CN117849495A - Transformer operation performance evaluation method and system - Google Patents
Transformer operation performance evaluation method and system Download PDFInfo
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Abstract
The application belongs to the technical field of power system technology, and provides a transformer operation performance evaluation method and a system thereof, wherein the method comprises the steps of obtaining operation state data and fault type information of a transformer, wherein the operation state data comprises an idle state, a short circuit state and a loaded state, and the fault type information comprises normal, abnormal and fault; determining electrical parameter data of the operation state data according to the operation state data and the fault type information; and determining fault position data according to the electrical parameter data. According to the method and the device, when the performance of the transformer is detected, the efficiency and the accuracy of performance evaluation are improved, meanwhile, the fault position of the transformer can be obtained in the performance evaluation process, and reliable guarantee is provided for normal operation of the transformer and timely fault discovery.
Description
Technical Field
The application belongs to the technical field of power system technology, and particularly relates to a transformer operation performance evaluation method and a system thereof.
Background
The transformer is a device for converting electric energy by electromagnetic induction, and consists of two or more coils which are mutually induced by mutual coupling of magnetic fields according to Faraday's law of electromagnetic induction. Through the transformer, the power can be efficiently transmitted and distributed to different positions, and therefore, the transformer is mainly applied to a power system to adjust the voltage level, so as to achieve the aims of power transmission and distribution. In addition, the transformer is widely applied to the fields of various electronic equipment, communication systems, power electronic equipment and the like.
At present, in performance detection of a transformer, a maintenance person often detects the transformer periodically, and there is a problem that the working performance of the transformer cannot be determined in real time, so a new performance detection method is required.
Disclosure of Invention
The invention aims to provide a transformer operation performance evaluation method and a system thereof, which aim to solve the technical problem that the performance evaluation of a transformer cannot be carried out in real time in the prior art.
In order to achieve the above object, the present invention provides a method for evaluating the operation performance of a transformer, comprising:
acquiring operation state data and fault type information of a transformer, wherein the operation state data comprises an idle state, a short circuit state and a loaded state, and the fault type information comprises normal, abnormal and fault;
determining electrical parameter data of the operation state data according to the operation state data and the fault type information;
and determining fault position data according to the electrical parameter data.
The beneficial effects of the invention are as follows: according to the transformer operation performance evaluation method, operation state data of a transformer are firstly obtained, different fault type information is determined according to different operation state data, and then operation performance evaluation is carried out on the transformer, wherein the operation state data comprise an idle state, a short circuit state and a loaded state, the fault type information comprises normal, abnormal and fault, then electrical parameter data of different operation state data are determined according to the operation state data and the fault type information, and finally fault position data of the transformer are determined according to the electrical parameter data, so that performance evaluation efficiency and evaluation accuracy can be improved when performance of the transformer is detected, meanwhile, fault positions of the transformer can be obtained in the performance evaluation process, and reliable guarantee is provided for normal operation of the transformer and timely fault discovery.
Optionally, current data of the transformer in a preset time range are obtained;
judging whether current data exist or not;
if the current data does not exist, the running state data is in an idle state;
if the current data exist, judging whether the current data increase speed is greater than or equal to a preset increase speed range in a preset time range;
if the current data increasing rate is greater than or equal to a preset increasing range in a preset time range, determining that the running state is a short-circuit state;
if the current data increasing rate is smaller than the preset increasing range in the preset time range, determining that the running state is a loaded state;
acquiring characteristic index data of a transformer;
and determining the fault type information according to the characteristic index data.
Optionally, determining health value data of the transformer according to the characteristic index data;
judging whether the health value data is equal to 1 or not;
if the health value data is equal to 1, the fault type information belongs to normal;
if the health value data is smaller than 1 and larger than 0, the fault type information belongs to abnormality;
and if the health value data is equal to 0, the fault type information belongs to faults.
Optionally, judging whether the fault type information is normal;
and if the fault type information is normal, acquiring life prediction data of the transformer, otherwise, determining the electrical parameter data.
Optionally, acquiring the running time and evaluation index data of the transformer;
determining index weight data according to the evaluation index data and the running time of the transformer;
and determining the life prediction data according to the index weight data.
And determining the electrical parameter data according to the operation state data.
Optionally, if the running state data is in an idle state, acquiring the electrical parameter data including idle current data, idle loss data and power factor;
if the running state data is in a short circuit state, acquiring the electrical parameter data including short circuit impedance, short circuit current and short circuit power;
and if the running state data is in a loaded state, acquiring the electrical parameter data including rated power, rated voltage, rated current and rated frequency.
