Power equipment temperature rise load performance index diagnosis method, electronic device, storage medium

Abstract

The application provides a power equipment temperature rise load performance index diagnosis method, comprising the following steps: establishing a power equipment load current and temperature mathematical model according to current heat generation and heat dissipation process analysis; calculating the equipment temperature rise load performance index according to the power equipment load current and temperature mathematical model; and judging the equipment fault state according to the amplitude and trend of the deviation of the equipment temperature rise load performance index with time or the three-phase deviation degree or the phase-to-phase temperature rise load variable ratio of the equipment temperature rise load performance index. The application relates to an electronic device and a storage medium, which are used for executing the above method. The application applies the load current and temperature relationship model to the monitoring and diagnosis of the power equipment, greatly promotes the development of the power equipment state monitoring and diagnosis technology, improves the accuracy and reliability of the power equipment monitoring and diagnosis, and well solves the inherent problems existing in the power equipment state monitoring and diagnosis.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of online monitoring of power equipment, and in particular to a power equipment temperature rise load performance index diagnosis method, an electronic device and a storage medium. BACKGROUND

[0002] In recent years, with the increasingly serious global energy problem, countries around the world have carried out research on smart grids. The ultimate goal of smart grids is to build a panoramic real-time system covering the entire production process of the power system, including power generation, power transmission, power transformation, power distribution, power utilization and dispatching. Power equipment state monitoring and diagnosis is an important part of smart grids, and the implementation of its key technologies can prolong the service life of equipment, reduce the occurrence of sudden failures and improve the reliability of power supply of power equipment, so it has been widely used in power systems.

[0003] Power equipment online monitoring data grows in real time, and current sensors and temperature sensors have gradually been widely used. The amount of monitoring data is extremely large, and the speed of monitoring data generation is extremely fast. Especially on load current heat type power equipment, such as power switch cabinet, cable and other equipment. In the industry, a large amount of load current and temperature data of on-site equipment has been collected, and most of them only use threshold judgment for alarm function. The state monitoring of power equipment has the disadvantage of insufficient diagnosis and early warning function, which greatly restricts the comprehensive promotion and application of power equipment state monitoring technology. SUMMARY

[0004] In order to overcome the shortcomings of the prior art, the purpose of the present application is to provide a power equipment temperature rise load performance index diagnosis method, which solves the inherent problems existing in the state monitoring and diagnosis of power equipment, and is an important means to realize the state maintenance management of power equipment and improve the lean level of power production and operation management.

[0005] The present application provides a power equipment temperature rise load performance index diagnosis method, comprising the following steps:

[0006] Physical mathematical modeling, according to the analysis of current heat and heat dissipation process, a mathematical model of power equipment load current and temperature is established;

[0007] Calculating the equipment temperature rise load performance index, calculating the equipment temperature rise load performance index according to the mathematical model of power equipment load current and temperature;

[0008] Judging the equipment fault state, according to the amplitude and trend of the deviation of the equipment temperature rise load performance index with time or the three-phase deviation degree of the equipment temperature rise load performance index or the inter-phase temperature rise load variable ratio, the equipment fault state is judged.

[0009] Further, the mathematical model of power equipment load current and temperature is:

[0010]

[0011] Let: Then

[0012] Wherein, Q(t) is the total heat generating power of the monitored section loop, R is the total resistance of the monitored section loop, I(t) is the steady load current of the monitored section loop, T1(t) is the temperature of the monitored part, T0(t) is the temperature of the environment where the monitored equipment is located, ΔT(t) is the temperature rise value of the monitored part, λ is the heat dissipation coefficient between the monitored part and the environment reference point, K Rλ is the load current and temperature relationship model coefficient, which is called the equipment temperature rise load performance index of the monitored part.

[0013] Further, in the step of calculating the equipment temperature rise load performance index, the equipment temperature rise load performance index is amplified by a fixed multiple.

[0014] Further, the judgment of the equipment fault state according to the amplitude and trend of the shift of the equipment temperature rise load performance index over time is specifically: the change process data of the equipment temperature rise load performance index over time is plotted in a two-dimensional plane coordinate graph with time as the horizontal axis, and a trend curve is connected, and the equipment fault state is judged according to the amplitude and trend of the shift of the equipment temperature rise load performance index in the trend graph.

