Method for calculating reliability of hybrid converter station

Abstract

The invention provides a hybrid converter station reliability calculation method, and the method comprises the steps: determining a first probability model based on a hybrid multi-level converter, and the first probability model is a probability model of the hybrid multi-level converter in each capacity state; based on the power grid commutation converter, a second probability model is determined, and the second probability model is a probability model of the first power grid commutation converter in each capacity state; based on the first probability model and the second probability model, constructing a hybrid converter station reliability evaluation model; and solving the reliability evaluation model of the hybrid converter station, and determining the reliability of the hybrid converter station. According to the method provided by the invention, the accuracy of reliability evaluation of the converter station is remarkably improved, the calculation complexity in engineering application is simplified, and more comprehensive and reliable technical support is provided for actual engineering.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electronic equipment, and in particular to a hybrid converter station reliability calculation method. BACKGROUND

[0002] To promote the green transformation of energy structure, it is necessary to accelerate the construction of large-scale wind and photovoltaic bases in "sand and desert" areas. These areas have abundant new energy resources, but energy loss in long-distance power transmission and resource cross-regional scheduling difficulties seriously restrict the large-scale development and utilization of new energy. To solve the above problems, it is urgent to develop extra-high voltage and large-capacity long-distance DC power transmission technology. Among them, the line commutated converter (LCC) and modular multilevel converter (MMC) are the main technical solutions.

[0003] As an important part of modern power systems, the operation stability and safety of hybrid converter stations directly affect power transmission. To ensure long-term operation of the system, it is necessary to ensure the performance of the converter station under different fault modes and operating conditions, making the reliability evaluation of the hybrid converter station one of the key problems. Since LCC and MMC have different characteristics in terms of technical performance and reliability, the applicable scenarios are significantly different. When evaluating the overall reliability level of the hybrid converter station, the interaction between LCC and MMC during operation needs to be considered. By quantitatively analyzing the operating characteristics of both, a reliability evaluation model that considers factors such as redundancy configuration and commutation failure is established to accurately evaluate the reliability of the converter station. For LCC reliability research, existing research mainly uses analytical methods, including probability distribution method and frequency and duration (FD) method based on Markov process, but none of them fully considers the commutation failure scenario. In addition, some research introduces a virtual device of commutation failure (VDoCF) model to quantify the impact of the first commutation failure, but does not consider subsequent commutation failures. MMC is composed of a series of sub-modules, and there is a complex interactive coupling influence between sub-modules. Analytical methods are difficult to effectively handle, and related evaluation methods mainly use Monte Carlo simulation. Under the Monte Carlo simulation framework, existing research has proposed reliability calculation methods from the perspective of classical probability, distribution function, etc., but such analytical methods only consider a single sub-module, which is not applicable to scenarios with mixed sub-modules. In research focusing on mixed sub-modules, correlation functions are used to handle the correlation between sub-modules, and the reliability of mixed MMC with and without redundancy configuration is calculated. However, the selection of functions is not based on sufficient evidence, and the replaceability between different types of sub-modules is not considered. SUMMARY

[0004] In order to overcome the above technical defects, the application provides a hybrid converter station reliability calculation method. In order to achieve the above purpose, the application is implemented according to the following technical scheme: The application provides a hybrid converter station reliability calculation method, the hybrid converter station includes a first subsystem and a second subsystem, the first subsystem is a hybrid multi-level converter, and the second subsystem is a grid commutation converter, which comprises: Based on the hybrid multi-level converter, a first probability model is determined, the first probability model is a probability model under each capacity state of the hybrid multi-level converter; Based on the grid commutation converter, a second probability model is determined, the second probability model is a probability model under each capacity state of the grid commutation converter; Based on the first probability model and the second probability model, a hybrid converter station reliability evaluation model is constructed; Solving the hybrid converter station reliability evaluation model determines the reliability of the hybrid converter station.

[0005] Optionally, the first probability model is determined based on the hybrid multi-level converter, which comprises: Based on the hybrid multi-level converter, an optimal Copula function is determined, the optimal Copula function is used to represent the coupling relationship between the submodules of the hybrid multi-level converter; The first probability model is determined based on the optimal Copula function.

[0006] Optionally, the optimal Copula function is determined based on the hybrid multi-level converter, which comprises: Based on the hybrid multi-level converter, a first number of Copula correlation functions is selected; The first number of Copula correlation functions are combined to obtain the optimal Copula function.

[0007] Optionally, the first probability model is determined based on the optimal Copula function, which comprises: Based on the optimal Copula function, a hybrid multi-level converter reliability evaluation model is constructed; Based on the hybrid multi-level converter reliability evaluation model, the first probability model is determined.

