Model Predictive Fault Ride-Through Method for the Sending-End MMC of a Wind Farm-Bipolar VSC-HVDC System

Abstract

The present invention discloses a method for a wind farm - bipolar flexible DC system sending - end MMC model - predictive fault - ride - through. This method addresses the problems of voltage fluctuations and unbalanced power distribution in the sending - end power grid when a fault occurs in the existing wind farm - bipolar flexible DC system. By adopting a model - predictive algorithm, it realizes the tracking of the voltage optimization command by the MMC voltage control pole and simplifies the control structure of the power control pole. The power and current double - loop control links in the traditional control strategy are replaced by a power prediction model and an objective function. Compared with existing methods, this method can significantly suppress over - voltage in the sending - end power grid of the wind farm - bipolar flexible DC system, balance the output power between the two poles in real - time, and has a simpler control structure.

Description

Technical Field

[0001] The present invention belongs to the technical field of power electronics, and particularly relates to a method for predicting faults and crossing through faults of a sending-end MMC in a wind farm - bipolar flexible DC system. Background Art

[0002] With the gradual increase of the voltage level and transmission capacity of flexible DC transmission systems, bipolar flexible DC transmission systems have received more and more attention due to their high flexibility and reliability. Flexible DC transmission technology based on the modular multilevel converter (MMC) topology has the advantages of low manufacturing difficulty, low system loss, and high waveform quality, and has very good application prospects in the transmission of wind power over long distances.

[0003] In a wind farm - bipolar flexible DC transmission system, the sending-end MMC needs to establish stable frequency and voltage for the wind farm, and generally adopts one-pole constant AC voltage control and the other-pole constant power control. When a fault occurs in the sending-end AC grid, the operating performance of the wind farm - bipolar flexible DC system will be seriously affected. Among them, the overvoltage problem caused by the fault will not only threaten the safe and stable operation of the entire system, but also pose high requirements for the overvoltage and insulation levels of equipment and lines, greatly increasing the engineering construction cost. Therefore, the research on the fault crossing strategy of the sending-end MMC in the wind farm - bipolar flexible DC system is of great significance.

[0004] Some literature has analyzed the fault characteristics of the sending-end AC grid in a wind farm - monopolar flexible DC transmission system and proposed corresponding control strategies, effectively suppressing the fault overvoltage level of the system. However, for a bipolar flexible DC transmission system, not only the overvoltage suppression method needs to be considered, but also the coordinated distribution of power between the two poles during the fault needs to be considered. The traditional control method based on a PI controller needs to be adjusted separately for different phase sequence variables, and the control strategy will become very complicated. As a non-linear control strategy, model predictive control is very suitable for using a unified control method to control different phase sequence components under grid faults. At present, there is still little research on the fault crossing strategy of the sending-end MMC in a wind farm - bipolar flexible DC system under a sending-end grid fault. There is an urgent need to propose a method for predicting faults and crossing through faults of the sending-end MMC in a wind farm - bipolar flexible DC system to ensure the safe and stable operation of the system. Summary of the Invention

[0005] The object of the present invention is to overcome the problems of voltage fluctuation and unbalanced power distribution in the existing wind farm - bipolar flexible DC transmission system when a fault occurs in the sending - end power grid, and to provide a method for predicting fault - ride - through of the sending - end MMC in the wind farm - bipolar flexible DC system. By adopting the model - predictive algorithm, the voltage - control pole of the MMC realizes the tracking of the voltage optimization command, and simplifies the control structure of the power - control pole. The power - prediction model and the objective function replace the power and current double - loop control links in the traditional control strategy. When a fault occurs in the sending - end power grid, this method can significantly suppress the over - voltage of the sending - end power grid of the wind farm - bipolar flexible DC system and balance the output power between the two poles in real time.

[0006] In order to achieve the above - mentioned object of the invention, the following technical solutions are adopted:

[0007] A method for predicting fault - ride - through of the sending - end MMC in the wind farm - bipolar flexible DC system, and the control system adopted to implement the method includes: a positive - pole sampling module and a negative - pole sampling module, a positive - pole coordinate - transformation module and a negative - pole coordinate - transformation module, a positive - pole voltage - reference - value calculation module, a positive - pole current - reference - value calculation module, a positive - pole output - current prediction module, a positive - pole output - current objective - function calculation module, a negative - pole power calculation module, a negative - pole power prediction module, a negative - pole power objective - function calculation module, a positive - pole internal - circulating - current prediction module and a negative - pole internal - circulating - current prediction module, a positive - pole internal - circulating - current objective - function calculation module and a negative - pole internal - circulating - current objective - function calculation module, a positive - pole final - objective - function calculation module and a negative - pole final - objective - function calculation module, a positive - pole objective - function comparison and control - command output module and a negative - pole objective - function comparison and control - command output module;