Optionally, acquiring surface temperature data of a transformer oil tank;
determining heat source abnormal parameter data according to the electrical parameter data and the surface temperature data;
and determining the fault part data according to the heat source abnormal parameter data.
The invention also provides a transformer operation performance evaluation system, which comprises:
and a data acquisition module: the method comprises the steps of acquiring operation state data and fault type information of a transformer, wherein the operation state data comprise an idle state, a short circuit state and a loaded state, and the fault type information comprises normal, abnormal and fault;
parameter acquisition module: the electrical parameter data is used for determining the operation state data according to the operation state data and the fault type information;
a fault determination module: and the fault location data is determined according to the electrical parameter data.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for evaluating operation performance of a transformer according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of operational status data judgment of a transformer operational performance evaluation method according to an embodiment of the present invention;
fig. 3 is a block diagram of a transformer operation performance evaluation system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an embodiment of a method for evaluating operation performance of a transformer according to an embodiment of the present invention may include:
s100, acquiring operation state data and fault type information of the transformer.
Specifically, real-time running state data of the transformer are obtained, whether the transformer has faults or not is monitored in real time, if the faults exist, fault type information of the transformer is obtained, wherein the running state data comprise an idle state, a short circuit state and a loaded state, and the fault type information comprises normal, abnormal and faults.
Specifically, when the transformer is in an empty state, the empty current and the empty damage of the transformer can be measured through the empty running of the transformer, when the short circuit state of the transformer is required to be tested, the high-voltage coil can be connected to a power supply, the low-voltage coil is directly short-circuited, and when the transformer is in an on-load state, whether the transformer runs normally can be judged through voltage, resistance and load loss tests.
In one embodiment, the step S100 includes:
s110, acquiring current data of the transformer within a preset time range.
Specifically, current data of each time point of the transformer in a preset time range is obtained.
S120, judging whether current data exist.
Specifically, referring to fig. 2, it is determined whether a current exists in the transformer, i.e. whether the current is greater than 0.
And S130, if the current data does not exist, the running state data is in an idle state.
Specifically, if the current data is present and vanishes in the preset time range, that is, the current data is occasionally present, the operation state data of the transformer is determined to be in an idle state.
And S140, if the current data exists, judging whether the current data increase speed in the preset time range is greater than or equal to a preset increase speed range.
Specifically, if the current data continuously exists in the preset time range, the increasing speed of the current data in the preset time range is further compared with the preset increasing speed range, and whether the increasing speed of the current data in the preset time range is larger than or equal to the preset increasing speed range is judged.
And S150, if the current data increase rate is greater than or equal to a preset increase rate range in a preset time range, determining that the operation state is a short circuit state.
Specifically, if the current data exists within the preset time range and the current data increase speed within the preset time range is greater than or equal to the preset increase speed range, the transformerThe operation state is a short circuit state, wherein the calculation formula of the current increasing rate is
And S160, if the current data increase rate is smaller than the preset increase rate range in the preset time range, determining that the running state is the loaded state.
Specifically, if the current data exist within the preset time range and the current data increase speed is smaller than the preset speed increase range within the preset time range, the running state of the transformer is a loaded state.
Specifically, the operation state data of the transformer can be determined by judging the voltage data of the transformer, firstly judging whether the voltage data exist in a preset time range, if the voltage data exist in the preset time range and the voltage data do not exist in the preset time range, the operation data are in an idle state, and if the voltage data exist in the preset time range and the voltage data continuously decrease in the preset time range, the operation data are determined to be in a short circuit state, otherwise, the operation data are determined to be in a loaded state.
S170, acquiring characteristic index data of the transformer.
Specifically, an amplitude signal, a temperature signal and an acoustic emission signal of the transformer are obtained, and the amplitude signal, the temperature signal and the acoustic emission signal of the transformer are subjected to analog-to-digital conversion to be converted into a series of characteristic index data.
S180, determining fault type information according to the characteristic index data.
Specifically, according to the characteristic index data, the health degradation characteristic index change data is determined, meanwhile, the health condition of the transformer is estimated according to the health degradation characteristic index change data, and the fault type information is determined.