[0008] Optionally, the hybrid multi-level converter reliability evaluation model is constructed based on the optimal Copula function, which comprises: determine, based on the optimal Copula function, a first reliability model of the hybrid multi-level converter when considering all sub-module correlations in a first case where the half-bridge sub-modules and the full-bridge sub-modules in the hybrid multi-level converter do not need to replace each other; determine, based on the optimal Copula function, a second reliability model of the hybrid multi-level converter when considering all sub-module correlations in a second case where the half-bridge sub-modules and the full-bridge sub-modules in the hybrid multi-level converter need to replace each other; construct a reliability model of the hybrid multi-level converter based on the first reliability model and the second reliability model.

[0009] Optionally, the determining the first probability model based on the reliability evaluation model of the hybrid multi-level converter comprises: determine, based on the reliability evaluation model of the hybrid multi-level converter, a first failure rate of the hybrid multi-level converter, the first failure rate being a failure rate of a single sub-module of the hybrid multi-level converter after considering the coupling and replaceability between the sub-modules; construct a first state transition graph of the hybrid multi-level converter based on the first failure rate; determine, based on the first state transition graph, a first state transition matrix of the hybrid multi-level converter; determine the first probability model based on the first state transition matrix.

[0010] Optionally, the determining the second probability model based on the grid commutation converter comprises: construct a reliability evaluation model of the grid commutation converter based on the grid commutation converter; determine the second probability model based on the reliability evaluation model of the grid commutation converter.

[0011] Optionally, the reliability evaluation model of the grid commutation converter is one of: a rectifier side reliability evaluation model of the grid commutation converter or an inverter side reliability evaluation model of the grid commutation converter; the constructing the reliability evaluation model of the grid commutation converter based on the grid commutation converter comprises: constructing an inverter side reliability evaluation model of the grid commutation converter based on the grid commutation converter; the constructing the inverter side reliability evaluation model of the grid commutation converter based on the grid commutation converter comprises: constructing a commutation failure probability calculation model; constructing the inverter side reliability evaluation model of the grid commutation converter based on the grid commutation converter and the commutation failure probability calculation model.

[0012] Optionally, the construction process of the commutation failure probability calculation model is as follows: Obtain different fault modes comprehensively covering commutation failure; Based on the different fault modes, determine a first influence factor affecting the first commutation failure and a second influence factor affecting the subsequent commutation failure; Based on the first influence factor and the second influence factor, establish a sample space of the commutation process; Based on the sample space, determine the turn-off angle under different influence mechanisms; Based on the turn-off angle under different influence mechanisms, construct a commutation failure probability calculation model.

[0013] Optionally, the second probability model is determined based on the grid commutation converter reliability evaluation model, comprising: Based on the grid commutation converter reliability evaluation model, determine the second failure rate and the failure repair time of the grid commutation converter, the second failure rate being the failure rate of the grid commutation converter; Based on the second failure rate and the failure repair time, construct a second state transition graph of the grid commutation converter; Based on the second state transition graph, determine a second state transition matrix of the grid commutation converter; Based on the second state transition matrix, determine the second probability model.

[0014] The present application has the following beneficial effects: The method provided by the present application not only significantly improves the accuracy of the reliability evaluation of the converter station, but also simplifies the calculation complexity in engineering application, and provides more comprehensive and reliable technical support for actual engineering.

[0015] In addition to the purposes, features and advantages described above, the present application has other purposes, features and advantages. The present application will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings, which form a part of the present application, are intended to provide further understanding of the present application, and the illustrative embodiments of the present application and their description serve the purpose of explaining the present application. The accompanying drawings should not be construed as an inappropriate limitation on the present application. In the accompanying drawings: Figure 1 is a flowchart of a hybrid converter station reliability calculation method provided by an embodiment of the present application; Figure 2 is a main circuit topology diagram of a hybrid converter station provided by an embodiment of the present application; Figure 3 is a main circuit schematic diagram of a hybrid multi-level converter provided by an embodiment of the present application; Fig. 4(a) is a structural schematic diagram of a rectifier side of a line commutated converter provided in an embodiment of the present application, and Fig. 4(b) is a structural schematic diagram of a rectifier side of a line commutated converter provided in an embodiment of the present application; Figure 5 is a first state transition diagram of a hybrid multi-level converter provided in an embodiment of the present application; Figure 6 is a second state transition diagram of a line commutated converter provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The embodiments of the present application are described in detail below with reference to the accompanying drawings, but the present application can be implemented in various different ways as limited and covered by the claims.