[0008] In the positive - pole sampling module, it includes:

[0009] A positive - pole voltage - sampling module, which samples the three - phase voltage U of the MMC AC power grid gabc ;

[0010] A positive - pole current - sampling module, which samples the three - phase current I of the positive - pole MMC AC power grid gabc1 , and the internal circulating current I of the positive - pole MMC cabc1 ;

[0011] In the negative - pole sampling module, it includes:

[0012] A negative - pole voltage - sampling module, which samples the three - phase voltage U of the MMC AC power grid gabc ;

[0013] A negative - pole current - sampling module, which samples the three - phase current I of the negative - pole MMC AC power grid gabc2 , and the internal circulating current I of the negative - pole MMC cabc2 ;

[0014] The positive - pole coordinate transformation module performs Clark transformation on the three - phase current \(I\) of the positive - pole AC power grid gabc1 and the internal circulating current \(I\) of the positive - pole cabc1 to obtain the corresponding positive - pole power - grid current vector \(I\) in the two - phase stationary \(\alpha-\beta\) coordinate system gαβ1 and the internal circulating current vector \(I\) of the positive - pole cαβ1 ; performs Park transformation on the three - phase voltage \(U\) of the AC power grid gabc to obtain the corresponding power - grid voltage vector \(U\) in the synchronous rotating \(d - q\) coordinate system gdq and the amplitude of the negative - sequence component of the power - grid voltage \(U\ g- ; performs Park inverse transformation on the positive - pole current reference value \(I\) in the \(d - q\) coordinate system gdqref1 to obtain the current reference value \(I\) in the \(\alpha-\beta\) coordinate system gαβref1 , and the angles used for Park transformation and Park inverse transformation are the reference phase \(\theta\ r ;

[0015] The negative - pole coordinate transformation module performs Clark transformation on the three - phase voltage \(U\) of the MMC AC power grid gabc , the three - phase current \(I\) of the negative - pole AC power grid gabc2 , and the internal circulating current \(I\) of the negative - pole cabc2 to obtain the corresponding power - grid voltage vector \(U\) in the two - phase stationary \(\alpha-\beta\) coordinate system gαβ , the negative - pole power - grid current vector \(I\ gαβ2 and the internal circulating current vector \(I\) of the negative - pole cαβ2 ;

[0016] The positive - pole voltage reference value calculation module calculates the positive - pole voltage reference value \(U\ g- according to the amplitude of the negative - sequence component of the power - grid voltage \(U\ gdqref ;

[0017] The positive - pole current reference value calculation module controls the \(d\) - axis and \(q\) - axis components of the power - grid voltage vector \(U\ gdq through a PI controller to make them follow the \(d\) - axis and \(q\) - axis components \(U\) of the given reference value \(U\ gdqref The output of the PI controller, after passing through a limiting link, is used as the positive - pole current reference value \(I\ gdref and \(U\ gqref ; gdqref1 The positive - pole output current prediction module calculates the positive - pole power - grid current vector \(I\) of the next sampling period

[0018] according to the power - grid voltage vector \(U\) obtained in the current sampling period sαβ and the positive - pole power - grid current vector \(I\ gαβ1 when different sub - module input methods are used for the upper and lower bridge arms in the current sampling period gαβ1(next) , where there are \(N + 1\) sub - module input methods in the current sampling period and \(N + 1\) calculations of \(I\) are requiredgαβ1(next) , obtain I gαβ1(next) (m), m = 1, 2, ... N+1;

[0019] The positive electrode output current target function calculation module, according to the positive electrode predicted current value I gαβ1(next) (m) and the positive electrode current reference value I in the α-β coordinate system gαβref1 Calculate the positive electrode output current target function J 11m , m = 1, 2, ... N+1;

[0020] The negative electrode power calculation module, according to the grid voltage vector U gαβ 、the negative electrode grid current vector I gαβ2 , calculate and obtain the negative electrode active and reactive powers P g2 and Q g2 ;

