CN115308640A - MMC submodule open-circuit fault positioning method based on data mining - Google Patents
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Abstract
The invention discloses an MMC submodule open-circuit fault positioning method based on data mining, and relates to the technical field of modular multilevel converters. The method aims at quickly detecting and positioning sub-modules of open-circuit faults in the MMC system, supposing that one bridge arm has N sub-modules, and automatically generating the adaptive parameter truncation distance D by using a truncation average method according to the actual capacitance voltage value of each sub-module at each sampling moment c (ii) a Generating a local density rho by using a Gaussian kernel method, further obtaining a local distance delta, calculating an average local distance AVE of each submodule according to the local density and the local distance, and judging the AVE with the largest value as an abnormal value; and if the AVE of one sub-module shows abnormal conditions in three continuous sampling periods, the corresponding sub-module is a fault sub-module. According to the invention, a complex mathematical model is not required to be constructed, an additional sensor is not required to be used, and a fault threshold value is not required to be manually set, so that the fault submodule can be timely positioned and eliminated, and the operation reliability of the MMC is improved.
Description
Technical Field
The invention relates to the technical field of modular multilevel converters, in particular to an MMC submodule open-circuit fault positioning method based on data mining
Background
The Modular Multilevel Converter (MMC) becomes a preferred converter topology of a flexible direct-current transmission system and is formed by cascading a plurality of Sub-modules (Sub-modules, SM) with the same structure, faults of a power switch device (IGBT) of the MMC Sub-modules can be divided into open-circuit faults and short-circuit faults, the short-circuit faults of the IGBT can be identified through conventional diagnosis methods such as overvoltage detection and overcurrent detection, the open-circuit faults of the IGBT do not have obvious fault characteristics under some working conditions, and the open-circuit faults of the IGBT can not be found in time without a specific diagnosis method. Therefore, in order to ensure safe and reliable operation of the MMC, the research on the characteristics of the open-circuit fault of the IGBT in the MMC sub-module and the effective diagnosis and positioning method of the open-circuit fault of the IGBT are of great importance.
In the prior art, methods for detecting and positioning open-circuit faults of MMC sub-modules are various and are roughly divided into three types: 1) Additional sensor based methods; 2) A mathematical model-based approach; 3) A machine learning based method. However, the method increases the construction cost of the converter, requires a complex mathematical model to be constructed, generally requires manual setting of a threshold value, increases the design difficulty and the operation cost of the system, but mostly has high implementation difficulty, and greatly increases the construction cost and the operation cost.
Disclosure of Invention
The invention aims to provide an MMC submodule open-circuit fault positioning method based on data mining, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: an MMC submodule open-circuit fault positioning method based on data mining comprises the following steps:
in each fault detection period delta t, updating and sampling the capacitance voltage values of N sub-modules on a single bridge arm, and according to the capacitance voltage set U = { U = { of the N sub-modules c1 ,u c2 ,u c2 ,···,u cN Get the set of indicated coordinates I U ＝{1,2,3,···,N}；
Obtaining the actually acquired capacitance voltage value of N submodules in a single bridge arm at each sampling moment to obtain the adaptive parameter truncation distance D c ；
Obtaining the average local distance AVE of the ith sub-module in the N sub-modules on a single bridge arm i ：
Where ρ is i Is the local density of the ith sub-module, δ i Is the local distance of the ith sub-module
And defining the maximum average local distance AVE in the N sub-modules on a single bridge arm as abnormal, and if three continuous sampling periods of the average local distance AVE of one sub-module are the maximum value in the N sub-modules AVE, the corresponding sub-module is a fault sub-module.
According to an aspect of the invention, the adaptive parameter truncates the distance D c The acquisition method comprises the following steps:
eliminating the maximum value and the minimum value of the capacitance voltage in the N sub-modules of the single bridge arm, and processing the capacitance voltage of the remaining N-2 sub-modules as follows:
in which MSE u Average capacitance voltage value, u, representing the remaining N-2 submodules cj Is the minimum value of the capacitor voltage, u, in the N submodules ck Is the maximum value of the capacitor voltage in the N sub-modules.
Then the truncation distance D c Can be expressed as:
wherein u is ci Is the capacitance voltage value of the ith sub-module
Further, the local density ρ of the ith sub-module of the N sub-modules on a single bridge arm i ：
Firstly, calculating a distance distribution matrix D according to the capacitance voltage values of the N sub-modules N×N ：
D N×N ＝{Dist(i,j)|1≤i≤N,1≤j≤N}
Wherein
Dist(i,j)＝|u ci -u cj |
u ci 、u cj The voltage value of the capacitor of the ith sub-module and the voltage value of the capacitor of the jth sub-module are respectively, and Dist (i, j) is u ci And u cj The euclidean distance between them.
