A method and system for identifying internal and external faults in a metal return dc grid

Abstract

The application discloses a metal reflux direct current power grid intra / inter-zone fault identification method and system, and relates to the technical field of power grids.The method comprises the following steps: a Bergeleon model is constructed, and a Kalman-Bell transformation is used for decoupling, so that an equivalent model of a metal reflux flexible direct current power grid under different fault types is constructed; based on a normalized cross-correlation algorithm, the similarity between a corresponding fault type traveling wave waveform and a reference waveform is quantitatively calculated; according to a pre-constructed differential criterion and a setting threshold, the similarity between the corresponding fault type traveling wave waveform and the reference waveform is used to determine the fault type; and a fault current differential ratio is used to construct a phase plane for fault type identification, and the fault polarity is selected. The application can quickly and accurately identify intra / inter-zone faults in the metal reflux direct current power grid, and distinguish different fault types, thereby improving the safety and reliability of the power grid.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid, in particular to a metal return DC power grid internal and external fault identification method and system. BACKGROUND

[0002] In recent years, with the continuous access of large-scale renewable energy such as wind energy and solar energy to the power grid, new technologies, new equipment and new power grid architectures must be adopted to meet the profound changes in the energy pattern. Flexible DC power grid has been widely regarded as one of the effective technologies to solve the challenge of intermittent new energy grid connection. While flexible DC power grid is rapidly developing, it also faces many technical challenges, one of which is the relay protection of DC lines, which is an important technical problem. Compared with traditional high-voltage DC transmission systems, flexible DC transmission systems have smaller damping and lower inertia. After a fault occurs in the DC line, the current will quickly rise, leading to rapid development of the fault. This means that the protection system must respond quickly within 3ms. In addition, in order to avoid metal corrosion and other problems, the actual project may use true bipolar connection with return lines. However, the high line fault rate poses a great risk to the safe and reliable operation of the system. When a high-resistance fault occurs in the DC line of the flexible DC power grid, the traditional traveling wave protection method cannot effectively identify the fault. In addition, existing protection methods ignore the impact of the coupling characteristics of the metal return line on protection, which may cause protection misoperation. Therefore, seeking a fast and reliable protection scheme has become a crucial issue and has attracted increasing research attention. SUMMARY

[0003] In view of the deficiencies of the prior art, the present application provides a metal return DC power grid internal and external fault identification method and system, which can quickly identify internal and external faults of the line, use the modulus current differential ratio to construct a phase plane for fault type identification, and select the pole to improve the accuracy and response speed of flexible DC power grid fault identification.

[0004] To solve the above technical problems, the present application adopts the following technical solutions:

[0005] A metal return DC power grid internal and external fault identification method, comprising the following steps:

[0006] S1, obtaining the topology structure of the metal return flexible DC power grid;

[0007] S2, constructing a Bergeron model according to the topology structure of the metal return flexible DC power grid, and decoupling by using the Kelvin-Bell transformation to construct an equivalent model of the metal return flexible DC power grid under different fault types;

[0008] S3, obtaining the expression of the voltage fault component in the modal domain and the current fault component in the modal domain under different fault types according to the equivalent model of the metal reflux flexible DC power grid under different fault types;

[0009] S4, performing differential processing on the voltage in the modal domain and the current in the modal domain at different fault positions based on the normalized cross-correlation algorithm to obtain the traveling wave waveform at different fault positions, and quantitatively calculating the similarity between the traveling wave waveform corresponding to the fault type and the reference wave to obtain the similarity between the traveling wave waveform corresponding to the fault type and the reference wave;

[0010] S5, determining the fault type according to the similarity between the traveling wave waveform corresponding to the fault type and the reference waveform according to the pre-constructed differential criterion and the setting threshold; wherein the fault type includes an internal fault, an external fault and an internal end fault;

[0011] S6, constructing a phase plane for fault type identification by using the fault current differential ratio according to the expression of the voltage fault component in the modal domain and the current fault component in the modal domain under different fault types;

[0012] S7, selecting the fault pole according to the determined fault type and the phase plane for fault type identification.