[0021] The negative electrode power prediction module, according to the grid voltage vector U obtained in this sampling period sαβ , the negative electrode active and reactive powers P g2 and Q g2 , respectively calculate the negative electrode active and reactive powers P in the next sampling period when different sub-module input methods are adopted for the upper and lower bridge arms in this sampling period g2(next) and Q g2(next) , where there are N+1 sub-module input methods in this sampling period, and P needs to be calculated N+1 times g2(next) and Q g2(next) , obtain P g2(next) (m) and Q g2(next) (m), m = 1, 2, ... N+1;

[0022] The negative electrode power target function calculation module, according to the negative electrode power prediction values P g2(next) (m), Q g2(next) (m) and the negative electrode power reference values P gref2 and Q gref2 , calculate the negative electrode power target function J 21m , m = 1, 2, ... N+1;

[0023] The positive electrode internal circulating current prediction module, according to the positive electrode internal circulating current I in this sampling period cαβ1 , respectively calculate the positive electrode internal circulating current I in the next sampling period when N+1 sub-module input methods are adopted for the upper and lower bridge arms in this sampling period cαβ1(next) (m), m = 1, 2, ... N+1;

[0024] The negative electrode internal circulating current prediction module, according to the negative electrode internal circulating current I in this sampling period cαβ2, respectively calculate the negative internal circulating current I in the next sampling period when the upper and lower bridge arms adopt the N + 1 seed module input method in this sampling period cαβ2(next) (m), where m = 1, 2,... N + 1;

[0025] The positive internal circulating current objective function calculation module calculates the positive internal circulating current objective function J according to the predicted positive internal circulating current I cαβ1(next) (m) and the internal circulating current reference value, where m = 1, 2,... N + 1, and the internal circulating current reference value is given as 0; 12m

[0026] The negative internal circulating current objective function calculation module calculates the negative internal circulating current objective function J according to the predicted negative internal circulating current I cαβ2(next) (m) and the internal circulating current reference value, where m = 1, 2,... N + 1, and the internal circulating current reference value is given as 0; 22m

[0027] The positive final objective function calculation module calculates the final positive objective function J according to the positive output current objective function J 11m , the positive internal circulating current objective function J 12m and the weight factors p 11 and p 12 , and calculates the final positive objective function J according to Equation (1) 1m ;

[0028] The negative final objective function calculation module calculates the final negative objective function J according to the negative output current objective function J 21m , the negative internal circulating current objective function J 22m and the weight factors p 21 and p 22 , and calculates the final negative objective function J according to Equation (1) 2m ;

[0029] J 1m = p 11 J 11m + p 12 J 12m

[0030] J 2m = p 21 J 21m + p 22 J 22m (1)

[0031] The positive objective function comparison and control instruction output module compares the final positive objective function J of the method of inputting N + 1 seed modules 1m ​​, where \(m = 1, 2, \cdots, N + 1\), select the sub-module input method with the minimum objective function as the control instruction for this sampling period to achieve the control of the positive MMC converter;

[0032] The negative terminal objective function comparison and control instruction output module compares the final objective function \(J\) of the negative terminal using \(N + 1\) sub-module input methods 2m , where \(m = 1, 2, \cdots, N + 1\), select the sub-module input method with the minimum objective function as the control instruction for this sampling period to achieve the control of the negative MMC converter.

[0033] Furthermore: In the negative terminal power prediction module, calculate \(P\) g2(next) (m) and \(Q\) g2(next) (m) according to the following method:

[0034]

[0035] where \(L\) is the equivalent inductance including the commutation transformer and the arm reactor, \(T\) s is the sampling period, \(U\) gα and \(U\) gβ are the \(\alpha\)-axis and \(\beta\)-axis components of the voltage vector \(U\) gαβ respectively, \(|U\) g |\) is the grid voltage amplitude, \(\omega_1\) is the grid voltage angular frequency, \(U\) nα2 (m), \(U\) nβ2 (m) are the \(\alpha\)-axis and \(\beta\)-axis components of the lower arm voltage of the negative terminal using the \(m\)-th sub-module input method respectively, and the calculation method is as follows:

[0036]

[0037] where \(l\) na2 , \(l\) nb2 and \(l\) nc2 are the number of sub-modules inserted into the lower arm of the corresponding phase of the negative terminal;

[0038] \(U\) pα2 (m), \(U\) pβ2 (m) are the \(\alpha\)-axis and \(\beta\)-axis components of the upper arm voltage of the positive terminal using the \(m\)-th sub-module input method respectively, and their calculation methods are the same as the corresponding components of the lower arm.