Reacquiring u ci Local density of (p) i ：
Further, the local distance δ of the ith sub-module i ：
Wherein
Where ρ is i 、ρ k The local density of the ith sub-module and the local density of the kth sub-module respectively
According to another aspect of the present invention, the present invention provides a modular multilevel converter, which includes 6 bridge arms, each bridge arm is composed of a plurality of submodules with the same structure and bridge arm inductors, each submodule adopts a half-bridge type structure, and each submodule includes a power switch device, a diode electrically connected to the power switch device, and a dc capacitor electrically connected to the power switch device.
According to yet another aspect of the invention, the invention further relates to a flexible direct current transmission system, the modular multilevel converter is used as a converter element of the flexible direct current transmission system, and the flexible direct current transmission system further comprises a converter unlocking controller, and the converter unlocking controller unlocks the modular multilevel converter through direct current voltage.
According to yet another aspect of the present invention, there is provided an apparatus comprising one or more processors, memory for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to execute a data mining based MMC sub-module open circuit fault location method.
The invention has at least the following beneficial effects:
the MMC sub-module open-circuit fault positioning method based on data mining does not need to add a sensor, can not increase the construction cost of a modular multilevel converter, is easy to implement in the conventional modular multilevel converter system, has strong practicability, does not need to construct a complex mathematical model during implementation, only uses the correlation of data characteristics to carry out fault diagnosis research on the basis of the difference of capacitance voltage change between a fault sub-module and a normal sub-module, has less calculated data amount and greatly reduces the operation cost, and simultaneously does not need to change the operation state of the MMC system, such as introduction of circulation, so the operation performance of the MMC system can not be influenced, and meanwhile, the MMC sub-module open-circuit fault positioning method based on data mining can be applied to the MMC system under any working condition, and further improves the practicability.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
Drawings
FIG. 1 is a schematic flow diagram of the overall process of the present invention;
FIG. 2 is a three-phase MMC and sub-module topology structure diagram of the present invention.
Detailed Description
Technical solutions in the embodiments of the present disclosure will be described below clearly and completely with reference to the accompanying drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only some embodiments of the present disclosure, not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without inventive step, are intended to be within the scope of the present disclosure.
The invention provides an MMC sub-module based on data miningThe method for locating the path fault comprises that the MMC topological structure consists of six bridge arms, as shown in figure 2, each bridge arm comprises N identical submodules and a bridge arm inductor L s The submodules adopt a half-bridge structure, and each submodule is composed of two power switches T 1 、T 2 Two diodes D 1 、D 2 And a DC capacitor.
As shown in fig. 1, an MMC submodule open-circuit fault location method based on data mining includes the following steps:
updating the capacitance voltage values of N sub-modules on a single bridge arm in each fault detection period delta t (20 ms), and according to the capacitance voltage set U = { U = { U } c1 ,u c2 ,u c2 ,···,u cN Get the set of indicated coordinates I U = 1,2,3, ·, N, the set of indicating coordinates being mainly used to find the local distances of the N submodules;
acquiring the actually acquired capacitor voltage value of N submodules in a single bridge arm at each sampling moment, and acquiring the adaptive parameter truncation distance D by using a truncation average method c ；
Generating a local density rho by using a Gaussian kernel method, further obtaining a local distance delta, and obtaining an average local distance AVE of each submodule according to the local density and the local distance;
the largest average local distance AVE in the N sub-modules on a single bridge arm is abnormal, and if the three continuous sampling periods of the AVE of a certain sub-module are the largest values in the AVE of the N sub-modules, the corresponding sub-module is a fault sub-module.
It should be noted that the adaptive parameter truncates the distance D c The acquisition comprises the following steps:
eliminating the maximum value and the minimum value of the capacitor voltage in the N sub-modules in a single bridge arm, and processing the capacitor voltage of the remaining N-2 sub-modules as follows:
wherein u cj Is N submodelsMinimum value of capacitor voltage in block, u ck Is the maximum value of the capacitor voltage in the N sub-modules.
Cut-off distance D c Can be expressed as:
wherein u is ci Is the value of the capacitance voltage of the ith sub-module.
Further, a distance distribution matrix D is calculated according to the capacitance voltage values of the N sub-modules N×N The method comprises the following steps:
D N×N ＝{Dist(i,j)|1≤i≤N,1≤j≤N}
wherein,
Dist(i,j)＝|u ci -u cj |
u ci 、u cj the voltage values of the capacitor of the ith sub-module and the jth sub-module are respectively, and Dist (i, j) is u ci And u cj The euclidean distance between them.
Calculating the local density rho of the ith sub-module i ：
On the other hand, the local distance δ of the ith sub-module i The calculation formula of (c) is:
wherein
Where ρ is i 、ρ k Respectively, the local density of the ith sub-module and the local density of the kth sub-module.
Thus, the method can obtain the result that,average local distance AVE of ith sub-module i The calculation method is as follows:
where ρ is i Is the local density of the ith sub-module, δ i Is the local distance of the ith sub-module.
