Direct-current side voltage protection method for flexible direct-current traction bidirectional converter

Abstract

The invention discloses a direct-current side voltage protection method for a flexible direct-current traction bidirectional converter. The method comprises the following steps of S1, calculating equivalent reactance of the converter to a low-voltage side of a power grid; s2, establishing a multi-objective optimization model for DC side voltage protection of the bidirectional converter under traction and feedback working conditions; s3, setting variable constraint conditions in the DC side voltage protection optimization model; s4, solving a current optimal solution of a particle swarm by adopting a multi-target particle swarm optimization algorithm according to the feasible region range; and S5, transmitting the optimal particle information to form new-generation particle information, judging whether the particles converge or not, solving a Pareto optimal solution of the current system, and outputting the Pareto optimal solution. The method has good adaptability and flexibility, multi-target optimization protection of the direct current side voltage is achieved, and meanwhile the safety and reliability of the system are improved.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of bidirectional converters for flexible DC traction power supply systems, and more specifically, to a DC side voltage protection method for a flexible DC traction bidirectional converter based on a multi-objective particle swarm optimization algorithm. Background Art

[0002] Flexible DC traction power supply system has been widely used in urban rail transit due to its advantages such as high efficiency and energy saving. As the core equipment of the system, the bidirectional converter undertakes the functions of power transmission and DC voltage modulation, which is crucial to the stable operation of the system. Traditional DC traction power supply systems have problems such as difficult voltage control and slow dynamic response speed. Especially in the case of dynamic changes in load power and frequent start and stop, higher requirements are placed on the DC voltage control of the bidirectional converter. Existing technologies mostly rely on precise model parameters, and are not adaptable enough to external disturbances and changes in system internal parameters, resulting in limited effects in practical applications. Summary of the invention

[0003] In order to solve the above problems, the present invention provides a DC side voltage protection method for a flexible DC traction bidirectional converter to improve the voltage control accuracy and dynamic response speed of the system, enhance the stability and reliability of the system, and at the same time reduce the dependence on precise model parameters and improve the adaptability and robustness of the algorithm.

[0004] In order to achieve the above object, the present invention is implemented by the following technical solutions: A method for protecting the DC side voltage of a flexible DC traction bidirectional converter, the method comprising the following steps: Step S1: Calculate the equivalent reactance of the converter to the low-voltage side of the power grid; Step S2: establishing a multi-objective optimization model for DC side voltage protection of a bidirectional converter under traction and regeneration conditions; Step S3: setting variable constraints in the DC side voltage protection optimization model; Step S4: according to the variable constraints set in step S3, a multi-objective particle swarm optimization algorithm is used to solve a current set of optimal solutions of the DC side voltage protection objective function of the flexible DC traction bidirectional converter; Step S5: The optimal particle information is transmitted to form a new generation of particle information, and it is determined whether the current particle meets the convergence condition. If the convergence condition is met, the Pareto optimal solution that meets the DC side voltage protection target of the current system is solved and output; otherwise, the optimal particle information is updated to meet the convergence condition.

[0005] Furthermore, the flexible DC traction system transformer adopts a three-winding structure with a rated transformation ratio of 35:0.9, a 35kV voltage deviation of ±10%, a 35kV voltage winding connected to the grid, a 0.9kV voltage winding connected to the converter, and another 0.9kV voltage winding connected to the filter.