[0018] Therefore, in order to solve the above problems, as shown in the present application, a hybrid converter station reliability calculation method is proposed, which is mainly applied to a hybrid converter station as shown in the present application. Figure 1 The hybrid converter station includes a first subsystem 1 and a second subsystem 2, and the probability of different operating states of the calculation subsystem is calculated to achieve mathematical equivalence, so that the hybrid converter station composed of different types of converter stations such as LCC and MMC can be analyzed for overall reliability through mathematical formulas. Figure 2 The hybrid converter station is briefly introduced here:

[0019] The first subsystem 1 is a hybrid multi-level converter (MMC), in order to more comprehensively analyze the interaction between submodules, the hybrid multi-level converter as shown in the present application is selected, which is composed of half-bridge submodules (HBSM) and full-bridge submodules (FBSM). Figure 3 The second subsystem 2 is a line commutated converter (LCC), the line commutated converter selected by the present application is distinguished according to the commutation direction, which can only be a line commutated converter rectifier side as shown in Fig. 4(a), or a line commutated converter inverter side as shown in Fig. 4(b), the difference between the line commutated converter inverter side and the line commutated converter rectifier side is that the line commutated converter inverter side has multiple series commutation failure simulation modules.

[0020] In combination with Figs. 3, 4(a) and 4(b), the hybrid converter station reliability calculation method as shown in the present application is described in detail as follows:

[0021] In combination with Figs. 3, 4(a) and 4(b), the hybrid converter station reliability calculation method as shown in the present application is described in detail as follows: Figure 3 Figure 1 ​​​Step S101: determining a first probability model based on the hybrid multi-level converter, the first probability model being a probability model in each capacity state of the hybrid multi-level converter; Since a single function has limitations in fitting when describing complex relationships, in order to more accurately describe the complex interactive coupling influence characteristics between the submodules of the hybrid multi-level converter, the first quantity Copula correlation function under the Archimedean Copula function family is selected, for example, N Gumbel, Clayton, Frank functions are used as analysis tools, the first quantity Copula correlation function is mixed with weights in a mathematical form, then the first quantity Copula correlation functions are combined, and then the optimal Copula function is obtained, and the optimal Copula function is used to represent the coupling relationship between the submodules of the hybrid multi-level converter. The process of determining the optimal Copula function is as follows: Firstly, the maximum likelihood method is used to estimate the correlation coefficient of each Copula function θ .

[0022] (1) In the formula, C represents a certain Copula function; n is the number of data groups; N is the number of submodules to be analyzed; F is a life distribution function, and argmax represents finding the value of that makes the log-likelihood function take the maximum value. θ For example, if 100 groups of cumulative distribution function data of 200 submodules are analyzed, then n=100, N =200).

[0023] Secondly, the weight coefficient of each copula function constituting the optimal copula function is calculated a i Each copula function generally includes an empirical copula function and a theoretical copula function, and the formula of the empirical copula function is: (2) In the formula, I (•) is an indicator function; is the rank statistic of the life sample T 1,…, T N .

[0024] The Euclidean distance between the theoretical Copula function and the empirical Copula function is: (3) Further select the Euclidean distance between the theoretical Copula function and the empirical Copula function As the weight coefficient of Copula.

[0025] Further, the combination of a plurality of Copula functions is obtained to express the optimal Copula function of the mixed MMC reliability, so as to represent the mutual relationship between the selected sub-modules: (4) Wherein, the subscript To distinguish different kinds of Copula functions, and have: (5) Therefore, combined with the N dimension Gumbel, Clayton, Frank function form, the optimal Copula function form is: (6) Wherein, p The number of F ( T ) is equal to The weight of Gumbel, Clayton, Frank function respectively; N The number of sub-modules to be analyzed, that is, the number of distribution functions F .

[0026] After obtaining the above optimal Copula function, the reliability evaluation model of the hybrid multi-level converter can be constructed according to the optimal Copula function, and then the first probability model is determined according to the reliability evaluation model of the hybrid multi-level converter. The process of constructing the reliability evaluation model of the hybrid multi-level converter is as follows: In order to ensure the reliability of the hybrid multi-level converter, in actual engineering, redundant sub-modules are generally configured for the sub-modules of the MMC, so that when the initial configuration sub-module fails, the redundant sub-module can be put into operation to replace the failed sub-module, and the normal operation of the hybrid multi-level converter is ensured. The failure of full-bridge sub-module FBSM and half-bridge sub-module HBSM will cause the failure of MMC, only when the normal operation of FBSM and HBSM is N F、 N H , can the MMC operate normally; and the FBSM redundant sub-module with fault current breaking capacity can replace the damaged HBSM.

[0027] Regarding Figure 3The reliability of hybrid MMC with both FBSM and HBSM is modeled, which is more complex than single MMC with only one type of sub-module because of the different sub-module replacement scenarios during fault. The reliability analysis model is established for each working mode.

