Probability risk assessment method for forced subsynchronous oscillation of doubly-fed wind power plant grid-connected system

Abstract

The invention discloses a probability risk assessment method for forced subsynchronous oscillation of a doubly-fed wind power plant grid-connected system, which is used for assessing the risk of forced subsynchronous oscillation and belongs to the technical field of doubly-fed wind power plant grid-connected systems. The method comprises the following steps: 1, fitting a probability distribution model of an actual wind speed; 2, generating m wind speed samples following the probability distribution; 3, calculating a severity index A (sih) of each wind speed sample; 4, calculating a forced subsynchronous oscillation risk index Rv of the system with the determined operation condition; 5, determining the probability w of each system operation condition, and then calculating a forced subsynchronous oscillation risk index R considering the system operation conditions and the wind speed uncertainty; 6, simulating two groups A corresponding to the low / medium risk threshold R1 and the medium / high risk threshold R2 according to the power grid standard, and calculating the thresholds R1 and R2 by using the two groups A; and 7, comparing R with R1 and R2 to determine the forced subsynchronous oscillation risk level of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of grid-connected systems for doubly-fed wind farms, and particularly relates to a probabilistic risk assessment method for forced subsynchronous oscillation in a doubly-fed wind farm grid-connected system. Background Art

[0002] With the large-scale use of wind power generation, subsynchronous oscillation in wind farm grid-connected systems has become an important research topic globally. Based on its occurrence mechanism, subsynchronous oscillation in wind farm grid-connected systems can be divided into two categories: negative-damping subsynchronous oscillation and forced subsynchronous oscillation. Wind turbines connected to the grid through converters can generate interharmonics with subsynchronous frequencies, and these interharmonics are prone to exciting subsynchronous modes that match the interharmonic frequencies in the system, thereby triggering forced subsynchronous oscillation and posing a threat to the safe operation of the system.

[0003] The risk assessment methods for subsynchronous oscillation in wind farm grid-connected systems are divided into deterministic methods and probabilistic methods. There are many uncertain factors in grid-connected wind farm systems, such as the uncertainty of wind speed and system operating conditions. The results obtained by deterministic methods only consider wind speed and system operating conditions with equal probabilities, so they cannot describe the influence of different probability distributions of system operating conditions and wind speed on the risk of forced subsynchronous oscillation. Damping or the phase margin related to damping is used as an index to evaluate the risk of negative-damping subsynchronous oscillation in the system. When the damping or phase margin is negative, the system is considered to be in an unstable state. If the damping or phase margin is negative and the probability of subsynchronous oscillation occurrence is high, then the risk of subsynchronous oscillation in the system is high. However, for forced subsynchronous oscillation, the damping and phase margin of the excited mode are both positive. Therefore, the risk index of negative-damping subsynchronous oscillation cannot be used to evaluate the risk of forced subsynchronous oscillation. Summary of the Invention

[0004] The purpose of the present invention is to provide a probabilistic risk assessment method for forced subsynchronous oscillation in a doubly-fed wind farm grid-connected system, which is used to evaluate the risk of forced subsynchronous oscillation.

[0005] The present invention is implemented by adopting the following technical solutions:

[0006] A probabilistic risk assessment method for forced subsynchronous oscillation in a doubly-fed wind farm grid-connected system includes the following steps:

[0007] Step 1: Fit the long-term actual wind speed data of the doubly-fed wind farm grid-connected system; select the model with the best fitting effect from them and use it as the probability distribution model of the actual wind speed;

[0008] Step 2: Use the Monte Carlo method to generate m wind speed samples that follow this probability distribution;

[0009] Step 3: Calculate the severity index A(s ih ) for each wind speed sample;

[0010] Define the ratio of the interharmonic current amplitude to the fundamental current amplitude in the system as the severity index A(s ih ) of forced subsynchronous oscillation. If the wind speed is not within the range that can excite forced subsynchronous oscillation, let A(s ih ) be 0; if the wind speed is within the range that can excite forced subsynchronous oscillation, calculate A(s ih ) by the following formula:

[0011]

