Inertia evaluation method for grid-connected wind farm based on fan operating state

Abstract

The method for assessing the inertia enhancement of grid-connected wind farms based on turbine operating status includes the following steps: Based on the characteristic that the inertia of a grid-connected doubly-fed induction generator (DFIG) wind farm is zero, the functional relationship between the inertia enhancement after modification and wind speed and turbine shutdown status is analyzed; based on the relationship between turbine rotor and wind speed at different wind speeds, a correlation equation for wind speed capture between turbines is established, and the inertia enhancement of a single turbine under normal operation is calculated; based on the transfer rate between turbine shutdown states, the operating state equation for each time period of the turbine is established, and the shutdown status of the wind turbine unit during the assessment period is calculated; finally, the inertia enhancement of the grid-connected DFIG wind farm after modification is calculated. This method can calculate the virtual inertia enhancement of a grid-connected DFIG wind farm after technical modification, providing an effective measure for analyzing the future inertia support capacity of grid-connected wind farms for the power system.

Description

Technical Field

[0001] This invention relates to the field of virtual inertia assessment technology for wind turbine units, and specifically to a method for assessing the inertia of grid-connected wind farms based on the operating status of the wind turbines. Background Technology

[0002] Currently, among large-scale grid-connected wind power systems, grid-connected wind turbines without virtual inertia control strategies still dominate and will maintain a high proportion throughout the long construction period. Grid-connected wind turbines themselves do not possess virtual inertia support characteristics, but virtual inertia response can be achieved through additional control modifications. Therefore, it is crucial to assess in advance the magnitude of the virtual inertia increase after technical upgrades to grid-connected wind farms. When studying the potential inertia improvement assessment of grid-connected wind farms, the main influencing factors are the wind speed captured by each turbine and its shutdown status. Current methods primarily focus on measuring real-time data from the wind farm and assess the inertia level of wind farms already employing virtual inertia control. When power disturbances occur, the inertia response is rapid and short-lived. Knowing in advance the magnitude of inertia the wind farm can provide can reduce the risk of frequency instability when the system operates at low inertia levels. Therefore, there is an urgent need for a method to assess the potential inertia improvement of grid-connected wind farms based on the turbine's operating status. Summary of the Invention

[0003] This invention proposes a method for assessing the inertia that can be improved in grid-connected wind farms based on the operating status of wind turbines. This method can calculate the virtual inertia that can be improved in grid-connected doubly-fed inertial wind farms after technical upgrades, providing an effective measure for analyzing the future inertia support capacity of grid-connected wind farms for the power system.

[0004] The technical solution adopted in this invention is as follows:

[0005] A method for assessing the inertia of grid-connected wind farms based on wind turbine operating status includes the following steps: Step 1: Based on the characteristic that the inertia of a grid-connected doubly-fed wind farm is 0, analyze the functional relationship between the inertia that can be improved after the modification and the wind speed and the wind turbine shutdown state. Step 2: Based on the relationship between the fan rotor and the wind speed under different wind speeds, establish the correlation equation for the wind speed captured between fans, and calculate the liftable inertia of a single fan under normal operation. Step 3: Establish the operating state equations of the wind turbine for each time period based on the transition rate between wind turbine shutdown states, and calculate the shutdown state of the wind turbine unit during the evaluation period; Step 4: Combining Steps 1 to 3, calculate the increase in inertia of the grid-connected doubly fed wind farm after the retrofit.

[0006] In step 1, for grid-connected wind farms that have been modified to have a virtual inertia control strategy, such as Figure 2As shown, based on the definition of the inertial time constant and considering the change in the system's synchronous angular velocity, the virtual inertia of the modified wind turbine is expressed as: (1); In formula (1): This represents the virtual inertia of the modified wind turbine; and These represent the initial angular velocities of the system and the fan rotor, respectively. and These represent the changes in system angular velocity and fan rotor speed, respectively. This is the rated angular velocity of the fan; The inherent inertial time constant of the wind turbine; By analogy with the mechanical rotor inertia of a synchronous generator, the virtual inertia of the modified wind turbine is obtained by calculating the electromagnetic torque variable. The transfer function is: (2); In equation (2), The gain is controlled by virtual inertia. The filtering time constant; and These are the proportional and integral coefficients of the speed controller, respectively. It is a complex parameter variable.

