; not only the reservoir flood control dispatching based on controllable risk is considered, but also the re-optimization dispatching technology of the power plant economic operation under total water quantity control is considered, thereby improving the accuracy of the power plant economic operation analysis and the calculation granularity. BRIEF DESCRIPTION OF DRAWINGS

[0052] The technical solutions and other beneficial effects of the present application will become apparent from the detailed description of specific embodiments of the present application given below, in conjunction with the accompanying drawings.

[0053] Figure 1 An operation flow chart of a method for determining economic operation of a power plant under dynamic control of reservoir flood season operation water level is shown.

[0054] Figure 2 A logic principle diagram of the method for determining economic operation of the power plant under dynamic control of reservoir flood season operation water level is shown.

[0055] Figure 3 A dynamic control domain diagram of the Three Gorges Reservoir flood season operation water level is shown.

[0056] Figure 4 A dynamic control scheduling diagram of the Three Gorges Reservoir flood season operation water level is shown.

[0057] Figure 5 A particle swarm algorithm iteration process of economic operation of the Three Gorges hydropower station power plant is shown.

[0058] Figure 6 A structure block diagram of a device for determining economic operation of a power plant under dynamic control of reservoir flood season operation water level is shown.

[0059] Figure 7 A structure block diagram of an execution device is shown. DETAILED DESCRIPTION

[0060] In order to make the above objectives, features and advantages of the present application more apparent, specific embodiments of the present application are described in detail below in conjunction with the accompanying drawings. In the following description, a lot of specific details are set forth in order to fully understand the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the spirit of the present application, so the present application is not limited to the specific embodiments disclosed below.

[0061] The terms "first", "second", and the like in the description and in the claims of the present application and above-described drawings are used to distinguish similar objects and are not necessarily used to describe a specific sequential or chronological order. It should be understood that the terms so used are interchangeable under appropriate circumstances and that the embodiments described herein are capable of functioning in other sequences than the one illustrated or described herein. Furthermore, the terms "comprise", "comprising", "include", "including", and "has", "having" and any variations thereof are intended to cover a non-exclusive inclusion, for example, a process, method, system, product or apparatus that comprises a list of steps or modules is not necessarily limited to those specifically listed, but can include other steps or modules not expressly listed or inherent to such process, method, product or apparatus. The naming or numbering of the steps in the present application does not mean that the steps in the method flow must be executed in the order / sequential order indicated by the naming or numbering. The steps that have been named or numbered can change the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved. The division of units in the present application is a logical division, and in actual application, it can have another division manner, for example, a plurality of units can be combined or integrated in another system, or some features can be ignored or not executed, in addition, the coupling or direct coupling or communication connection between the units shown or discussed can be through some interface, the indirect coupling or communication connection between the units can be electrical or other similar forms, which are not limited in the present application. In addition, the units or sub-units described as separate components can or can not be physically separated, can or can not be physical units, or can be distributed in a plurality of circuit units, and part or all of the units can be selected according to actual needs to achieve the purpose of the present application.

[0062] Reference is made to Figure 1 , wherein Figure 1 A flow chart of a method for determining economic operation of a power plant under dynamic control of reservoir flood season operation water level is shown. The method is implemented by steps 102-106.

[0063] In step 102, based on the dynamic control strategy of reservoir flood season operation water level, the flood control risk is determined to determine the reservoir flood control risk.

[0064] Reference is made to Figure 2 It can be understood that the dynamic control strategy of reservoir flood season operation water level is based on the pre-accumulation and pre-discharge method, which means that the design principle of the dynamic control strategy of reservoir flood season operation water level is based on the pre-accumulation and pre-discharge method.

[0065] As a preferred specific example, the dynamic control strategy of reservoir flood season operation water level includes:

[0066] Step 102A1: Predefine the water level range for dynamic control of water level during the flood season, wherein the reservoir water level is within the water level range at any given time.

[0067] In this step 102A1, it is assumed that the time is... Reservoir water level Within the dynamic control range of the operating water level during the flood season, it is denoted as Furthermore, the outflow is controlled to equal the inflow, ensuring that the reservoir's water level is at a certain level. Please refer to Figure 3 .

[0068] Step 102A2: If a super flood is predicted to occur within a certain forecast period, the pre-storage, pre-discharge and recharge method is adopted. The water level at the end of the forecast period is calculated from the allowable discharge flow within the forecast period, and the discharge scheme is optimized based on the water level at the end of the forecast period and the water level range.

