Vibration absorption control method and system for power regulation transition process of hydroelectric generating set

Abstract

The invention discloses an anti-vibration control method and system for a power regulation transition process of a hydroelectric generating set. The method comprises the following steps: constructing a control model for power regulation of a water delivery and power generation system of a hydropower station; importing key parameters during simulation of the control model; the control parameters of the control model serve as decision variables, constraint conditions of the decision variables are set, and target functions of the anti-vibration performance and the power regulation performance are set; performing optimization solution on the control parameters of the control model according to the set objective function and constraint conditions to obtain an optimal solution set; and evaluating the optimal solution set and selecting a final optimal solution, and performing power control on the control model by using the final optimal solution as an optimal control parameter. While the power regulation performance meets the standard requirement, the frequency that the unit passes through the vibration area is obviously reduced, the operation time of the vibration area is shortened, the power regulation dynamic quality of the unit is improved, and the operation life of the unit is prolonged.

Description

Technical Field

[0001] The invention relates to a hydroelectric generator set control technology, and in particular to a hydroelectric generator set power regulation transition process vibration avoidance control method and system. Background Art

[0002] When the turbine deviates from the optimal operating conditions, the hydraulic characteristics will deteriorate significantly, causing hydraulic phenomena such as flow separation, vortex, cavitation, etc., resulting in increased vibration of the turbine. If it runs in the vibration zone for a long time, it will cause safety problems such as fatigue damage of turbine structural components and loosening of fasteners. In severe cases, it may even cause major safety accidents such as flooding of the plant. In order to ensure the safe operation of hydropower units, all large hydropower plants will conduct on-site vibration zone tests and divide the vibration zones of the turbines. Under stable operating conditions of the hydropower units, the operating personnel and the monitoring system of the hydropower station will avoid the vibration zone of the turbine. However, during the load regulation of the unit, the hydropower unit may pass through the vibration zone. Due to poor setting of the control system parameters, the unit will run in the vibration zone for a long time. In addition, due to factors such as the dead zone of the control system and hydraulic fluctuations, the hydropower unit will enter the vibration zone during the load regulation process (such as Figure 1 As shown), leading to the damage of key components of the turbine.

[0003] The current vibration-avoidance operation strategy for hydropower units mainly focuses on vibration-avoidance operation under stable unit operation. Generally, the power grid will issue a total power command to the hydropower plant, and the power plant will distribute the total load adjustment command to each unit according to the actual load and operation status of each unit. In order to avoid the unit from operating in the vibration zone, it is necessary to consider avoiding the vibration zone. At present, enumeration method, dynamic programming, genetic algorithm, particle swarm optimization algorithm and other methods are used to distribute power command values ​​to prevent the power command values ​​issued to each unit from falling into the vibration zone of the hydropower unit.

[0004] The patent application with publication number CN 115453931 A discloses an optimization method and device for active power control of a hydropower unit monitoring system, the method comprising: constructing a power control model of the hydropower unit monitoring system, importing basic parameters and initial conditions for solving the model; setting relevant parameters of a multi-objective genetic algorithm; obtaining individuals represented by a decision variable set, inputting the model to obtain the active power regulation thread of the hydropower unit, and constructing an objective function according to the optimization index obtained from the regulation thread; using an improved multi-objective genetic algorithm to solve the control model and obtain an optimal solution set; obtaining a decision variable set with the best objective function value from the optimal solution set, and performing active power control of the hydropower unit. However, the optimization target of this scheme is only the response speed and power reverse regulation of the unit power, and does not consider the requirement of vibration-avoiding operation of the unit during the power regulation process, which will cause the hydropower unit to operate in the vibration zone for a long time during the power regulation process, causing excessive vibration of the hydropower unit and affecting the safety of the unit.

[0005] In summary, the current research results on vibration-avoiding operation of units are mainly concentrated on the distribution of load instructions of hydropower units, without considering the transition process in the hydropower power regulation process. Although it can effectively avoid the target value of the hydropower unit power regulation from entering the vibration zone of the unit, the unit may frequently cross the vibration zone, stay in the vibration zone for too long, and the regulation quality may not meet the requirements of the power grid during the regulation process. Therefore, it is necessary to consider the above comprehensive factors and propose a vibration-avoiding control method for the transition process of hydropower unit power regulation. Summary of the invention

[0006] The technical problem to be solved by the present invention is as follows: In view of the above-mentioned problems in the prior art, a vibration avoidance control method for the transition process of power regulation of a hydropower unit is provided, which can significantly reduce the number of times the unit passes through the vibration zone and the operating time in the vibration zone while the power regulation performance meets the standard requirements, thereby improving the dynamic quality of the unit's power regulation and increasing the unit's operating life.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0008] A method for avoiding vibration during a transient process of power regulation of a hydropower unit comprises the following steps:

[0009] Construct a control model for power regulation of the units in the water transmission and power generation system of a hydropower station;

[0010] Importing key parameters of the control model for simulation;

[0011] The control parameters of the control model are used as decision variables, the constraint conditions of the decision variables are set, and the objective functions of the vibration avoidance performance and the power regulation performance are set;

[0012] Optimizing the control parameters of the control model according to the set objective function and constraint conditions to obtain an optimal solution set;

[0013] The optimal solution set is evaluated and a final optimal solution is selected, and the final optimal solution is used as an optimal control parameter to perform power control on the control model.