[0013] As a preferred scheme, the step S2 is specifically:

[0014] S201, constructing the electrical quantity relationship between sub-circuits based on the Bergeon model according to the topological structure of the metal reflux flexible DC power grid, and decoupling by using the Krylov-Belytschko transformation;

[0015] S202, analyzing the fault types of different metal reflux flexible DC power grids based on the Krylov-Belytschko transformation, obtaining the boundary conditions corresponding to each fault type of the different metal reflux flexible DC power grids, and constructing the equivalent model of the metal reflux flexible DC power grid under different fault types according to the boundary conditions corresponding to each fault type.

[0016] As a preferred scheme, in the step S201, the formula for constructing the electrical quantity relationship between sub-circuits based on the Bergeon model is:

[0017] B k (s)=e -γ(s)l (2U m (s)-B m (s));

[0018] B m (s)=e -γ(s)l (2U k (s)-B k (s));

[0019] In the formula, B k(s) and B m (s) are equivalent voltage sources in the DC line Bergeon model, U k (s), U m (s), I k (s), I m (s) are the voltages and currents at the ends of the lines k, m, respectively, and γ(s) is the propagation coefficient of the fault traveling wave, and l is the length of the line.

[0020] As a preferred solution, in step S201, the formula for decoupling by using the Karhunen-Loeve transform is:

[0021]

[0022] In the formula, T K is the decoupling matrix of the Karhunen-Loeve transform, x p , x m , x n are the coordinates of the fault currents or voltages in the standard in the real physical system, and x1, x2, x0 are the coordinates in the module domain after the Karhunen-Loeve transform.

[0023] As a preferred solution, in step S202, the fault types of the different metal return flexible DC power grid include single-pole ground fault, pole-to-pole fault, and pole-to-return line fault.

[0024] The single-pole ground fault includes a positive pole ground fault.

[0025] The pole-to-pole fault is a short circuit fault between a positive pole and a negative pole.

[0026] The pole-to-return line fault includes a short circuit fault between a positive pole and a metal return line.

[0027] As a preferred solution, in step S3, the expressions of the module domain voltage fault component and the module domain current fault component under different fault types specifically include:

[0028] When the positive pole ground fault occurs:

[0029]

[0030] When the short circuit fault between the positive pole and the negative pole occurs:

[0031]

[0032] When the short circuit fault between the positive pole and the metal return line occurs:

[0033]

[0034] In the formula, U R2 , U R1 , UR0 are the 2nd, 1st and 0th modal voltage measured after the fault, respectively; I R2 , I R1 and I R0 are the 2nd, 1st and 0th modal current measured after the fault, respectively; Lsr is the smoothing reactor; Z MAC1 is the equivalent impedance of the converter MMC1; Z c2 , Z c1 and Z c0 are the 2nd, 1st and 0th modal wave impedance of the DC line, respectively; B KR2 , B KR1 and B KR0 are the 2nd, 1st and 0th modal equivalent voltage source of the Berthon model of the DC line measured by the measuring device after the fault; (s) represents the Laplace transform.

[0035] As a preferred solution, in step S4, the reference wave is the 1st modal fault voltage differential waveform occurring at the end resistor grounding in the zone; and the traveling wave waveform is the 1st modal fault voltage differential waveform.

[0036] The formula for quantitatively calculating the similarity between the traveling wave waveform and the reference waveform corresponding to the fault type based on the normalized cross-correlation algorithm is:

[0037]

[0038] In the formula, n c is the normalized cross-correlation similarity between the traveling wave waveform and the reference waveform, N is the sampling length of the waveform signal, x is the traveling wave waveform signal, y is the reference waveform signal, x[i] is the sampling value of the traveling wave waveform signal x at the i-th time point, y[j] is the sampling value of the reference waveform signal y at the j-th time point, μ x and μ y respectively represent the signal sampling mean of x and y.

[0039] As a preferred solution, in step S5, the differential criterion and the setting threshold are specifically:

[0040]

[0041] In the formula, n set is the setting threshold, ε is the differential criterion, n c is the normalized cross-correlation coefficient.

[0042] As a preferred solution, the setting threshold n set = 0.99, and the differential criterion ε = -0.01.

[0043] Correspondingly, the application also provides a metal return DC grid internal and external fault identification system, comprising:

[0044] A power grid topology design module is configured to obtain a topology structure of the metal return flexible DC grid.