[0039] The beneficial effects of the present invention are:

[0040] Due to the adoption of the technical solution of the present invention, when a fault occurs in the sending-end power grid of the wind farm - bipolar flexible DC system, it can significantly suppress the overvoltage of the sending-end power grid and balance the output power between the two poles in real time. After the faulty line is removed, the power grid voltage can recover smoothly and quickly. Compared with the existing methods, the power control pole of this method replaces the power and current double-loop control links in the traditional control strategy through a power prediction model and an objective function, and the control structure is simpler. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 FIG. is a typical topological diagram of an island wind farm - bipolar flexible DC transmission system.

[0042] Figure 2 FIG. is a specific example structure diagram of a single-pole MMC in a bipolar flexible DC transmission system, where, u ga , u gb , u gc are the grid voltages; i ga , i gb , i gc are the grid currents; u pa , u pb , u pc are the upper arm voltages of the MMC; u na , u nb , u nc are the lower arm voltages of the MMC; i pa , i pb , i pc are the upper arm currents of the MMC; i na , i nb , i nc are the lower arm currents of the MMC; U dc is the DC bus voltage, i dc is the DC bus current, L0 is the arm inductor, SM (N) is the sub-module in the MMC; N is the sub-module serial number.

[0043] Figure 3 FIG. is a schematic diagram of a specific example system of the control method of the present invention.

[0044] Figure 4 FIG. is a schematic diagram of the method for inserting N + 1 sub-modules in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] In order to describe the present invention more specifically, the technical solution of the present invention will be described in detail below with reference to the drawings and specific embodiments.

[0046] The system implementation of the model predictive fault ride-through method for the sending-end MMC of the wind farm - bipolar flexible DC system in the present invention is as Figure 3As shown, it includes a positive - pole voltage sampling module 1, a positive - pole current sampling module 2, a positive - pole coordinate transformation module 3, a positive - pole voltage reference value calculation module 4, a positive - pole current reference value calculation module 5, a positive - pole Park inverse transformation module 6, a positive - pole output current prediction module 7, a positive - pole output current objective function calculation module 8, a positive - pole internal circulating current prediction module 9, a positive - pole internal circulating current objective function calculation module 10, a positive - pole final objective function calculation module 11, a positive - pole objective function comparison and control instruction output module 12, a negative - pole voltage sampling module 13, a negative - pole current sampling module 14, a negative - pole coordinate transformation module 15, a negative - pole power calculation module 16, a negative - pole power prediction module 17, a negative - pole power objective function calculation module 18, a negative - pole internal circulating current prediction module 19, a negative - pole internal circulating current objective function calculation module 20, a negative - pole final objective function calculation module 21, and a negative - pole objective function comparison and control instruction output module 22.

[0047] As Figure 3 shown, the method for the sending - end MMC model - predictive fault - ride - through of a wind farm - bipolar VSC - HVDC system in the present invention includes the following steps:

[0048] Collect the three - phase voltage U of the MMC AC power grid gabc (the same for the positive and negative poles) through the positive - pole voltage sampling module 1 and the negative - pole voltage sampling module 13, and collect the three - phase current I of the positive - pole MMC AC power grid gabc1 and the three - phase current I of the negative - pole MMC AC power grid gabc2 , the internal circulating current I of the positive - pole MMC cabc1 and the internal circulating current I of the negative - pole MMC cabc2 .

[0049] Utilize the positive - pole coordinate transformation module 3 and the negative - pole coordinate transformation module 15 to perform Clark transformation on the three - phase voltage U of the MMC AC power grid gabc , the three - phase current I of the positive - pole AC power grid gabc1 and the three - phase current I of the negative - pole AC power grid gabc2 , the internal circulating current I of the positive - pole cabc1 and the internal circulating current I of the negative - pole cabc2 to obtain the corresponding grid - voltage vector U in the two - phase stationary α - β coordinate system gαβ , the positive - pole grid - current vector I gαβ1 and the negative - pole grid - current vector I gαβ2 , the positive - pole internal - circulating - current vector I cαβ1 and the negative - pole internal - circulating - current vector I cαβ2 ; perform Park transformation on the three - phase voltage U of the AC power grid gabc to obtain the corresponding grid - voltage vector U in the synchronous rotating d - q coordinate system gdq and the amplitude U of the negative - sequence component of the grid voltage g-, the angle used in the Park transformation is the reference phase θ r .

[0050] Using the positive - pole voltage reference value calculation module 4, according to the negative - sequence component amplitude U of the grid voltage g- , the positive - pole voltage reference value U gdqref in the d - axis and q - axis components U gdref and U gqref are calculated. The specific calculation method is as follows:

[0051]

[0052] where U g- is the negative - sequence voltage amplitude of the grid, U base is the base value of the grid voltage, and 1 p.u. represents a per - unit value of 1.