[0006] Furthermore, the calculation of the equivalent reactance of the converter to the low-voltage side of the power grid in step S1 specifically includes: Step S1.1: Calculate the equivalent reactance of the transformer in star connection. The relationship between the transformer self-leakage reactance and mutual leakage reactance is as follows: ; in, Z 1 is the self-leakage reactance of the grid-side winding, Z 2 is the self-leakage reactance of the converter side winding, Z 3 is the self-leakage reactance of the filter side winding, Z 12 is the mutual leakage reactance of the grid-side winding and the converter-side winding, Z 13 is the mutual leakage reactance of the grid-side winding and the filter-side winding, Z 23 is the mutual leakage reactance of the converter side winding and the filter side winding; Ignoring the influence of internal resistance, we have: ; in, X 1 is the equivalent reactance of the transformer grid side, X 2 is the equivalent reactance of the transformer converter side, X 3 is the equivalent reactance on the transformer filter side; Step S1.2: According to the transformer capacity S , Transformer winding turns ratio k , Transformer grid side voltage frequency f Equivalent reactance of transformer grid side X 1 , Transformer converter side equivalent reactance X 2 Calculate the nominal value of equivalent reactance on the grid side respectively L g And the nominal value of equivalent reactance on the converter side L l , the nominal value of equivalent reactance on the grid side L g Calculated by the following formula: ; Nominal value of equivalent reactance on the converter side L l Calculated by the following formula: ; According to the valve group AC reactance L ac And the number of valve groups H The equivalent reactance of the valve group is calculated by the following formula: L f : ; According to the system impedance L sr The equivalent reactance of the system is calculated by the following formula: L s : ; Equivalent reactance of converter to low voltage side of power grid L Calculated according to the following formula: .

[0007] Furthermore, the multi-objective optimization model of the DC side voltage protection of the bidirectional converter under traction and regeneration conditions in step S2 includes three objective functions: the relationship between the DC voltage and the total output power under traction and regeneration conditions, the fault debouncing time of the control and protection device, and the power supply reliability, which are specifically as follows: The relationship between the DC side voltage and the total output power under traction and feedback conditions is the first objective function F 1 , the minimum value of DC side voltage protection is obtained V dcmin : ; Where: m The SPWM modulation ratio for valve group control, V min Indicates the minimum voltage on the inverter AC side. E Indicates the low voltage side voltage of the transformer converter winding. V L Indicates the voltage across the valve group AC reactor. is the angular frequency of the low voltage side winding of the transformer converter side, I Indicates the inverter AC side current, P Indicates the total output power; The fault elimination time of the control and protection device is the second objective function F 2 , calculate the maximum value of various error fault signals, and obtain the minimum time T for fault elimination of the control and protection device kbmin , the second objective function F2 As shown in the following formula: ; Where: q To control the number of elements that affect the program fault debounce time, T 1 ~ T q They are the specific delay time of each influencing element; Power supply reliability is the third objective function F 3 , it is necessary to calculate the probability of erroneous action of the control and protection device and reduce it to the minimum: ; Where: Indicates the number of valve group locks caused by erroneous action of the control and protection device. It represents the probability of failure or malfunction of the control and protection device, and n represents the number of converters installed in the station.

[0008] Furthermore, the variable constraints in the DC side voltage protection optimization model in step S3 specifically include: Constraint 1: DC side voltage V dc The upper and lower limit constraints; ; Where: and Indicates the minimum and maximum values ​​of DC voltage setting; Constraint 2: Fault debounce time of the control and protection program T kb Constraints of ; Where: Indicates the voltage transmitter response time; Indicates the total length of the optical fiber. is the propagation speed of light, take 3×10 8 m / s.

[0009] Furthermore, the specific process of solving the current set of optimal solutions of the DC side voltage protection objective function of the flexible DC traction bidirectional converter in step S4 includes: Step S4.1: Initialize the particles in the particle swarm in the feasible domain of the system, assuming It is a particle The current position of the particle is determined so that it can traverse the entire solution domain as much as possible and give each particle a different initial velocity. Assume It is a particle Current flight speed; Step S4.2: Calculate the particle's best historical position and global best position and , the evolution equation based on particle swarm optimization algorithm is as follows: ; ; Where: represents iterative algebra, represents the dimension of the particle, Represents particles The best location in history, is the optimal position searched by the current particle swarm, also known as the global best position. For personal cognitive learning factors, is the social learning factor, and Usually the value is between 0 and 2. and are two independent random numbers on [0,1], so that particles can make corresponding changes every time they evolve.

[0010] Further, the specific process of step S5 includes: Step S5.1: transmit the position information of the optimal particle to other particles so that they can learn from and get closer to the optimal particle; Step S5.2: After the particles are updated, a new generation of and ; Step S5.3: Determine whether the particle meets the termination condition: whether the number of iterations is reached and whether the constraints are met. When the termination condition is met, solve the Pareto optimal solution of the current system and output it, otherwise return to step S4 to re-update the position and velocity of the particle and calculate accordingly.