[0045] A fault equivalent model module is configured to construct a Bergeron model according to the topology structure of the metal return flexible DC grid, and decouple by using a Kalman-Beltrami transformation to construct an equivalent model of the metal return flexible DC grid under different fault types.

[0046] A fault feature extraction module is configured to obtain expressions of the modal voltage fault component and the modal current fault component under different fault types according to the equivalent model of the metal return flexible DC grid under different fault types.

[0047] A similarity calculation module is configured to perform differential processing on the modal voltage and the modal current at different faults based on a normalized cross-correlation algorithm to obtain the traveling wave waveform at different faults, and quantitatively calculate the similarity between the traveling wave waveform corresponding to the fault type and the reference wave to obtain the similarity between the traveling wave waveform corresponding to the fault type and the reference wave.

[0048] A fault type determination module is configured to determine the fault type according to the similarity between the traveling wave waveform corresponding to the fault type and the reference waveform according to a pre-constructed differential criterion and a setting threshold.

[0049] A fault pole selection module is configured to construct a phase plane for fault type identification by using the fault current differential ratio according to the expressions of the modal voltage fault component and the modal current fault component under different fault types, and select a fault pole according to the determined fault type and the phase plane for fault type identification.

[0050] Compared with the prior art, the application has the following technical effects:

[0051] (1) The application realizes decoupling of the line by using the Kalman-Beltrami transformation and the Bergeron model of the DC line, solves the problem that the coupling characteristics of the metal return line are ignored in the existing protection method, avoids protection misoperation that may occur in actual engineering, and improves the safe and reliable operation of the system.

[0052] (2) The application is based on the normalized cross-correlation algorithm, and the similarity between the fault waveform and the reference waveform is compared, the method can tolerate a higher transition resistance, and the response speed of fault identification is improved, solving the problem that the current rises rapidly when the flexible DC system fails, and the system needs to respond quickly.

[0053] (3) The application uses the modulus current differential ratio to construct a phase plane for fault type identification, further realizes the selection of the fault polarity and the identification of the fault type, so that the fault polarity can be quickly and accurately determined. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to make the objectives, technical solutions and advantages of the application clearer, the following will further describe the application in detail with reference to the accompanying drawings, in which:

[0055] Figure 1 A flow chart of the metal return DC power grid internal and external fault identification method of the application;

[0056] Figure 2 A metal return flexible DC power grid topology structure diagram of an embodiment of the application;

[0057] Figure 3 A Bergeron model of a metal return flexible DC power grid transmission line of an embodiment of the application;

[0058] Figure 4 An equivalent circuit diagram when a positive pole grounding fault occurs in an embodiment of the application;

[0059] Figure 5 An equivalent circuit diagram when a positive and negative pole short circuit fault occurs in an embodiment of the application;

[0060] Figure 6 An equivalent circuit diagram when a positive pole and metal return line short circuit fault occurs in an embodiment of the application;

[0061] Figure 7 A modulus current differential ratio phase plane diagram of an embodiment of the application. DETAILED DESCRIPTION

[0062] In order to make the objectives, technical solutions and advantages of the embodiments of the application clearer, the following will further describe the technical solutions of the embodiments of the application with reference to the accompanying drawings of the embodiments of the application. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments. The components of the embodiments of the application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but only represents selected embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the application.

[0063] The application will be further described in detail below with reference to the accompanying drawings.

[0064] In view of the problems of easy rejection of the fault blocking and complex coupling relationship in the metal return flexible DC power grid, the application provides a metal return DC power grid internal and external fault identification method and system, the Bessel transformation is used, the Bergeron model of the line is combined, the metal return DC power grid fault equivalent model under the Bessel transformation is taken as the basis, the expression of the modulus voltage fault component and the modulus current fault component under different faults is derived, and a new DC line protection principle based on the normalized cross-correlation algorithm is provided based on the correlation between the voltage differential waveform similarity and the peak valley time, so that the fault type and position are accurately segmented, and the protection performance and operation safety of the power grid are improved.