[0069] Please refer to Figure 4 As a typical specific demonstration, the water level at the end of the forecast period is calculated from the allowable discharge flow within the forecast period using the following formula.

[0070] ;

[0071] ;

[0072] ;

[0073] In the formula: for t Allow flow to be released at any time; The safe flow rate for flood control targets; The inflow is the section between the reservoir dam section and the flood control section. In preparation for the moment, For flood forecast period, This refers to the amount of water that can be pre-discharged within the forecast period. To predict the inbound flow during the forecast period, To calculate the length of the time period, To anticipate the end of the period The water level is constantly dropping. This is a function that converts water level into reservoir capacity.

[0074] In step 102A2, optimizing the discharge scheme based on the predicted drawdown water level and the water level range includes:

[0075] Step 102A21, if the water level at the end of the predicted period is lower than the water level range of the dynamic control of the water level during the flood season, the reservoir capacity difference is determined, and the rechargeable water amount is determined by using the simplified water balance equation in which the recession curve is approximated as a straight line, wherein the simplified water balance equation is represented by the following formula,

[0076]

[0077] wherein, is the rechargeable water amount; is the inflow at the end of the predicted period, is the minimum water supply requirement corresponding flow, is the occurrence time of the flow equal to during the recession process, is the facing time.

[0078] Here, the formula for determining the reservoir capacity difference can be: wherein, is the function of converting the reservoir capacity into the water level.

[0079] It can be understood that in this step 102A21, if the water level at the end of the predicted period is higher than the lower limit of the water level range of the dynamic control of the water level during the flood season, i.e. , it means that the discharge scheme is feasible; if the water level at the end of the predicted period is equal to the lower limit of the water level range of the dynamic control of the water level during the flood season, i.e. , it means that the discharge scheme is optimal.

[0080] Step 102A22, if the rechargeable water amount is equal to the dischargeable water amount during the predicted period or the rechargeable water amount is greater than the reservoir capacity difference, i.e. or , the discharge scheme is maintained.

[0081] Step 102A23, if the rechargeable water amount is lower than the reservoir capacity difference, i.e. , the discharge flow is reduced until the lower limit value of the water level range of the dynamic control of the water level during the flood season, i.e. .

[0082] Step 102A3, if the future predicted period will have a large flood, the reservoir water level is determined as the facing time reservoir water level.

[0083] In this case, the average discharge flow during the predicted period can be determined by the following formula ,

[0084] ;

[0085] ;

[0086] wherein:​ is the maximum value of inflow in the interval between the cross section of the reservoir dam and the flood control cross section in the forecast period, is the flow corresponding to the minimum water supply requirement, is the safety flow of the flood control object, is the inflow in the forecast period, is the length of the calculation period, is the facing time, is the flood forecast period.

[0087] Step 102A4, if it is predicted that a small or medium flood will occur in the future forecast period at the facing time, the reservoir water level is determined as the upper limit value of the water level range.

[0088] In this case, the average discharge in the forecast period can be determined by the following formula ,

[0089] ;

[0090] ;

[0091]

[0092] In the formula: is the water level at the facing time is the reservoir storage capacity difference between the dynamic control upper limit water level of the flood season operation water level , is a function of converting reservoir capacity into water level, is the flow corresponding to the minimum water supply requirement, is the safety flow of the flood control object, is the inflow in the forecast period, is the length of the calculation period, is the facing time, is the flood forecast period.

[0093] As a preferred specific example, the process of determining the flood control risk can be: taking the allowed maximum storage water level of the planning approval (the allowed maximum discharge ) as the flood control index, assuming different flood control water levels , when the reservoir resists floods of different design frequencies, the flood is regulated in the conventional dispatching manner of the approval, and the flood control risk rate of the flood control standard exceeding the design frequency is calculated . , .

[0094] That is, it is executed by the following formula

[0095] ;

[0096] ;

[0097] In the formula: To protect the reservoir from the design frequency The maximum permissible water level for flood storage; To protect the reservoir from the design frequency The maximum permissible discharge flow rate of the flood; For the first n Individual flood control limit water level The flood control risk rate exceeding the maximum allowable water storage level after flood regulation; For the first n Individual flood control limit water level The flood control risk rate of exceeding the maximum allowable discharge flow after flood regulation; To protect the reservoir from the design frequency Flood risk rate; To protect the reservoir from the design frequency During floods, the first method is adopted. n The highest flood control water level corresponding to the flood control limit water level; To protect the reservoir from the design frequency During floods, the first method is adopted. n The flood control limit level corresponds to the highest flood control level for each flood.

