Transformer short circuit fault identification method and system

Abstract

The invention discloses a transformer short-circuit fault identification method and system. The method comprises the following steps: establishing a field-circuit coupling model of a distribution transformer; performing simulation according to the field-circuit coupling model to obtain each state quantity when single-phase short circuit occurs at different positions of the low-voltage winding of the distribution transformer; calculating the maximum change rate of each state quantity when the single-phase short circuit occurs at different positions; selecting an optimal state quantity according to the maximum change rate of all state quantities when single-phase single-turn short circuit occurs at different positions; simulating according to a field-circuit coupling model to obtain the maximum change rate of the optimal state quantity under different insulation resistances and different numbers of short-circuit turns of the low-voltage winding of the distribution transformer, and obtaining a first threshold value of the change rate and a second threshold value of the change rate; and during actual operation of the distribution transformer, judging whether the distribution transformer has a fault or not and judging the fault phase according to the optimal state quantity obtained in real time and the first threshold value and the second threshold value of the change rate.

Description

Technical Field

[0001] This invention belongs to the field of online monitoring and fault diagnosis technology for power equipment, and more specifically, relates to a method and system for identifying transformer short-circuit faults. Background Technology

[0002] Distribution transformers are critical equipment in power distribution networks, and their operational reliability directly affects power supply quality. Inter-turn short-circuit faults are among the most common internal faults in transformers, accounting for over 50% of all internal faults, according to statistics. When such a fault occurs, the current within the short-circuit turn can reach tens of times the rated value, generating enormous heat and electrodynamic forces, rapidly leading to insulation failure and equipment malfunction.

[0003] Currently, detection methods for inter-turn short-circuit faults in transformers mainly include DC resistance testing, short-circuit impedance methods, voltage ratio measurement, and frequency sweep short-circuit impedance methods. However, most of these methods are offline or preventative testing items, requiring the transformer to be taken out of operation, and cannot achieve real-time online monitoring. Furthermore, when an inter-turn short circuit occurs in the line, due to the large impedance of the fault circuit, the change in the transformer's main circuit current is minimal, usually insufficient to trigger traditional overcurrent protection devices (such as fuses or overcurrent relays), resulting in the fault not being cleared in time, thus escalating into serious equipment damage and power outage accidents. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for identifying transformer short-circuit faults.

[0005] The present invention adopts the following technical solution.

[0006] The first aspect of this invention proposes a method for identifying transformer short-circuit faults, comprising: A three-dimensional geometric model and short-circuit equivalent circuit of the distribution transformer are constructed. The three-dimensional geometric model and short-circuit equivalent circuit are coupled in a field-circuit manner to establish a field-circuit coupled model. The state quantities of the distribution transformer when a single-phase short circuit occurs at different positions of the low-voltage winding are obtained by simulation based on the field-circuit coupling model. The state quantities include short-circuit loop current, spatial magnetic field strength, winding power loss and force acting on the bend. The difference between the maximum value of each state quantity when a single-phase short circuit occurs at different positions and the corresponding rated value is calculated and divided by the corresponding rated value to obtain the maximum rate of change of the corresponding state quantity when a single-phase short circuit occurs at the corresponding position. The optimal state variable is selected based on the maximum rate of change of all state variables when a single-phase single-turn short circuit occurs at different locations. The maximum rate of change of the optimal state quantity of the low-voltage winding of the distribution transformer under different insulation resistances and different short-circuit turns is obtained by simulation based on the field-circuit coupling model, and the first threshold and the second threshold of the rate of change are obtained. When a distribution transformer is actually in operation, the system determines whether the distribution transformer is faulty and the faulty phase based on the real-time acquired optimal state variables and the first and second thresholds of the rate of change.

[0007] Preferably, the construction of the three-dimensional geometric model of the distribution transformer specifically involves: The three-dimensional geometric model of a distribution transformer includes a three-phase model. Each phase model consists of a transformer core, a low-voltage internal winding, a low-voltage external winding, and a high-voltage winding. Each turn of the low-voltage internal winding and the low-voltage external winding is numbered.