[0014] Furthermore, when constructing the control model of power regulation of the hydropower station water transmission and power generation system, it includes:

[0015] Construct a monitoring system mathematical model. The control signal calculation formula of the PWM controller of the monitoring system mathematical model is as follows:

[0016]

[0017] Where M is the output amplitude of the monitoring system; T is the pulse period; ΔP is the difference between the actual turbine active power and the power regulation target value; sign is the sign function; Tk is the pulse width of the PWM output, and the calculation formula of sign is as follows:

[0018]

[0019] T k The calculation formula is as follows:

[0020]

[0021] Where β is the adjustment parameter; T kmax is the maximum pulse width limit; T kmin is the minimum pulse width limit; and T kmin ≤T kmax ≤T;

[0022] Construct a mathematical model of the speed regulator, and its transfer function is as follows:

[0023]

[0024] Where u(s) is the Laplace transform of the input signal, y(s) is the Laplace transform of the output signal, T iy The time constant of the integrator is given by the speed regulator opening, T y is the reaction time constant of the relay of the speed control system, s is the Laplace operator;

[0025] The turbine model is constructed, and the specific expression of the turbine operation characteristic curve is as follows:

[0026] Q=f(α,H)

[0027] P=g(α,H)

[0028] Where: Q is the turbine flow; P is the turbine output; α is the guide vane opening; H is the turbine working head;

[0029] Construct a mathematical model of the water diversion system, the formula is as follows:

[0030]

[0031] Where h(s) is the Laplace transform of the turbine head, q(s) is the Laplace transform of the turbine flow, T w is the inertia time constant of water flow in the water delivery system, h f0 is the head loss of the water delivery system, H0 is the initial turbine head;

[0032] Combining the monitoring system model, the speed governor mathematical model, the turbine mathematical model and the water diversion system model, a control model for power regulation of the water transmission and power generation system units of the hydropower station is obtained.

[0033] Furthermore, the key parameters specifically include the comprehensive characteristic curve of turbine operation, the water flow inertia time constant T w , speed control system relay reaction time constant T y , initial working head H0, initial output N t0 , initial flow Q0, turbine head and the vibration zone of the turbine under different heads expressed in terms of unit active power.

[0034] Furthermore, the constraint conditions include the magnitude constraint conditions of the monitoring system and the speed regulator parameters, and the expressions are as follows:

[0035] M[T,T kmax ,T kmin ,β,T iy ]=0.1

[0036] Among them, M[] represents the magnitude of the decision variable, T represents the pulse period, and T kmax Indicates the maximum pulse width, T kmin represents the minimum pulse width, β represents the adjustment parameter, T iy Indicates the speed regulator opening given integral time constant.

[0037] Furthermore, the constraint condition includes a magnitude constraint condition of the unit load distribution coefficient, which is expressed as follows:

[0038] M[P1]=0.01

[0039] Among them, M[] represents the magnitude of the decision variable, and P1 represents the load distribution coefficient.

[0040] Furthermore, the constraint condition includes an inequality constraint condition of a monitoring system control parameter, and the expression is as follows:

[0041] T kmin ≤T kmax ≤T

[0042] Where, T represents the pulse period, T kmax Indicates the maximum pulse width, T kmin Indicates the minimum pulse width.

[0043] Furthermore, the objective functions of the vibration avoidance performance and the power regulation performance include the vibration avoidance performance objective function, which is expressed as follows:

[0044] Minobj1(T,T kmax ,T kmin ,β,T iy ,P1)=ki+ti

[0045] Where, T represents the pulse period, T kmax Indicates the maximum pulse width, T kminrepresents the minimum pulse width, β represents the adjustment parameter, T iy represents the speed regulator opening given integral time constant, P1 represents the load distribution coefficient, k i Indicates the number of times the time domain curve of the parameterized unit passes through the corresponding vibration zone of the unit, t i Indicates the time the parameter unit stays in the corresponding vibration zone during the adjustment process.

[0046] Furthermore, the vibration range expression corresponding to the parameter adjustment unit is as follows:

[0047]

[0048] in, represents the vibration zone when the working water head of the i-th unit is H0, P i1 min represents the lower limit of the first vibration zone of the i-th parameter setting unit, P i1 max represents the upper limit of the first vibration zone of the i-th parameter setting unit, P i2 min represents the lower limit of the second vibration zone of the i-th parameter setting unit, P i2 max Represents the upper limit of the second vibration zone of the i-th parameter setting unit.

[0049] Furthermore, the objective functions of the vibration avoidance performance and the power regulation performance include the power regulation performance objective function, which is expressed as follows:

[0050]

[0051] Where, T represents the pulse period, T kmax Indicates the maximum pulse width, T kmin represents the minimum pulse width, β represents the adjustment parameter, T iy represents the speed regulator opening given integral time constant, P1 represents the load distribution coefficient, T p Indicates the power adjustment time, E p Indicates the power regulation accuracy, P s Indicates power overshoot, T pmin 、E pmin , P smin They are the minimum recommended values ​​for power regulation time, power regulation accuracy, and power overshoot respectively.

[0052] Further, when optimizing the control parameters of the control model according to the set objective function and constraint conditions, a multi-objective genetic algorithm is used to optimize the control parameters of the control model according to the set objective function and constraint conditions, including the following steps:

[0053] Randomly generate initial decision variables that meet the constraints. The expression is as follows:

[0054] X i_0 =(T,T kmin ,T kmax ,T iy ,β,P1)

[0055] Among them, X i_0 represents the i-th initial decision variable, i = 1, 2, ..., N, N represents the total number of initial decision variables, T represents the pulse period, T kmax Indicates the maximum pulse width, T kmin represents the minimum pulse width, β represents the adjustment parameter, T iy It represents the given integral time constant of the speed regulator opening, and P1 represents the load distribution coefficient;

[0056] The decision variables are brought into the control model for simulation calculation to obtain the dynamic time domain waveform of the active power of the hydropower unit. The number of vibration zone crossings k1, the time t1 that the unit stays in the corresponding vibration zone during the adjustment process, and the unit power adjustment time T are calculated according to the waveform curve. p , power regulation accuracy E p , power overshoot P s ;