[0065] As shown in Figure 1 The embodiment discloses a metal return DC power grid internal and external fault identification method, which comprises the following steps:

[0066] S1, acquiring the topological structure of the metal return flexible DC power grid;

[0067] S2, constructing the Bergeron model according to the topological structure of the metal return flexible DC power grid, and decoupling by using the Bessel transformation to obtain the metal return flexible DC power grid equivalent model under different fault types;

[0068] S3, obtaining the expression of the modulus voltage fault component and the modulus current fault component under different fault types according to the metal return flexible DC power grid equivalent model under different fault types;

[0069] S4, based on the normalized cross-correlation algorithm, differentiating the modulus voltage and the modulus current at different faults to obtain the traveling wave waveform at different faults, and quantitatively calculating the similarity between the traveling wave waveform of the corresponding fault type and the reference wave to obtain the similarity between the traveling wave waveform of the corresponding fault type and the reference wave;

[0070] S5, determining the fault type according to the similarity between the traveling wave waveform of the corresponding fault type and the reference waveform according to the pre-constructed differential criterion and the setting threshold; wherein the fault type comprises an internal fault, an external fault and an internal end fault;

[0071] S6, constructing the phase plane of the fault type identification by using the fault current differential ratio according to the expression of the modulus voltage fault component and the modulus current fault component under different fault types;

[0072] S7, selecting the pole according to the determined fault type and the phase plane of the fault type identification.

[0073] In the specific application implementation, in step S1, the topological structure of the metal return flexible DC power grid is as shown in Figure 2As shown in the topology diagram of the flexible DC power grid with metallic return based on modular multilevel converter stations, AC1 to A4 are four AC power sources, MMC1 to MMC4 are four converter stations, P, M, and N represent the positive transmission line, metallic return line, and negative transmission line, respectively. sr For a current-limiting reactor, R xx To protect the measuring device, DCCB is a DC circuit breaker, and f1 to f5 represent faults at different locations.

[0074] In this embodiment, step S2 specifically includes:

[0075] S201. Based on the topology of the metal return flexible DC power grid, construct the electrical quantity relationships between sub-circuits using the Berylon model, and decouple them using the Karen Bell transformation.

[0076] S202. Based on the Kelvin transform, analyze the fault types of different metal return flexible DC grids, obtain the boundary conditions corresponding to each fault type of different metal return flexible DC grids, and construct equivalent models of metal return flexible DC grids under different fault types according to the boundary conditions corresponding to each fault type.

[0077] In practical applications, the Beryllon model of a metal-return flexible DC power grid transmission line based on a modular multilevel converter station is as follows: Figure 3 As shown, for a bipolar DC system with a metallic return line, where the positive, neutral, and negative terminals are coupled in the polar component coordinate space, it is necessary to express the coordinates of the fault current i or voltage u in the standard base [x] of the real physical system. p ,x m ,x n ] T The polar mode transformation decomposes the model into coordinates [x1, x2, x0] in the mode domain. T Decoupling is achieved. In this embodiment, decoupling is achieved using the Kelvin transform decoupling matrix. The formula for decoupling using the Kelvin transform is as follows:

[0078]

[0079] In the formula, T K Let x be the decoupling matrix of the Kelenberg transformation. p x m x n x1, x2, and x0 are the coordinates of the fault current or voltage in the real physical system under standard conditions, respectively, and the coordinates of the module domain after Kelenberg transformation, respectively.

[0080] In practical applications, based on traveling wave propagation theory, the electrical quantity relationships between sub-circuits are constructed, and the formula for these relationships is as follows:

[0081] B k (s) = e -γ(s)l (2U m (s)-B m (s));

[0082] B m (s) = e -γ(s)l (2U k (s)-B k (s));

[0083] In the formula, B k (s) and B m (s) are equivalent voltage sources in the DC line Bergeon model, U k (s), U m (s), I k (s), I m (s) are the voltages and currents at the ends of the lines k and m, e -γ(s)l is a frequency-varying parameter

[0084] γ(s) = (Z a (s) Y a (s)) 1 / 2 ;

[0085] In the formula, γ(s) is the propagation coefficient of the fault traveling wave, l is the line length, Z a (s) and Y a (s) are the series impedance and shunt admittance per unit length of the transmission line, respectively;

[0086] In order to realize the time-domain analysis of DC line faults, the line frequency-varying parameter model needs to be reasonably simplified by reasonably simplifying the traveling wave propagation characteristics and DC control characteristics, and e -γ(s)l is approximated as:

[0087]

[0088] In the formula, K a / (1+sT a ) is the distortion and attenuation of the traveling wave in the propagation process, e -sl / v is the delay caused by the traveling wave along the line, v is the wave speed, K a represents the line attenuation proportionality coefficient, i.e., the ratio of the amplitude after the traveling wave propagates a distance l to the initial amplitude, T a is the line dispersion time constant, and 1 / (1+sT a ) represents the distortion degree of the wave shape after the traveling wave propagates a distance l relative to the initial wave shape.