[0015] Further, the judgment of the equipment fault state according to the three-phase deviation degree of the equipment temperature rise load performance index is specifically: the three-phase deviation degree of the equipment temperature rise load performance is calculated, and it is judged whether the three-phase deviation degree of the equipment temperature rise load performance index is within the allowable range, yes, which represents that the equipment is normal, otherwise, which represents that there is an abnormal situation in the equipment.

[0016] Further, when the equipment fault state is judged according to the three-phase deviation degree of the equipment temperature rise load performance index, the sampling data of the same moment of the three phases of the equipment is compared and calculated; and the calculation formula of the three-phase deviation degree of the equipment temperature rise load performance index is:

[0017]

[0018] K Rλ (t)max=max(K Rλ a(t),K Rλ b(t),K Rλ c(t))

[0019] K Rλ (t)ave=average(K Rλ a(t),KRλ b(t),K Rλ c(t))

[0020] If ε(t) is not within the allowable range, it is determined that an abnormal situation has occurred in the equipment.

[0021] Further, the inter-phase temperature rise load variation ratio calculation formula is:

[0022]

[0023] Wherein, Ta(t), Tb(t) are the temperatures of any two phases of the three-phase equipment; ΔTa(t), ΔTb(t) are the temperature rises of any two phases of the three-phase equipment; Ia(t), Ib(t) are the current values of any two phases of the three-phase equipment; d ab (t) is the temperature rise load variation ratio between any two phases of the three-phase equipment.

[0024] Further, the inter-phase temperature rise load variation ratio calculation formula is simplified by taking the extreme value method:

[0025]

[0026] T max (t) = max(T a (t), T b (t), T c (t))

[0027] T min (t) = min(T a (t), T b (t), T c (t))

[0028] I max (t) = max(I a (t), I b (t), I c (t))

[0029] I min (t) = min(I a (t), I b (t), I c (t))

[0030] Wherein, d(t) is the temperature rise load variation ratio between the phases of the equipment; T max (t) takes the maximum value of the temperatures of the ABC three-phase; T min (t) takes the minimum value of the temperatures of the ABC three-phase; I max (t) takes the maximum value of the currents of the ABC three-phase; I min(t) take the minimum value of the current in the ABC three-phase; M is the magnification;

[0031] When d(t) deviates from K Rλ When the value is not in the allowable range, it represents that an abnormal situation occurs in one phase of the three-phase of the device.

[0032] An electronic device, comprising: a processor; a memory; and a program, wherein the program is stored in the memory and configured to be executed by the processor, the program comprising instructions for executing a power equipment temperature rise load performance index diagnosis method.

[0033] A computer-readable storage medium having stored thereon a computer program, the computer program being executed by a processor to perform a power equipment temperature rise load performance index diagnosis method.

[0034] Compared with the prior art, the present application has the following beneficial effects:

[0035] The present application provides a power equipment temperature rise load performance index diagnosis method, comprising the following steps: physical and mathematical modeling, establishing a power equipment load current and temperature mathematical model according to current heating and heat dissipation process analysis; calculating the equipment temperature rise load performance index, calculating the equipment temperature rise load performance index according to the power equipment load current and temperature mathematical model; judging the equipment fault state, judging the equipment fault state according to the amplitude and trend of the equipment temperature rise load performance index deviating over time or the three-phase deviation degree of the equipment temperature rise load performance index or the inter-phase temperature rise load variation ratio. The present application relates to an electronic device and a storage medium for executing a power equipment temperature rise load performance index diagnosis method. The present application applies the load current and temperature relationship model to the monitoring and diagnosis of power equipment, greatly promoting the development of power equipment state monitoring and diagnosis technology, improving the accuracy and reliability of power equipment monitoring and diagnosis, and solving the inherent problems in power equipment state monitoring and diagnosis. It is an important means to realize power equipment state maintenance management and improve the lean level of power production and operation management.