[0028] Firstly, the first reliability model of hybrid MMC is determined according to the optimal Copula function, which considers the correlation between all sub-modules in the first case, i.e., the half-bridge sub-modules and full-bridge sub-modules in the hybrid MMC do not need to replace each other. The specific process is as follows: When the half-bridge sub-modules and full-bridge sub-modules do not need to replace each other, the reliability distribution function of each bridge arm configuration is N H + N 0H where n is the number of half-bridge sub-modules, N H is the number of normal half-bridge sub-modules, N 0H is the number of redundant half-bridge sub-modules. Let the number of sub-modules currently in normal working state be j , the sub-module life samples are arranged according to the working state, the normal sub-modules are , and the faulty sub-modules are . The reliability distribution function of half-bridge sub-modules is (7) There is a -dimensional Copula such that the joint distribution is (8) In equation (8), p is the number of F ( T ).

[0029] According to the Sklar theorem, equation (7) is expressed as a Copula function composed of two joint distribution functions, and the following equation is obtained: (9) where , , M is the number of Monte Carlo sampling times. is a N -dimensional hybrid copula function, and its expansion form is shown in equation (6).

[0030] The specific derivation of equation (9) is as follows: (10) "expressed as a Copula function composed of two joint distribution functions" refers to the two functions (min, max) in P subtracted in the second step can also be written as a Copula function.

[0031] Since the reliability distribution function of the aforementioned half-bridge sub-module is the same as the reliability reasoning process of the full-bridge sub-module when it is normal, there is also a dimension Copula , so that the joint distribution is: (11) According to the Sklar theorem, formula (11) is expressed as a Copula function composed of two joint distribution functions, and the reliability of the bridge arm of the full-bridge sub-module is obtained: (12) Therefore, the first reliability model of the hybrid multi-level converter considering the correlation of all sub-modules in the first case is as follows: (13) In the formula, is the first reliability model.

[0032] Secondly, according to the optimal Copula function, the second reliability model of the hybrid multi-level converter considering the correlation of all sub-modules in the second case is determined, and the second case is that the half-bridge sub-module and the full-bridge sub-module in the hybrid multi-level converter need to replace each other. The specific process is as follows: When FBSM and HBSM need to replace each other, that is, when the number of half-bridge redundant modules is insufficient to replace all faulty half-bridge sub-modules, the remaining redundant full-bridge modules need to be called by the converter station for supplement until the total number of running half-bridge sub-modules returns to the minimum number required for normal work. At this time, the half-bridge sub-module is equivalent to the normally working sub-module in case one , and the reliability distribution function of the half-bridge sub-module is obtained by substituting formula (8) as: (14) Among them, .

[0033] According to the first case, the same operation is performed on the full-bridge sub-module, and j F sub-modules are selected to be normal, which is: ; At the same time, the total number of full-bridge and half-bridge faults is ensured not to exceed the total redundancy, so that the half-bridge can work normally after replacement, so the remaining standby sub-modules N 0 changes with the number of faulty sub-modules. Similarly, according to formula (8), the reliability formula of the full-bridge sub-module is obtained as: (15) wherein, j F number of failed sub-modules, remaining sub-modules .

[0034] The second reliability model of the hybrid MMC in the second case, considering the correlation of all sub-modules, is: (16) wherein, is the first reliability model.

[0035] Finally, the reliability evaluation model of the hybrid MMC can be constructed according to the first reliability model and the second reliability model: (17) wherein, is the reliability evaluation model of the hybrid MMC.

[0036] After the reliability evaluation model of the hybrid MMC is constructed, since the relationship between the reliability function and the failure rate satisfies the exponential change, the first failure rate of the hybrid MMC can be determined, and the first failure rate is the failure rate of a single sub-module of the hybrid MMC after considering the coupling and replaceability between sub-modules . (18) The change of the converter station state is mainly triggered by events such as failure occurrence or repair completion, and the dynamic processes are described by state variables. The failure and recovery processes of the sub-modules are quantified by parameters such as failure rate, repair rate and installation rate. Based on the state transition diagram, the state transition rate matrix of the system can be established, and the probabilities of the converter station in different states are obtained by solving the linear equation set, thereby realizing the evaluation of the reliability of the converter station.

[0037] Therefore, according to the first failure rate, the first state transition diagram of the hybrid MMC as shown in Figure 5 can be constructed, and then according to the first state transition diagram, the first state transition matrix of the hybrid MMC as shown below can be determined, as shown in the following formula: (19) wherein, N is the number of all sub-modules of an arm of the MMC, is the recovery rate of a single sub-module, is the installation rate of a single sub-module (refer to existing data).