The invention further provides a modular multilevel converter, which includes 6 bridge arms, each bridge arm is formed by cascading a plurality of submodules with the same structure, each submodule adopts a half-bridge structure, and each submodule includes a power switch device, a diode electrically connected to the power switch device, and a dc capacitor electrically connected to the power switch device.
Furthermore, the invention also relates to a flexible direct current transmission system which uses the modularized multi-level converter as a converter element and also comprises a converter unlocking controller, wherein the converter unlocking controller unlocks the modularized multi-level converter through direct current voltage.
In another aspect, the present invention provides an apparatus comprising one or more processors, a memory for storing one or more programs, the one or more programs, when executed by the one or more processors, cause the one or more processors to execute an MMC submodule open circuit fault location method based on data mining
Specifically, the method is particularly suitable for the MMC system, compared with the traditional submodule open-circuit fault positioning method, the method does not need to construct a complex mathematical model, does not need to use an additional sensor, does not need to manually set a fault threshold value, can timely position and clear the fault submodule, and improves the operation reliability of the modular multilevel converter.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to specific situations. When an element is referred to as being "mounted to," "secured to," or "disposed on" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. As used herein, the terms "vertical," "horizontal," "upper," "lower," "left," "right," and the like are for purposes of illustration only and do not denote a particular embodiment.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
In the description herein, references to the description of "one embodiment," "an example," "a specific example," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the disclosure. In this specification, a schematic representation of the above terms does not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Claims (10)
1. An MMC submodule open-circuit fault positioning method based on data mining is characterized by comprising the following steps:
and updating and sampling the capacitance voltage values of the N sub-modules on a single bridge arm in each fault detection period delta t, and according to the capacitance voltage set U of the N sub-modules, the value is Uk = { U = c1 ,u c2 ,u c2 ,…,u cN Get the indicated coordinate set I U ＝{1,2,3,…,N}；
Obtaining the actually acquired capacitance voltage value of N submodules in a single bridge arm at each sampling moment to obtain the adaptive parameter truncation distance D c ；
Obtaining the average local distance AVE of the ith sub-module in the N sub-modules on a single bridge arm i ：
Where ρ is i Is the local density of the ith sub-module, δ i Is the local distance of the ith sub-module;
and defining the maximum average local distance AVE in the N sub-modules on a single bridge arm as abnormal, and if three continuous sampling periods of the average local distance AVE of one sub-module are the maximum value in the N sub-modules AVE, the corresponding sub-module is a fault sub-module.
2. The MMC sub-module open-circuit fault location method based on data mining of claim 1, wherein adaptive parameter truncation distance D c The acquisition steps are as follows:
eliminating the maximum value and the minimum value of the capacitor voltage in N SMs in a single bridge arm, and processing the capacitor voltage of the remaining N-2 sub-modules as follows:
wherein MSE u Represents the average capacitance voltage value, u, of the remaining N-2 sub-modules cj Is the minimum value of the capacitor voltage, u, in the N submodules ck Is the maximum value of the capacitor voltage in the N sub-modules.
Then the truncation distance D c Can be expressed as:
wherein u is ci Is the value of the capacitor voltage in the ith sub-module.
3. The MMC sub-module open-circuit fault location method based on data mining of claim 2, wherein a local density p of an ith sub-module i The acquisition steps are as follows:
calculating a distance distribution matrix D according to the capacitance voltage values of the N sub-modules N×N ：
D N×N ＝{Dist(i,j)|1≤i≤N,1≤j≤N}
Wherein
Dist(i,j)＝|u ci -u cj |
Wherein u is ci 、u cj The voltage value of the capacitor of the ith sub-module and the voltage value of the capacitor of the jth sub-module are respectively, and Dist (i, j) is u ci And u cj The euclidean distance between them.
Calculating u ci Local density of (p) i ：
4. The MMC sub-module open-circuit fault location method based on data mining of claim 1, wherein a local distance δ of an ith sub-module i The calculation formula of (a) is as follows:
wherein
Where ρ is i 、ρ k Respectively, the local density of the ith sub-module and the local density of the kth sub-module.
5. The modular multilevel converter based on data mining according to claim 1, wherein the modular multilevel converter comprises 6 bridge arms, each bridge arm is formed by cascading a plurality of submodules with the same structure, and the open-circuit fault locating method of the submodules uses the open-circuit fault locating method of the MMC submodule based on data mining according to any one of claims 1 to 4.
6. The modular multilevel converter based on data mining of claim 5, wherein: the submodules are of the half-bridge type.
7. The modular multilevel converter based on data mining of claim 5, wherein: the sub-module comprises a power switch device, a diode electrically connected to the power switch device, and a direct current capacitor electrically connected to the power switch device.
8. A flexible direct current transmission system comprising a modular multilevel converter according to any of claims 5-7 as a converter element.
9. A flexible direct current transmission system according to claim 8, characterized in that: the modularized multi-level converter is unlocked by the converter unlocking controller through direct-current voltage.
10. An apparatus, comprising:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a data mining based MMC sub-module open circuit fault locating method as claimed in any one of claims 1-4.
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