[0036] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, and to implement the content of the description, the following will be described in detail with the preferred embodiments of the present application and the accompanying drawings. The specific embodiments of the present application are given in detail by the following examples and accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0037] The drawings described herein are used to provide further understanding of the present application, and form a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0038] Figure 1Flow chart of the power equipment temperature rise load performance index diagnosis method of the present application;

[0039] Figure 2 Temperature rise load performance index transition diagram of the present application. DETAILED DESCRIPTION

[0040] The present application will be further described below in conjunction with the drawings and specific embodiments, and it should be noted that the following described embodiments or technical features can be combined in any manner to form new embodiments without conflict.

[0041] The power equipment temperature rise load performance index diagnosis method, as shown in Figure 1 includes the following steps:

[0042] Physical mathematical modeling, according to the current heating and heat dissipation process analysis, a mathematical model of the load current and temperature of the power equipment is established; the model equation under the static condition of the system is:

[0043]

[0044] Let: Then

[0045] Wherein, Q(t) is the total heating power of the monitored section circuit, R is the total resistance of the monitored section circuit, I(t) is the steady-state load current of the monitored section circuit, T1(t) is the temperature of the monitored part, T0(t) is the temperature of the environment where the monitored equipment is located, ΔT(t) is the temperature rise value of the monitored part, λ is the heat dissipation coefficient between the monitored part and the environment reference point, K Rλ is the load current and temperature relationship model coefficient, which is called the equipment temperature rise load performance index of the monitored part.

[0046] Physical meaning of the equipment temperature rise load performance index:

[0047] R is the total resistance of the measured section circuit, which is composed of two parts: conductor resistance and contact resistance. The conductor resistance increases with the increase of temperature, and the relationship is approximately linear; the contact resistance can be divided into shrinkage resistance and surface film resistance, and the contact resistance is affected by many factors, such as contact form, contact pressure, contact surface finish, chemical corrosion, electrochemical corrosion, thermal cycle aging, material properties, critical voltage and current effect, etc., resulting in nonlinear change of contact resistance under certain critical influence factor conditions. But for long-term stable working state, the contact resistance shows a stable value. The contact resistance value under the thermal steady state of the equipment can be used to indicate the good or bad of the electrical connection performance.

[0048] Theoretical analysis and experience show that the change of the contact resistance of the electrical connection point is probably in accordance with the distribution law of the "bathtub curve" known in the field of equipment management, i.e. the contact resistance is relatively large in the early and late periods of operation of the equipment, the contact resistance is relatively small in the normal trial period, and the contact resistance presents a gradually rapid increasing trend in the early period of the late failure. The contact resistance is one of the main physical factors for judging the temperature rise load performance state of the power equipment. Therefore, in the diagnosis method, by seeking or designing a physical index having an equivalent or proportional relationship with the contact resistance as a diagnosis criterion, the good or bad and aging degree of the electrical connection performance of the equipment can be judged. Load current and temperature relationship model coefficient K Rλ The load current and temperature relationship model coefficient K is in proportional relationship with the total resistance R of the loop of the measured section, and is designed as the equipment temperature rise load performance index of the monitored part.

[0049] λ is the heat dissipation coefficient between the monitored part and the environmental reference point, which is generally irrelevant to the temperature rise load performance and operating state of the equipment itself. λ is related to the structure of the sensor and the environment. The heat dissipation process of the heating part is divided into three ways: heat conduction, air convection and heat radiation. The heat dissipation coefficient of the heat conduction process is related to the conductor material and the medium material, and is approximately linear; the air convection heat dissipation process is positively correlated with the air temperature; the heat radiation heat dissipation process is positively correlated with the conductor temperature and negatively correlated with the environmental temperature. The related experimental results show that λ increases with the increase of the conductor temperature, and is approximately linear.

[0050] From the temperature rise load relationship model, it can be seen that K Rλ represents the temperature rise value per unit current square, and is also an index directly reflecting the temperature rise load performance of the equipment. The larger the value is, the lower the load performance is.