[0008] Preferably, the short-circuit equivalent circuit is as follows: The short-circuit equivalent circuit includes the high-voltage side equivalent circuit and the low-voltage side equivalent circuit; The equivalent circuit on the high-voltage side is as follows: one end of the high-voltage side operating phase voltage of each phase is grounded, and the other end is connected to one end of the self-inductance of the high-voltage winding through the winding resistance of the corresponding phase's high-voltage winding. The other ends of the self-inductance of the high-voltage windings of all phases are connected together. The equivalent circuit on the low-voltage side is as follows: For two phases that are not short-circuited, one end of the winding resistance of the low-voltage winding of all phases is connected; the other end of the winding resistance of the low-voltage winding of each phase is connected to ground in sequence through the self-inductance of the low-voltage winding of the corresponding phase and the load impedance of the corresponding phase; the low-voltage winding consists of an internal low-voltage winding and an external low-voltage winding. For a short-circuited phase, the winding resistance and self-inductance of the low-voltage winding of the corresponding phase are divided into two parts. One end of the first winding resistance of the low-voltage winding of the corresponding phase is connected to one end of the winding resistance of the low-voltage winding of the two phases that are not short-circuited; the other end of the first winding resistance of the low-voltage winding of the corresponding phase is connected to one end of the short-circuit equivalent circuit through the first self-inductance of the low-voltage winding of the corresponding phase; the other end of the short-circuit equivalent circuit is connected to ground in sequence through the second self-inductance of the low-voltage winding of the corresponding phase, the second winding resistance of the low-voltage winding of the corresponding phase, and the load impedance of the corresponding phase.

[0009] Preferably, if the short circuit is a single-turn short circuit, the short circuit loop is as follows: the equivalent inductance and equivalent resistance of the short-circuited turn are connected in series to form a series structure, and the series structure is connected in parallel with the insulation resistance of the short-circuit point when the single-turn short circuit occurs. If the short circuit is a multi-turn short circuit, the short circuit loop is as follows: the equivalent inductance and equivalent resistance of each short-circuited turn are connected in series to form a branch. All branches corresponding to the short-circuited turns are connected in parallel, and then connected in parallel with an equivalent insulation resistance characterizing the insulation state of the short-circuit point. Preferably, the selection of the optimal state variable based on the maximum rate of change of all state variables when a single-phase, single-turn short circuit occurs at different locations specifically involves: The different positions refer to each turn of the low-voltage inner winding and each turn of the low-voltage outer winding. For each state variable, the maximum rate of change of the corresponding state variable when a single-turn short circuit occurs in each turn of the inner winding of the low-voltage winding is obtained to form the inner winding sequence, and the maximum rate of change of the corresponding state variable when a single-turn short circuit occurs in each turn of the outer winding of the low-voltage winding is obtained to form the outer winding sequence. The inner winding sequence and the outer winding sequence are spliced ​​together to form a total sequence. The maximum value in the total sequence of each state variable is used as the sensitivity index of the corresponding state variable. The reciprocal of the standard deviation of the total sequence for each state variable is used as the stability index of the corresponding state variable. Calculate the absolute value of the difference between the average value of the inner winding sequence and the average value of the outer winding sequence for each state variable, and use the reciprocal of the absolute value as the discrimination index. The sensitivity index, stability index, and discrimination index are weighted and summed according to the set weights to obtain the final evaluation index of the corresponding state quantity. The state quantity with the largest evaluation index is taken as the optimal state quantity.

[0010] Preferably, obtaining the first threshold and the second threshold of the rate of change specifically involves: Set critical resistance values ​​for insulation degradation and insulation collapse, with the critical resistance value for insulation degradation being greater than the critical resistance value for insulation collapse. Multiple simulations are performed. In the first simulation, the insulation resistance is set to the initial value, and the number of short-circuit turns is set to 1. If the current insulation resistance is greater than or equal to the critical insulation degradation value, the insulation resistance in the next simulation is the insulation resistance in the current simulation divided by the set attenuation coefficient, and the number of short-circuit turns remains unchanged. If the current insulation resistance is less than the critical insulation degradation value, the insulation resistance in the next simulation is the insulation resistance in the current simulation divided by the set attenuation coefficient, and the number of short-circuit turns increases by a set constant value. The maximum rate of change of the optimal state variable is recorded in each simulation. If the current insulation resistance is less than the critical insulation collapse value and the number of short-circuit turns increases to the set maximum number of turns threshold, the simulation is stopped. The maximum value among the maximum rates of change of the optimal state variables corresponding to all insulation resistance values ​​that are greater than or equal to the critical insulation degradation value is used as the first threshold of the rate of change. The maximum value among the maximum rates of change of the optimal state variables corresponding to all simulations where the insulation resistance value is less than the critical insulation degradation value is obtained as the second threshold of the rate of change. When the number of short-circuit turns is 1, the insulation resistance is the insulation resistance of the short-circuit point when the series structure is short-circuited and a single turn is short-circuited; otherwise, the insulation resistance is the equivalent insulation resistance that characterizes the insulation state of the short-circuit point.

[0011] Preferably, determining whether the distribution transformer is faulty involves: Obtain the current load rate and the optimal state quantity of each phase. Obtain the reference value of the optimal state quantity under the current load rate. Calculate the difference between the optimal state quantity of each phase and the reference value, and divide the reference value by the reference value to obtain the real-time change rate of the corresponding phase. If the real-time change rate of at least one phase is greater than or equal to the first threshold of change rate and less than the second threshold of change rate, it is judged as an inter-turn insulation abnormality. If the real-time change rate of at least one phase exceeds the second threshold of change rate, it is judged as a short-circuit fault. Otherwise, the inter-turn insulation is normal.