[0012] where i g.ih (s ih ) is the interharmonic current in the system; i g0 is the fundamental current in the system; i ih (s ih ) is the interharmonic current output by the wind farm; Z dfig (s ih ) and Z g (s ih ) are the equivalent impedances of the doubly-fed wind farm and the power grid at the interharmonic frequency respectively, and its amplitude |i g0 | can be calculated by , where n is the number of doubly-fed wind turbines in the wind farm, U pcc is the effective value of the grid connection point voltage, and P DFIG is the output power of the doubly-fed wind turbine;

[0013] Step 4: Calculate the forced subsynchronous oscillation risk index R v of the system with determined operating conditions, and the calculation formula is as follows:

[0014] R v = ∫P r (A) S(A) dA (7)

[0015] where P r (A) is the probability density function of A at different wind speeds, obtained by the kernel density estimation method; S(A) is the defined continuous severity function, as follows:

[0016]

[0017] Step 5: Determine the probability w of each system operating condition, and then calculate the forced subsynchronous oscillation risk index R considering the system operating conditions and wind speed uncertainty through the following formula:

[0018]

[0019] where, w i is the probability of the i-th operating condition, and R vi is the R under the i-th system operating condition v ;

[0020] Step 6: According to the grid standard, simulate two sets of A corresponding to the low / medium risk threshold R1 and the medium / high risk threshold R2, and use these two sets of A to calculate the thresholds R1 and R2.

[0021] Step 7: Determine the forced subsynchronous oscillation risk level of the system by comparing R with R1 and R2.

[0022] The present invention uses the ratio of the interharmonic current amplitude to the fundamental current amplitude obtained based on the impedance method as the severity index of forced subsynchronous oscillation, establishes a forced subsynchronous oscillation risk function considering the probability distribution of system operating conditions and wind speed, and quantitatively evaluates the forced subsynchronous oscillation risk of the system by combining the occurrence probability and severity. The probability risk assessment method for forced subsynchronous oscillation of the doubly-fed wind farm grid-connected system proposed by the present invention takes into account the uncertainties of system operating conditions and wind speed, avoids the conservatism and optimism of the deterministic risk assessment method, and can provide more effective information for operators to make risk judgments and preventive decisions.

[0023] The beneficial effects of the present invention are as follows:

[0024] 1. The proposed probability risk assessment method for forced subsynchronous oscillation of the present invention can avoid the conservatism and optimism of the deterministic risk assessment method, and can provide more effective information for operators to make risk judgments and preventive decisions;

[0025] 2. The proposed probability risk assessment method for forced subsynchronous oscillation of the present invention can be applied to various complex and uncertain situations, especially suitable for multivariable systems and dynamic environments, and solves the problem that the deterministic method is not flexible enough in complex situations.

[0026] 3. The proposed probability risk assessment method for forced subsynchronous oscillation of the present invention can continuously update and adjust the risk assessment results with the acquisition of new data, making risk management more adaptable. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present invention, and are used together with the specification to explain the principles of the present invention.

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0029] Figure 1 It is a grid-connected system for a doubly-fed wind farm.

[0030] Figure 2 It is the steady-state circuit (fundamental wave circuit) of the grid-connected system for a doubly-fed wind farm.

[0031] Figure 3 It is the steady-state circuit (interharmonic circuit) of the grid-connected system for a doubly-fed wind farm.

[0032] Figure 4 It is a flowchart for the probabilistic risk assessment of forced subsynchronous oscillation. Specific implementation manners

[0033] In order to more clearly understand the above-mentioned objects, features, and advantages of the present invention, the solution of the present invention will be further described below. It should be noted that, without conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0034] In the description, it should be noted that the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. It should be noted that unless otherwise clearly defined and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific situations.

[0035] Many specific details are set forth in the following description in order to fully understand the present invention, but the present invention may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only a part of the embodiments of the present invention, rather than all the embodiments.

[0036] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0037] Embodiment 1, a method for probabilistic risk assessment of forced subsynchronous oscillation in a grid-connected system for a doubly-fed wind farm, includes the following steps:

[0038] Step 1: Fit the long-term actual wind speed data of the grid-connected system for a doubly-fed wind farm by using Rayleigh distribution, Weibull distribution, and lognormal distribution; select the model with the best fitting effect from them and use it as the probability distribution model of the actual wind speed.

[0039] Step 2: Use the Monte Carlo method to generate m wind speed samples that follow this probability distribution.