[0053] Using the positive - pole current reference value calculation module 5, the d - axis and q - axis components of the grid voltage vector U gdq are controlled by a PI controller to follow the given reference values U gdqref in the d - axis and q - axis components U gdref and U gqref . After passing through the limiter, the output of the controller is used as the positive - pole current reference value I gdqref1 . The specific implementation method is as follows:

[0054]

[0055] where: F PId (s) and F PIq (s) are the transfer functions of the d - axis and q - axis PI controllers respectively, k pd and k pq are the proportional coefficients of the d - axis and q - axis PI controllers respectively, k id and k iq are the integral coefficients of the d - axis and q - axis PI controllers respectively, I gdref1 , I gqref1 are the d - axis and q - axis components of I gdqref1 . The limiting value of the limiter is set to ±I lim , and I lim is 1.1 times the rated operating current under the full - power operating state of the system.

[0056] Using the positive - pole Park inverse transformation module 6, the Park inverse transformation of the positive - pole current reference value I gdqref1 in the d - q coordinate system is performed to obtain the current reference value I gαβref1 in the α - β coordinate system. The angle used in the Park inverse transformation is the reference phase θ r .

[0057] Using the positive - terminal output current prediction module 7, based on the grid voltage vector U obtained in this sampling period sαβ , the positive - terminal grid current vector I gαβ1 , calculate the positive - terminal grid current vector I of the next sampling period when different sub - module input methods are adopted for the upper and lower bridge arms in this sampling period gαβ1(next) , where there are N + 1 sub - module input methods in this sampling period, and I needs to be calculated N + 1 times gαβ1(next) , to obtain I gαβ1(next) (m), m = 1, 2,... N + 1;

[0058] The N + 1 sub - module input methods are as shown in the appendix Figure 4 .

[0059] The positive - terminal grid current vector I of the next sampling period gαβ1(next) (m) is calculated according to the following method:

[0060]

[0061] where L is the equivalent inductance including the commutation transformer and the arm reactor, T s is the sampling period, U gα and U gβ are the α - axis and β - axis components of the voltage vector U gαβ respectively, I gα1 and I gβ1 are the α - axis and β - axis components of I gαβ1 respectively, I gα1(next) (m) and I gβ1(next) (m) are the α - axis and β - axis components of I gαβ1(next) (m) respectively; U nα1 (m), U nβ1 (m) are the α - axis and β - axis components of the positive - terminal lower - bridge - arm voltage when the m - th sub - module input method is adopted, and the calculation method is as follows:

[0062]

[0063] where l na1 , l nb1 and l nc1 are the number of sub - modules input to the positive - terminal corresponding - phase lower bridge arm.

[0064] U pα1 (m), U pβ1 (m) are the α - axis and β - axis components of the positive - terminal upper - bridge - arm voltage when the m - th sub - module input method is adopted, and their calculation methods are the same as the corresponding components of the lower bridge arm.

[0065] Using the positive - terminal output current objective - function calculation module 8, according to the positive - terminal predicted current value I gαβ1(next)(m) and the reference value of the positive - electrode current I in the α - β coordinate system gαβref1 Calculate the objective function J of the positive - electrode output current 11m , m = 1, 2,... N + 1, and the specific calculation method is as follows:

[0066] J 11m =|I gαref1 -I gα1(next) (m)|+|I gβref1 -I gβ1(next) (m)|

[0067] Utilize the negative - electrode power calculation module 16, and calculate the negative - electrode active power and reactive power P gαβ and Q gαβ2 according to the grid voltage vector U g2 and the negative - electrode grid current vector I g2 , and the specific calculation method is as follows:

[0068]

[0069] Utilize the negative - electrode power prediction module 17, and calculate the negative - electrode active power and reactive power P sαβ and Q g2 in the next sampling period when different sub - module input methods are adopted for the upper and lower bridge arms in this sampling period, according to the grid voltage vector U g2 obtained in this sampling period, the negative - electrode active power and reactive power P g2(next) and Q g2(next) . Among them, there are N + 1 sub - module input methods in this sampling period, and P g2(next) and Q g2(next) need to be calculated N + 1 times to obtain P g2(next) (m) and Q g2(next) (m), m = 1, 2,... N + 1, and the specific implementation method is as follows:

[0070]

[0071] Among them, L is the equivalent inductance including the commutation transformer and the arm reactor, T s is the sampling period, U gα and U gβ are the α - axis and β - axis components of the voltage vector U gαβ respectively, |U g | is the grid voltage amplitude, ω1 is the grid voltage angular frequency, U nα2 (m), U nβ2 (m) are the α - axis and β - axis components of the negative - electrode lower - bridge - arm voltage when the m - th sub - module input method is adopted, and the calculation method is as follows:

[0072]

[0073] Among them, l na2 , l nb2 and l nc2 are the number of sub-modules put into the lower arm of the corresponding phase of the negative electrode.