[0012] Preferably, obtaining the baseline value of the optimal state quantity under the current load rate specifically involves: First, establish a mapping relationship between the baseline values ​​of each state quantity, excluding winding power loss, and the load rate based on historical data; When the optimal state quantity is the winding power loss, the reference value of the optimal state quantity is equal to the square of the current load rate multiplied by the winding load loss of the transformer under rated load plus the no-load loss of the transformer. When the optimal state variable is not the winding power loss, the optimal state variable corresponding to the current load rate is obtained.

[0013] Preferably, determining the faulty phase specifically involves: The real-time change rate of each phase at the moment when an inter-turn insulation abnormality or short-circuit fault is determined is divided by the total real-time change rate to obtain the proportion of the corresponding phase. The total real-time change rate is the sum of the real-time change rates of all phases. If the proportion of a phase exceeds a set proportion threshold, it indicates that the corresponding phase is a fault phase; otherwise, it is considered an abnormal state.

[0014] The second aspect of this invention proposes a transformer short-circuit fault identification system based on the method described in the first aspect of this invention, comprising: a field-circuit coupling model construction module, a maximum rate of change acquisition module, an optimal state variable selection module, a rate of change threshold setting module, and a fault identification module, specifically: Field-circuit coupling model construction module: Constructs a three-dimensional geometric model and short-circuit equivalent circuit of the distribution transformer, performs field-circuit coupling on the three-dimensional geometric model and the short-circuit equivalent circuit, and establishes a field-circuit coupling model; Maximum rate of change module: Based on the field-circuit coupling model simulation, the state quantities of the distribution transformer at different positions of the low-voltage winding when a single-phase short circuit occurs are obtained. The state quantities include short-circuit loop current, spatial magnetic field strength, winding power loss and force acting on the bend; the difference between the maximum value of each state quantity at different positions of a single-phase short circuit and the corresponding rated value is divided by the corresponding rated value, which is taken as the maximum rate of change of the corresponding state quantity at the corresponding position of a single-phase short circuit. Optimal state quantity selection module: Selects the optimal state quantity based on the maximum rate of change of all state quantities when a single-phase single-turn short circuit occurs at different locations; Change rate threshold setting module: Based on the field-circuit coupling model simulation, the maximum change rate of the optimal state quantity of the low-voltage winding of the distribution transformer under different insulation resistances and different short-circuit turns is obtained, and the first and second change rate thresholds are obtained. Fault identification module: When the distribution transformer is actually running, it determines whether the distribution transformer is faulty and the faulty phase based on the real-time acquired optimal state quantity and the first and second thresholds of the rate of change.

[0015] The beneficial effects of this invention are as follows: Compared with the prior art, this invention selects one of various state variables, such as winding power loss, as the optimal state variable through simulation, and uses the change rate of the optimal state variable as the core criterion. This achieves highly sensitive identification and early warning of inter-turn short-circuit faults in transformers, enabling timely detection of insulation degradation risks before the main circuit current increases significantly. Combined with a set critical resistance value for insulation, the judgment threshold is calibrated by simulating fault paths of decreased resistance and increased number of turns, covering a wider range of fault types, thus making the diagnostic system more robust and reliable. Simultaneously, this method also possesses fault phase location capabilities and requires only conventional instrument transformer signals, eliminating the need for special sensors. This provides an efficient and practical technical means for online monitoring and proactive early warning of the insulation status of distribution transformers. Attached Figure Description

[0016] Figure 1 This is a three-dimensional model of the distribution transformer proposed in this invention; Figure 2 This is a schematic diagram of the number of turns in the winding of the distribution transformer proposed in this invention; Figure 3 This is the equivalent circuit diagram of single-turn short circuit and multi-turn short circuit of the distribution transformer proposed in this invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0018] Embodiment 1 of the present invention proposes a method for identifying transformer short-circuit faults, comprising: A three-dimensional geometric model and short-circuit equivalent circuit of the distribution transformer are constructed. The three-dimensional geometric model and short-circuit equivalent circuit are coupled in a field-circuit manner to establish a field-circuit coupled model. It should be noted that the constructed field-circuit coupling model needs to be verified through no-load tests, short-circuit tests, and short-circuit loop current tests to ensure that the maximum error of key parameters (such as no-load loss, load loss, and short-circuit impedance) between the simulated values, theoretical calculation values, and measured values ​​is less than 5%, so as to ensure the accuracy and reliability of the model.