[0040] Step 3: Calculate the severity index A(s ih ) of each wind speed sample;

[0041] Define the ratio of the interharmonic current amplitude to the fundamental current amplitude in the system as the severity index A(s ih ) of forced subsynchronous oscillation. If the wind speed is not within the range that can excite forced subsynchronous oscillation, let A(s ih ) be 0; if the wind speed is within the range that can excite forced subsynchronous oscillation, calculate A(s ih ) from the following formula:

[0042]

[0043] In the formula, i g.ih (s ih ) is the interharmonic current in the system; i g0 is the fundamental current in the system; i ih (s ih ) is the interharmonic current output by the wind farm; Z dfig (s ih ) and Z g (s ih ) are the equivalent impedances of the doubly-fed wind farm and the power grid at the interharmonic frequency respectively. The amplitude |i g0 | can be calculated through , where n is the number of doubly-fed wind turbines in the wind farm, U pcc is the effective value of the grid-connected point voltage, and P DFIG is the output power of the doubly-fed wind turbine;

[0044] Step 4: Calculate the forced subsynchronous oscillation risk index R v of the system with determined operating conditions, and the calculation formula is as follows:

[0045] R v = ∫P r (A)S(A)dA (7)

[0046] In the formula, P r (A) is the probability density function of A at different wind speeds, obtained by the kernel density estimation method; S(A) is the defined continuous severity function, as follows:

[0047]

[0048] Step 5: Determine the probability w of each system operating condition, and then calculate the forced subsynchronous oscillation risk index R considering the system operating condition and wind speed uncertainty through the following formula:

[0049]

[0050] In the formula, wi is the probability of the i-th operating condition, R vi is the R under the i-th system operating condition v ;

[0051] Step 6: According to the grid standard, simulate two sets of A corresponding to the low / medium risk threshold R1 and the medium / high risk threshold R2, and use these two sets of A to calculate the thresholds R1 and R2.

[0052] Step 7: Determine the forced subsynchronous oscillation risk level of the system by comparing R with R1 and R2.

[0053] Example 2, in step three, the doubly-fed wind farm grid-connected system is as shown in the appendix Figure 1 shown, its steady-state circuit is divided into a fundamental wave circuit with a frequency of the grid fundamental frequency and an interharmonic circuit with a frequency of the interharmonic frequency, as shown in Figure 2 and Figure 3 shown. From Figure 3 the interharmonic current i g.ih (s ih ) in the system can be obtained as follows:

[0054]

[0055] In the formula, i ih (s ih ) is the interharmonic current output by the wind farm; Z dfig (s ih ) and Z g (s ih ) are the equivalent impedances of the doubly-fed wind farm and the power grid at the interharmonic frequency respectively.

[0056] Define the ratio of the interharmonic current amplitude to the fundamental current amplitude in the system as the severity index A(s ih ) of forced subsynchronous oscillation, as follows:

[0057]

[0058] In the formula, i g0 is the fundamental current in the system, and its amplitude |i g0 | can be calculated by . Among them, n is the number of doubly-fed wind turbines in the wind farm; U pcc is the effective value of the grid-connected point voltage; P DFIG is the output power of the doubly-fed wind turbine.

[0059] The frequency of the interharmonic output by the doubly-fed wind turbine is as follows:

[0060] f ih =|(6k±1)f0 - 6kf r|, k = 1, 2, 3, … (3)

[0061] where f0 is the fundamental frequency of the power grid; f r is the rotor frequency of the doubly-fed wind turbine; the interharmonic with frequency f ih1 = (6k + 1)f0 - 6kf r is positive sequence; the interharmonic with frequency f ih2 = (6k - 1)f0 - 6kf r is negative sequence. The interharmonics that can excite forced subsynchronous oscillation are positive-sequence interharmonics with frequencies between 0 and 2f0. The negative-sequence interharmonic with frequency f ih2 is equivalent to the positive-sequence interharmonic with frequency f ih3 = -f ih2 . It can be calculated that f ih1 + f ih3 = 2f0. Therefore, when f ih1 > 0 and f ih3 = -f ih2 > 0 are satisfied simultaneously, the interharmonics generated by the doubly-fed wind turbine can excite forced subsynchronous oscillation. Substituting the expressions of f ih1 and f ih2 into the above conditions, the range of f r that can excite forced subsynchronous oscillation can be deduced as follows:

[0062] [1 - 1 / (6k)]f0 < f r < [1 + 1 / (6k)]f0 (4)

[0063] Since the amplitude of the interharmonic when k = 1 is much larger than that of other interharmonics, we only consider the forced subsynchronous oscillation excited by the interharmonic current when k = 1. Substituting k = 1 into equation (4), the range of f r that can excite forced subsynchronous oscillation is obtained as follows:

[0064] 5 / 6f0 < f r < 7 / 6f0 (5)

[0065] Let the wind speeds corresponding to f r = 5 / 6f0 and f r = 7 / 6f0 be v p and v q respectively. When the wind speed is not within the interval (v p , v q ), the interharmonics generated by the doubly-fed wind turbine cannot excite forced subsynchronous oscillation. For each system operating condition, use formula (2) to calculate the severity indices A(s p ) and A(s q ) for each wind speed sample within the interval (v ih1 ), and A(s ih3 ), and for the interval (vp , v q Set the severity index of each wind speed sample other than () to 0.

[0066] Example 3: According to the Chinese standard GB / T 24337 in step 4, the percentage of sub / super-synchronous frequency interharmonics in the system caused by the connection of the wind farm shall not exceed 0.2%. Define the continuous severity function of forced sub-synchronous oscillation as follows:

[0067]

[0068] The risk of forced sub-synchronous oscillation is directly related to the occurrence probability and severity. Although the severity is high, if the occurrence probability is small, the risk of forced sub-synchronous oscillation may be low. Conversely, when the severity is small, if the occurrence probability is large, the risk of forced sub-synchronous oscillation may be high. A continuous risk function is introduced, which considers the occurrence probability and severity of forced sub-synchronous oscillation under random wind speeds and is used to quantitatively evaluate the risk of forced sub-synchronous oscillation of a system with determined operating conditions, as follows:

[0069] R v = ∫ P r (A) S(A) dA (7)

[0070] In the formula, A is the larger value of A(s ih1 ) and A(s ih3 ) at each wind speed; P r (A) is the probability density function of A at different wind speeds, obtained by the kernel density estimation method.

[0071] Substitute the A corresponding to different wind speeds under the same system operating conditions into equation (7), and the R under each system operating condition can be calculated. v .

[0072] Example 4: The ratio of the interharmonic current amplitude to the fundamental current amplitude in the system in Example 1 is the severity index A(s ih ) of forced sub-synchronous oscillation, which is obtained by the impedance method. Specifically: Step 1, determine the interharmonic frequency f of the double-fed wind turbine output ih , and judge whether it will excite the forced sub-synchronous oscillation of the double-fed wind farm grid-connected system;

[0073] Step 2, establish a small-signal impedance model of the double-fed wind farm and the power grid;

[0074] The double-fed wind farm with grid-following control is equivalent to a Norton equivalent circuit in parallel with a small-signal current source Δi cr (s) and a small-signal impedance Z dfig (s); the power grid is equivalent to a small-signal voltage source Δu g(s) and small-signal impedance Z g The Thevenin equivalent circuit in series with (s); x and y are the common connection points of the doubly-fed wind farm and the power grid.

[0075] Step 3: Calculate the amplitude ratio and phase difference of the impedance of the wind farm and the power grid at the interharmonic frequency;

[0076] Substitute the positive-sequence interharmonic frequencies f ih1 and f ih3 with complementary frequencies and the system parameters into Z dfig (s) and Z g (s), and calculate the amplitude ratio and phase difference of the impedance of the wind farm and the power grid at two different interharmonic frequencies, namely the amplitude ratio D1 and phase difference δ1 of Z g (s ih1 ) and Z dfig (s ih1 ), as well as the amplitude ratio D3 and phase difference δ3 of Z g (s ih3 ) and Z dfig (s ih3 ).

[0077] Step 4: Calculate the ratio A(s ih ) of the interharmonic current amplitude to the fundamental current amplitude based on the steady-state equivalent circuit of the system.