[0011] Compared with the prior art, the beneficial effects of the present invention are: The multi-objective particle swarm optimization algorithm in the present invention is proposed to improve the control strategy of the bidirectional converter because of its effectiveness in dealing with complex optimization problems. By establishing a multi-objective optimization model including voltage-power relationship, fault debounce time and power supply reliability, the system operation state is optimized in an all-round way. The algorithm traverses the entire solution domain, which can effectively prevent the search process from converging to the local optimum. It has no requirements for the objective function and has a wide range of applications. By introducing the dual guidance mechanism of individual optimum and group optimum, the optimization process has both directionality and purposefulness, and selectively develops in a better direction according to the set evolutionary parameters, rather than blindly exhaustively or completely randomly searching, which greatly saves the calculation time and the number of operations. The calculation speed can be improved through large-scale parallel computing, the convergence speed is fast, the setting parameters are few, the convergence speed is fast, and it has strong robustness. The DC side voltage protection method of the flexible DC traction system provided by the present invention has good adaptability and flexibility, realizes multi-objective optimization protection of the DC side voltage, and improves the safety and reliability of the system. After appropriate adjustment, it can be extended to multiple fields such as new energy power generation and smart grid, showing a good prospect for promotion and application. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a specific flow chart of the method of the present invention; Figure 2 This is a schematic diagram of the structure of a winding transformer according to the third embodiment of the present invention; Figure 3 This is a third winding transformer impedance circuit diagram of the present invention; Figure 4 This is a main circuit diagram of the flexible DC traction power supply system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0013] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to be able to fully convey the scope of the present invention to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0014] The present invention proposes an embodiment of a DC side voltage protection method for a flexible DC traction bidirectional converter, the process is as follows: Figure 1As shown in the figure, the flexible DC traction system transformer adopts a three-winding structure with a rated transformation ratio of 35:0.9, a 35kV voltage deviation of ±10%, a 35kV voltage winding connected to the grid, a 0.9kV voltage winding connected to the converter, and another 0.9kV voltage winding connected to the filter. The three-winding transformer structure is as follows Figure 2 shown.

[0015] The specific steps include: Step S1: Calculate the equivalent reactance of the converter to the low-voltage side of the power grid. The specific process is as follows: Step S1.1: Calculate the equivalent reactance of the transformer in star connection. The relationship between the transformer self-leakage reactance and mutual leakage reactance is as follows: ;

[0016] in, Z 1 is the self-leakage reactance of the grid-side winding, Z 2 is the self-leakage reactance of the converter side winding, Z 3 is the self-leakage reactance of the filter side winding, Z 12 is the mutual leakage reactance of the grid-side winding and the converter-side winding, Z 13 is the mutual leakage reactance of the grid-side winding and the filter-side winding, Z 23 is the mutual leakage reactance of the converter side winding and the filter side winding.

[0017] Ignoring the influence of internal resistance, we have: ; in, X 1 is the equivalent reactance of the transformer grid side, X 2 is the equivalent reactance of the transformer converter side, X 3 is the equivalent reactance on the transformer filter side, and the impedance circuit of the three-winding transformer is as follows: Figure 3 shown.

[0018] Step S1.2: Figure 4 From the main circuit diagram of the flexible DC traction power supply system, it can be seen that the equivalent reactance of the converter to the low-voltage side of the grid is the sum of the 1# equivalent reactance on the grid side of the transformer, the 2# equivalent reactance on the converter side of the transformer, the equivalent reactance of the valve group and the equivalent reactance of the system. S , Transformer winding turns ratio k , Transformer grid side voltage frequency f Equivalent reactance of transformer grid side X 1 , Transformer converter side equivalent reactanceX 2 Calculate the nominal value of equivalent reactance on the grid side respectively L g And the nominal value of equivalent reactance on the converter side L l , the nominal value of equivalent reactance on the grid side L g Calculated by the following formula: ; In the formula, V 1 Indicates the transformer grid side voltage, I e is the per unit current of the transformer grid side, R b is the per unit value of the equivalent resistance on the grid side of the transformer, Z 1b is the per unit value of the equivalent impedance on the grid side of the transformer, L 1h is the per unit value of equivalent reactance on the grid side of the transformer; The equivalent reactance value of the grid side is obtained L g for: ; Nominal value of equivalent reactance on the converter side L l Calculated by the following formula: ; In the formula, Z 2b is the per unit value of the equivalent impedance on the transformer converter side, L 2h is the per unit value of equivalent reactance on the converter side; The nominal value of equivalent reactance on the converter side is obtained L l for: ; According to the valve group AC reactance L ac And the number of valve groups H The equivalent reactance of the valve group is calculated by the following formula: L f : ; According to the system impedance L sr The equivalent reactance of the system is calculated by the following formula: L s : ; Equivalent reactance of converter to low voltage side of power gridL Calculated according to the following formula: .