[0019] The state quantities of a distribution transformer when a single-phase short circuit occurs at different positions of the low-voltage winding are obtained by simulation based on the field-circuit coupling model. The state quantities include short-circuit loop current, spatial magnetic field strength, winding power loss and force acting on the bend. The difference between the maximum value and the corresponding rated value of each state quantity when a single-phase short circuit occurs at different locations is divided by the corresponding rated value, which is used as the maximum rate of change of the corresponding state quantity when a single-phase short circuit occurs at the corresponding location. The optimal state variable is selected based on the maximum rate of change of all state variables when a single-phase single-turn short circuit occurs at different locations. The maximum rate of change of the optimal state quantity of the low-voltage winding of the distribution transformer under different insulation resistances and different short-circuit turns is obtained by simulation based on the field-circuit coupling model, and the first threshold and the second threshold of the rate of change are obtained. When a distribution transformer is actually in operation, the system determines whether the distribution transformer is faulty and the faulty phase based on the real-time acquired optimal state variables and the first and second thresholds of the rate of change.

[0020] In this preferred embodiment, the construction of the three-dimensional geometric model of the distribution transformer specifically involves: The three-dimensional geometric model of a distribution transformer includes a three-phase model. Each phase model consists of a transformer core, a low-voltage internal winding, a low-voltage external winding, and a high-voltage winding. Each turn of the low-voltage internal winding and the low-voltage external winding is numbered.

[0021] Specifically, the computational domain of the three-dimensional geometric model of the distribution transformer is drawn based on the actual dimensions of the tank casing, such as... Figure 1 As shown. The material properties of each winding, core, and transformer oil in the three-dimensional geometric model of the distribution transformer are set based on actual properties. Furthermore, Figure 1 L1 and L2 are simulation models of each inner and outer coil of the low-voltage winding a phase from top to bottom, as detailed below. Figure 2 As shown; exist Figure 2 In the diagram, 1 represents the transformer core, 2 represents the low-voltage internal winding, 3 represents the low-voltage external winding, and 4 represents the high-voltage winding. Each turn of the low-voltage internal winding and the low-voltage external winding is numbered, i.e., the first to sixteenth turns of the low-voltage external winding are W1-W16, and the first to sixteenth turns of the low-voltage internal winding are N1-N16.

[0022] In this preferred embodiment, the short-circuit equivalent circuit is specifically: The short-circuit equivalent circuit includes the high-voltage side equivalent circuit and the low-voltage side equivalent circuit; The equivalent circuit on the high-voltage side is as follows: one end of the high-voltage side operating phase voltage of each phase is grounded, and the other end is connected to one end of the self-inductance of the high-voltage winding through the winding resistance of the corresponding phase's high-voltage winding. The other ends of the self-inductance of the high-voltage windings of all phases are connected together. The equivalent circuit on the low-voltage side is as follows: For two phases that are not short-circuited, one end of the winding resistance of the low-voltage winding of all phases is connected; the other end of the winding resistance of the low-voltage winding of each phase is connected to ground in sequence through the self-inductance of the low-voltage winding of the corresponding phase and the load impedance of the corresponding phase; the low-voltage winding consists of an internal low-voltage winding and an external low-voltage winding. For a short-circuited phase, the winding resistance and self-inductance of the low-voltage winding of the corresponding phase are divided into two parts. One end of the first winding resistance of the low-voltage winding of the corresponding phase is connected to one end of the winding resistance of the low-voltage winding of the two phases that are not short-circuited; the other end of the first winding resistance of the low-voltage winding of the corresponding phase is connected to one end of the short-circuit equivalent circuit through the first self-inductance of the low-voltage winding of the corresponding phase; the other end of the short-circuit equivalent circuit is connected to ground in sequence through the second self-inductance of the low-voltage winding of the corresponding phase, the second winding resistance of the low-voltage winding of the corresponding phase, and the load impedance of the corresponding phase.

[0023] In this preferred embodiment, if the short circuit is a single-turn short circuit, the short circuit loop is as follows: the inductance and resistance of the short circuit loop formed when the single-turn short circuit is connected in series to form a series structure, and the series structure is connected in parallel with the insulation resistance of the short circuit point when the single-turn short circuit is short-circuited. If the short circuit is a multi-turn short circuit, the short circuit loop is as follows: the equivalent inductance and equivalent resistance of each short-circuited turn are connected in series to form a branch. After all the branches corresponding to the short-circuited turns are connected in parallel, they are then connected in parallel with an equivalent insulation resistance that characterizes the insulation state of the short-circuit point.