[0078] The output current of the doubly-fed wind farm in the steady state contains both the fundamental current with the frequency of the power grid fundamental frequency f0 and the interharmonic current with the frequency of the interharmonic frequency f ih ; according to the different current frequencies, the doubly-fed wind farm is equivalent to a Norton equivalent circuit in parallel with the fundamental current source i cr0 and the impedance Z dfig0 ; the power grid is equivalent to a Thevenin equivalent circuit in series with the fundamental voltage source u g0 and the impedance Z g0 ; the equivalent interharmonic voltage source of the power grid is 0 and is regarded as a short circuit, and the power grid is only equivalent to the impedance Z g (s ih ); according to the established steady-state interharmonic circuit model of the system, the expression of the interharmonic current i g.ih (s ih ) in the system current is shown in formula (1).

[0079] The amplitude of the fundamental current |i g0 | at different wind speeds can be calculated through . Among them, n is the number of doubly-fed wind turbines in the wind farm; U pcc is the effective value of the voltage at the common coupling point. Each wind speed can correspond to a calculated fixed value |i g0 |. By calculating |i g.ih (sih )|The ratio with |i g0 , that is, the proportion A(s of the interharmonic current amplitude to the fundamental current amplitude ih ), is used as the index expression for evaluating the severity of forced subsynchronous oscillation, as shown in formula (2).

[0080] The amplitude of the interharmonic current |i ih (s ih ) output by the doubly-fed wind farm also has a time-varying characteristic that changes with the wind speed. However, the f range that can excite forced subsynchronous oscillation is small, and the corresponding wind speed interval is also small. The change of |i r (s ih ) within this wind speed interval is small. On the other hand, in practice, |i ih (s ih ) is very small, and the occurrence of forced subsynchronous oscillation mainly depends on whether |1 + Z ih (s g ) / Z ih (s dfig ) is small enough. For the above reasons, when calculating A(s ih ) at different wind speeds, |i ih (s ih ) can be set as a small constant. Substituting |i ih (s ih ), |i ih | and the two sets of sample values D1 / δ1 and D3 / δ3 described above into formula (2), the proportion A(s g0 ) of the interharmonic current amplitude corresponding to the two interharmonic frequencies and A(s ih1 ) can be obtained. ih3 )

[0081] Step 5. Determine the severity of forced subsynchronous oscillation according to the calculated A(s ih ).

[0082] According to the Chinese standard GBT / 24337, the percentage of sub / supersynchronous frequency harmonics in the system caused by the grid connection of the wind farm cannot exceed 0.2%. When A(s ih ) ≤ 0.2%, it is considered that the severity of the system's forced subsynchronous oscillation is low; when A(s ih ) > 0.2%, it is considered that the severity of the system's forced subsynchronous oscillation is high, and the higher the value, the higher the severity.

[0083] Example 5: By fitting the observed wind speed data of a wind farm in Guyuan, China from 2014 to 2015, the Weibull distribution model was selected as the probability distribution model of wind speed. The actual average wind speed was 6.43 m / s; the variance was 9.30. The short-circuit ratio (SCR) is an indicator of the strength of the AC power grid, defined as the ratio of the short-circuit capacity of the AC system to the rated capacity of the wind farm. SCR = 2, 3, and 4 were selected as different system operating conditions, and the system parameters are shown in Table 1.

[0084] Table 1 System parameters

[0085]

[0086] The results of the forced subsynchronous oscillation risk assessment for systems with different operating conditions and wind speed probability distributions are shown in Table 2. The first column lists the different system operating condition probability distributions; the second column lists the different average wind speeds; the third column lists the forced subsynchronous oscillation risk indicators under different system operating conditions and wind speed probability distributions; the fourth column lists the forced subsynchronous oscillation risk levels of the systems under different system operating conditions and wind speed probability distributions. The Monte Carlo sample size was 100,000, and the number of repetitions was 10. The low / medium risk threshold for forced subsynchronous oscillation was set as R1 = 1×10 -6 , and the medium / high risk threshold for forced subsynchronous oscillation was set as R2 = 2×10 -6 .