[0038] ​After obtaining the first state transition matrix, the first probability model of formula (21) can be determined by combining the linear equations of formula (20) As follows: (20) Wherein, is the first probability model, and the first probability model is a probability model of each capacity state of the hybrid multi-level converter is the state of the converter station, P is the probability of each state in the Figure 5

[0039] (21) Wherein, is the probability of being in outage in each operating state (1 to S ) calculated by formula (20), is the probability of being in reduced capacity operation in each operating state (1 to ) calculated by formula (20), S is the probability of being in normal operation in each operating state (1 to ) calculated by formula (20). S The number of normal operating sub-modules of the MMC converter station can be 100% of the normal operating capacity, 50% of the reduced capacity operating capacity and 0% of the outage capacity, and the number of corresponding sub-modules is determined according to the actual engineering; the probabilities in each state calculated above are classified and added according to the available capacity levels provided by the LCC and the MMC, and then substituted into formula (44) to calculate the reliability of the hybrid converter station. Step S102: determining a second probability model based on the grid commutation converter, the second probability model being a probability model of each capacity state of the grid commutation converter;

[0040] First, a grid commutation converter reliability evaluation model is constructed according to the grid commutation converter, and then the second probability model is determined according to the grid commutation converter reliability evaluation model.

[0041] Step S102: determining a second probability model based on the grid commutation converter, the second probability model being a probability model of each capacity state of the grid commutation converter; First, a grid commutation converter reliability evaluation model is constructed according to the grid commutation converter, and then the second probability model is determined according to the grid commutation converter reliability evaluation model.

[0042] ​​The grid commutated converter is distinguished according to the commutation direction, and can only be the grid commutated converter rectifier side or the grid commutated converter inverter side. Therefore, the grid commutated converter reliability evaluation model is either the grid commutated converter rectifier side reliability evaluation model or the grid commutated converter inverter side reliability evaluation model. That is, according to the grid commutated converter, two specific technical solutions are constructed for the grid commutated converter reliability evaluation model, one of which is to construct the grid commutated converter rectifier side reliability evaluation model according to the grid commutated converter, and the other is to construct the grid commutated converter inverter side reliability evaluation model according to the grid commutated converter.

[0043] The grid commutated converter rectifier side reliability evaluation model is constructed as follows: As shown in FIG. 4(a), each pole group of the LCC rectifier side converter station is shown, the system is composed of series and parallel components, first, the series reliability parameters of the two cascaded components of the circuit breaker and the transformer are calculated according to the positive pole, then the obtained parameters are calculated in the same way as the valve, and the series reliability parameters of the four positive pole components are obtained in this way; the formula is expressed as: (22) Wherein: (23) Wherein, is the failure rate of the positive pole of the grid commutated converter rectifier side, is the failure frequency of the positive pole of the grid commutated converter rectifier side, both of which constitute the positive pole reliability evaluation model of the grid commutated converter rectifier side, and subscripts a, b, c and d respectively represent the circuit breaker, the transformer, the valve and the reactor, is the failure rate of the aforementioned component, is the failure frequency of the aforementioned component, is the repair time of the aforementioned component arranged in the rectifier side, which is obtained according to actual engineering data.

[0044] By substituting the above formula (22)-(23) into the circuit breaker, transformer, valve and reactor parameters of the rectifier side negative pole, the failure rate of the grid commutated converter rectifier side negative pole λ r负 , the failure frequency of the grid commutated converter rectifier side negative pole , both of which constitute the negative pole reliability evaluation model of the grid commutated converter rectifier side: (24) Finally, since the positive pole and the negative pole of the grid commutated converter rectifier side are in parallel, the grid commutated converter rectifier side reliability evaluation model is obtained as: (25) in, is the failure rate of the rectifier side of the grid commutation converter, is the fault frequency on the rectifier side of the grid commutation converter, To obtain the repair time of the positive and negative electrodes on the rectifier side, calculate according to the following formula: (26) in, are the series repair time of two cascade components, namely, circuit breaker and transformer, and valve and reactor; for Repair time of four positive electrode assemblies in series calculated.

[0045] Similarly, the repair time of the negative pole of the rectifier side LCC is obtained by substituting the parameters of the circuit breaker, transformer, valve and reactor into formula (26): (27) in, are the series repair time of the two cascade components of circuit breaker and transformer, valve and reactor after substituting the negative pole parameters; for Repair time of four negative electrode assemblies in series calculated.

[0046] After a commutation failure occurs, the LCC will be forced to exit operation. When constructing the inverter-side reliability model, the fault simulation module is taken into consideration as a series element. The composition of the LCC inverter-side converter station is shown in Figure 4 (b).