Specifically, the characteristic index data includes a time domain characteristic index and a frequency domain characteristic index, and a calculation formula of the time domain characteristic index includes: the waveform index calculation formula of the time domain characteristic index isThe peak index calculation formula isKurtosis index calculation formula is->Wherein K is a waveform index, C f Is the peak index, K V Is the kurtosis index, X rms Is an effective value, < >>Is the absolute average amplitude, X max The method is characterized in that the method comprises the steps of peak value, beta is kurtosis, wherein a waveform index is used for representing the overall stability of a vibration signal, the peak value index is used for detecting whether an impact characteristic exists in the signal, the kurtosis index is used for describing the steepness degree of the peak top of a probability density function of the vibration signal, and a calculation formula of a frequency domain characteristic index comprises: the calculation formula of the spectrum mean value of the frequency domain characteristic index is +.>The calculation formula of the spectrum variance is +.>The calculation formula of the spectral kurtosis is->In (1) the->Is the spectrum mean value, V fft Is the spectrum variance, beta is the spectrum kurtosis, N is the distribution point, C i Is the amplitude { C } of the signal frequency i }，(i＝1,2，……,N)。
In one embodiment, the step S180 includes:
s181, determining health value data of the transformer according to the characteristic index data.
Specifically, since different data distribution is generated by the vibration signals of the transformer in different states, the difference and the similarity of the current data and the historical health state data are obtained by comparing the characteristic index data with the data in the normal health state, and the health value data of the transformer are further estimated and determined.
S182, judging whether the health value data is equal to 1.
Specifically, the health value data is compared, the health value data is a numerical value between 0 and 1, when the health value is 1, namely, the two functions are completely overlapped, the transformer is in a full normal state, when the health value is between 0 and 1, namely, the two functions have partial overlapped parts, the transformer has partial abnormal parts, when the health value is 0, namely, the two functions are completely separated, the transformer has larger abnormality, and the calculation formula of the health value data is as followsWherein p (x) is a normal distribution function, q (x) is a current distribution function, L2 is a loss value, CV is health value data, namely, a numerical value of coincidence of the p (x) and q (x) functions, and when describing coincidence data of the p (x) and q (x) functions, probability density of a coincidence point can be described by using a Gaussian density function, and a calculation formula of the Gaussian density function is as follows: />Where g x, μ, Σ) is a gaussian density function, μ is the center point of the density function, Σ is the co-variation matrix of the density function, and x is the function point.
S183, if the health value data is equal to 1, the failure type information belongs to normal.
Specifically, if the health data is equal to 1, that is, the p (x) function and the q (x) function are completely overlapped, the performance of the transformer is consistent with that of a preset standard transformer, and the fault type information belongs to normal, the method can be used for judging whether the transformer meets the factory standard when the transformer leaves the factory.
S184, if the health value data is smaller than 1 and larger than 0, the fault type information belongs to abnormality.
Specifically, if the health value data is between 1 and 0, that is, the p (x) and q (x) functions have partial overlapping portions, the transformer has partial abnormality, the partial abnormality needs to be detected, and it is determined that the fault type information belongs to the abnormality.
S185, if the health value data is equal to 0, the fault type information belongs to a fault.
Specifically, if the health data is smaller than 0, that is, the p (x) function and the q (x) function are completely separated, no overlapping part exists, the performances of the transformer are completely different from those of the preset standard transformer, the whole transformer needs to be maintained, and the fault type information is determined to be a fault.
S200, determining the electrical parameter data of the operation state data according to the operation state data and the fault type information.
Specifically, various fault type data of the transformer under different operation state data are judged, whether the transformer needs to be overhauled is determined according to the fault type data, and if the transformer needs to be overhauled, the electrical parameter data corresponding to the operation state data are determined.
S210, judging whether the fault type information is normal.
Specifically, the fault type information of the transformer is compared, and whether the fault type information is normal or not is judged.
S220, if the fault type information is normal, life prediction data of the transformer are obtained, and otherwise, electrical parameter data are determined.
Specifically, if the fault type information of the transformer is not normal, that is, the transformer is different from the standard transformer to a certain extent, the abnormal position of the transformer needs to be overhauled, meanwhile, the electrical parameter data corresponding to the running state data of the abnormal transformer is determined, and life prediction data of the transformer is obtained.
In one embodiment, the step S220 includes:
s221, acquiring the running time of the transformer and evaluation index data.
Specifically, the used running time of the transformer is firstly obtained, and then the evaluation index data of the transformer is obtained according to the standard evaluation data, wherein the evaluation index data are used for evaluating the service life data of the transformer.
S222, determining index weight data according to the evaluation index data and the running time of the transformer.
Specifically, according to a plurality of evaluation index data and the running time of the transformer, index weight data occupied by each index are determined.