[0087] Table 2 Results of forced subsynchronous oscillation risk assessment

[0088]

[0089] The working principle of this method is as follows: First, the long-term actual wind speed data of the doubly-fed wind farm grid-connected system are fitted using the Rayleigh distribution, Weibull distribution, and lognormal distribution, and the model with the best fitting effect is selected as the probability distribution model of the actual wind speed. Then, the Monte Carlo method is used to generate 100,000 wind speed samples that follow this probability distribution, and the wind speed interval range that can excite forced subsynchronous oscillation is calculated based on Equation (5). Next, for a certain determined system operating condition, the forced subsynchronous oscillation severity index A corresponding to the wind speeds within this wind speed interval range is calculated based on Equation (2), the A corresponding to the wind speeds outside this wind speed interval range is set to 0, and all the A corresponding to the wind speeds are substituted into (7) to calculate the forced subsynchronous oscillation risk index R under this system operating condition v . Repeat this step to calculate the R under each system operating condition v . The probability of each system operating condition and the R corresponding to each operating condition vSubstitute into (9) to calculate the forced subsynchronous oscillation risk index R considering the system operating conditions and wind speed uncertainty. Repeat the above steps 10 times (i.e., generate 10 wind speed samples using the Monte Carlo method) and calculate the average value of R. Subsequently, according to the grid standard, simulate two sets of A corresponding to the low / medium risk threshold R1 and the medium / high risk threshold R2, and calculate the thresholds R1 and R2 by substituting these two sets of A into equation (7). Finally, Compare with R1 and R2 to determine the forced subsynchronous oscillation risk level of the system.

[0090] The above are only specific implementation manners of the present invention, enabling those skilled in the art to understand or implement the present invention. Although the foregoing embodiments have been described in detail, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments, and they should all be covered by the protection scope of the claims.

Claims

1. A probabilistic risk assessment method for forced subsynchronous oscillation in a doubly-fed wind farm grid-connected system, characterized in that: It includes the following steps: Step 1: Fit the long-term actual wind speed data of the doubly-fed wind farm grid-connected system; select the model with the best fitting effect from them and use it as the probability distribution model of the actual wind speed; Step 2: Use the Monte Carlo method to generate m wind speed samples that follow this probability distribution; Step 3: Calculate the severity index A for each wind speed sample ( s ih) ; Define the ratio of the interharmonic current amplitude to the fundamental current amplitude in the system as the severity index A of the forced subsynchronous oscillation ( s ih) . If the wind speed is not within the range that can excite the forced subsynchronous oscillation, let A ( s ih) be 0; if the wind speed is within the range that can excite the forced subsynchronous oscillation, calculate A ( s ih) by the following formula: Where, i g.ih (s ih ) is the interharmonic current in the system; i g0 is the fundamental current in the system; i ih (s ih ) is the interharmonic current output by the wind farm; Z dfig (s ih ) and Z g (s ih ) are the equivalent impedances of the doubly-fed wind farm and the power grid at the interharmonic frequency respectively, and its amplitude |i g0 | can be calculated by , where n is the number of doubly-fed wind turbines in the wind farm, U pcc is the effective value of the grid-connected point voltage, and P DFIG is the output power of the doubly-fed wind turbine; Step 4: Calculate the forced subsynchronous oscillation risk index R of the system with definite operating conditions v , and the calculation formula is as follows: R v = ∫ P r (A) S(A) dA (7) where P r (A) is the probability density function of A at different wind speeds, obtained by the kernel density estimation method; S(A) is the defined continuous severity function, as follows: Step 5: Determine the probability w of each system operating condition, and then calculate the forced subsynchronous oscillation risk index R considering the system operating condition and wind speed uncertainty through the following formula: where w i is the probability of the i-th operating condition, and R vi is the R under the i-th system operating condition v ; Step 6: According to the grid standard, simulate two sets of A corresponding to the low / medium risk threshold R1 and the medium / high risk threshold R2, and use these two sets of A to calculate the thresholds R1 and R2; Step 7: Determine the forced subsynchronous oscillation risk level of the system by comparing R with R1 and R2.

2. The probability risk assessment method for forced subsynchronous oscillation of a doubly-fed wind farm grid-connected system according to claim 1, wherein: The steady-state circuit of the doubly-fed wind farm grid-connected system is divided into a fundamental wave circuit with the frequency of the power grid fundamental frequency and an inter-harmonic circuit with the frequency of the inter-harmonic frequency. The inter-harmonic current i g.ih (s ih ) is expressed as follows: where i ih (s ih ) is the interharmonic current output by the wind farm; Z dfig (s ih ) and Z g (s ih ) are the equivalent impedances of the doubly-fed wind farm and the power grid at the interharmonic frequency, respectively.