[0098] In practice, when determining , After that, it can be drawn Relationship curve and The relationship curve is used to assess the flood control risk rate of dynamic water level control during the flood season in step one. Dynamic water level control during the flood season of the reservoir is implemented. The flood control method employs pre-storage, pre-discharge, and recharge, adhering to the principle of not lowering flood control standards, to achieve the reservoir's water storage and release process to withstand secondary rainstorms. This water storage and release process will serve as the water quantity constraint for the subsequent "water-based power generation" mode of economic operation of the power plant.

[0099] In step 104, the water volume of the reservoir hydropower station is determined based on the water storage and release volume of the reservoir to resist the secondary rain flood, and an economic operation model of the power plant is constructed. The economic operation model of the power plant includes an objective function that maximizes the total power generation of the hydropower station within the foreseeable period and at least the generator unit parameters, the power output limit of the hydropower station, and the water volume of the reservoir hydropower station as constraints.

[0100] The objective function is expressed by the following formula.

[0101] ;

[0102] In the formula: For the first tThe number of generating units that can be put into operation at any given time is less than or equal to the total number of generating units; w The unit number is less than or equal to the number of the unit being put into operation. ; For the first t Time of the first w The number can be assigned to the power plant number corresponding to the generating unit; For the power plant g The output of Unit 1.

[0103] The constraints of the power plant economic operation model include the following:

[0104] (1) Total water volume constraint:

[0105]

[0106] In the formula: For the first t The hydroelectric power generation flow rate at any given time; For the first t Real-time reservoir discharge volume; For the first t Time of the first g Power generation flow of Unit No. 1; Forecast period The total outflow from the inner reservoir is based on the reservoir's flow rate in step one. The water release process for dynamic control of water level during the flood season is calculated within the forecast period.

[0107] (2) Water balance constraints of reservoirs and hydropower stations

[0108] .

[0109] (3) Reservoir water level constraints

[0110] ;

[0111] In the formula: For the first t Real-time reservoir water level; and The first t The reservoir's minimum and maximum allowable water levels are specified at all times. The minimum allowable water level is usually the dead water level, while the maximum allowable water level is the reservoir water level process line dynamically controlled during the flood season.

[0112] (4) Unit head constraint

[0113] ;

[0114] In the formula: For the first t Time of the first g Unit 1 clean water head; and are the minimum and maximum water head of the g th unit, respectively; is the downstream water level at time t th unit; is the water head loss of the t th unit at time g th unit; is the water head loss function of the g th unit.

[0115] (5) Unit output limit

[0116] ;

[0117] wherein: and are the minimum and maximum output of the t th unit at time g th unit, respectively.

[0118] (6) Unit water consumption characteristic

[0119] ;

[0120] wherein: is the water consumption characteristic curve of the g th unit, reflecting the relationship between the unit output and water head and the unit power generation flow.

[0121] (7) Total output limit of the hydropower station

[0122] ;

[0123] wherein: is the output of the hydropower station at time t th unit, respectively. and are the minimum and maximum output of the hydropower station at time t th unit, respectively.

[0124] (8) Comprehensive utilization constraint

[0125] ;

[0126] wherein: is the minimum downstream flow determined by considering the ecological, water supply, shipping and other needs.

[0127] (9) Initial reservoir water level constraint

[0128] ;

[0129] wherein: initial reservoir water level for the forecasting period; the reservoir water level at the moment, which is obtained according to the dynamic control calculation of the reservoir flood season operation water level in step 102.

[0130] In addition to satisfying the above constraint conditions, the reservoir hydropower station dispatching operation also needs to satisfy its own characteristic curve constraints, such as the reservoir water level-reservoir capacity relationship curve, the reservoir water level-discharge capacity curve, the downstream water level-flow relationship curve, the unit expected output limit line, and the optimal dynamic characteristic curve of the whole plant. In addition, various variables must be non-negative variables.

[0131] The economic operation of the power plant aims to seek the optimal number of working units, combination, and distribution of active loads among working units under the optimal generation capacity criterion. According to the unique conversion relationship characteristics between the key variables of the reservoir (reservoir storage at the end of the period) and the key variables of the hydropower station (unit generation output and generation flow in the period), and considering the water-to-power mode, the reservoir storage at the end of the period is selected as the decision variable of the economic operation model of the power plant.

[0132] In step 106, a particle swarm algorithm is used to perform optimization calculation on the economic operation model of the power plant to determine the optimal dispatching condition of the generator unit.