[0047] The reliability parameter calculation of the LCC inverter side in Figure 4 (b) is the same as that in Figure 4 (a), except that a commutation failure simulation module is connected in series on both the positive and negative poles. The parameter calculation process will be described in detail later. Finally, the positive pole reliability assessment model of the inverter side of the grid commutation converter is obtained by the same calculation method according to Equation (22): (28) in: (29) In the formula ， is the failure rate of the positive pole on the inverter side of the grid commutation converter, is the fault frequency of the positive pole on the inverter side of the grid commutation converter, and the two together constitute the positive pole reliability assessment model on the inverter side of the grid commutation converter. Refers to circuit breaker, transformer, valve and reactor respectively, is the failure rate of the aforementioned components, is the failure frequency of the aforementioned components, is the repair time of each component in the rectifier side, which is obtained according to actual engineering data, is the failure rate of the commutation failure simulation module.

[0048] Similarly, according to formula (28) and (29), the parameters of the circuit breaker, transformer, valve, reactor and commutation failure simulation module of the negative electrode of the inverter side are substituted to calculate the failure rate of the negative electrode of the inverter side of the grid commutation converter , the failure frequency of the negative electrode of the inverter side of the grid commutation converter , which together constitute the reliability evaluation model of the negative electrode of the inverter side of the grid commutation converter: (30) Finally, considering the parallel connection of the positive electrode and the negative electrode of the inverter side of the grid commutation converter, the reliability evaluation model of the LCC inverter side is obtained by the same calculation method according to formula (25): (31) wherein, is the failure rate of the inverter side of the grid commutation converter, is the failure frequency of the inverter side of the grid commutation converter, is the repair time of the positive electrode and the negative electrode of the inverter side, since the commutation failure simulation module is a module only for quantifying the failure probability, the repair time is not considered, so According to formula (26) and (27), the parameters of the circuit breaker, transformer, valve and reactor of the positive electrode and the negative electrode of the inverter side are substituted to calculate: (32) Similarly, according to formula (32), the repair time of the circuit breaker, transformer, valve and reactor parameters of the negative electrode of the inverter side is substituted: (33) wherein, respectively, are the series repair times of the two cascaded components of the circuit breaker and the transformer, the valve and the reactor after substituting the parameters of the negative electrode of the inverter side; is the series repair time of the four negative electrode components calculated in series.

[0049] The above commutation failure simulation module parameters are calculated according to the commutation failure probability calculation model, that is, the reliability evaluation model of the inverter side of the grid commutation converter in the present application is determined according to the grid commutation converter and the commutation failure probability calculation model. The construction process of the above commutation failure probability calculation model is as follows: The operation state of the converter station is mainly divided into three-phase voltage symmetric change and asymmetric fault, both of which can occur commutation success or failure, which depends on the size of the turn-off angle and the minimum turn-off angle (the minimum turn-off angle in engineering application, the turn-off angle of the inverter is generally 15°-18°).

[0050] For three-phase voltage symmetric change, the calculation formula of the turn-off angle is: (34) wherein, is the firing angle, is the electric angle at which the voltage drop occurs; is the DC current; is the commutation reactance; is the effective value of the AC line voltage, is the effective value of the voltage after the change, is the time delay of the voltage change relative to the valve firing time, and is ( is the power frequency angle frequency, 100 π ).

[0051] And for asymmetric fault, the calculation formula of the turn-off angle is: (35) wherein, A is the symmetric component of the voltage waveform during commutation, which is taken as ; B is the asymmetric component, which is taken as .

[0052] Because the factors affecting commutation failure are different under different fault modes, i.e., the first influencing factor affecting the first commutation failure and the second influencing factor affecting the subsequent commutation failure are different, the different fault modes covering commutation failure are first obtained, and then the influence of these factors on the turn-off angle is considered, and whether the commutation fails is judged according to the turn-off angle result, so as to accurately characterize the commutation failure characteristics.

[0053] For the first commutation failure, the first influencing factor is summarized as four points: commutation voltage drop amplitude, commutation voltage amplitude change rate, fault occurrence time, and DC current.

[0054] For the subsequent commutation failure, the second influencing factor includes the influencing factors of three-phase symmetric and asymmetric faults, and the influencing factors of the two are different. The main reason for the subsequent commutation failure under three-phase symmetry is that the commutation voltage amplitude is too low and the DC current is too large. After the first commutation failure, the LCC will pass through the low-voltage current limiting link, so when analyzing the subsequent commutation failure, the low-voltage current limiting strategy also needs to be considered, i.e.: (36) Where, DC voltage , current limit value All are expressed in per-unit values.

[0055] The main cause of asymmetric faults is the advanced firing angle The fluctuation contains both the second harmonic component and regular fluctuation with a period of 6 commutations: (37) in, is the DC current change, is the DC component; is the amplitude of the second harmonic component; is the phase of the 2nd harmonic component; is the phase interval of adjacent phase voltages when a fault occurs, is the number of commutation times, is the power frequency angular frequency, equal to 100 π , For the m The actual leading trigger angle of the commutation phase is is the initial value of the actual advance trigger angle.