[0019] Step S2: Establish a multi-objective optimization model for DC side voltage protection of bidirectional converter under traction and regeneration conditions, including the following contents: The relationship between the DC side voltage and the total output power under traction and feedback conditions is the first objective function F 1 , according to the valve group AC reactance L ac and inverter AC side current I The voltage across the valve group AC reactance can be obtained V L : ; in is the transformer converter side winding angular frequency, P is the total output power, V 2 is the voltage on the transformer converter side; According to the positive and negative resistance characteristics, the minimum voltage on the AC side of the valve group can be obtained. V min : ; According to the voltage relationship between the AC and DC sides of the ANPC topology inverter, the minimum DC side voltage of the valve group can be obtained: V dcmin , that is, the first objective function F1: ; in m Control SPWM modulation ratio for valve group; The fault elimination time of the control and protection device is the second objective function F 2 During the operation of the system, various force majeure factors may generate shorter error fault signals (such as electromagnetic interference, error signals from the hardware circuit itself, error signals caused by software logic, etc.), which will affect the judgment of the actual fault state by the control and protection device. It is necessary to calculate the maximum value of various error fault signals and obtain the minimum time for the control and protection device to eliminate fault jitter. T kbmin , that is, the second objective function F 2 : ; Where: q To control the number of elements that affect the program fault debounce time, T 1 ~ Tq They are the specific delay time of each influencing element; Power supply reliability is the third objective function F 3 , it is known that n sets of power supply devices are set in a subway station, one control and protection device controls one power supply system, and H valve group modules are set in one power supply system. When the control and protection device issues an error protection command, multiple valve group modules may be locked at the same time, causing a large amount of power loss. Therefore, it is necessary to calculate the probability of error events and minimize them: ; Where: Indicates the number of converter lockouts caused by erroneous operation of the control and protection device. It represents the probability of failure or malfunction of the control and protection device, and n represents the number of converters installed in the station.

[0020] Step S3: setting the variable constraints in the DC side voltage protection optimization model, as follows: Constraint 1: Upper and lower limits of DC voltage: ; Where: and Indicates the minimum and maximum values ​​of the DC voltage setting. Generally, the DC voltage setting value of the flexible DC traction power supply system is 1300-1800V.

[0021] Constraint 2: Fault debounce time of the control and protection program T kb The upper and lower limit constraints are: ; Where: Indicates the voltage transmitter response time, generally less than 400ms; Indicates the total length of the optical fiber. is the propagation speed of light, take 3×10 8 m / s.

[0022] Step S4: According to the variable constraints set in step S3, a multi-objective particle swarm optimization algorithm is used to solve the current set of optimal solutions of the DC side voltage protection objective function of the flexible DC traction bidirectional converter, including the following steps: S4.1 Initialize the particles in the particle swarm in the feasible domain of the system, assuming It is a particle The current position of the particle is determined so that it can traverse the entire solution domain as much as possible and give each particle a different initial velocity. Assume It is a particle Current flight speed; S4.2 Calculate the best historical position and global best position of the particle and , the evolution equation based on particle swarm optimization algorithm is as follows: ; ; Where: represents iterative algebra, represents the dimension of the particle, Represents particles The best location in history, is the optimal position searched by the current particle swarm, also known as the global best position. For personal cognitive learning factors, is the social learning factor, and Usually the value is between 0 and 2. and are two independent random numbers on [0,1], so that particles can make corresponding changes every time they evolve.