[0074] U pα2 (m), U pβ2 (m) are the α-axis and β-axis components of the voltage of the upper arm of the positive electrode using the m-th sub-module input method, respectively, and their calculation methods are the same as the corresponding components of the lower arm.

[0075] Calculate module 18 using the negative power objective function. According to the predicted negative power value P g2(next) (m), Q g2(next) (m) and the negative power reference values P gref2 and Q gref2 , calculate the negative power objective function J 21m , m = 1, 2,... N + 1. The specific calculation method is as follows:

[0076] J 21m = |P gref2 - P g2(next) (m)| + |Q gref2 - Q g2(next) (m)|

[0077] Using the positive internal circulating current prediction module 9 and the negative internal circulating current prediction module 19, according to the positive internal circulating current I cαβ1 and the negative internal circulating current I cαβ2 in this sampling period, calculate the positive internal circulating current I cαβ1(next) (m) and the negative internal circulating current I cαβ2(next) (m) in the next sampling period when the upper and lower arms adopt N + 1 sub-module input methods, m = 1, 2,... N + 1;

[0078] Calculate the positive internal circulating current I cαβ1(next) (m) in the next sampling period using the following method (the calculation method of the negative internal circulating current vector I cαβ2(next) (m) is the same in principle, just replace the corresponding subscript 1 with 2):

[0079]

[0080] Among them: T s is the sampling period, L0 is the inductance of the arm reactor, I cα1 and I cβ1 are the α-axis and β-axis components of I cαβ1 respectively, I cα1(next) (m) and I cβ1(next) (m) are the α-axis and β-axis components of I cαβ1(next)The α-axis and β-axis components of (m), U dc1 is the DC bus voltage of the positive MMC.

[0081] Using the positive internal circulating current objective function calculation module 10 and the negative internal circulating current objective function calculation module 20, according to the predicted positive internal circulating current I cαβ1(next) (m) and the predicted negative internal circulating current I cαβ2(next) (m), and the internal circulating current reference value, calculate the positive internal circulating current objective function J 12m and the negative internal circulating current objective function J 22m , m = 1, 2,... N + 1; The specific calculation method is as follows:

[0082] J 12m = |I cαref1 - I cα1(next) (m)| + |I cβref1 - I cβ1(next) (m)|

[0083] J 22m = |I cαref2 - I cα2(next) (m)| + |I cβref2 - I cβ2(next) (m)|

[0084] Among them, I cαref1 and I cβref1 are the α-axis and β-axis components of the positive internal circulating current reference value I cαβref1 , I cαref2 and I cβref2 are the α-axis and β-axis components of the negative internal circulating current reference value I cαβref2 , I cαref1 , I cβref1 , I cαref2 and I cβref2 are given as 0.

[0085] Using the positive (negative) final objective function calculation module 11 (21), according to the positive (negative) output current objective function J 11m (J 21m ), the positive (negative) internal circulating current objective function J 12m (J 22m ), and the weight factors p 11 , p 12 , p 21 , p 22 , calculate the positive (negative) final objective function J 1m (J 2m ), and the calculation method is as follows:

[0086] J 1m = p 11 J11m +p 12 J 12m

[0087] J 2m = p 21 J 21m +p 22 J 22m

[0088] Compare the positive - terminal objective - function comparison and control - instruction output module 12 and the negative - terminal objective - function comparison and control - instruction output module 22 by using the positive - terminal objective function, and compare the final positive - terminal objective function J of the method of putting N + 1 seed modules into operation 1m and the final negative - terminal objective function J 2m , where m = 1, 2,... N + 1, select the method of putting the sub - module with the minimum objective function as the control instruction for this sampling period, and realize the control of the positive - terminal MMC converter and the negative - terminal MMC converter.

[0089] The above description of the embodiments is to enable those of ordinary skill in the art to understand and apply the present invention. It is obvious that those skilled in the art can easily make various modifications to the above - mentioned embodiments and apply the general principles described herein to other embodiments without creative efforts. Therefore, the present invention is not limited to the above - mentioned embodiments, and all improvements and modifications made by those skilled in the art according to the disclosure of the present invention should fall within the protection scope of the present invention.