S223, determining life prediction data according to the index weight data.
Specifically, life prediction is performed on the transformer according to index weight data occupied by each index. Meanwhile, the service life of the transformer can be estimated, the aging rate of the transformer can be estimated, and the service life calculation formula of the transformer is as follows: service life = life expectancy/(1-actual aging rate), where life expectancy is the life expectancy estimated when the transformer leaves the factory, and actual aging rate of the transformer is the aging speed of the transformer in actual use.
S224, determining electrical parameter data according to the operation state data.
Specifically, according to the operation state data of the transformer, the electrical parameter data of different operation states are determined.
In one embodiment, the step S224 includes:
and S225, if the running state data is in an idle state, acquiring electrical parameter data including idle current data, idle loss data and power factor.
Specifically, different electrical parameter data are determined according to different operation state data. When the operation state data is in an idle state, fault information of the transformer can be judged according to the idle current data, the idle loss data and the power factor, wherein the idle current is smaller in the idle state of the transformer, so that an average value and a standard deviation can be calculated when the idle current is obtained to obtain a more accurate evaluation result of the transformer, the idle loss is the sum of the iron loss and the air leakage loss of the transformer in the idle state of the transformer, and the power factor of the transformer is the ratio of the actual consumed useful power and the total power in the idle state.
And S226, if the operation state data is in a short circuit state, acquiring electrical parameter data including short circuit impedance, short circuit current and short circuit power.
Specifically, when the running state of the transformer is a short-circuit state, the fault information of the transformer can be judged according to the short-circuit impedance, the short-circuit current and the short-circuit power, wherein the short-circuit impedance is the resistance to the flowing current in the short-circuit state of the transformer, the current passing through the transformer in the short-circuit state is the short-circuit current, the short-circuit current and the short-circuit impedance have certain relevance, and the short-circuit power is the output power of the transformer in the short-circuit state.
S227, if the operation state data is the on-load state, the electrical parameter data including the rated power, the rated voltage, the rated current and the rated frequency is acquired.
Specifically, when the operating state of the transformer is a loaded state, whether the transformer has a fault or not can be judged according to rated power, rated voltage, rated current and rated frequency of the transformer, the rated power of the transformer is maximum output power under the rated operating condition, the rated voltage of the transformer is voltage allowed to be applied by a coil, the primary winding and the secondary winding allow current to pass under the rated operating condition when the rated current of the transformer passes, and the rated frequency of the transformer is operating frequency under the rated operating condition.
S300, determining fault location data according to the electrical parameter data.
Specifically, the fault location data detected in different operation states are determined according to the electrical parameter data of the different operation state data of the transformer.
In one embodiment, the step S300 includes:
s310, acquiring surface temperature data of a transformer oil tank.
Specifically, the light scattering frequency data of the transformer after operation can be firstly obtained by obtaining the surface temperature data of the transformer oil tank, the light scattering frequency data and the standard frequency data are compared, and the surface temperature data of the transformer oil tank is determined according to the difference between the light scattering frequency data and the standard frequency data.
S320, determining heat source abnormal parameter data according to the electrical parameter data and the surface temperature data.
Specifically, according to the electrical parameter data of the transformer and the surface temperature data of the oil tank, judging whether the surface temperature data is in a preset temperature data range, and if the surface temperature data is not in the preset temperature data range, determining heat source abnormality parameter data at an abnormality position.
S330, determining fault location data according to the heat source abnormal parameter data.
Specifically, according to the abnormal parameter data of the heat source of the transformer, the position information of the abnormal temperature position of the transformer is determined, and the fault position data is further determined.
The implementation principle of the technical supervision policy method applied to the power grid equipment in the embodiment of the application is as follows: monitoring operation state data of the transformer in real time, determining the operation state data of the transformer according to the current data, determining fault type data of different operation state data at the same time, further determining whether the transformer is abnormal or not and whether maintenance is needed, predicting the service life of the transformer, and performing performance evaluation of the transformer, wherein the operation state of the transformer comprises an idle state, a short circuit state and a loaded state, the fault type information comprises normal, abnormal and fault, and meanwhile, determining electrical parameter data of the transformer according to the operation state data and the fault type information of the transformer, and determining fault position data of the transformer according to the electrical parameter data, so that performance evaluation efficiency and evaluation accuracy can be improved when the performance of the transformer is detected, and meanwhile, the fault position of the transformer can be obtained in the performance evaluation process, and reliable guarantee is provided for normal operation of the transformer and timely fault discovery.