[0089] As can be seen in this embodiment, the simplified frequency-varying parameters can not only accurately characterize the distortion and attenuation of the fault traveling wave, but also greatly simplify the calculation.

[0090] In this embodiment, the fault types of the different metal return flexible DC grids include single-pole grounding faults, pole-to-pole faults, and pole-to-return line faults; the single-pole grounding faults include positive-pole grounding faults and negative-pole grounding faults; the pole-to-pole faults are short-circuit faults between the positive and negative poles; the pole-to-return line faults include short-circuit faults between the positive and metal return lines and short-circuit faults between the negative and metal return lines.

[0091] In practical applications, based on the different fault types of flexible DC power grids with different metal return circuits, the corresponding polar and modal boundary conditions can be obtained. For example, faults occurring within the positive pole region of DC line Line 12 via the transition resistor R... f Taking a ground fault as an example, the phase domain boundary condition equation for the fault point (f3) is as follows:

[0092]

[0093] In the formula, U f U is the DC voltage at the fault point before the fault. fp I fp I fm and I fn These represent the voltage at the positive fault point, and the current flowing into the positive, neutral, and negative fault points, respectively.

[0094] Based on the decoupling matrix T using polar mode transformation K Its modular domain form equation can be obtained as follows:

[0095]

[0096] Similarly, assume that a short-circuit fault occurs in the positive and negative terminals of DC line Line 12 through the transition resistor Rf. The phase domain boundary condition equation at the fault point is:

[0097]

[0098] Based on the decoupling matrix T using polar mode transformation K Its modular domain form equation can be obtained as follows:

[0099]

[0100] Similarly, assuming that the positive terminal of DC line 12 connects to the metal return line via the transition resistor R f Short-circuit fault. The phase domain boundary condition equations at the fault point are:

[0101]

[0102] According to the decoupling matrix T K , the equation in the form of its modulus field can be obtained as:

[0103]

[0104] According to the boundary conditions corresponding to each fault, the equivalent model of the metal return flexible DC power grid under different fault types is obtained as shown in Figure 4 、 Figure 5 、 Figure 6 In the embodiment, according to the equivalent model of the metal return flexible DC power grid under different fault types, the expression of the modulus field voltage fault component and the modulus field current fault component corresponding to different fault types can be obtained, so as to obtain the frequency variation characteristics of the fault current and voltage. In the specific application, when the positive pole grounding fault occurs, the expression of the modulus field voltage fault component and the modulus field current fault component is:

[0105]

[0106] When the positive pole and negative pole short circuit fault occurs, the expression of the modulus field voltage fault component and the modulus field current fault component is:

[0107]

[0108] When the positive pole and metal return line short circuit fault occurs, the expression of the modulus field voltage fault component and the modulus field current fault component is:

[0109]

[0110] In the formula, U R2 , U R1 and U R0 are respectively the 2nd modulus field voltage, the 1st modulus field voltage and the 0th modulus field voltage measured after the fault occurs; I R2 , I R1 and I R0 are respectively the 2nd modulus field current, the 1st modulus field current and the 0th modulus field current measured after the fault occurs; Lsr is the smoothing reactor; Z MAC1 is the equivalent impedance of the converter MMC1; Z c2 , Z c1 and Z c0 are respectively the 2nd modulus field, the 1st modulus field and the 0th modulus field wave impedance of the DC line; B KR2 , B KR1 and B KR0 are respectively the 2nd modulus field, the 1st modulus field and the 0th modulus field equivalent voltage source of the K terminal in the Berrengueron model of the DC line measured by the measuring device after the fault occurs; (s) represents the Laplace transform.

[0111] The boundary conditions for negative pole grounding fault and negative pole short circuit fault to metal return line are obtained from the above. However, since negative pole grounding fault and negative pole short circuit fault to metal return line cannot form a fault equivalent model of metal return flexible DC grid, the expressions of the mode domain voltage fault component and mode domain current fault component under the fault cannot be obtained.