[0057] The number of vibration zone crossings k1, the time t1 that the unit stays in the corresponding vibration zone during adjustment, and the unit power adjustment time T p , power regulation accuracy E p , power overshoot P s , substitute the objective function formula of vibration avoidance performance and power regulation performance, and obtain the corresponding objective function values ​​obj1 and obj2;

[0058] Performing non-dominated quick sorting and crowding evaluation according to the two objective function values ​​of the decision variables to determine the priority of each decision variable, then screening high-priority decision variables to form a parent population according to the results of the non-dominated quick sorting and crowding evaluation, and using the parent population to generate a new generation population;

[0059] If the maximum number of evolutionary generations has been reached, the new generation population is taken as the optimal solution set. Otherwise, the new generation population is merged with the parent population, and for each individual in the merged population, the step of bringing the decision variables into the control model for simulation calculation is executed again until the maximum number of evolutionary generations is reached.

[0060] Furthermore, when evaluating the optimal solution set and selecting the final optimal solution, specifically, calculating the closeness of each optimal solution in the optimal solution set, and then selecting the optimal solution with the largest closeness, including the following steps:

[0061] Construct the normalized initial matrix J, the expression is as follows:

[0062]

[0063] Among them, x ij represents the value of the i-th solution in the optimal solution set on the j-th objective function, i = 1, 2, ..., n, n is the number of solutions in the optimal solution set, j = 1, 2, j = 1 represents the objective function of vibration avoidance performance, j = 2 represents the objective function of power regulation performance;

[0064] Set the maximum value of each column element in matrix J to the positive ideal point J + , set the minimum value of each column element in J to the negative ideal point J - , calculate each element and the positive ideal point J + and negative ideal point J - The Euclidean distance is expressed as follows:

[0065]

[0066] Calculate the closeness of each solution in the optimal solution set. The expression is as follows:

[0067]

[0068] Among them, T i , where represents the closeness corresponding to the i-th solution in the optimal solution set.

[0069] The present invention also proposes a vibration avoidance control system for a hydropower unit power regulation transition process, comprising a microprocessor and a computer-readable storage medium connected to each other, wherein the microprocessor is programmed or configured to execute any one of the vibration avoidance control methods for a hydropower unit power regulation transition process.

[0070] Compared with the prior art, the advantages of the present invention are:

[0071] The present invention is based on a control model of power regulation of a unit in a water transmission and power generation system of a hydropower station, constructs a vibration avoidance performance objective function and a power regulation performance objective function, optimizes control parameters using a multi-objective optimization algorithm to obtain an optimal solution set, then performs scheme evaluation and optimal parameter selection for the optimal solution set, and uses the optimal parameters finally obtained to perform power regulation, so that the power regulation performance can meet the requirements of the power regulation performance index, while reducing the number of times the unit passes through the vibration zone and the operation time in the vibration zone, thereby improving the unit life and power station safety.

[0072] When constructing the vibration avoidance performance objective function and the power regulation performance objective function, the present invention uses the vibration zone data actually divided by the hydropower unit as an objective function for power regulation of the hydropower unit, and adopts a multi-objective optimization strategy to obtain the optimal parameters that take into account both power regulation performance and vibration avoidance requirements. On the basis of improving the power regulation performance, the operating time of the hydropower unit in the vibration zone during the power regulation process is shortened, and the damage caused by vibration to the structural components of the unit is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 Schematic diagram of fluctuations during the unit power regulation transition process.

[0074] Figure 2 The present invention is a flow chart of the method.

[0075] Figure 3 This is a schematic diagram of the water supply system of the hydropower station.

[0076] Figure 4 It is the power regulation principle in the power control mode of the monitoring system.

[0077] Figure 5 Schematic diagram of the mathematical model of the speed regulator.

[0078] Figure 6 It is a model based on the turbine operating characteristic curve.

[0079] Figure 7 For the overall model.

[0080] Figure 8 This is a schematic diagram of the vibration zone of the unit.

[0081] Fig. 9 Schematic diagram of the objective function value of each solution in the optimal solution set.

[0082] Fig.10 Schematic diagram of the closeness calculation results DETAILED DESCRIPTION

[0083] The present invention is further described below in conjunction with the accompanying drawings and specific preferred embodiments, but the protection scope of the present invention is not limited thereby.

[0084] Embodiment 1

[0085] This embodiment proposes a vibration avoidance control method for the power regulation transition process of a hydropower unit. Based on the power control model of the hydropower station monitoring system, a vibration avoidance performance objective function and a power regulation performance objective function are constructed. The improved non-dominated sorting genetic algorithm NSGA-II (Non-dominated Sorting Genetic Algorithms II) is used to optimize key control parameters. The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) decision theory is introduced to evaluate the scheme and select parameters for the obtained optimal solution set. The recommended parameters are used for power regulation so that the power regulation performance can meet the requirements of the power regulation performance indicators. At the same time, the number of times the unit passes through the vibration zone and the operation time in the vibration zone are reduced, thereby improving the unit life and power station safety. Figure 2 As shown, the following steps are included:

[0086] Step 1: Construct a control model for power regulation of the hydropower station’s water transmission and power generation system units.