[0133] Please refer to Figure 5 , as a practical operation demonstration of the particle swarm algorithm, which can include the following processes:

[0134] Step 1061, set the particle swarm algorithm parameters and initialize the population. Set the three hyperparameters (inertia weight =0.9, individual learning factor c 1=3.5 and group learning factor c 2=1.5) of the particle swarm algorithm and the population size N pop =500 and the maximum number of iterations G max =200. Encode and randomly generate N pop size decision variables, i.e., reservoir water level at the end of the period .

[0135] Step 1062, update the individual extreme value and the global extreme value . After initializing the position and speed of the particle swarm, add the constraints in the form of a penalty function to the objective function, and evaluate the fitness with the new objective function added with the constraints; according to the maximum generation capacity principle, calculate the local optimal of each particle; calculate and update the Archive set (store the current non-inferior solution, and pay attention to prevent overflow); calculate the congestion degree in the Archive set to select the global optimal of the particle swarm in the Archive set.

[0136] Step 1063: Update the particle's velocity and position. The formulas for updating the particle's velocity and position are as follows:

[0137] ;

[0138] ;

[0139] In the formula, m Indicates the current iteration number;

[0140] j Indicates the particle (feasible solution) index. , It is the size of the particle swarm.

[0141] Let be the particle dimension. ,in The number of decision variables (particle dimension);

[0142] For the first m The second iteration The first particle The velocity component serves as the distance and direction of the particle's movement in the next optimization iteration;

[0143] For the first m The second iteration The first particle The positional component, i.e., the decision variable's positional component. m The result of the next iteration;

[0144] For the first m The second iteration The first particle Individual extreme value components;

[0145] For the first m The second iteration dimensional global extremum components;

[0146] The inertia weight (hyperparameter) is a non-negative number used to adjust the search range of the solution space;

[0147] These are the individual learning factor and the group learning factor (hyperparameters), which can be used as weights to adjust the maximum learning step size;

[0148] All are uniformly distributed in [0,1]. m The next iteration random factor is used to increase the randomness of the search.

[0149] Step 1064: Determine the termination condition. If the current iteration number is less than the maximum iteration number G. max If the condition is met, repeat steps 1062-1064; otherwise, terminate the calculation and determine the optimal number of working units, combination, and active load distribution among working units for each time period by querying the optimal characteristic curve.

[0150] Please refer to Figure 6 This application illustrates a block diagram of the device for determining the economic operation of a power plant under dynamic control of reservoir operating water levels during the flood season, as provided in this application. The device 200 includes:

[0151] The first determining module 202 is used to determine the flood control risk based on the reservoir's dynamic water level control strategy during the flood season, which is based on the pre-storage and pre-discharge recharge method, and to determine the amount of water to be stored and released by the reservoir to resist the next rainstorm flood based on the flood control risk.

[0152] The second determining module 204 is used to determine the water volume of the reservoir hydropower station based on the water storage and release volume of the reservoir to resist the secondary rain flood, and to construct an economic operation model of the power plant. The economic operation model of the power plant includes an objective function of maximizing the total power generation of the hydropower station within the foreseeable period and at least the generator unit parameters, the power output limit of the hydropower station and the water volume of the reservoir hydropower station as constraints.

[0153] The third determining module 206 is used to perform optimization calculations on the power plant's economic operation model using the particle swarm optimization algorithm to determine the optimal scheduling status of the generator units.

[0154] Since the methods mentioned above have already been discussed in detail, the specific execution of the above modules will not be repeated here.

[0155] The following describes an execution device provided in an embodiment of this application. Please refer to [link / reference]. Figure 7 , Figure 7 This is a schematic diagram of an execution device provided in an embodiment of this application. The execution device 300 can specifically be an autonomous vehicle, a mobile phone, a tablet, a laptop, a desktop computer, a monitoring data processing device, etc., and is not limited thereto. The execution device 300 is used to implement... Figure 1 The corresponding embodiment executes the function of the device. Specifically, the execution device 300 includes: a receiver 301, a transmitter 302, a processor 303, and a memory 304 (wherein the execution device 300 may have one or more processors 303). Figure 7 (Taking a processor as an example), processor 303 may include application processor 3031 and communication processor 3032. In some embodiments of this application, receiver 301, transmitter 302, processor 303 and memory 304 may be connected via bus or other means.