[0112] Based on the established expressions for the fault components of the modal voltage and current, the influence of the transition resistance on the fault signal characteristics can be analyzed. Thus, it can be concluded that the transition resistance only affects the amplitude of the fault modal voltage and current, and does not affect the peak-valley time.

[0113] In practical application, in step S4, the traveling wave waveform is the differential waveform of the fault voltage in the first mode domain, that is, let du R1 The time when / dt reaches its minimum value is the peak-to-valley time t. v The transition resistance R is obtained from the expressions for the voltage fault component and the current fault component in the mode domain. f It only affects the amplitude of the fault modulus voltage and current measured at the protection point, and does not affect t. v To avoid any impact, in this embodiment, the reference waveform is set as the first-mode fault voltage micro-component du at the positive high-resistance (1000Ω) ground point at the end of the region. R1 The waveform of / dt is used to obtain the similarity between the traveling wave waveform inside and outside the area and the reference waveform based on the normalized cross-correlation algorithm, thereby identifying faults inside and outside the area. The specific formula is as follows:

[0114]

[0115] In the formula, n c Let be the normalized cross-correlation similarity between the traveling wave waveform and the reference waveform, N be the sampling length of the waveform signal, x be the traveling wave waveform signal, y be the reference waveform signal, x[i] be the sampled value of the traveling wave waveform signal x at time point i, y[j] be the sampled value of the reference waveform signal y at time points j, and μ be the reference waveform signal y at time points j. x and μ y Let x and y represent the signal sampling mean values, respectively.

[0116] In practical applications, in step S5, the normalized cross-correlation coefficient ranges from -1 to 1, where 1 represents a perfect match, 0 represents no correlation, and -1 represents a complete opposite. c <ε indicates an internal fault has occurred, while ε <n c <n set This indicates that an external fault has occurred; therefore, the protection criterion is:

[0117]

[0118] In the formula, n setLet n be the tuning threshold, ε be the differential criterion, and n be the variable. c This is the normalized cross-correlation coefficient.

[0119] To account for errors caused by end-point faults within the zone, n is set. set =0.99, and to avoid errors during data measurement, set ε = -0.01.

[0120] In practical application, in step S6, based on the modular multilevel converter station's metal return flexible DC grid, the fault current differential ratio is used to construct, as shown in step S6. Figure 7 The phase plane for fault type identification is shown. When a fault is determined to occur within the fault zone, the ratio of the differential component of the fault current in the first mode domain to the differential component of the fault current in the second mode domain is used, i.e., (di... R1 The ratio of ( / dt) / (di / dt) to the differential component of the fault current in the 0th mode and the differential component of the fault current in the 1st mode, i.e. (di / dt) R0 / dt) / (di R1 / dt), thus distinguishing five typical fault types: positive to ground fault (PG), negative to ground fault (NG), positive and negative short circuit (PN), positive to return line short circuit (PM), and negative to return line short circuit (NM), as shown in Table 1:

[0121] Table 1. Fault Modulus Differential Current Characteristics under Different Fault Types

[0122]

[0123] In summary, the above embodiments verify the correctness and feasibility of the present invention.

[0124] This invention proposes a fault identification method based on waveform similarity, utilizing the correlation between voltage differential waveform similarity and peak-valley time. After quantitatively analyzing traveling wave differences using a normalized cross-correlation algorithm, the fault type can be determined. The phase plane is constructed using the differential ratio of the fault current, thereby enabling fault pole selection. This invention can complete fault identification within an extremely short time and can identify high-resistance faults, which is difficult to achieve with traditional traveling wave protection methods, thus improving the safety and reliability of the power grid. Because this invention is based on the Kelvin transform and the Beryllon model, it solves the coupling characteristics of metallic loops, thereby more accurately identifying fault conditions in the power grid.

[0125] Based on the above-mentioned method for identifying faults inside and outside a metal-return DC power grid area, the present invention also provides a system for identifying faults inside and outside a metal-return DC power grid area, comprising:

[0126] The power grid topology design module is used to obtain the topology of a metal-backflow flexible DC power grid.