[0087] Hydropower station water transmission and power generation system Figure 3 As shown, it includes a water delivery system, a turbine and control equipment. The active power control system of a hydropower station is a complex nonlinear system that integrates hydraulic, mechanical and electrical processes. The control equipment includes a monitoring system and a turbine speed governor. The active power response characteristics of the hydropower unit participating in the power regulation process are closely related to the characteristics of each subsystem, and each subsystem is coupled with each other. In order to accurately simulate the transition process of the hydropower unit participating in power regulation, step S1 of this embodiment is combined with the results of the inventor's previous research (Fu Liang, Bao Haiyan, Huang Bo. Simulation study on active power regulation of hydropower unit monitoring system [J]. Journal of Hydroelectric Engineering, 2020, 39(01): 62-71.) to establish a hydropower unit power regulation mathematical model that considers the nonlinear characteristics of each link and the mutual coupling effects in detail, including the following steps:

[0088] Step 1.1: Construct a mathematical model of the monitoring system:

[0089] The closed-loop regulation principle of active power in the monitoring system of a hydropower station is as follows: Figure 4 After receiving the power regulation command from the power grid, the monitoring system of the hydropower station sends the active power regulation command to the local control unit (LCU) of the relevant unit. After receiving the power regulation command, the unit LCU uses the pulse width modulation (PWM) method to adjust. When the absolute value of the deviation between the actual active power and the power target value is greater than the regulation dead zone, the LCU sends a power "increase / decrease" pulse signal to the speed governor in real time until the active power deviation enters the dead zone and stops sending commands. Finally, the speed governor adjusts the guide vane opening to change the output of the turbine.

[0090] The control signal u(t) of the PWM controller is calculated as follows:

[0091]

[0092] Where M is the output amplitude of the monitoring system, in MW; T is the pulse period, in s; ΔP is the difference between the actual turbine active power and the power regulation target value, in MW; sign is the sign function; T k is the pulse width of the PWM output (k=0, 1, 2, ...). The calculation formula of sign is shown in formula (2):

[0093]

[0094] T k The calculation formula is as follows:

[0095]

[0096] Where β is the adjustment parameter; T kmax is the maximum pulse width limit, in seconds (s); T kmin is the minimum pulse width limit, in seconds (s); and T kmin ≤T kmax ≤T, the above parameters can be set manually.

[0097] Step 1.2: Construct the speed regulator mathematical model:

[0098] The turbine speed governor consists of two parts: the regulator and the electro-hydraulic follow-up system. Figure 5 Its transfer function is shown in formula (4).

[0099]

[0100] Where u(s) is the Laplace transform of the input signal, y(s) is the Laplace transform of the output signal, T iy The time constant of the integrator is given by the speed regulator opening, T y is the reaction time constant of the relay of the speed control system, and s is the Laplace operator.

[0101] In the power control opening mode, the main task of the speed governor is to act as an actuator, receive the power adjustment command from the monitoring system, adjust the turbine guide vane opening, and thus change the output to achieve the purpose of power regulation.

[0102] Figure 5 The input signal u is the command output by the unit LCU, and the output signal y is the relative value of the guide vane opening. D is the differential gain; K P is the proportional gain; K Iis the integral gain; T lv is the differential link attenuation time constant, in seconds (s); b p is the permanent slip coefficient; T iy T is the time constant of the speed regulator opening given integrator, in seconds (s); y is the speed control system relay reaction time constant, in seconds (s). The above parameters are generally set manually, where T y Obtained through on-site measurement.

[0103] After the LCU outputs the increase or decrease pulse signal, the speed regulator issues a guide vane opening step according to the received pulse command, and the step amplitude is ±100%. For a step signal, the output is a ramp signal, and the slope of this ramp signal is determined by T iy The calculated guide vane opening signal is output to the electro-hydraulic servo system.

[0104] The electro-hydraulic servo system converts the input guide vane opening adjustment electrical signal through the electro-hydraulic conversion link and hydraulic amplification to control the guide vane servomotor of the unit to adjust the guide vane opening.

[0105] Step 1.3: Build the turbine model:

[0106] In this embodiment, the turbine operation characteristic curve is used for modeling, and the differential link in the water diversion system is changed into an integral link to eliminate the algebraic loop. The model block diagram based on the turbine operation characteristic curve is shown in FIG. Figure 6 shown.

[0107] Since the turbines in the numerical simulation calculation of active power regulation of the hydropower station operate within the normal working range, in order to prevent algebraic loops from appearing in the model, the turbine operation characteristic curve is used to describe the nonlinear characteristics of the turbine, and the head H and power P are set as the vertical and horizontal coordinates.

[0108] The turbine operating characteristic curve reflects the relationship between turbine flow, output, water head and guide vane opening. The specific expression is as follows:

[0109] Q=f(α,H) (5)

[0110] P=g(α,H) (6)

[0111] Where: Q is the turbine flow rate, unit is m 3 / s; P is the turbine output, in MW; α is the guide vane opening, in mm; H is the turbine working head, in m.

[0112] Step 1.4: Construct a mathematical model of the water diversion system:

[0113] The mathematical model of the water delivery system is shown in formula (7).

[0114]

[0115] Where: h(s) is the Laplace transform of the turbine head, q(s) is the Laplace transform of the turbine flow, T w is the inertia time constant of water flow in the water delivery system, h f0 is the head loss of the water delivery system, H0 is the initial turbine head, and s is the Laplace operator.

[0116] Step 1.5: Construct the overall mathematical model:

[0117] Combining the monitoring system model, the speed governor mathematical model, the turbine mathematical model and the water diversion system model, the overall mathematical model of the power regulation of the hydropower unit monitoring system is obtained, such as Figure 7 How to combine these models to obtain an overall mathematical model is well known to those skilled in the art. This embodiment does not involve improvements to the specific process, so the specific model combination process will not be described in detail.

[0118] Step 2: Import the control model to simulate the key parameters of the power regulation of the hydropower station's water transmission and power generation system.