Claims

1. A method for predicting fault ride-through of the sending - end MMC in a wind farm - bipolar flexible DC system, characterized in that, The control system adopted to implement the method includes: a positive electrode sampling module and a negative electrode sampling module, a positive electrode coordinate transformation module and a negative electrode coordinate transformation module, a positive electrode voltage reference value calculation module, a positive electrode current reference value calculation module, a positive electrode output current prediction module, a positive electrode output current objective function calculation module, a negative electrode power calculation module, a negative electrode power prediction module, a negative electrode power objective function calculation module, a positive electrode internal circulating current prediction module and a negative electrode internal circulating current prediction module, a positive electrode internal circulating current objective function calculation module and a negative electrode internal circulating current objective function calculation module, a positive electrode final objective function calculation module and a negative electrode final objective function calculation module, a positive electrode objective function comparison and control instruction output module and a negative electrode objective function comparison and control instruction output module; In the positive electrode sampling module, it includes: Positive voltage sampling module, sampling the three-phase voltages U of the MMC AC power grid gabc for sampling; The positive electrode current sampling module samples the three-phase current I of the positive electrode MMC AC power grid gabc1 and the internal circulating current I of the positive electrode MMC cabc1 for sampling; In the negative electrode sampling module, it includes: The negative electrode voltage sampling module samples the three-phase voltages U of the MMC AC power grid gabc for sampling; The negative electrode current sampling module samples the three-phase current I of the negative electrode MMC AC power grid gabc2 and the internal circulating current I of the negative electrode MMC cabc2 for sampling; The positive - pole coordinate transformation module performs Clark transformation on the three - phase current \(I\) of the positive - pole AC power grid gabc1 and the internal circulating current \(I\) of the positive - pole cabc1 to obtain the corresponding positive - pole power - grid current vector \(I\) in the two - phase stationary \(\alpha-\beta\) coordinate system gαβ1 and the internal circulating current vector \(I\) of the positive - pole cαβ1 ; performs Park transformation on the three - phase voltage \(U\) of the AC power grid gabc to obtain the corresponding power - grid voltage vector \(U\) in the synchronous rotating \(d - q\) coordinate system gdq and the amplitude \(U\) of the negative - sequence component of the power - grid voltage g- ; performs inverse Park transformation on the positive - pole current reference value \(I\) in the \(d - q\) coordinate system gdqref1 to obtain the current reference value \(I\) in the \(\alpha-\beta\) coordinate system gαβref1 , and the angles used for Park transformation and inverse Park transformation are the reference phase \(\theta\) r ; The negative - pole coordinate transformation module performs Clark transformation on the three - phase voltage U of the MMC AC power grid gabc , the three - phase current I of the negative - pole AC power grid gabc2 , the internal circulating current I of the negative - pole cabc2 to obtain the corresponding grid - voltage vector U gαβ in the two - phase stationary α - β coordinate system, the negative - pole grid - current vector I gαβ2 and the negative - pole internal - circulating - current vector I cαβ2 ; The positive electrode voltage reference value calculation module calculates the positive electrode voltage reference value U g- based on the amplitude U of the negative sequence component of the grid voltage and obtains the positive electrode voltage reference value U gdqref ; The positive electrode current reference value calculation module controls the d-axis and q-axis components of the grid voltage vector U gdq through a PI controller to make them follow the given reference values U gdqref of the d-axis and q-axis components U gdref and U gqref . After passing through a limiting link, the output of the PI controller is used as the reference value I gdqref1 of the positive electrode current; The positive electrode output current prediction module calculates, according to the grid voltage vector U obtained in the current sampling period sαβ , and the positive electrode grid current vector I gαβ1 , respectively, the positive electrode grid current vector I gαβ1(next) in the next sampling period when different sub-module input methods are adopted for the upper and lower bridge arms in the current sampling period. Among them, there are N + 1 sub-module input methods in the current sampling period, and I gαβ1(next) needs to be calculated N + 1 times to obtain I gαβ1(next) (m), where m = 1, 2,... N + 1; The positive electrode output current objective function calculation module calculates the positive electrode output current objective function J according to the predicted positive electrode current value I gαβ1(next) (m) and the positive electrode current reference value I in the α-β coordinate system gαβref1 where m = 1, 2,... N + 1; 11m ​ The negative electrode power calculation module calculates the active and reactive powers P gαβ and Q gαβ2 of the negative