[0007] Performing an inverse Laplace transform on equation (2), we obtain The time-domain equation is: (3); In formula (3): This represents the increased virtual inertia of the modified grid-type wind turbine at a certain moment; among which, , , , All parameters are known. in: (4); (5); In the formula: ; It is a discriminant; The linear part of the phase It is a time variable; , , , , This represents the decay process at the corresponding pole. like There are three single roots. , , The corresponding coefficient , , This is the expansion of a partial fraction; like There is a single root and two conjugate complex roots , , , Parameters corresponding to the poles The imaginary unit; coefficient , This is the expansion of a partial fraction.

[0008] Considering that wind farms typically use the same type of wind turbines with identical control parameters, the virtual inertia of each turbine is aggregated to obtain the equivalent inertial constant of the wind farm, meaning the wind farm can increase its inertia. : (6); In formula (6): Let represent the virtual inertia of the i-th wind turbine after the modification; This represents the virtual inertia of the wind turbine before the modification; These represent the kinetic energy stored in each wind turbine; Let m be the rated capacity of the i-th fan, i = 1, 2, 3, ..., m; Indicates the number of wind turbines in the wind farm; This represents the operating status of the i-th wind turbine; This indicates that the fan is in normal operating condition; This indicates that the fan is in a stopped state; These represent the virtual inertia of each wind turbine; Indicates the first i The inertial time constant of a typhoon generator; In equations (3) and (6), the following are set The angular velocity of the fan rotor is a fixed value. and running status The main factor affecting the inertia that a wind farm can increase is the magnitude of the inertia; the other parameters are all known constants.

[0009] In step 2, according to equation (3), the main factor affecting the increase of the inertia of the fan is the wind speed captured by the fan; the wind speeds captured by the upstream and downstream fans will affect each other, and the relationship is as follows: (7); In equation (7), The wind speed captured by the downstream wind turbine; The wind speed captured by the upstream wind turbine; This is the wind speed attenuation coefficient. This represents the thrust coefficient of the wind turbine. The radius of the wind turbine blades; Distance between adjacent units; The wake descent coefficient is typically taken as the average value for onshore wind farms. =0.075.

[0010] The wind speed prediction equation for wind turbine units can be expressed as: (8); In equation (8), and The coefficients to be estimated are based on historical wind speed data. For the shift operator; It is a difference operator; This indicates the order of difference in historical wind speed data; This represents the actual wind speed value predicted based on historical wind speed data. This is represented as a mean of 0 and a variance of . The normal white noise process.

[0011] in: (9); (10); (11); In the above formula: These are the autoregressive parameters and moving average parameters calculated from historical wind speed data, respectively. , These are the autoregression order and moving average order of the historical data, respectively.

[0012] according to Figure 3 As shown, the relationship between the fan rotor and the wind speed at different wind speeds is as follows: (12); In equation (12), This indicates the angular velocity of the fan rotor corresponding to different wind speeds; Indicates the transmission coefficient of the wind turbine gearbox; This indicates the optimal tip speed ratio of the fan; This indicates the actual wind speed at the wind farm; Indicates the radius of the fan blades; The wind speed at which the wind turbine is connected to the grid; The wind speed is the speed required for the fan to enter the constant speed zone. Indicates the maximum speed of the fan; This indicates the fan speed when it enters the constant speed zone; Rated wind speed; This indicates the cut-out wind speed.

[0013] The actual wind speed of the wind farm calculated according to equation (8) Based on the geographical location of the wind turbines in the wind farm, the actual wind speed captured by each turbine is obtained, and the rotor speed of each turbine is obtained through equation (12). Therefore, by combining formula (3), the liftable inertia of a single wind turbine under normal operation can be calculated. .

[0014] In step 3, the state transition rate between unit operating states for: (13); In equation (13), This represents the transition rate from state i to state j; This represents the number of transitions from state i to state j within the statistical range; This represents the total duration of state i within the statistical range.