[0119] Import the characteristic parameters required for simulation control model, including comprehensive characteristic curve of turbine operation, water flow inertia time constant T w , speed control system relay reaction time constant T y At the same time, the initial working conditions of the model are set, including the initial working head H0, the initial output N t0 , initial flow Q0.

[0120] For the vibration-avoiding operation control of the hydropower unit, it is also necessary to import the vibration zone data of the hydropower unit, mainly including the turbine head [H1, H2, ... H n ], and also includes the vibration area of ​​the turbine under different water heads expressed in terms of unit active power, e.g. It represents the vibration zone of the 1st to 4th turbine units under the 1st to nth water heads.

[0121] Step 3: Set the multi-objective genetic algorithm parameters, specifically, use the control parameters of the control model as decision variables, set the constraints of the decision variables, and set the objective functions of the vibration avoidance performance and power regulation performance.

[0122] In this embodiment, the multi-objective genetic algorithm adopts an improved non-dominated sorting genetic algorithm NSGA-II (Non-dominated Sorting Genetic Algorithms II). When setting the parameters of the multi-objective genetic algorithm, the following are specifically included:

[0123] Step 3.1: Initialize NSGA-II parameters:

[0124] Set the number of objective functions nobj to 2, the population number npop to 100, the maximum number of iterations maxit to 60, the crossover ratio pc to 0.8, the mutation probability mu to 0.05, and the decision variable nvar to 6. In this embodiment, the decision variable nvar is set to 6 because the key control parameters of the required solution include the pulse period T, the maximum pulse width T kmax , minimum pulse width T kmin , adjustment parameter β, speed regulator opening given integral time constant T iy , load distribution coefficient P1, after taking the key control parameters of the model demand solution as decision variables, the individual set composed of decision variables can be expressed as:

[0125] X=(T,T kmin ,T kmax ,T iy ,β,P1)

[0126] Step 3.2: Set constraints, that is, set constraints on decision variables:

[0127] Usually, in actual operation, hydropower plants set the precision of control parameters to one significant digit after the decimal point. The magnitude constraints of monitoring system and speed regulator parameters can be expressed as:

[0128] M[T,T kmax ,T kmin ,β,T iy ]=0.1 (8)

[0129] The magnitude constraint adjustment of the unit load distribution coefficient can be expressed as

[0130] M[P1]=0.01 (9)

[0131] In equations (8) and (9), M[] represents the magnitude of the decision variable.

[0132] Monitoring system control parameter maximum pulse width T kmax , minimum pulse width T kmin , the pulse period T has the following inequality constraints:

[0133] T kmin ≤T kmax ≤T

[0134] Step 3.3: Set the objective function, specifically, set the objective function of vibration avoidance performance and power regulation performance, where:

[0135] For the vibration-proof performance objective function of this embodiment, there are multiple vibration zones in the hydropower plant unit, which are generally obtained through field tests after the unit is put into operation. The vibration zone of the hydropower unit changes with the working water head. The schematic diagram of the vibration zone of the unit is shown in Figure 8 As shown. Among them, represents the vibration zone when the working water head of the i-th parameter unit is H0, { i1 min represents the lower limit of the first vibration zone of the i-th parameter setting unit, P i1 max represents the upper limit of the first vibration zone of the i-th parameter setting unit, P i2 min represents the lower limit of the second vibration zone of the i-th parameter setting unit, P i2 max Represents the upper limit of the second vibration zone of the i-th parameter-adjusted unit. When the unit participates in power regulation, its active power dynamic time domain curve is tracked, and the number of times the parameter-adjusted unit time domain curve passes through the corresponding vibration zone of the unit is output as k. i , the time the unit stays in the corresponding vibration area during the adjustment process is output as t i , the vibration zone range corresponding to the unit can be expressed as:

[0136]

[0137] The above formula can be expressed as the vibration zone range of the i-th parameter-adjusted unit when the working water head is H0.

[0138] In summary, the objective function of the unit vibration avoidance performance can be expressed as:

[0139] Minobj1(T,T kmax ,T kmin ,β,T iy ,P1)=k i +t i (11)

[0140] All the indicators in formula (11) are as small as possible.

[0141] For the power regulation performance objective function of this embodiment, it is composed of the regulation time T p , Adjustment accuracy E p , overshoot P s The three indicators can be expressed as:

[0142]

[0143] In this embodiment, the power adjustment time T is defined as pIt is the total time from the start of active power regulation to the time when the unit power enters the dead zone. The active power of the hydropower unit entering the dead zone means that the deviation between the hydropower unit power and the target value is within the range of ±1% of the rated power.

[0144] In this embodiment, the power adjustment accuracy E is defined as p It is the ratio of the average value of the active power of the hydropower unit after entering the dead zone to the rated power of the unit.

[0145] In this embodiment, the power overshoot P is defined as s as follows:

[0146] Detect whether the grid instruction is a load reduction instruction or a load increase instruction. If the adjustment instruction is a load reduction instruction, obtain the minimum value in the load reduction process, and set the difference between the power adjustment target value and the minimum value as the power overshoot; if the adjustment command is a load increase, obtain the maximum value in the load increase process, and set the difference between the maximum value and the power adjustment target value as the power overshoot.

[0147] T pmin 、E pmin , P smin These are the minimum recommended values ​​for power regulation time, power regulation accuracy, and power overshoot specified in the standard.