[0023] Step S5: The optimal particle information is transmitted to form a new generation of particle information, and it is determined whether the current particle meets the convergence condition. If the convergence condition is met, the Pareto optimal solution that meets the DC side voltage protection target of the current system is solved and output; otherwise, the optimal particle information is updated to meet the convergence condition, including the following steps: S5.1 transmits the position information of the optimal particle to other particles, so that they can learn from the optimal particle and get closer to it; S5.2 After the particles are updated, a new generation of and ; S5.3 determines whether the particle meets the termination conditions: whether the number of iterations has been reached and whether the constraints are met. When the termination conditions are met, the Pareto optimal solution of the current system is solved and output, otherwise return to step S4 to re-update the position and speed of the particle and calculate accordingly.

[0024] In general, the DC side voltage protection method of a flexible DC traction bidirectional converter based on a multi-objective particle swarm optimization algorithm provided by the present invention improves the voltage control accuracy and dynamic response speed of the system, enhances the stability and reliability of the system, and reduces the dependence on precise model parameters, thereby improving the adaptability and robustness of the algorithm.

[0025] The present invention has been described in detail above through embodiments, but the contents described are only exemplary embodiments of the present invention and cannot be considered to limit the scope of implementation of the present invention. The protection scope of the present invention is defined by the claims. Anyone who utilizes the technical solution described in the present invention, or a technician in the field, inspired by the technical solution of the present invention, designs a similar technical solution within the essence and protection scope of the present invention to achieve the above technical effects, or makes equal changes and improvements to the scope of application, shall still belong to the scope of protection covered by the patent of the present invention. It should be noted that in order to make a clear statement, the description of some components and processes that have no direct and obvious connection with the scope of protection of the present invention but are known to those skilled in the art are omitted in the description of the present invention.

Claims

1. A method for protecting the DC side voltage of a flexible DC traction bidirectional converter, characterized in that: The method comprises the following steps: Step S1: Calculate the equivalent reactance of the converter to the low-voltage side of the power grid; Step S2: establishing a multi-objective optimization model for DC side voltage protection of a bidirectional converter under traction and regeneration conditions; Step S3: setting variable constraints in the DC side voltage protection optimization model; Step S4: according to the variable constraints set in step S3, a multi-objective particle swarm optimization algorithm is used to solve a current set of optimal solutions of the DC side voltage protection objective function of the flexible DC traction bidirectional converter; Step S5: The optimal particle information is transmitted to form a new generation of particle information, and it is determined whether the current particle meets the convergence condition. If the convergence condition is met, the Pareto optimal solution that meets the DC side voltage protection target of the current system is solved and output; otherwise, the optimal particle information is updated to meet the convergence condition.

2. The method according to claim 1, characterized in that The transformer of the flexible DC traction system adopts a three-winding structure with a rated transformation ratio of 35:0.9 and a 35kV voltage deviation of ±10%. The 35kV voltage winding is connected to the grid, the 0.9kV voltage winding is connected to the converter, and the other 0.9kV voltage winding is connected to the filter.