[0015] Wind turbine downtime relocation rate and express: This indicates the frequency at which the system transitions from normal operating state R to stopped operating state F. This indicates the frequency at which the system transitions from the stopped operating state F to the normal operating state R.

[0016] The state transition matrix of the wind turbine is obtained according to equation (13). for: (14); According to the Markov approximation principle, the equation can be obtained as follows: (15); In equation (15), , and These represent the probabilities of the normal operating state and the stopped operating state, respectively. This is the frequency transition matrix between different states of the wind turbine; Through the interval Randomly selected uniformly distributed numbers According to equation (16), the shutdown state of the fan at the sampling time is obtained: (16); In equation (16), Indicates the operating status of the fan; , These represent the normal operation and shutdown states of the wind turbine, respectively, and their corresponding probabilities are as follows: , .

[0017] exist Draw another random number within the interval The actual duration of each state of the wind turbine can be represented by the cumulative probability distribution function. express: (17); In equation (17), In order to be in Random numbers drawn from within the interval; The cumulative distribution function representing the duration of a state. It represents the proportional relationship between the duration of each operating state of the wind turbine and the average duration, reflecting the exponential decay characteristic of the duration of a certain state of the wind turbine; This represents the actual duration of the state. Indicates the average duration of the state; in, (18); In equation (18), This represents the average duration of state i, where i = normal state R, shutdown state F; Indicates the number of times state i has been left; This represents the transition rate from state i to state j.

[0018] In step 4, the inertia that each fan can improve is determined based on the inertia obtained in step 2. Combined with the shutdown status of each wind turbine at different times obtained in step 3 Using formula (6), the achievable inertia of the grid-type doubly-fed wind farm at different times after the retrofit is calculated. .

[0019] like Figure 2 As shown, for grid-connected wind farms that currently lack virtual inertia control, the increase in virtual inertia of the entire wind farm compared to before the upgrade, after future technological transformation to enable virtual inertia control, represents the potential increase in inertia. .

[0020] Based on formula (6), the achievable inertia of the modified wind farm The main factors affecting its virtual inertia are the wind speed captured by each wind turbine and its shutdown state. By establishing and solving the wind speed prediction equation and the operation state simulation equation, the magnitude of the increase in inertia of the wind farm after future renovation relative to before renovation can be calculated.

[0021] This invention provides a method for assessing the inertia of grid-connected wind farms based on wind turbine operating status, with the following technical advantages: 1) In step 1 of this invention, for grid-connected wind farms with virtual inertia after future modifications, the rotor speed of each wind turbine in the wind farm is predicted. and the operating status of each fan This allows for the calculation of the virtual inertia that the wind farm can provide in advance. .

[0022] 2) In step 2 of this invention, based on the wind speed prediction equation and the wake effect equation, and utilizing the historical wind speed data of the wind farm and the geographical location relationship of each wind turbine, the wind speed captured by each wind turbine at different times in the modified wind farm is accurately predicted, and the liftable inertia of each wind turbine under normal operation is calculated. .

[0023] 3) In step 3 of the present invention, the operating status of each wind turbine at different times is accurately evaluated based on the historical failure rate of each wind turbine in the wind farm, and the duration of each status is flexibly simulated within the evaluation interval.

[0024] 4) In step 4 of the present invention, combining steps 1 to 3, the inertia that each fan can increase is obtained from step 2. Combined with the shutdown status of each wind turbine at different times obtained in step 3 Using formula (6), the achievable inertia of the grid-type doubly-fed wind farm at different times after the retrofit is calculated. This avoids the significant errors that can result from equating each wind turbine to a single wind turbine in calculations.

[0025] 5) For future grid-connected doubly-fed induction generator (DFIG) wind farms that will be converted to have virtual inertia control strategies, the method proposed in this invention can be applied to predict the wind speed captured by each turbine and its shutdown status in advance, and calculate the inertia that the wind farm can increase. This method provides an effective approach for analyzing the inertia support capability of grid-connected wind farms for the power system. Attached Figure Description

[0026] The present invention will be further described below with reference to the accompanying drawings and examples; Figure 1 This is a flowchart of an embodiment of the present invention.