[0148] Step 4: Using the improved non-dominated sorting genetic algorithm NSGA-II, the control parameters of the control model for power regulation of the hydropower station water transmission and power generation system are optimized according to the set objective function and constraints, including:

[0149] Step 4.1: Generate initial decision variables:

[0150] Randomly generate N initial decision variables that meet the constraints. The expression is as follows:

[0151] X i_0 =(T,T kmin ,T kmax ,T iy ,β,P1) (13)

[0152] Among them, X i_0 represents the i-th initial decision variable, i = 1, 2, ..., N, T represents the pulse period, T kmax Indicates the maximum pulse width, T kmin represents the minimum pulse width, β represents the adjustment parameter, T iy It represents the given integral time constant of the speed regulator opening, and P1 represents the load distribution coefficient;

[0153] Step 4.2: Calculate the objective function:

[0154] Each decision variable is brought into the control model constructed in step 1 for simulation calculation to obtain the dynamic time domain waveform of the active power of the hydropower unit. According to the waveform curve, the number of times the vibration zone is crossed k1, the time t1 that the unit stays in the corresponding vibration zone during the adjustment process, and the unit power adjustment time T p , power regulation accuracy E p , power overshoot P s How to simulate and calculate the control model to obtain the dynamic time domain waveform of the active power of the hydropower unit, and how to calculate these parameters according to the waveform curve of the dynamic time domain waveform of the active power of the hydropower unit are well known to those skilled in the art. This embodiment does not involve improvements to the specific calculation process, and the specific calculation process will not be repeated here.

[0155] Substitute the number of vibration zone crossings k1 of each decision variable and the time t1 that the unit stays in the corresponding vibration zone during the adjustment process into formula (11) to obtain the value obj1 of the vibration avoidance performance objective function corresponding to each decision variable, and the unit power adjustment time T p , power regulation accuracy E p , power overshoot P s Substituting into equation (12), we can obtain the value obj2 of the power regulation performance objective function corresponding to each decision variable.

[0156] Step 4.3: Non-dominated quick sort and crowding evaluation

[0157] Each decision variable is regarded as an individual, and non-dominated quick sorting and crowding evaluation are performed according to the two objective function values ​​of the individual to determine the priority of the individual.

[0158] In this embodiment, non-domination is defined as: for two different individuals X in the population i and X j , the two objective function values ​​obtained by bringing these two individuals into the model both satisfy Minobj k (X i )≤Minobj k (X j ) is called X i DominateX j This embodiment generates multiple "levels" or "fronts" (Pareto fronts) of individuals in the population through non-dominated quick sorting. The first front contains all non-dominated solutions, the second front contains solutions dominated by the first front, and so on, thereby helping to identify better solutions in the population. The less dominated a solution is by other solutions, the higher its ranking.

[0159] In this embodiment, crowding is defined as: first, the population is sorted in ascending order according to the size of each objective function value, and then the crowding is evaluated, that is, the boundary solution of each objective function (i.e., the solution with the maximum and minimum values) is assigned a value of infinite distance, and all other intermediate solutions are assigned to be equal to the normalized absolute difference of the objective function values ​​of two adjacent solutions. In this embodiment, through crowding evaluation, the "crowding" between individuals is further evaluated in the frontier of the same level to measure the density of individuals in the target space.

[0160] In this embodiment, after determining the priority of each individual, it is necessary to screen N high-priority individuals, specifically, to select individuals in the higher-level frontier of non-dominated quick sort, and to give priority to retaining individuals with low congestion in the same frontier to enhance the diversity of the population. So far, the first-generation population G containing N individuals is obtained = (X1, X2, X3, ..., X n ), and X i =(T,T kmax ,T kmin ,T iy , β, P1), i = 1, 2, …, N, the individuals in the population are prioritized through non-dominated quick sorting and crowding evaluation of the objective function value, which helps to select high-priority individuals in the evolutionary algorithm to generate a new generation of population.

[0161] Step 4.4: Generate a new generation of population:

[0162] The first generation population is used as the parent population, and genetic operations are performed to generate a new generation population, and the new generation population is used as the child population of the parent population. How to perform genetic operations on the parent population to generate a new generation population is well known to those skilled in the art. This embodiment does not involve improvements on the specific implementation process of genetic operations, and the specific process will not be repeated here.

[0163] After generating a new generation of population, check whether the current evolutionary generation has reached the maximum evolutionary generation. If so, output the new generation of population as the optimal solution set. Otherwise, merge the parent population with the child population, and execute steps 4.2 to 4.4 on the merged population to recalculate the objective function value. Obtain the next generation of population through non-dominated quick sorting and crowding evaluation, use the next generation of population as the parent population, and generate a new generation of population through genetic operations, and use the new generation of population as the child population of the parent population, until the current evolutionary generation reaches the maximum evolutionary generation, and output the optimal population as the optimal solution set. Fig. 9 As shown, the two objective function values ​​of each solution in the optimal solution set show a trend that the power regulation performance objective function value increases as the vibration avoidance performance objective function value decreases in a two-dimensional coordinate system with the vibration avoidance performance objective function as the vertical axis and the power regulation performance objective function as the horizontal axis.

[0164] Step 5: Evaluate the optimal solution set and select the final optimal solution, and use the final optimal solution as the optimal control parameter to perform power control on the control model.

[0165] In this embodiment, in order to Fig. 9 The optimal solution is obtained from the optimal solution set shown in the figure. The optimal solution is obtained by using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) decision theory, which specifically includes the following steps:

[0166] Step 5.1: Perform isotropic processing on the optimal solution set:

[0167] Construct the normalized initial matrix J, the formula is:

[0168]

[0169] In the formula, x ij It represents the value of the i-th solution in the optimal solution set on the j-th objective function, i=1,2,…,n, n is the number of solutions in the optimal solution set, j=1,2, j=1 represents the objective function of vibration avoidance performance, and j=2 represents the objective function of power regulation performance.