[0127] A fault equivalent model module is configured to construct a Bergeon model according to a topological structure of the metal reflux flexible DC power grid, and decouple by using a Kalman-Bell transformation, thereby constructing an equivalent model of the metal reflux flexible DC power grid under different fault types;

[0128] A fault feature extraction module is configured to obtain expressions of the modal voltage fault component and the modal current fault component under different fault types according to the equivalent model of the metal reflux flexible DC power grid under different fault types.

[0129] A similarity calculation module is configured to perform differential processing on the modal voltage and the modal current at different faults based on a normalized cross-correlation algorithm, thereby obtaining the traveling wave waveform at different faults, and quantitatively calculating the similarity between the traveling wave waveform corresponding to the fault type and the reference wave, thereby obtaining the similarity between the traveling wave waveform corresponding to the fault type and the reference wave.

[0130] A fault type determination module is configured to determine the fault type according to the similarity between the traveling wave waveform corresponding to the fault type and the reference waveform according to a pre-constructed differential criterion and a setting threshold.

[0131] A fault pole selection module is configured to construct a phase plane for fault type identification by using a fault current differential ratio according to the expressions of the modal voltage fault component and the modal current fault component under different fault types, and to perform fault pole selection according to the determined fault type and the phase plane for fault type identification.

[0132] The application is based on the difference in waveform similarity of the traveling wave waveform under intra-zone fault and extra-zone fault, and proposes a metal reflux DC power grid fault identification method and system based on a normalized cross-correlation algorithm. When the method and system determine an intra-zone fault, the fault pole is selected according to the ratio of the modal fault current differential component. The method and system can tolerate a transition resistance of up to 1000Ω or more, and can reliably identify faults and act within 1ms even under large transition resistance changes, thereby significantly improving the efficiency of fault identification.

[0133] Finally, it should be pointed out that the above examples are only used to illustrate the technical solutions of the application and are not limiting. Although the application has been described by referring to the preferred embodiments of the application, those skilled in the art should understand that various changes can be made in form and details without departing from the spirit and scope of the application as defined in the appended claims.

Claims

1. A method for identifying internal and external faults in a metal return DC grid, characterized by, The method comprises the following steps: S1, obtaining the topology structure of the metal return flexible DC power grid; S2, constructing a Bergeron model according to the topology structure of the metal return flexible DC power grid, and decoupling by using the Krylov-Bogoliubov transformation to obtain an equivalent model of the metal return flexible DC power grid under different fault types; S3, obtaining the expression of the modal voltage fault component and the modal current fault component under different fault types according to the equivalent model of the metal return flexible DC power grid under different fault types; S4, based on the normalized cross-correlation algorithm, differentiating the modal voltage and the modal current at different fault positions to obtain the traveling wave waveform at different fault positions, and quantitatively calculating the similarity between the traveling wave waveform corresponding to the fault type and the reference wave to obtain the similarity between the traveling wave waveform corresponding to the fault type and the reference wave; S5, determining the fault type according to the similarity between the traveling wave waveform corresponding to the fault type and the reference waveform according to the pre-constructed differential criterion and setting threshold; wherein the fault type includes an internal fault, an external fault and an internal end fault; S6, constructing a phase plane for fault type identification by using the fault current differential ratio according to the expression of the modal voltage fault component and the modal current fault component under different fault types; S7, selecting the fault pole according to the determined fault type and the phase plane for fault type identification.

2. The method of claim 1, wherein, The step S2 is specifically: S201, constructing the electrical quantity relationship between sub-circuits based on the Bergeron model according to the topology structure of the metal return flexible DC power grid, and decoupling by using the Krylov-Bogoliubov transformation; S202, analyzing the fault types of different metal return flexible DC power grids based on the Krylov-Bogoliubov transformation, obtaining the boundary conditions corresponding to each fault type of different metal return flexible DC power grids, and constructing the equivalent model of the metal return flexible DC power grid under different fault types according to the boundary conditions corresponding to each fault type.

3. The method of claim 2, wherein, In step S201, the formula for constructing the electrical quantity relationship between sub-circuits based on the Bergeron model is: B k (s) = e -γ(s)l (2U m (s)-B m (s)) B m (s) = e -γ(s)l (2U k (s)-B k (s)) where B k (s) and B m (s) are the equivalent voltage sources in the DC line Bergeon model, U k (s) and U m (s) and I k (s) and I m (s) are the voltage and current at the ends of the lines k, m, respectively, and γ(s) is the propagation coefficient of the fault traveling wave, and l is the line length.