[0056] The above factors will affect the AC voltage amplitude in equations (34) and (35). U , DC current I d The first influencing factor and the second influencing factor are established as the sample space of the commutation process. , take different values ​​under Monte Carlo according to the nature of the influencing factors, and then combine equations (34) and (35) to calculate the turn-off angle under different influencing mechanisms, and record the number of commutation failures during the entire Monte Carlo simulation, so as to calculate the failure rate of the fault simulation module .

[0057] (38) in, is the number of commutation failures, is the number of commutations, i.e. the number of Monte Carlo simulations.

[0058] Combining the obtained turn-off angle with equation (39) allows us to construct a commutation failure probability calculation model. The numerator represents the case where the turn-off angle is less than the minimum turn-off angle, i.e., the commutation failure case; the denominator represents all calculated commutation cases. This metric reflects the relative degree of commutation failure, rather than simply the proportion of failures. Even if a certain extinction angle is slightly less than the minimum extinction angle, it is still included in the calculation, reflecting the degree of commutation failure and providing a more detailed assessment.

[0059] (39) in, is the arc extinction angle margin, is the minimum turn-off angle, if , then the commutation is successful, if , the commutation fails. represents the number of Monte Carlo simulations, .

[0060] Furthermore, in order to achieve a quantitative assessment of the commutation failure risk, the probability result obtained by Equation (39) is converted into fault frequency and duration indicators, thereby establishing a commutation failure simulation module.

[0061] (40) in, The fault frequency of the commutation failure simulation module, is the probability and average duration of commutation failure.

[0062] After obtaining the above-mentioned grid commutation converter reliability assessment model, the second probability model can be determined. Since the state transitions of the LCC rectifier side and the inverter side are the same, the obtained state transition space diagrams can be used. Figure 6 As shown, the state transition rate matrix obtained is also in the same form. Taking the LCC rectifier side as an example, the determination process is explained as follows: According to the above formula (22), the second failure rate of the grid-commutated converter can be obtained, that is, the failure rate of the rectifier side of the grid-commutated converter ;Fault repair time It is based on the repair time of the positive and negative poles on the rectifier side The process is as follows: (41) According to the second failure rate and the fault repair time, the second state transition diagram of the power grid converter can be constructed, such as Figure 6 shown.

[0063] Then, according to the second state transition diagram, the second state transition matrix of the grid-commutated converter is determined as shown in the following equation (42): (42) wherein, , ， LCC rectifier side installation rate (reference existing data).

[0064] According to the above second state transition matrix, combined with the linear equation set (formula 20), the second probability model The second probability model is as follows: the probability model of each capacity state of the grid commutation converter: (43) wherein, is the probability of bipolar shutdown in each operating state (1 to S ) calculated by formula (20), is the probability of monopole operation in each operating state (1 to ) calculated by formula (20), S is the probability of bipolar operation in each operating state (1 to ) calculated by formula (20). S The LCC converter station has three available capacity levels, which are 100% capacity of bipolar operation, 50% capacity of monopole operation and 0% capacity of bipolar shutdown; according to the available capacity level provided by the LCC, the probabilities of each state (1 to ) calculated above are classified and added to obtain the second probability model

[0065] . S Step S103: based on the first probability model and the second probability model, a mixed converter station reliability evaluation model is constructed; .

[0066] Step S103: based on the first probability model and the second probability model, a mixed converter station reliability evaluation model is constructed; Considering the connection between subsystems, the operating state probabilities of all subsystems at different capacity levels are integrated by formula (40) convolution method to obtain the operating state probabilities of the entire mixed converter station at different capacity levels.

[0067] (44) wherein, indicates that subsystems 1 and 2 are in series and parallel; is the operating state probability of subsystems 1 and 2 at their respective capacity levels . ; is the capacity level of the integrated converter station of the subsystems. Take ​​The probability other than 0 is taken as a reliability index of the hybrid converter station, thereby establishing a reliability model of the hybrid converter station.

[0068] Step S104: solving the reliability evaluation model of the hybrid converter station to determine the reliability of the hybrid converter station.

[0069] Solving the above formula (44) can obtain the reliability of the hybrid converter station.

[0070] To sum up, the method provided in the application constructs a representation model of the mutual relationship of the sub-modules of the MMC system based on the optimal combination of multiple correlation functions; meanwhile, a multi-scenario probability model is constructed by considering the subsequent commutation failure of the LCC. By systematically integrating the reliability models of the two types of converters, a multi-state reliability evaluation system of the hybrid converter station is constructed. The method not only significantly improves the accuracy of the reliability evaluation of the converter station, but also simplifies the calculation complexity in engineering application, and provides more comprehensive and reliable technical support for actual engineering.