[0170] Step 5.2: Calculate the Euclidean distance:

[0171] Set the maximum value of each column element in matrix J to the positive ideal point J + , set the minimum value of each column element in J to the negative ideal point J - , calculate each element and the positive ideal point J + and negative ideal point J - The Euclidean distance is expressed as follows:

[0172]

[0173] Step 5.3: Calculate the closeness:

[0174] According to the positive ideal point J + and negative ideal point J - The Euclidean distance is used to calculate the closeness of each solution in the optimal solution set. The expression is as follows:

[0175]

[0176] In the above formula, T i In it, it represents the closeness corresponding to the i-th solution in the optimal solution set. The larger the closeness value is, the better the control scheme of this solution in the optimal solution set is. For example, Fig.10 As shown, the figure is based on Fig. 9The progress of each solution calculated by the optimal solution set shown is obtained by Fig.10 It can be seen that the 20th solution has the largest degree of closeness, indicating that the control scheme of the 20th solution is the optimal solution. Therefore, the pulse period T and the maximum pulse width T in the decision variables of the 20th solution are kmax , minimum pulse width T kmin , adjustment parameter β, speed regulator opening given integral time constant T iy The load distribution coefficient P1 is input into the control model constructed in step S1 or the actual control system corresponding to the control model to perform power control to achieve the best power regulation performance and vibration avoidance performance.

[0177] Embodiment 2

[0178] This embodiment proposes a vibration avoidance control system for the transient process of power regulation of a hydropower unit, comprising a microprocessor and a computer-readable storage medium connected to each other, wherein the microprocessor is programmed or configured to execute the vibration avoidance control method for the transient process of power regulation of a hydropower unit described in Embodiment 1.

[0179] In summary, the present invention aims at the problems that the hydropower unit may frequently cross the vibration zone, operate in the vibration zone for a long time, and the regulation performance does not meet the requirements during the load regulation transition process, and proposes a vibration avoidance control method and system for the power regulation transition process of the hydropower unit, which has the following advantages:

[0180] 1. The power regulation performance objective function and the vibration avoidance performance objective function are set at the same time to take into account both the power regulation performance and the vibration avoidance requirements.

[0181] 2. NSGA-II is used to optimize the control parameters, and TOPSIS decision theory is used to evaluate and select the optimal solution set, thereby obtaining the optimal solution for the control parameters that takes into account both power regulation performance and vibration avoidance performance. This provides new technical means for active power control of hydropower units, and improves the power regulation quality of the hydropower unit monitoring system and the safety of unit operation.

[0182] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A vibration avoidance control method for a hydropower unit power regulation transition process, characterized in that: The following steps are involved: Construct a control model for power regulation of the units in the water transmission and power generation system of a hydropower station; Importing key parameters of the control model for simulation; The control parameters of the control model are used as decision variables, the constraint conditions of the decision variables are set, and the objective functions of the vibration avoidance performance and the power regulation performance are set; Optimizing the control parameters of the control model according to the set objective function and constraint conditions to obtain an optimal solution set; The optimal solution set is evaluated and a final optimal solution is selected, and the final optimal solution is used as an optimal control parameter to perform power control on the control model.

2. The vibration avoidance control method for the transient process of power regulation of a hydropower unit according to claim 1 is characterized in that: When constructing a control model for power regulation of the hydropower station's water transmission and power generation system, it includes: Construct a monitoring system mathematical model. The control signal calculation formula of the PWM controller of the monitoring system mathematical model is as follows: Where M is the output amplitude of the monitoring system; T is the pulse period; ΔP is the difference between the actual turbine active power and the power regulation target value; sign is the sign function; T k is the pulse width of the PWM output, and the calculation formula of sign is as follows: T k The calculation formula is as follows: In the formula, β is the adjustment parameter; T kmax is the maximum pulse width limit; T kmin is the minimum pulse width limit; and T kmin ≤T kmax ≤T; Construct a mathematical model of the speed regulator, and its transfer function is as follows: Where u(s) is the Laplace transform of the input signal, y(s) is the Laplace transform of the output signal, T iy The time constant of the integrator is given by the speed regulator opening, T y is the reaction time constant of the relay of the speed control system, s is the Laplace operator; The turbine model is constructed, and the specific expression of the turbine operation characteristic curve is as follows: Q=f(α,H) P=g(α,H) Where: Q is the turbine flow; P is the turbine output; α is the guide vane opening; H is the turbine working head; Construct a mathematical model of the water diversion system, the formula is as follows: Where h(s) is the Laplace transform of the turbine head, q(s) is the Laplace transform of the turbine flow, T w is the inertia time constant of water flow in the water delivery system, h f0 is the head loss of the water delivery system, H0 is the initial turbine head; Combining the monitoring system model, the speed governor mathematical model, the turbine mathematical model and the water diversion system model, a control model for power regulation of the water transmission and power generation system units of the hydropower station is obtained.

3. The vibration avoidance control method for the transient process of power regulation of a hydropower unit according to claim 1 is characterized in that: The key parameters specifically include the comprehensive characteristic curve of turbine operation, the water flow inertia time constant T w , speed control system relay reaction time constant T y , initial working head H0, initial output N t0 , initial flow Q0, turbine head and the vibration zone of the turbine under different heads expressed in terms of unit active power.

4. The vibration avoidance control method for the transient process of power regulation of a hydropower unit according to claim 1 is characterized in that: The constraints are: Including the magnitude constraints of the monitoring system and speed regulator parameters, the expression is as follows: M[T,T kmax ,T kmin ,β,T iy ]=0.1 Among them, M[] represents the magnitude of the decision variable, T represents the pulse period, and T kmax Indicates the maximum pulse width, T kmin represents the minimum pulse width, β represents the adjustment parameter, T iy Indicates the speed regulator opening given integral time constant The magnitude constraint of the unit load distribution coefficient is expressed as follows: M[P1]=0.01 Among them, M[] represents the magnitude of the decision variable, P1 represents the load distribution coefficient; Including the inequality constraints of the monitoring system control parameters, the expression is as follows: T kmin ≤T kmax ≤T Where, T represents the pulse period, T kmax Indicates the maximum pulse width, T kmin Indicates the minimum pulse width.