[0051] The equipment temperature rise load performance index is calculated. In the normal state, according to the load current and temperature mathematical model of the power equipment (system static condition), the equipment temperature rise load performance index formula is:

[0052] Standard unit: K / A 2 ×10 5

[0053] Because the square of the current is used as the denominator, the order of magnitude of the performance index is very small. The equipment temperature rise load performance index is enlarged by a fixed multiple, which is 10 5 times in this embodiment, for the convenience of calculation and diagnosis.

[0054] The equipment fault state is judged. According to the amplitude and trend of the deviation of the equipment temperature rise load performance index with the passage of time or the three-phase deviation degree or the inter-phase temperature rise load variation ratio of the equipment temperature rise load performance index, the equipment fault state is judged.

[0055] In an embodiment, asFigure 2 The device temperature rise load performance index K is calculated Rλ K is calculated Rλ The change process data over time is plotted in a two-dimensional plane coordinate graph with time as the horizontal axis, and a trend curve is connected. Ideally, it is a fluctuating horizontal line, and it conforms to the normal distribution in the data distribution probability. It is suitable for analysis and diagnosis by SPC tools. Management control can be carried out through Xbar-R (mean range chart) in SPC tools.

[0056] When the device fails (contact resistance mutation, local overheating, partial discharge, heat dissipation structure mutation, etc.), K Rλ (t) will be offset. According to the amplitude and trend of the offset of K Rλ (t), the judgment of the device failure state is made.

[0057] In an embodiment, for normal power equipment three-phase, when the three-phase monitoring points are the same, the sensors are the same, and the distances are similar, it can be considered that the temperature rise load performance factors are similar: λa≈λb≈λc, Ra≈Rb≈Rc, then K Rλ a≈K Rλ b≈K Rλ c. And generally, the three-phase of the device is similar at the same time, the load of the three-phase is similar, and the temperature rise is similar. From the device temperature rise load performance index algorithm, it can be concluded that the three-phase has similar device temperature rise load performance indexes.

[0058] Sampling data at the same time for the three-phase of the device and comparing and calculating can effectively reduce the measurement deviation existing in the dynamic process of the system, and increase the reliability and accuracy of the diagnosis conclusion.

[0059] The device temperature rise load performance index three-phase deviation degree calculation formula is:

[0060]

[0061] K Rλ (t)max=max(K Rλ a(t),K Rλ b(t),K Rλ c(t)),K Rλ (t)max takes the maximum value in the three-phase ABC;

[0062] K Rλ (t)ave=average(K Rλ a(t),K Rλ b(t),K Rλ c(t)),K Rλ (t)ave takes the average value of the three-phase ABC.

[0063] The three-phase deviation degree of the temperature rise load performance of the device is set to an allowable range, and a state diagnosis is made. In an ideal case, there is: ε(t)≈0; when ε(t) is large, it represents that an abnormal situation occurs in a certain phase of the device. In the embodiment, the three-phase deviation degree of the temperature rise load performance of the device and the diagnosis criterion are as follows:

[0064]

[0065] In an embodiment, when the monitoring points of the three phases of the device are the same, the sensors are the same, the distances are similar, and the synchronous sampling is performed, the environment temperature is almost the same, the collection and calculation of the environment temperature can be avoided in the comparison calculation, the optimization calculation process is simplified, and the diagnosis result is optimized. The inter-phase temperature rise load variable ratio calculation formula is:

[0066]

[0067] And according to mathematical derivation, in an ideal case, there is: d ab (t)=K Rλ

[0068] Wherein, Ta(t) and Tb(t) are the temperatures of the monitored parts of any two phases of the three phases of the device; ΔTa(t) and ΔTb(t) are the temperature rises of the monitored parts of any two phases of the three phases of the device; Ia(t) and Ib(t) are the current values of any two phases of the three phases of the device; d ab (t) is the temperature rise load variable ratio between any two phases of the three phases of the device.

[0069] In engineering application, the temperature rise load variable ratio between any two phases of the three phases of the device can be calculated, and then diagnosis is performed. The extreme value method can be used for simplification, and the calculation formula is:

[0070]

[0071] T max (t)=max(T a (t),T b (t),T c (t))

[0072] T min (t)=min(T a (t),T b (t),T c (t))

[0073] I max (t)=max(I a (t),I b (t),I c (t))

[0074] I min(t) = min(I a (t), I b (t), I c (t))

[0075] where d(t) is the temperature rise load ratio between the devices; T max (t) is the maximum temperature in the ABC three-phase; T min (t) is the minimum temperature in the ABC three-phase; I max (t) is the maximum current in the ABC three-phase; I min (t) is the minimum current in the ABC three-phase; M is the magnification.