3. The probability risk assessment method for forced subsynchronous oscillation of a doubly-fed wind farm grid-connected system according to claim 1, characterized in that: The frequency of the interharmonics output by the doubly-fed fan is shown by the following formula: f ih = |(6k ± 1)f0 - 6kf r |, k = 1, 2, 3, … (3) where f0 is the power grid fundamental frequency; f r is the rotor frequency of the doubly-fed wind turbine; the frequency is f ih1 =(6k + 1)f0 - 6kf r of the interharmonic is positive sequence; the frequency is f ih2 =(6k - 1)f0 - 6kf r of the interharmonic is negative sequence; The interharmonics that can excite forced subsynchronous oscillation are positive-sequence interharmonics with frequencies between 0 and 2f0, and the negative-sequence interharmonics with a frequency of f ih2 are equivalent to positive-sequence interharmonics with a frequency of f ih3 =-f ih2 of the positive-sequence interharmonics. It can be calculated that f ih1 +f ih3 =2f0. Therefore, when f ih1 >0 and f ih3 =-f ih2 >0 are satisfied simultaneously, the interharmonics generated by the doubly-fed wind turbine can excite forced subsynchronous oscillation.

4. A probability risk assessment method for forced subsynchronous oscillation of a doubly-fed wind farm grid-connected system according to claim 3, characterized in that: Substitute the expressions of f ih1 and f ih2 into the above conditions, and the range of f r that can trigger forced subsynchronous oscillation can be derived as follows: [1 - 1 / (6k)]f0 < f r < [1 + 1 / (6k)]f0 (4) Since the amplitude of the interharmonic at k = 1 is much larger than that of other interharmonics, only consider the forced subsynchronous oscillation excited by the interharmonic current at k = 1. Substitute k = 1 into Equation (4) to obtain the range of f that can excite the forced subsynchronous oscillation as follows: r as follows: 5 / 6f0 < f r <7 / 6f0 (5) Let the corresponding f r = 5 / 6f0 and f r = 7 / 6f0 have wind speeds of v p and v q , respectively. When the wind speed is not in the interval (v p , v q ), the interharmonics generated by the doubly-fed wind turbine cannot excite the forced subsynchronous oscillation; for each system operating condition, use formula (2) to calculate the severity indices A(s p ) and A(s q ) for each wind speed sample within the interval (v ih1 , v ih3 ), and set the severity index of each wind speed sample outside the interval (v p , v q ) to 0.

5. The probability risk assessment method for forced subsynchronous oscillation of a doubly-fed wind farm grid-connected system according to claim 1, characterized in that: Substitute A corresponding to different wind speeds under the same system operating conditions into Equation (7), and then the R under each system operating condition can be calculated. v .

6. The probability risk assessment method for forced subsynchronous oscillation of a doubly-fed wind farm grid-connected system according to claim 1, characterized in that: The forced subsynchronous oscillation risk of the system is also affected by uncertain system operating conditions. Among them, the grid strength changes with the connection and disconnection of the transmission lines near the grid connection point of the wind farm based on the doubly-fed induction generator. The uncertainty of the grid strength can be represented by a discrete probability distribution: P(i) = w i i = 1, 2, …, n (8) where w i is the probability of the i-th operating condition; n is the number of operating conditions; w1 + w2 +... + w n = 1。 7. A probability risk assessment method for forced subsynchronous oscillation of a doubly-fed wind farm grid-connected system according to claim 1, characterized in that: The operator determines the probability \(w\) of each system operating condition, and then combines \(w\) and \(R\) under different system operating conditions v and substitutes them into (9) to calculate the system forced subsynchronous oscillation risk index \(R\).

8. A probability risk assessment method for forced subsynchronous oscillation of a doubly-fed wind farm grid-connected system according to any one of claims 1-7, characterized in that: Repeat steps 2 to 5 and calculate the average value of R. Then perform step 7 Compare with R1 and R2 to determine the forced sub-synchronous oscillation risk level of the system.

9. A method for probabilistic risk assessment of forced subsynchronous oscillation in a doubly-fed wind farm grid-connected system according to any one of claims 1-7, characterized in that: Use the Rayleigh distribution, Weibull distribution, and lognormal distribution to fit the long-term actual wind speed data of the doubly-fed wind farm grid-connected system; select the model with the best fitting effect from them and use it as the probability distribution model of the actual wind speed.

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