5. The vibration avoidance control method for the transient process of power regulation of a hydropower unit according to claim 1 is characterized in that: The objective functions of vibration avoidance performance and power regulation performance include the vibration avoidance performance objective function, which is expressed as follows: Minobj1(T,Tkmax,Tkmin,β,Tiy,P1)=ki+ti Where, T represents the pulse period, T kmax Indicates the maximum pulse width, T kmin represents the minimum pulse width, β represents the adjustment parameter, T iy represents the speed regulator opening given integral time constant, P1 represents the load distribution coefficient, k i Indicates the number of times the time domain curve of the parameterized unit passes through the corresponding vibration zone of the unit, t i Indicates the time the parameter unit stays in the corresponding vibration zone during the adjustment process.

6. The vibration avoidance control method for the transient process of power regulation of a hydropower unit according to claim 5 is characterized in that: The vibration range expression corresponding to the parameter adjustment unit is as follows: in, represents the vibration zone when the working water head of the i-th unit is H0, P i1 min represents the lower limit of the first vibration zone of the i-th parameter setting unit, P i1 max represents the upper limit of the first vibration zone of the i-th parameter setting unit, P i2 min represents the lower limit of the second vibration zone of the i-th parameter setting unit, P i2 max Represents the upper limit of the second vibration zone of the i-th parameter setting unit.

7. The vibration avoidance control method for the transient process of power regulation of a hydropower unit according to claim 1 is characterized in that: The objective functions of vibration avoidance performance and power regulation performance include the power regulation performance objective function, which is expressed as follows: Where, T represents the pulse period, T kmax Indicates the maximum pulse width, T kmin represents the minimum pulse width, β represents the adjustment parameter, T iy represents the speed regulator opening given integral time constant, P1 represents the load distribution coefficient, T p Indicates the power adjustment time, E p Indicates the power regulation accuracy, P s Indicates power overshoot, T pmin 、E pmin , P smin They are the minimum recommended values ​​for power regulation time, power regulation accuracy, and power overshoot respectively.

8. The vibration avoidance control method for the transient process of power regulation of a hydropower unit according to claim 1 is characterized in that: When optimizing the control parameters of the control model according to the set objective function and constraint conditions, specifically using a multi-objective genetic algorithm to optimize the control parameters of the control model according to the set objective function and constraint conditions, the following steps are included: Randomly generate initial decision variables that meet the constraints. The expression is as follows: X i_0 =(T,T kmin ,T kmax ,T iy ,β,P1) Among them, X i_0 represents the i-th initial decision variable, i = 1, 2, ..., N, N represents the total number of initial decision variables, T represents the pulse period, T kmax Indicates the maximum pulse width, T kmin represents the minimum pulse width, β represents the adjustment parameter, T iy It represents the given integral time constant of the speed regulator opening, and P1 represents the load distribution coefficient; The decision variables are brought into the control model for simulation calculation to obtain the dynamic time domain waveform of the active power of the hydropower unit. The number of vibration zone crossings k1, the time t1 that the unit stays in the corresponding vibration zone during the adjustment process, and the unit power adjustment time T are calculated according to the waveform curve. p , power regulation accuracy E p , power overshoot P s ; The number of vibration zone crossings k1, the time t1 that the unit stays in the corresponding vibration zone during adjustment, and the unit power adjustment time T p , power regulation accuracy E p , power overshoot P s , substitute the objective function formula of vibration avoidance performance and power regulation performance, and obtain the corresponding objective function values ​​obj1 and obj2; Performing non-dominated quick sorting and crowding evaluation according to the two objective function values ​​of the decision variables to determine the priority of each decision variable, then screening high-priority decision variables to form a parent population according to the results of the non-dominated quick sorting and crowding evaluation, and using the parent population to generate a new generation population; If the maximum number of evolutionary generations has been reached, the new generation population is taken as the optimal solution set. Otherwise, the new generation population is merged with the parent population, and for each individual in the merged population, the step of bringing the decision variables into the control model for simulation calculation is executed again until the maximum number of evolutionary generations is reached.

9. The vibration avoidance control method for the transient process of power regulation of a hydropower unit according to claim 1, characterized in that: When evaluating the optimal solution set and selecting the final optimal solution, specifically, the closeness is calculated for each optimal solution in the optimal solution set, and then the optimal solution with the largest closeness is selected, including the following steps: Construct the normalized initial matrix J, the expression is as follows: Among them, x ij represents the value of the i-th solution in the optimal solution set on the j-th objective function, i = 1, 2, ..., n, n is the number of solutions in the optimal solution set, j = 1, 2, j = 1 represents the objective function of vibration avoidance performance, j = 2 represents the objective function of power regulation performance; Set the maximum value of each column element in matrix J to the positive ideal point J + , set the minimum value of each column element in J to the negative ideal point J - , calculate each element and the positive ideal point J + and negative ideal point J - The Euclidean distance is expressed as follows: Calculate the closeness corresponding to each solution in the optimal solution set. The expression is as follows: Among them, T i , where represents the closeness corresponding to the i-th solution in the optimal solution set.

10. A vibration-proof control system for a hydropower unit power regulation transition process, characterized in that: The invention comprises a microprocessor and a computer-readable storage medium connected to each other, wherein the microprocessor is programmed or configured to execute the vibration-avoiding control method for the transient process of power regulation of a hydropower unit as claimed in any one of claims 1 to 9.

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