[0027] Figure 2 Doubly fed wind farm topology with virtual inertia control Figure 3 This is a schematic diagram showing the operating range of a doubly fed fan at various wind speeds.

[0028] Figure 4 This is a simulation system diagram of an embodiment of the present invention.

[0029] Figure 5 The inertia curve can be improved for wind farms.

[0030] Figure 6 The curve showing the inertia of the wind farm under wind condition 1.

[0031] Figure 7 The curve showing the inertia of the wind farm under wind condition 2. Detailed Implementation

[0032] This paper presents a method for assessing the inertia that can be improved in grid-connected wind farms based on turbine operating status. The method calculates the amount of inertia that the modified wind farm can provide in advance. First, based on the characteristic that the inertia of a grid-connected doubly-fed induction generator (DFIG) wind farm is zero, the functional relationship between the improved inertia after modification and wind speed and turbine shutdown status is analyzed. Then, based on the relationship between turbine rotor and wind speed at different wind speeds, a correlation equation for the wind speed captured by each turbine is established, and the improved inertia of a single turbine under normal operation is calculated. The operating state equations for each time period of the turbine are established using the transfer rate between turbine shutdown states, and the shutdown status of the wind turbine units during the assessment period is calculated. The improved inertia of the grid-connected wind farm after modification is calculated aggregated. Finally, the effectiveness of the method and results is verified through an improved four-turbine, two-zone simulation system. The flowchart is shown below. Figure 1 As shown.

[0033] In the MATLAB / Simulink environment, build Figure 4 The simulation system is a four-machine, two-zone system. The parameter settings of the simulation system are shown in Table 1.

[0034]

[0035] The wind speed data from the wind farm's meteorological towers (sampled at one point every 10 minutes) is used as historical wind speed data. The wind speed during the assessment period is predicted using the method described in step 2. The virtual inertia provided by each wind turbine can be calculated using equation (2). Combining steps 2 and 3 above, the inertia provided by the wind farm during the assessment period is calculated using equation (6), such as... Figure 5 As shown. According to Equation (12), the wind speed is divided into three intervals: low, medium and high. For the three typical wind speed scenarios, the magnitude of the inertia that the wind farm can increase under the corresponding wind speed is analyzed and calculated.

[0036] Scenario 1: In the medium wind speed area (10m / s), the inertia increase after the grid-type wind farm is calculated to be 4.15s using the above steps, and the actual increase in inertia is 4.03s.

[0037] Scenario 2: In the low wind speed area (7 m / s), the wind turbine operates within the MPPT range. This invention calculates the inertia increase after wind farm modification to be 7.54 s, while the actual increase is 7.16 s. The accuracy is lower than in the medium wind speed case because wind speed changes in the MPPT range have a significant impact on wind turbine rotation speed, requiring a high degree of accuracy in the wind speed model.

[0038] Scenario 3: In a high wind speed area (13 m / s), the wind turbine output power remains constant. This invention calculates the inertia increase after wind farm modification to be 8.04 s, while the actual increase is 8.12 s. The accuracy is high because the rotational speed in the constant power area is not affected by wind speed and is mainly related to the turbine's shutdown state. This invention demonstrates high accuracy in simulating the turbine's operating state, reflecting its effectiveness.

[0039] Set different virtual inertia control gains The impact of grid-connected wind farms on the increase of inertia is considered under two wind conditions: (1) Wind condition 1: Wind speed is 11m / s (medium wind speed); (2) Wind Condition 2: Wind speed is 7m / s (low wind speed). At t=30s, the load increase L3=260MW is set for the simulation system.

[0040] Figure 6 and Figure 7 The inertia response curves of the wind farm under wind conditions 1 and 2 are shown respectively. Figure 6 The magnitude of inertia increase was compared between the effects of virtual inertia control without virtual inertia control and after technical modifications, under the same initial wind speed, when As the value gradually increases from 10 to 25, the overall virtual inertia of the wind farm increases, from a maximum of 4.03s to 10.08s. This is because the virtual inertia of the wind farm is achieved by introducing the system frequency change rate signal into the control loop to realize the inertia response. As the value increases, the rotor speed of the wind turbine drops more during the moment of disturbance, thereby releasing more kinetic energy and making its inertial response capability stronger.