[0024] Specifically, by coupling the geometric model of the distribution transformer with the external circuit, a "field-circuit" coupled model can be established. The external equivalent circuits for single-turn and multi-turn short circuits are as follows: Figure 3 As shown. Figure 3 Middle,U A U B U C I is the operating phase voltage on the high-voltage side of the transformer. A I B I C I represents the phase current of each phase winding on the high-voltage side. a I b I c R represents the phase current of each phase winding on the low-voltage side. A R B R C R represents the winding resistance of each phase winding on the high-voltage side. a Ra2 The resistance of the first and second windings of phase A on the low-voltage side (phase A is the fault phase); R b R c L is the winding resistance of the low-voltage side B-phase and C-phase windings; A L B L C For the self-inductance of each phase winding on the high-voltage side; L a1 L a2 The self-inductance of the first and second windings of phase A on the low-voltage side (phase A is the fault phase); L b L c Z represents the self-inductance of the low-voltage side B-phase and C-phase windings; A Z B Z C M is the load impedance; Aa1 M Aa2 M Aad1 M Bb M cc Mutual inductance between high and low voltage sides; M ad1a1 M ad1a2 M a1a2 For the mutual inductance between the low-voltage side winding and the faulty turn; L ad1 R ad1 I represents the inductance and resistance of the short-circuit loop when a single turn is short-circuited. d1 R is the short-circuit loop current flowing through the short-circuit point when a single-turn short circuit occurs. dld1 L is the insulation resistance at the short-circuit point during a single-turn short circuit. adn and R adn I represents the inductance and resistance between each faulty turn during a multi-turn short circuit. dn It is the current flowing through the short-circuit point during a multi-turn short circuit; R dln It is the equivalent insulation resistance that characterizes the insulation state at the short-circuit point. Therefore, it can be adjusted by changing R. dld1 R dldn This is to achieve the deterioration of the inter-turn insulation of the transformer windings.

[0025] In this preferred embodiment, the step of selecting the optimal state variable based on the maximum rate of change of all state variables when a single-phase single-turn short circuit occurs at different locations specifically involves: For each state variable, the maximum rate of change of the corresponding state variable when a single-turn short circuit occurs in the first to Nth turns of the low-voltage winding is obtained to form the inner winding sequence. The maximum rate of change of the corresponding state variable when a single-turn short circuit occurs in the first to Mth turns of the low-voltage winding is obtained to form the outer winding sequence. N is the total number of turns in the low-voltage inner winding, and M is the total number of turns in the low-voltage outer winding. The inner winding sequence and the outer winding sequence are spliced ​​together to form a total sequence X containing N+M maximum rates of change. The maximum value in the total sequence of each state variable is used as the sensitivity index of the corresponding state variable. Specifically, the formula for the sensitivity index is: ; in, The sensitivity index directly reflects the response amplitude of the state quantity to a short-circuit fault; the larger the value, the more sensitive the condition.

[0026] The reciprocal of the standard deviation of the total sequence for each state variable is used as the stability index of the corresponding state variable. The formula for the stability index is:

[0027] in, For stability indicators; is the standard deviation of the sequence; this index measures the consistency of the response of a state quantity. The smaller the standard deviation or other measure of fluctuation (such as the coefficient of variation), the more stable the change of the quantity caused by short circuits at different locations, and the larger its reciprocal. Calculate the absolute value of the difference between the average value of the inner winding sequence and the average value of the outer winding sequence for each state variable, and use the reciprocal of the absolute value as the discrimination index. The formula for the discrimination index is:

[0028] in, , These are the average values ​​of the inner and outer winding sequences, respectively. This index considers the consistency of the behavior of state variables under the structural differences between the inner and outer windings of the transformer. The smaller the difference, the more similar the response characteristics of the inner and outer windings are; its reciprocal... S div The larger the value, the less the state variable is affected by the winding structure position, and the more universal it is.

[0029] The sensitivity index, stability index, and discrimination index are weighted and summed according to the set weights to obtain the final evaluation index of the corresponding state quantity. The state quantity with the largest evaluation index is taken as the optimal state quantity.

[0030] In this preferred embodiment, obtaining the first threshold and the second threshold of the rate of change specifically involves: Set critical resistance values ​​for insulation degradation and insulation collapse, with the critical resistance value for insulation degradation being greater than the critical resistance value for insulation collapse. Multiple simulations are performed. In the first simulation, the insulation resistance is set to the initial value, and the number of short-circuit turns is set to 1. If the current insulation resistance is greater than or equal to the critical insulation degradation value, the insulation resistance in the next simulation is the insulation resistance in the current simulation divided by the set attenuation coefficient, and the number of short-circuit turns remains unchanged. If the current insulation resistance is less than the critical insulation degradation value, the insulation resistance in the next simulation is the insulation resistance in the current simulation divided by the set attenuation coefficient, and the number of short-circuit turns increases by a set constant value. The maximum rate of change of the optimal state variable is recorded in each simulation. If the current insulation resistance is less than the critical insulation collapse value and the number of short-circuit turns increases to the set maximum number of turns threshold, the simulation is stopped. The maximum value among the maximum rates of change of the optimal state variables corresponding to all insulation resistance values ​​that are greater than or equal to the critical insulation degradation value is used as the first threshold of the rate of change. The maximum value among the maximum rates of change of the optimal state variables corresponding to all simulations where the insulation resistance value is less than the critical insulation degradation value is obtained as the second threshold of the rate of change. When the number of short-circuit turns is 1, the insulation resistance is the insulation resistance of the short-circuit point when the series structure is short-circuited and a single turn is short-circuited; otherwise, the insulation resistance is the equivalent insulation resistance that characterizes the insulation state of the short-circuit point.