Referring to fig. 3, an embodiment of a transformer operation performance evaluation system according to an embodiment of the present invention may include:
and a data acquisition module: the method comprises the steps of acquiring operation state data and fault type information of a transformer, wherein the operation state data comprise an idle state, a short circuit state and a loaded state, and the fault type information comprises normal, abnormal and fault;
parameter acquisition module: the electrical parameter data is used for determining the operation state data according to the operation state data and the fault type information;
a fault determination module: and the fault location data is determined according to the electrical parameter data.
In one embodiment, embodiments of the present application further provide a fault determination module, including:
temperature acquisition submodule: the method comprises the steps of acquiring surface temperature data of a transformer oil tank;
a heat source determination sub-module: the heat source abnormal parameter data are determined according to the electrical parameter data and the surface temperature data;
and a fault acquisition sub-module: and the fault part data is determined according to the heat source abnormal parameter data.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. A method for evaluating the operational performance of a transformer, comprising:
acquiring operation state data and fault type information of a transformer, wherein the operation state data comprises an idle state, a short circuit state and a loaded state, and the fault type information comprises normal, abnormal and fault;
determining electrical parameter data of the operation state data according to the operation state data and the fault type information;
and determining fault position data according to the electrical parameter data.
2. The method of claim 1, wherein the obtaining operational status data and fault type information for the transformer comprises:
acquiring current data of a transformer within a preset time range;
judging whether current data exist or not;
if the current data does not exist, the running state data is in an idle state;
if the current data exist, judging whether the current data increase speed is greater than or equal to a preset increase speed range in a preset time range;
if the current data increasing rate is greater than or equal to a preset increasing range in a preset time range, determining that the running state is a short-circuit state;
if the current data increasing rate is smaller than the preset increasing range in the preset time range, determining that the running state is a loaded state;
acquiring characteristic index data of a transformer;
and determining the fault type information according to the characteristic index data.
3. The method of claim 2, wherein said determining said fault type information from said characteristic index data comprises:
determining health value data of the transformer according to the characteristic index data;
judging whether the health value data is equal to 1 or not;
if the health value data is equal to 1, the fault type information belongs to normal;
if the health value data is smaller than 1 and larger than 0, the fault type information belongs to abnormality;
and if the health value data is equal to 0, the fault type information belongs to faults.
4. The method of claim 1, wherein determining electrical parameter data for the operating state data based on the operating state data and fault type information comprises:
judging whether the fault type information is normal or not;
and if the fault type information is normal, acquiring life prediction data of the transformer, otherwise, determining the electrical parameter data.
5. The method of claim 4, wherein if the fault type information is normal, obtaining life prediction data of the transformer, and otherwise determining the electrical parameter data, comprises:
acquiring the running time and evaluation index data of the transformer;
determining index weight data according to the evaluation index data and the running time of the transformer;
and determining the life prediction data according to the index weight data.
And determining the electrical parameter data according to the operation state data.
6. The method of claim 5, wherein said determining said electrical parameter data from said operational status data comprises:
if the running state data is in an idle state, acquiring the electrical parameter data including idle current data, idle loss data and power factor;
if the running state data is in a short circuit state, acquiring the electrical parameter data including short circuit impedance, short circuit current and short circuit power;
and if the running state data is in a loaded state, acquiring the electrical parameter data including rated power, rated voltage, rated current and rated frequency.
7. The method of claim 1, wherein said determining fault location data from said electrical parameter data comprises:
acquiring surface temperature data of a transformer oil tank;
determining heat source abnormal parameter data according to the electrical parameter data and the surface temperature data;
and determining the fault part data according to the heat source abnormal parameter data.
8. A transformer operating performance evaluation system, comprising:
and a data acquisition module: the method comprises the steps of acquiring operation state data and fault type information of a transformer, wherein the operation state data comprise an idle state, a short circuit state and a loaded state, and the fault type information comprises normal, abnormal and fault;
parameter acquisition module: the electrical parameter data is used for determining the operation state data according to the operation state data and the fault type information;
a fault determination module: and the fault location data is determined according to the electrical parameter data.
9. The system of claim 8, wherein the fault determination module comprises:
temperature acquisition submodule: the method comprises the steps of acquiring surface temperature data of a transformer oil tank;
a heat source determination sub-module: the heat source abnormal parameter data are determined according to the electrical parameter data and the surface temperature data;
and a fault acquisition sub-module: and the fault part data is determined according to the heat source abnormal parameter data.
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