[0156] The memory 304 can include read-only memory and random access memory, and provide instructions and data to the processor 303. A portion of the memory 304 can also include non-volatile random access memory (NVRAM). The memory 304 stores processor and operating instructions, executable modules, or data structures, or a subset thereof, or an extended set thereof, wherein the operating instructions can include various operating instructions for implementing various operations.

[0157] The processor 303 controls the operation of the execution device. In a specific application, various components of the execution device are coupled together through a bus system, which can include a data bus, a power bus, a control bus, and a state signal bus, etc. However, for the sake of clarity, all the buses are referred to as a bus system in the figure.

[0158] The method disclosed in the above embodiments of the present application can be applied in the processor 303 or implemented by the processor 303. The processor 303 can be an integrated circuit chip with a processing capability of signals. In the implementation process, each step of the above method can be completed by integrated logic circuits or instructions in the form of software in the processor 303. The processor 303 mentioned above can be a general processor, a digital signal processor (DSP), a microprocessor or a microcontroller, and can further include an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The processor 303 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, or other mature storage media in the art. The storage medium is located in the memory 304, and the processor 303 reads the information in the memory 304 and combines the hardware to complete the steps of the above method.

[0159] The receiver 301 can be used to receive inputted digital or character information, and generate signal input related to the relevant settings of the execution device and the function control. The transmitter 302 can be used to output digital or character information through the first interface; the transmitter 302 can also be used to send instructions to the disk group through the first interface to modify the data in the disk group; the transmitter 302 can also include a display device such as a display screen.

[0160] In the embodiment of the application, the processor 303 is used to execute Figure 1 The processor 303 in the corresponding embodiment executes the specific manner of each step, which is the same as the description of the method embodiment in the application Figure 1 The corresponding method embodiments are based on the same concept, and the technical effects brought by the method embodiments are the same as the description of the method embodiment in the application Figure 1 The corresponding method embodiments are the same, and the specific content can be referred to the description of the method embodiment in the application, which will not be repeated here.

[0161] The above is only the preferred specific implementation of the application, but the protection scope of the application is not limited to this. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed in the application, which should be covered within the protection scope of the application.

Claims

1. A method for determining the economic operation of a power plant under the dynamic control of the reservoir operating level during the flood season, characterized in that, The method comprises the following steps: A flood control risk is determined based on a water storage and discharge method for pre-discharge and pre-storage and recharge, and the water storage and discharge amount of the reservoir against secondary rain floods is determined according to the flood control risk. The water storage and discharge method for pre-discharge and pre-storage and recharge comprises the following steps: A water level range for dynamic control of the reservoir in the flood season is predefined, wherein the water level of the reservoir at a current time is located in the water level range; If it is predicted that a super-large flood will occur in a future prediction period at a current time, the water level at the end of the prediction period is calculated according to the allowable discharge flow in the prediction period, and a discharge scheme is optimized according to the water level at the end of the prediction period and the water level range; If it is predicted that a large flood will occur in a future prediction period at a current time, the water level of the reservoir is determined as the water level of the reservoir at the current time; If it is predicted that a medium or small flood will occur in a future prediction period at a current time, the water level of the reservoir is determined as the upper limit value of the water level range; ； ； In the formula: To protect the reservoir from the design frequency The maximum permissible water level for flood storage; To protect the reservoir from the design frequency The maximum permissible discharge flow rate of the flood; For the first n Individual flood control limit water level The flood control risk rate exceeding the maximum allowable water storage level after flood regulation; For the first n Individual flood control limit water level The flood control risk rate of exceeding the maximum allowable discharge flow after flood regulation; To protect the reservoir from the design frequency Flood risk rate; To protect the reservoir from the design frequency During floods, the first method is adopted. n The highest flood control water level corresponding to the flood control limit water level; To protect the reservoir from the design frequency During floods, the first method is adopted. n The maximum downstream discharge corresponding to the flood control limit water level; The flood control risk is determined by the following formula: The water and electricity amount of the reservoir hydropower station is determined according to the water storage and discharge amount of the reservoir against secondary rain floods, and an economic operation model of the power plant is constructed, wherein the economic operation model of the power plant comprises a target function of maximizing the total power generation of the hydropower station in the prediction period and at least a constraint condition of a generator set parameter, a hydropower station output limit and a reservoir hydropower station water amount; 2. The method of claim 1, wherein, A particle swarm optimization algorithm is used to perform optimization calculation on the economic operation model of the power plant to determine the optimal scheduling condition of the generator set. ； ； ； In the formula: is t the allowable outflow at the moment; is the safety flow of the flood control object; is the inflow in the interval from the reservoir dam section to the flood control control section, is the facing moment, is the flood forecasting period, is the water that can be discharged in the forecasting period, is the inflow in the reservoir in the forecasting period, is the calculation period length, is the end of the forecasting period is the water level at the moment of falling, is the function of converting the water level into reservoir capacity; is the water level at the facing moment.