[0031] It should be noted that the initial value of the insulation resistance is set to 1000 mΩ; the set attenuation coefficient is 10, meaning that the insulation resistance is reduced by one order of magnitude in each simulation; when the insulation resistance value is less than the critical insulation degradation value, it is considered that the degradation has spread to adjacent turns, and the number of short-circuit turns is adjusted, with a set value of 1 or 2; it should be noted that if the number of short-circuit turns exceeds the total number of turns, the number of short-circuit turns will not be increased; through the above steps, a series of simulation operating points covering insulation degradation from slight degradation to complete breakdown, accompanied by the expansion of the fault range, are obtained. In real inter-turn short-circuit faults, the result is often the combined effect of insulation degradation (reduced resistance) and the expansion of the fault range (increased number of turns). Changing only the resistance simulates the decrease in insulation strength at a fixed short-circuit point; while simultaneously increasing the number of turns simulates the spread of the degradation area. The latter produces stronger and more dangerous electrical effects (such as circulating current superposition and a sharp increase in losses). If the threshold is set only based on simulations of a fixed single turn and resistance variation, then when a multi-turn, medium-resistance fault occurs in the field, the rate of change of its state variables may be misaligned with the calibrated threshold, leading to misjudgment or missed diagnosis. This embodiment, by simulating a fault path of decreased resistance and increased number of turns, calibrates a threshold that can cover a wider range of fault types, thereby making the diagnostic system more robust and reliable.

[0032] In this preferred embodiment, obtaining the baseline value of the optimal state quantity under the current load rate specifically involves: First, establish a mapping relationship between the baseline values ​​of each state quantity, excluding winding power loss, and the load rate based on historical data; When the optimal state quantity is the winding power loss, the reference value of the optimal state quantity is equal to the square of the current load rate multiplied by the winding load loss of the transformer under rated load plus the no-load loss of the transformer. When the optimal state variable is not the winding power loss, the optimal state variable corresponding to the current load rate is obtained.

[0033] In this preferred embodiment, determining whether the distribution transformer is faulty specifically involves: Obtain the current load rate and the optimal state quantity of each phase. Obtain the reference value of the optimal state quantity under the current load rate. Calculate the difference between the optimal state quantity of each phase and the reference value, and divide the difference by the reference value to obtain the real-time change rate of the corresponding phase. If the real-time change rate of at least one phase is greater than or equal to the first threshold and less than the second threshold, it is judged as an inter-turn insulation anomaly. If the real-time change rate of at least one phase exceeds the second threshold, it is judged as a short-circuit fault; otherwise, the inter-turn insulation is normal. In this embodiment, the fault phase is determined as follows: The real-time change rate of each phase at the moment when an inter-turn insulation abnormality or short-circuit fault is determined is divided by the total real-time change rate to obtain the proportion of the corresponding phase. The total real-time change rate is the sum of the real-time change rates of all phases. If the proportion of a phase exceeds a set proportion threshold, it indicates that the corresponding phase is a fault phase; otherwise, it is considered an abnormal state and further human judgment and confirmation are required.

[0034] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for identifying transformer short-circuit faults, characterized in that, include: A three-dimensional geometric model and short-circuit equivalent circuit of the distribution transformer are constructed. The three-dimensional geometric model and short-circuit equivalent circuit are coupled in a field-circuit manner to establish a field-circuit coupled model. The state quantities of the distribution transformer when a single-phase short circuit occurs at different positions of the low-voltage winding are obtained by simulation based on the field-circuit coupling model. The state quantities include short-circuit loop current, spatial magnetic field strength, winding power loss and force acting on the bend. The difference between the maximum value of each state quantity when a single-phase short circuit occurs at different positions and the corresponding rated value is calculated and divided by the corresponding rated value to obtain the maximum rate of change of the corresponding state quantity when a single-phase short circuit occurs at the corresponding position. The optimal state variable is selected based on the maximum rate of change of all state variables when a single-phase single-turn short circuit occurs at different locations. The maximum rate of change of the optimal state quantity of the low-voltage winding of the distribution transformer under different insulation resistances and different short-circuit turns is obtained by simulation based on the field-circuit coupling model, and the first threshold and the second threshold of the rate of change are obtained. When a distribution transformer is actually in operation, the system determines whether the distribution transformer is faulty and the faulty phase based on the real-time acquired optimal state variables and the first and second thresholds of the rate of change.