[0076] The algorithm conditions are: (1) T max (t) and I max (t), T min (t) and I min (t) must be the same phase, if not the same phase, do not calculate, directly let d(t) = -1, representing the diagnosis result is "device fault alarm" state; (2) value limit conditions: |I max (t) - I min (t)| > > 0, preferably, requires: |I max (t) - I min (t)| ≥ 100 A. If |I max (t) - I min (t)| < 100 A, it means that the load difference between the phases is too small, which is not suitable for this method of diagnosis, directly let d(t) = 0, representing the method cannot be diagnosed or the diagnosis result is "device normal" state.

[0077] Set the allowable range of three-phase deviation degree of the device temperature rise load performance, and make a state diagnosis. In the ideal case, there is: d(t) = k Rλ ; when d(t) deviates from kRλ greatly, it represents that there is an abnormal situation in one of the three phases of the device.

[0078] The allowable range of three-phase deviation degree of the device temperature rise load performance and the diagnosis criterion are as follows:

[0079] Device-to-device temperature rise load variation ratio d(t) range Fault level |d(t)-K Rλ |≥35%K Rλ ]]> Alarm 25% K Rλ ≤ |d(t) - K Rλ < 35% K Rλ ]]> Warning 15% K Rλ ≤ |d(t) - K Rλ < 25% K Rλ ]]> Attention |d(t)-K Rλ |<15%K Rλ ]]> Normal

[0080] An electronic device, comprising: a processor; a memory; and a program, wherein the program is stored in the memory and configured to be executed by the processor, the program comprising a power device temperature rise load performance index diagnosis method.

[0081] A computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to perform a power device temperature rise load performance index diagnosis method.

[0082] The application provides a power equipment temperature rise load performance index diagnosis method, comprising the following steps: physical mathematical modeling, establishing a power equipment load current and temperature mathematical model according to current heating and heat dissipation process analysis; calculating the equipment temperature rise load performance index, calculating the equipment temperature rise load performance index according to the power equipment load current and temperature mathematical model; judging the equipment fault state, judging the equipment fault state according to the amplitude and trend of the deviation of the equipment temperature rise load performance index with the passage of time or the three-phase deviation degree of the equipment temperature rise load performance index or the inter-phase temperature rise load variation ratio. The application relates to an electronic device and a storage medium, which are used to execute the power equipment temperature rise load performance index diagnosis method. The application applies the load current and temperature relationship model to the monitoring and diagnosis of the power equipment, greatly promotes the development of the power equipment state monitoring and diagnosis technology, improves the accuracy and reliability of the power equipment monitoring and diagnosis, and well solves the inherent problems existing in the power equipment state monitoring and diagnosis. The application is an important means for realizing the power equipment state maintenance management and improving the lean level of the power production operation management.

[0083] The above is only a preferred embodiment of the application, and does not limit the application in any form; any person skilled in the art can easily implement the application according to the above and the drawings; however, any equivalent changes, modifications and evolutions of the above disclosed technical content without departing from the technical solution range of the application are equivalent embodiments of the application; at the same time, any equivalent changes, modifications and evolutions of the above embodiments according to the essential technology of the application are still within the protection scope of the technical solution of the application.