[0041] contrast Figure 6 and Figure 7 The results show that, under the two wind conditions, the magnitude of the wind farm's inertia increase before and after the adoption of virtual inertia control indicates that when disturbances occur, the greater the wind speed of the wind turbine, the more space there is for the rotational speed to decrease, and the stronger its inertia response capability.

Claims

1. A method for assessing the inertia of grid-connected wind farms based on wind turbine operating status, characterized in that... Includes the following steps: Step 1: Based on the characteristic that the inertia of a grid-connected doubly-fed wind farm is 0, analyze the functional relationship between the inertia that can be improved after the modification and the wind speed and the wind turbine shutdown state. Step 2: Based on the relationship between the fan rotor and the wind speed under different wind speeds, establish the correlation equation for the wind speed captured between fans, and calculate the liftable inertia of a single fan under normal operation. Step 3: Establish the operating state equations of the wind turbine for each time period based on the transition rate between wind turbine shutdown states, and calculate the shutdown state of the wind turbine unit during the evaluation period; Step 4: Calculate the inertia that can be increased after the grid-connected doubly fed wind farm is retrofitted.

2. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 1, characterized in that: In step 1, for the grid-connected wind farm with a virtual inertia control strategy after modification, based on the definition of the inertial time constant and combined with the change in the system's synchronous angular velocity, the virtual inertia of the modified wind turbine is expressed as: （1）； In formula (1): This represents the virtual inertia of the modified wind turbine; and These represent the initial angular velocities of the system and the fan rotor, respectively. and These represent the changes in system angular velocity and fan rotor speed, respectively. This is the rated angular velocity of the fan; is the inherent inertial time constant of the wind turbine.

3. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 2, characterized in that: The virtual inertia of the modified wind turbine is obtained by calculating the electromagnetic torque variable. The transfer function is: （2）； In equation (2), The gain is controlled by virtual inertia. The filtering time constant; and These are the proportional and integral coefficients of the speed controller, respectively. It is a complex parameter variable.

4. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 3, characterized in that: Performing an inverse Laplace transform on equation (2), we obtain The time-domain equation is: （3）； In formula (3): This represents the increased virtual inertia of the modified grid-type wind turbine at a certain moment; among which, , , , All parameters are known. in: （4）； （5）； In the formula: ; It is a discriminant; The linear part of the phase It is a time variable; , , , , This represents the decay process at the corresponding pole. like There are three single roots. , , The corresponding coefficient , , This is the expansion of a partial fraction; like There is a single root and two conjugate complex roots , , , Parameters corresponding to the poles The imaginary unit; coefficient , This is the expansion of a partial fraction.

5. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 4, characterized in that: Considering that the wind farm uses the same type of wind turbines with the same control parameters, the virtual inertia of each wind turbine is aggregated to obtain the equivalent inertial constant of the wind farm, that is, the wind farm can increase its inertia. : （6）； In formula (6): Let represent the virtual inertia of the i-th wind turbine after the modification; This represents the virtual inertia of the wind turbine before the modification; These represent the kinetic energy stored in each wind turbine; Let m be the rated capacity of the i-th fan, i = 1, 2, 3, ..., m; Indicates the number of wind turbines in the wind farm; This represents the operating status of the i-th wind turbine; This indicates that the fan is in normal operating condition; This indicates that the fan is in a stopped state; These represent the virtual inertia of each wind turbine; Indicates the first i The inertial time constant of a typhoon.

6. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 5, characterized in that: In equations (3) and (6), the following are set The angular velocity of the fan rotor is a fixed value. and running status The magnitude of the inertia that can be increased by the wind farm is affected; the other parameters are all known constants.

7. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 6, characterized in that: In step 2, according to equation (3), the factor affecting the increase of the inertia of the fan is the wind speed captured by the fan; the wind speeds captured by the upstream and downstream fans will affect each other, and the relationship is as follows: （7）； In equation (7), The wind speed captured by the downstream wind turbine; The wind speed captured by the upstream wind turbine; This is the wind speed attenuation coefficient. This represents the thrust coefficient of the wind turbine. The radius of the wind turbine blades; Distance between adjacent units; This is the wake descent coefficient; The wind speed prediction equation for wind turbine units is expressed as: （8）； In equation (8), and The coefficients to be estimated are based on historical wind speed data. For the shift operator; It is a difference operator; This indicates the order of difference in historical wind speed data; This represents the actual wind speed value predicted based on historical wind speed data. This is represented as a mean of 0 and a variance of . The normal white noise process; in: （9）； （10）； （11）； In the above formula: These are the autoregressive parameters and moving average parameters calculated from historical wind speed data, respectively. , These are the autoregression order and moving average order of the historical data, respectively.

8. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 7, characterized in that: The relationship between the fan rotor and the wind speed at different wind speeds is as follows: （12）； In equation (12), This indicates the angular velocity of the fan rotor corresponding to different wind speeds; Indicates the transmission coefficient of the wind turbine gearbox; This indicates the optimal tip speed ratio of the fan; This indicates the actual wind speed at the wind farm; Indicates the radius of the fan blades; The wind speed at which the wind turbine is connected to the grid; The wind speed is the speed required for the fan to enter the constant speed zone. Indicates the maximum speed of the fan; This indicates the fan speed when it enters the constant speed zone; Rated wind speed; Indicates the cut-out wind speed; The actual wind speed of the wind farm calculated according to equation (8) Based on the geographical location of the wind turbines in the wind farm, the actual wind speed captured by each turbine is obtained, and the rotor speed of each turbine is obtained through equation (12). Therefore, by combining formula (3), the liftable inertia of a single wind turbine under normal operation can be calculated. .

9. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 8, characterized in that: In step 3, the state transition rate between unit operating states for: （13）； In equation (13), This represents the transition rate from state i to state j; This represents the number of transitions from state i to state j within the statistical range; This represents the total duration of state i within the statistical range; Wind turbine downtime relocation rate and express: This indicates the frequency at which the system transitions from normal operating state R to stopped operating state F. This indicates the frequency at which the system transitions from the stopped operating state F to the normal operating state R. The state transition matrix of the wind turbine is obtained according to equation (13). for: （14）； According to the Markov approximation principle, the equation can be obtained as follows: （15）； In equation (15), , and These represent the probabilities of the normal operating state and the stopped operating state, respectively. This is the frequency transition matrix between different states of the wind turbine; Through the interval Randomly selected uniformly distributed numbers According to equation (16), the shutdown state of the fan at the sampling time is obtained: （16）； In equation (16), Indicates the operating status of the fan; , These represent the normal operation and shutdown states of the wind turbine, respectively, and their corresponding probabilities are as follows: , ; exist Draw another random number within the interval The actual duration of each state of the wind turbine can be represented by the cumulative probability distribution function. express: （17）； In equation (17), In order to be in Random numbers drawn from within the interval; The cumulative distribution function representing the duration of a state. It represents the proportional relationship between the duration of each operating state of the wind turbine and the average duration, reflecting the exponential decay characteristic of the duration of a certain state of the wind turbine; This represents the actual duration of the state. Indicates the average duration of the state; in, （18）； In equation (18), This represents the average duration of state i, where i = normal state R, shutdown state F; Indicates the number of times state i has been left; This represents the transition rate from state i to state j.

10. The method for assessing the inertia of grid-connected wind farms based on wind turbine operating status as described in claim 9, characterized in that: In step 4, the inertia that each fan can improve is determined based on the inertia obtained in step 2. Combined with the shutdown status of each wind turbine at different times obtained in step 3 Using formula (6), the achievable inertia of the grid-type doubly-fed wind farm at different times after the retrofit is calculated. ; For grid-connected wind farms that currently lack virtual inertia control, future technological upgrades to include virtual inertia control will result in an increase in virtual inertia for the entire wind farm compared to before the upgrades; this increase represents the potential improvement in inertia. ; Based on formula (6), the achievable inertia of the modified wind farm The factors affecting its virtual inertia include the wind speed captured by each wind turbine and its shutdown status. By establishing and solving the wind speed prediction equation and the operation state simulation equation, the magnitude of the increase in inertia of the wind farm after future renovation relative to before renovation can be calculated.

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