2. The transformer short-circuit fault identification method according to claim 1, characterized in that: The construction of the three-dimensional geometric model of the distribution transformer is specifically as follows: The three-dimensional geometric model of a distribution transformer includes a three-phase model. Each phase model consists of a transformer core, a low-voltage internal winding, a low-voltage external winding, and a high-voltage winding. Each turn of the low-voltage internal winding and the low-voltage external winding is numbered.

3. The transformer short-circuit fault identification method according to claim 2, characterized in that: The short-circuit equivalent circuit is specifically as follows: The short-circuit equivalent circuit includes the high-voltage side equivalent circuit and the low-voltage side equivalent circuit; The equivalent circuit on the high-voltage side is as follows: one end of the high-voltage side operating phase voltage of each phase is grounded, and the other end is connected to one end of the self-inductance of the high-voltage winding through the winding resistance of the corresponding phase's high-voltage winding. The other ends of the self-inductance of the high-voltage windings of all phases are connected together. The equivalent circuit on the low-voltage side is as follows: For two phases that are not short-circuited, one end of the winding resistance of the low-voltage winding of all phases is connected; the other end of the winding resistance of the low-voltage winding of each phase is connected to ground in sequence through the self-inductance of the low-voltage winding of the corresponding phase and the load impedance of the corresponding phase; the low-voltage winding consists of an internal low-voltage winding and an external low-voltage winding. For a short-circuited phase, the winding resistance and self-inductance of the low-voltage winding of the corresponding phase are divided into two parts. One end of the first winding resistance of the low-voltage winding of the corresponding phase is connected to one end of the winding resistance of the low-voltage winding of the two phases that are not short-circuited; the other end of the first winding resistance of the low-voltage winding of the corresponding phase is connected to one end of the short-circuit equivalent circuit through the first self-inductance of the low-voltage winding of the corresponding phase; the other end of the short-circuit equivalent circuit is connected to ground in sequence through the second self-inductance of the low-voltage winding of the corresponding phase, the second winding resistance of the low-voltage winding of the corresponding phase, and the load impedance of the corresponding phase.

4. The transformer short-circuit fault identification method according to claim 3, characterized in that: If the short circuit is a single-turn short circuit, then the short circuit loop is: the equivalent inductance and equivalent resistance of the short-circuited turn are connected in series to form a series structure, and the series structure is connected in parallel with the insulation resistance of the short-circuit point when the single-turn short circuit occurs. If the short circuit is a multi-turn short circuit, the short circuit loop is as follows: the equivalent inductance and equivalent resistance of each short-circuited turn are connected in series to form a branch. After all the branches corresponding to the short-circuited turns are connected in parallel, they are then connected in parallel with an equivalent insulation resistance that characterizes the insulation state of the short-circuit point.

5. The transformer short-circuit fault identification method according to claim 2, characterized in that: The selection of the optimal state variable based on the maximum rate of change of all state variables when a single-phase, single-turn short circuit occurs at different locations is specifically as follows: The different positions refer to each turn of the low-voltage inner winding and each turn of the low-voltage outer winding. For each state variable, the maximum rate of change of the corresponding state variable when a single-turn short circuit occurs in each turn of the inner winding of the low-voltage winding is obtained to form the inner winding sequence, and the maximum rate of change of the corresponding state variable when a single-turn short circuit occurs in each turn of the outer winding of the low-voltage winding is obtained to form the outer winding sequence. The inner winding sequence and the outer winding sequence are spliced ​​together to form a total sequence. The maximum value in the total sequence of each state variable is used as the sensitivity index of the corresponding state variable. The reciprocal of the standard deviation of the total sequence for each state variable is used as the stability index of the corresponding state variable. Calculate the absolute value of the difference between the average value of the inner winding sequence and the average value of the outer winding sequence for each state variable, and use the reciprocal of the absolute value as the discrimination index. The sensitivity index, stability index, and discrimination index are weighted and summed according to the set weights to obtain the final evaluation index of the corresponding state quantity. The state quantity with the largest evaluation index is taken as the optimal state quantity.