Claims

1. A method for diagnosing the temperature rise load performance index of power equipment, characterized in that, Includes the following steps: Physical mathematical modeling: Based on the analysis of current-induced heating and heat dissipation processes, a mathematical model of load current and temperature for power equipment is established. Calculate the equipment temperature rise load performance index, and calculate the equipment temperature rise load performance index according to the mathematical model of the power equipment load current and temperature; To determine the equipment fault status, the judgment is made based on the magnitude and trend of the deviation of the equipment temperature rise load performance index over time, or the three-phase deviation of the equipment temperature rise load performance index, or the phase-to-phase temperature rise load ratio. The formula for calculating the interphase temperature rise load ratio is as follows: Where, Ta(t) and Tb(t) are the temperatures of any two phases of the three-phase equipment being monitored; ΔTa(t) and ΔTb(t) are the temperature rises of any two phases of the three-phase equipment being monitored; Ia(t) and Ib(t) are the current values ​​of any two phases of the three-phase equipment; d ab (t) represents the temperature rise load ratio between any two phases of the three-phase equipment; The calculation formula for the interphase temperature rise load ratio is simplified by taking the extreme value method: T max (t)=max(T a (t),T b (t),T c (t)) T min (t)=min(T a (t),T b (t),T c (t)) I max (t)=max(I a (t),I b (t),I c (t)) I min (t)=min(I a (t),I b (t),I c (t)) Where d(t) is the temperature rise load ratio between equipment phases; T max (t) Take the maximum temperature among the three phases A, B, and C; T min (t) Take the minimum temperature among the three phases A, B, and C; I max (t) Take the maximum current value among the three phases A, B, and C; I min (t) Take the minimum current among the three phases A, B, and C; M is the amplification factor; When d(t) deviates from K Rλ When the value is outside the allowable range, it indicates that an abnormality has occurred in one of the three phases of the equipment; where K Rλ The temperature rise load performance index of the equipment in the monitored part.

2. The method for diagnosing the temperature rise load performance index of power equipment as described in claim 1, characterized in that: The mathematical model for the load current and temperature of the power equipment is as follows: make: but Where Q(t) is the total heat generation power of the monitored section of the circuit, R is the total resistance of the monitored section of the circuit, I(t) is the steady-state load current of the monitored section of the circuit, T1(t) is the temperature of the monitored part, T0(t) is the ambient temperature of the monitored equipment, ΔT(t) is the temperature rise of the monitored part, λ is the heat dissipation coefficient between the monitored part and the environmental reference point, and K Rλ The coefficients of the load current-temperature relationship model are called the temperature rise load performance index of the monitored equipment.

3. The method for diagnosing the temperature rise load performance index of power equipment as described in claim 2, characterized in that: In the step of calculating the temperature rise load performance index of the equipment, the temperature rise load performance index of the equipment is amplified by a fixed factor.

4. The method for diagnosing the temperature rise load performance index of power equipment as described in claim 1, characterized in that: The method of judging the equipment fault status based on the magnitude and trend of the shift of the equipment temperature rise load performance index over time is as follows: plot the data of the change process of the equipment temperature rise load performance index over time on a two-dimensional plane coordinate graph with time as the horizontal axis, and connect them to form a trend curve. The equipment fault status is judged based on the magnitude and trend of the shift of the equipment temperature rise load performance index in the trend graph.

5. The method for diagnosing the temperature rise load performance index of power equipment as described in claim 1, characterized in that: The method of judging the equipment fault status based on the three-phase deviation of the equipment temperature rise load performance index is as follows: calculate the three-phase deviation of the equipment temperature rise load performance index, and determine whether the three-phase deviation of the equipment temperature rise load performance index is within the allowable range. If it is, it means that there is no abnormality in the equipment; otherwise, it means that there is an abnormality in a certain phase of the equipment.

6. The method for diagnosing the temperature rise load performance index of power equipment as described in claim 5, characterized in that: When judging the equipment fault status based on the three-phase deviation of the equipment temperature rise load performance index, sampling data of the three phases of the equipment at the same moment are performed for comparison and calculation; the calculation formula for the three-phase deviation of the equipment temperature rise load performance index is: K Rλ (t)max=max(K Rλ a(t),K Rλ b(t),K Rλ c(t)) K Rλ (t)ave=average(K Rλ a(t),K Rλ b(t),K Rλ c(t)) If ε(t) is not within the allowable range, then it is determined that an abnormality has occurred in some part of the equipment.

7. An electronic device, characterized in that... include: processor; Memory; And a program, wherein the program is stored in the memory and configured to be executed by a processor, the program comprising methods for performing any one of claims 1-6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor according to any one of claims 1-6.

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