3. The method of claim 2, wherein, The water level at the end of the prediction period is calculated according to the allowable discharge flow in the prediction period, which is performed by the following formula: The discharge scheme is optimized according to the water level at the end of the prediction period and the water level range, which comprises the following steps: wherein is the amount of water that can be recharged; is the time of the end of the forecast period is the inflow at the time of the moment, is the flow corresponding to the minimum water supply requirement, is the time of the occurrence of the flow equal to during the outflow process, is the moment of time; If the water level at the end of the prediction period is lower than the water level range for dynamic control of the reservoir in the flood season, a reservoir capacity difference is determined, and a simplified water balance formula in which the recession curve is approximated as a straight line is used to determine the rechargeable water amount, wherein the simplified water balance formula is represented by the following formula: If the rechargeable water amount is equal to the dischargeable water amount in the prediction period or the rechargeable water amount is greater than the reservoir capacity difference, the discharge scheme is maintained; 4. The method of claim 1, wherein, If the future is predicted by the flood forecast at the moment, the average discharge in the prediction period will be determined by the following formula , ； ； wherein: is the maximum value of the inflow in the interval between the reservoir dam cross-section and the flood control cross-section during the prediction period, is the flow corresponding to the minimum water supply requirement, is the safety flow of the flood control object, is the inflow into the reservoir during the prediction period, is the length of the calculation period, is the moment of time, is the flood prediction period; If the small and medium flood will appear in the foreseeable future, the average discharge in the foreseeable future is determined by the following formula , ； ； wherein: is the water level at the moment of facing is the dynamic control upper limit water level of the reservoir in flood season operation, is the storage capacity tolerance of the reservoir, is the function of converting the reservoir capacity into water level, is the flow corresponding to the minimum water supply requirement, is the safety flow of the flood control object, is the inflow into the reservoir in the forecast period, is the length of the calculation period, is the moment of facing, is the flood forecast period.

5. The method of claim 2, wherein, If the rechargeable water amount is lower than the reservoir capacity difference, the discharge flow is reduced until the lower limit value of the water level range for dynamic control of the reservoir in the flood season. ； In the formula: is the number of the unit to be put into operation at the time t ; w is the number of the unit to be put into operation at the time ; is the number of the unit to be put into operation at the time t ; w is the number of the unit to be put into operation at the time ; g is the output of the unit The target function is represented by the following formula: The constraint condition of the generator set parameter comprises a unit head constraint, a unit output limit and a unit water consumption characteristic, and the constraint condition of the reservoir hydropower station water amount comprises a total water amount constraint, a reservoir hydropower station water amount balance constraint, a reservoir water level constraint and an initial reservoir water level constraint; 6. The method of claim 1, wherein, The constraint condition of the economic operation model of the power plant further comprises a minimum discharge flow required by downstream comprehensive utilization and a reservoir hydropower station characteristic curve constraint.

7. A reservoir flood season operation water level dynamic control under power plant economic operation determination device for executing the steps of the reservoir flood season operation water level dynamic control under power plant economic operation determination method of any one of claims 1-6, characterized in that, In the process of performing optimization calculation by using the particle swarm optimization algorithm, the population size is determined by the reservoir water level at the end of the period as a decision variable. The method comprises the following steps: A first determination module is configured to determine a flood control risk based on a water storage and discharge method for pre-discharge and pre-storage and recharge, and determine a water storage and discharge amount of a reservoir against secondary rain floods according to the flood control risk. The second determining module is configured to determine the reservoir water power station water volume according to the water storage and release amount of the reservoir resisting secondary rain floods, and to construct an economic operation model of the power plant, the economic operation model of the power plant including a target function of maximizing total power generation of the power station in a forecast period and at least a constraint condition of generator set parameters, power station output limit and reservoir water power station water volume; The third determining module is configured to perform optimization calculation on the economic operation model of the power plant by using a particle swarm algorithm to determine an optimal dispatching condition of the generator set.

8. An execution device, characterized by The device comprises a processor and a memory, and the processor is coupled with the memory; The memory is configured to store a program; The processor is configured to execute the program in the memory, so that the execution device executes the method in any one of claims 1 to 6.

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