3. The method according to claim 2, characterized in that The calculation of the equivalent reactance of the converter to the low-voltage side of the power grid in step S1 specifically includes: Step S1.1: Calculate the equivalent reactance of the transformer in star connection. The relationship between the transformer self-leakage reactance and mutual leakage reactance is as follows: ； in, Z 1 is the self-leakage reactance of the grid-side winding, Z 2 is the self-leakage reactance of the converter side winding, Z 3 is the self-leakage reactance of the filter side winding, Z 12 is the mutual leakage reactance of the grid-side winding and the converter-side winding, Z 13 is the mutual leakage reactance of the grid-side winding and the filter-side winding, Z 23 is the mutual leakage reactance of the converter side winding and the filter side winding; Ignoring the influence of internal resistance, we have: ； in, X 1 is the equivalent reactance of the transformer grid side, X 2 is the equivalent reactance of the transformer converter side, X 3 is the equivalent reactance on the transformer filter side; Step S1.2: According to the transformer capacity S , Transformer winding turns ratio k , Transformer grid side voltage frequency f Equivalent reactance of transformer grid side X 1 , Transformer converter side equivalent reactance X 2 Calculate the nominal value of equivalent reactance on the grid side respectively L g And the nominal value of equivalent reactance on the converter side L l , the nominal value of equivalent reactance on the grid side L g Calculated by the following formula: ； Nominal value of equivalent reactance on the converter side L l Calculated by the following formula: ； According to the valve group AC reactance L ac And the number of valve groups H The equivalent reactance of the valve group is calculated by the following formula: L f : ； According to the system impedance L sr The equivalent reactance of the system is calculated by the following formula: L s : ； Equivalent reactance of converter to low voltage side of power grid L Calculated according to the following formula: 。 4. The method according to claim 3, characterized in that The multi-objective optimization model of the DC side voltage protection of the bidirectional converter under traction and regeneration conditions in step S2 includes three objective functions: the relationship between the DC voltage and the total output power under traction and regeneration conditions, the fault debounce time of the control and protection device, and the power supply reliability. Specifically, it is as follows: The relationship between the DC side voltage and the total output power under traction and feedback conditions is the first objective function F 1 , the minimum value of DC side voltage protection is obtained V dcmin : ； Where: m The SPWM modulation ratio for valve group control, V min Indicates the minimum voltage on the inverter AC side. E Indicates the low voltage side voltage of the transformer converter winding. V L Indicates the voltage across the valve group AC reactor. is the angular frequency of the low voltage side winding of the transformer converter side, I Indicates the inverter AC side current, P Indicates the total output power; The fault elimination time of the control and protection device is the second objective function F 2 , calculate the maximum value of various error fault signals, and obtain the minimum time for fault elimination of the control and protection device T kbmin , the second objective function F 2 As shown in the following formula: ； Where: q is the number of elements that affect the fault debounce time of the control and protection program, T 1 ~ T q They are the specific delay time of each influencing element; Power supply reliability is the third objective function F 3 , it is necessary to calculate the probability of erroneous action of the control and protection device and reduce it to the minimum: ； Where: Indicates the number of converter lockouts caused by erroneous operation of the control and protection device. It represents the probability of failure or malfunction of the control and protection device, and n represents the number of converters installed in the station.

5. The method according to claim 4, characterized in that The variable constraints in the DC side voltage protection optimization model in step S3 specifically include: Constraint 1: DC side voltage V dc The upper and lower limit constraints; ； Where: and Indicates the minimum and maximum values ​​of DC voltage setting; Constraint 2: Fault debounce time of the control and protection program T kb Constraints of ； Where: Indicates the voltage transmitter response time; Indicates the total length of the optical fiber. is the propagation speed of light, take 3×10 8 m / s.

6. The method according to claim 1, characterized in that The specific process of solving the current set of optimal solutions of the DC side voltage protection objective function of the flexible DC traction bidirectional converter in step S4 includes: Step S4.1: Initialize the particles in the particle swarm in the feasible domain of the system, assuming It is a particle The current position of the particle is determined so that it can traverse the entire solution domain as much as possible and give each particle a different initial velocity. Assume It is a particle Current flight speed; Step S4.2: Calculate the particle's best historical position and global best position and , the evolution equation based on particle swarm optimization algorithm is as follows: ； ； Where: represents iterative algebra, represents the dimension of the particle, Represents particles The best location in history, is the optimal position searched by the current particle swarm, also known as the global best position. For personal cognitive learning factors, is the social learning factor, and Usually the value is between 0 and 2. and are two independent random numbers on [0,1], so that particles can make corresponding changes every time they evolve.

7. The method according to claim 6, characterized in that The specific process of step S5 includes: Step S5.1: transmit the position information of the optimal particle to other particles so that they can learn from and get closer to the optimal particle; Step S5.2: After the particles are updated, a new generation of and ; Step S5.3: Determine whether the particle meets the termination condition: whether the number of iterations is reached and whether the constraints are met. When the termination condition is met, solve the Pareto optimal solution of the current system and output it, otherwise return to step S4 to re-update the position and velocity of the particle and calculate accordingly.

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