electrode based on the grid voltage vector U g2 and the negative electrode grid current vector I g2 ; The negative - terminal power prediction module calculates, based on the grid voltage vector U obtained in the current sampling period sαβ , the active and reactive powers P g2 and Q g2 , respectively, the active and reactive powers P g2(next) and Q g2(next) of the next sampling period when different sub - module input methods are adopted for the upper and lower bridge arms in the current sampling period. Among them, there are N + 1 sub - module input methods in the current sampling period, and P g2(next) and Q g2(next) need to be calculated N + 1 times to obtain P g2(next) (m) and Q g2(next) (m), where m = 1, 2,... N + 1; The negative electrode power target function calculation module calculates the negative electrode power target function J g2(next) (m) based on the predicted negative electrode power value P g2(next) (m), Q gref2 (m), and the negative electrode power reference values P gref2 and Q 21m , where m = 1, 2,... N + 1; The positive electrode internal circulation prediction module calculates the positive electrode internal circulation I in the next sampling period when the N+1 seed modules are put into use in the upper and lower bridge arms in this sampling period, based on the positive electrode internal circulation I in this sampling period cαβ1 respectively cαβ1(next) (m), where m = 1, 2,... N+1; The negative electrode internal circulation prediction module calculates the negative electrode internal circulation I in the next sampling period when the N+1 seed modules are put into use in the upper and lower bridge arms of the current sampling period, respectively, based on the negative electrode internal circulation I in the current sampling period cαβ2 , where I cαβ2(next) (m), m = 1, 2,... N+1 cαβ2(next) (m), m = 1, 2,... N+1; The positive electrode internal circulation objective function calculation module calculates the positive electrode internal circulation objective function J according to the predicted internal circulation I cαβ1(next) (m) of the positive electrode and the internal circulation reference value, where m = 1, 2,... N + 1, and the internal circulation reference value is given as 0; 12m ​ The negative electrode internal circulation objective function calculation module calculates the negative electrode internal circulation objective function J according to the predicted internal circulation I of the negative electrode cαβ2(next) (m) and the internal circulation reference value, where m = 1, 2,... N + 1 and the internal circulation reference value is given as 0; 22m ​ The positive electrode final objective function calculation module calculates the final objective function J of the positive electrode according to the positive electrode output current objective function J 11m , the positive electrode internal circulation objective function J 12m , and the weight factors p 11 , p 12 , and calculates the final objective function J of the positive electrode according to Equation (1) 1m ; The negative electrode final objective function calculation module calculates the final objective function J of the negative electrode according to the negative electrode output current objective function J 21m , the negative electrode internal circulation objective function J 22m , the weight factors p 21 and p 22 , and calculates the final objective function J of the negative electrode according to Equation (1) 2m ; J 1m = p 11 J 11m + p 12 J 12m J 2m = p 21 J 21m + p 22 J 22m (1) The positive electrode target function comparison and control instruction output module compares the final positive electrode target function J of the method of putting N + 1 seed modules into operation 1m , where m = 1, 2,... N + 1, and selects the sub-module input method with the smallest target function as the control instruction for this sampling period to achieve the control of the positive electrode MMC converter; The negative terminal objective function comparison and control instruction output module compares the final negative terminal objective function J of the method of putting N + 1 sub-modules into operation 2m , where m = 1, 2,... N + 1, selects the sub-module putting method with the minimum objective function as the control instruction for this sampling period, and realizes the control of the negative terminal MMC converter.

2. The method for predicting fault ride - through of the sending - end MMC in a wind farm - bipolar flexible DC system according to claim 1, characterized in that: In the negative electrode power prediction module, P g2(next) (m) and Q g2(next) (m) are calculated according to the following method: Among them, L is the equivalent inductance including the commutation transformer and the arm reactor, T s is the sampling period, U gα and U gβ are the α-axis and β-axis components of the voltage vector U gαβ respectively, |U g | is the amplitude of the grid voltage, ω1 is the angular frequency of the grid voltage, U nα2 (m), U nβ2 (m) are the α-axis and β-axis components of the voltage of the lower negative arm using the m-th sub-module input method respectively, and the calculation method is as follows: where l na2 , l nb2 and l nc2 are the number of sub-modules inserted in the lower arm of the phase corresponding to the negative electrode; U pα2 (m), U pβ2 (m) are the α-axis and β-axis components of the voltage of the upper bridge arm of the positive electrode using the m-th sub-module input method, and their calculation methods are the same as the corresponding components of the lower bridge arm.

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