6. The transformer short-circuit fault identification method according to claim 4, characterized in that: The specific steps for obtaining the first threshold and the second threshold of the rate of change are as follows: Set critical resistance values ​​for insulation degradation and insulation collapse, with the critical resistance value for insulation degradation being greater than the critical resistance value for insulation collapse. Multiple simulations are performed. In the first simulation, the insulation resistance is set to the initial value and the number of short-circuit turns is set to 1. If the current insulation resistance value is greater than or equal to the critical insulation degradation value, the insulation resistance in the next simulation is the insulation resistance in the current simulation divided by the set attenuation coefficient, and the number of short-circuit turns remains unchanged in the next simulation. If the current insulation resistance value is less than the critical insulation degradation value, the insulation resistance in the next simulation will be the insulation resistance in the current simulation divided by the set attenuation coefficient, and the number of short-circuit turns will increase by the set fixed value. The maximum change rate of the optimal state quantity will be recorded in each simulation. If the current insulation resistance value is less than the critical insulation collapse value and the number of short-circuit turns increases to the set maximum number of turns threshold, the simulation will stop. The maximum value among the maximum rates of change of the optimal state variables corresponding to all insulation resistance values ​​that are greater than or equal to the critical insulation degradation value is used as the first threshold of the rate of change. The maximum value of the maximum rate of change of the optimal state quantity corresponding to all simulations with insulation resistance values ​​less than the critical insulation degradation value is used as the second threshold of the rate of change. When the number of short-circuit turns is 1, the insulation resistance is the insulation resistance of the short-circuit point when the series structure is short-circuited and a single turn is short-circuited; otherwise, the insulation resistance is the equivalent insulation resistance that characterizes the insulation state of the short-circuit point.

7. The transformer short-circuit fault identification method according to claim 6, characterized in that: To determine if a distribution transformer is faulty, the specific steps are as follows: Obtain the current load rate and the optimal state quantity of each phase. Obtain the reference value of the optimal state quantity under the current load rate. Calculate the difference between the optimal state quantity of each phase and the reference value, and divide the reference value by the reference value to obtain the real-time change rate of the corresponding phase. If the real-time change rate of at least one phase is greater than or equal to the first threshold of change rate and less than the second threshold of change rate, it is judged as an inter-turn insulation abnormality. If the real-time change rate of at least one phase exceeds the second threshold of change rate, it is judged as a short-circuit fault. Otherwise, the inter-turn insulation is normal.

8. The transformer short-circuit fault identification method according to claim 7, characterized in that: The benchmark value for obtaining the optimal state quantity under the current load rate is specifically as follows: First, establish a mapping relationship between the baseline values ​​of each state quantity, excluding winding power loss, and the load rate based on historical data; When the optimal state quantity is the winding power loss, the reference value of the optimal state quantity is equal to the square of the current load rate multiplied by the winding load loss of the transformer under rated load plus the no-load loss of the transformer. When the optimal state variable is not the winding power loss, the optimal state variable corresponding to the current load rate is obtained.

9. The transformer short-circuit fault identification method according to claim 7, characterized in that: To determine the faulty phase, the specific steps are as follows: The real-time change rate of each phase at the moment when an inter-turn insulation abnormality or short-circuit fault is determined is divided by the total real-time change rate to obtain the proportion of the corresponding phase. The total real-time change rate is the sum of the real-time change rates of all phases. If the proportion of a phase exceeds a set proportion threshold, it indicates that the corresponding phase is a fault phase; otherwise, it is considered an abnormal state.

10. A transformer short-circuit fault identification system based on the method of any one of claims 1-9, comprising: The module comprising a field-path coupling model construction module, a maximum rate of change acquisition module, an optimal state variable selection module, a rate of change threshold setting module, and a fault identification module is characterized by: Field-circuit coupling model construction module: Constructs a three-dimensional geometric model and short-circuit equivalent circuit of the distribution transformer, performs field-circuit coupling on the three-dimensional geometric model and the short-circuit equivalent circuit, and establishes a field-circuit coupling model; Maximum rate of change module: Based on the field-circuit coupling model simulation, the state quantities of the distribution transformer at different positions of the low-voltage winding when a single-phase short circuit occurs are obtained. The state quantities include short-circuit loop current, spatial magnetic field strength, winding power loss and force acting on the bend; the difference between the maximum value of each state quantity at different positions of a single-phase short circuit and the corresponding rated value is divided by the corresponding rated value, which is taken as the maximum rate of change of the corresponding state quantity at the corresponding position of a single-phase short circuit. Optimal state quantity selection module: Selects the optimal state quantity based on the maximum rate of change of all state quantities when a single-phase single-turn short circuit occurs at different locations; Change rate threshold setting module: Based on the field-circuit coupling model simulation, the maximum change rate of the optimal state quantity of the low-voltage winding of the distribution transformer under different insulation resistances and different short-circuit turns is obtained, and the first and second change rate thresholds are obtained. Fault identification module: When the distribution transformer is actually running, it determines whether the distribution transformer is faulty and the faulty phase based on the real-time acquired optimal state quantity and the first and second thresholds of the rate of change.

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