[0071] The above only describes the preferred embodiments of the application and is not intended to limit the application. The application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method for calculating the reliability of a hybrid converter station, wherein the hybrid converter station comprises a first subsystem and a second subsystem, wherein the first subsystem is a hybrid multilevel converter and the second subsystem is a grid-commutated converter; include: Determining a first probability model based on the hybrid multilevel converter, where the first probability model is a probability model of the hybrid multilevel converter under various capacity states; Determining a second probability model based on the grid-commutated converter, where the second probability model is a probability model of the grid-commutated converter under various capacity states; constructing a hybrid converter station reliability assessment model based on the first probability model and the second probability model; The reliability assessment model of the hybrid converter station is solved to determine the reliability of the hybrid converter station.

2. The method according to claim 1, characterized in that The step of determining a first probability model based on the hybrid multilevel converter comprises: Determining an optimal Copula function based on the hybrid multilevel converter, wherein the optimal Copula function is used to characterize a coupling relationship between submodules of the hybrid multilevel converter; Based on the optimal Copula function, a first probability model is determined.

3. The method according to claim 2, characterized in that The determining of an optimal Copula function based on the hybrid multilevel converter includes: Based on the hybrid multilevel converter, selecting a first number of Copula correlation functions; The first number of Copula-related functions are combined to obtain an optimal Copula function.

4. The method according to claim 2, characterized in that Determining a first probability model based on the optimal Copula function includes: Based on the optimal Copula function, a hybrid multilevel converter reliability evaluation model is constructed; Based on the hybrid multilevel converter reliability assessment model, a first probability model is determined.

5. The method according to claim 4, characterized in that The step of constructing a hybrid multilevel converter reliability assessment model based on the optimal Copula function includes: determining, based on the optimal copula function, a first reliability model of the hybrid multilevel converter under a first scenario, taking into account the relevance of all sub-modules, wherein the first scenario is that half-bridge sub-modules and full-bridge sub-modules in the hybrid multilevel converter do not need to be replaced with each other; determining, based on the optimal copula function, a second reliability model of the hybrid multilevel converter under a second scenario, taking into account the relevance of all sub-modules, wherein the second scenario is that half-bridge sub-modules and full-bridge sub-modules in the hybrid multilevel converter need to be replaced with each other; A hybrid multilevel converter reliability model is constructed based on the first reliability model and the second reliability model.

6. The method according to claim 4, characterized in that The determining of a first probability model based on the hybrid multilevel converter reliability assessment model includes: determining, based on the hybrid multilevel converter reliability assessment model, a first failure rate of the hybrid multilevel converter, where the first failure rate is a failure rate of a single submodule of the hybrid multilevel converter after considering coupling and replaceability between submodules; constructing a first state transition diagram of the hybrid multilevel converter based on the first failure rate; determining a first state transition matrix of the hybrid multilevel converter based on the first state transition diagram; A first probability model is determined based on the first state transition matrix.

7. The method according to claim 1, characterized in that The determining of a second probability model based on the grid-commutated converter includes: Based on the grid-commutated converter, a grid-commutated converter reliability assessment model is constructed; Based on the grid-commutated converter reliability assessment model, a second probability model is determined.

8. The method according to claim 7, characterized in that The grid commutation converter reliability assessment model is one of the following: Reliability assessment model for the rectifier side of a power grid commutating converter or reliability assessment model for the inverter side of a power grid commutating converter; The step of constructing a grid-commutated converter reliability assessment model based on the grid-commutated converter includes: Based on the grid-commutated converter, a grid-commutated converter inverter side reliability assessment model is constructed; The step of constructing a grid-commutated converter inverter-side reliability assessment model based on the grid-commutated converter includes: Construct a commutation failure probability calculation model; Based on the grid-commutated converter and the commutation failure probability calculation model, a grid-commutated converter inverter side reliability assessment model is constructed.

9. The method according to claim 8, characterized in that The construction process of the commutation failure probability calculation model is as follows: Get comprehensive coverage of different failure modes of commutation failure; Based on the different failure modes, determining a first influencing factor affecting a first commutation failure and a second influencing factor affecting a subsequent commutation failure; Establishing a sample space of a commutation process based on the first influencing factor and the second influencing factor; determining a shutoff angle under different impact mechanisms based on the sample space; Based on the turn-off angles under the different influencing mechanisms, a commutation failure probability calculation model is constructed.

10. The method according to claim 7, characterized in that The determining of the second probability model based on the grid-commutated converter reliability assessment model includes: determining, based on a grid-commutated converter reliability assessment model, a second failure rate and a fault repair time of the grid-commutated converter, wherein the second failure rate is a failure rate of the grid-commutated converter; constructing a second state transition diagram of the grid-commutated converter based on the second failure rate and the fault repair time; determining a second state transition matrix of the grid-commutated converter based on the second state transition diagram; A second probability model is determined based on the second state transition matrix.

Images