4. The method of claim 2, wherein, In step S201, the formula for decoupling by using the Krylov-Bogoliubov transformation is: where T K is the Kalman transformation decoupling matrix, x p , x m , x n are the coordinates of the fault current or voltage in the real physical system under the standard, and x1, x2, x0 are the coordinates in the modular domain after the Kalman transformation.

5. The method of claim 2, wherein, In step S202, the fault types of different metal return flexible DC power grids include a single-pole grounding fault, a pole-to-pole fault and a pole-to-return line fault; The single-pole grounding fault includes a positive pole grounding fault; The pole-to-pole fault is a short circuit fault between a positive pole and a negative pole; The pole-to-return line fault includes a short circuit fault between a positive pole and a metal return line.

6. The method of claim 1, wherein, In step S3, the expression of the modal voltage fault component and the modal current fault component under different fault types specifically includes: When the positive pole grounding fault occurs: When the short circuit fault between the positive pole and the negative pole occurs: When the short circuit fault between the positive pole and the metal return line occurs: wherein U R2 , U R1 , and U R0 are the 2nd, 1st and 0th modal voltages measured after the fault, respectively; I R2 , I R1 , and I R0 are the 2nd, 1st and 0th modal currents measured after the fault, respectively; Lsr is the smoothing reactor; Z MAC1 is the equivalent impedance of the converter MMC1; Z c2 , Z c1 , and Z c0 are the 2nd, 1st and 0th modal wave impedances of the DC line, respectively; B KR2 , B KR1 , and B KR0 are the 2nd, 1st and 0th modal equivalent voltage sources at the K end of the Berrengueron model of the DC line measured by the measuring device after the fault; (s) represents the Laplace transform.

7. The method of claim 1, wherein, In step S4, the reference wave is the first modal domain fault voltage differential waveform occurring at the internal end resistance grounding position; and the traveling wave waveform is the first modal domain fault voltage differential waveform; The formula for quantitatively calculating the similarity between the traveling wave waveform corresponding to the fault type and the reference waveform based on the normalized cross-correlation algorithm is: where n c is the normalized cross-correlation similarity between the traveling wave waveform and the reference waveform, N is the sampling length of the waveform signal, x is the traveling wave waveform signal, y is the reference waveform signal, x[i] is the sampling value of the traveling wave waveform signal x at the i-th time point, y[j] is the sampling value of the reference waveform signal y at the j-th time point, μ x and μ y respectively represent the signal sampling mean values of x and y.

8. The method of claim 1, wherein, In step S5, the differential criterion and the setting threshold are specifically: where n set is the set threshold, ε is the differential criterion, and n c is the normalized cross-correlation coefficient.

9. The method of claim 8, wherein, The setting threshold n set = 0.99, the differential criterion ε = -0.

01.

10. A fault identification system for internal and external areas of a metal-return DC power grid, characterized in that, including: A power grid topology design module is configured to obtain a topology structure of the metal-reflux flexible HVDC power grid. A fault equivalent model module is configured to construct a Bergeon model according to the topology structure of the metal-reflux flexible HVDC power grid, and decouple the Bergeon model by using a Karen Bell transformation to construct an equivalent model of the metal-reflux flexible HVDC power grid under different fault types. A fault feature extraction module is configured to obtain expressions of the modal voltage fault component and the modal current fault component under different fault types according to the equivalent model of the metal-reflux flexible HVDC power grid under different fault types. A similarity calculation module is configured to perform differential processing on the modal voltage and the modal current at different faults based on a normalized cross-correlation algorithm to obtain a traveling wave waveform at the different faults, and quantitatively calculate a similarity between the traveling wave waveform corresponding to the fault type and a reference wave to obtain the similarity between the traveling wave waveform corresponding to the fault type and the reference wave. A fault type determination module is configured to determine the fault type according to the similarity between the traveling wave waveform corresponding to the fault type and the reference wave based on a pre-constructed differential criterion and a setting threshold. A fault pole selection module is configured to construct a phase plane for fault type identification by using a fault current differential ratio according to the expressions of the modal voltage fault component and the modal current fault component under different fault types, and select a fault pole according to the determined fault type and the phase plane for fault type identification.

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