Transformer oil temperature prediction method and system
By constructing the accumulated sequence of transformer oil temperature and winding temperature and calculating the prediction coefficient, the problem of insufficient oil temperature prediction accuracy in traditional monitoring methods is solved, and accurate prediction of transformer oil temperature is achieved, fault risk is reduced, and the stable operation of the power system is supported.
Patent Information
- Application Number
- CN202411298451.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-18
- Publication Date
- 2025-01-14
AI Technical Summary
The prior art has problems such as sensor failure, maintenance difficulties and inability to provide future oil temperature prediction in the oil temperature monitoring of transformers, resulting in insufficient response delay and prediction accuracy.
By constructing an accumulated sequence of oil temperature and winding temperature, the prediction coefficient is calculated, and matrix operations are performed to generate oil temperature prediction values to improve prediction accuracy.
It realizes accurate prediction of transformer oil temperature, reduces the chance of failure, supports preventive maintenance, and extends the stable operation and equipment life of the power system.
Smart Images
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Abstract
Description
Technical Field
[0001] The present invention relates to an oil temperature prediction method and system, and in particular to a transformer oil temperature prediction method and system. Background Art
[0002] In the power transmission and distribution system, the transformer is a core component responsible for the efficient transmission and distribution of electrical energy. Transformer oil temperature is an important indicator that affects the cooling efficiency, insulation performance and ultimate operating life of the transformer. Therefore, accurate monitoring and prediction of transformer oil temperature is essential to ensure the reliable operation of the power system. At present, the monitoring of transformer oil temperature mainly relies on temperature sensors that can provide real-time temperature readings. Although this method directly measures the oil temperature, there are problems such as sensor failure, maintenance difficulties, and monitoring blind spots in actual applications. In addition, traditional monitoring methods cannot provide predictions of future oil temperature changes, so response measures may be delayed when abnormal conditions occur.
[0003] In recent years, with the improvement of computing power and the advancement of data processing technology, methods for predicting transformer oil temperature using algorithms have been studied and applied. These methods predict future oil temperature changes by analyzing historical data to provide decision support for transformer operation and maintenance. However, existing prediction methods often require a large amount of historical data and are not sensitive enough to complex changes in the transformer operating environment, which limits the prediction accuracy and applicability. Summary of the invention
[0004] Purpose of the invention: The purpose of the present invention is to provide a transformer oil temperature prediction method and system to improve the prediction accuracy of transformer oil temperature.
[0005] Technical solution: The present invention comprises the following steps:
[0006] Input data definition: extract oil temperature history data and winding temperature history data, and convert them into corresponding matrix form;
[0007] Cumulative sequence calculation: Based on the original historical data, the oil temperature data and winding temperature historical data are accumulated respectively to generate the corresponding cumulative sequence;
[0008] Prediction coefficient calculation: According to the oil temperature accumulation sequence and the winding temperature accumulation sequence, the first coefficient matrix, the second coefficient matrix and the third coefficient matrix are constructed, and the corresponding first prediction coefficient and the second prediction coefficient are obtained by performing matrix operations on the three coefficient matrices. The first prediction coefficient and the second prediction coefficient are the key parameters for temperature prediction;
[0009] A matrix operation is performed according to the first prediction coefficient, the second prediction coefficient, and the winding temperature accumulation sequence to obtain the corresponding oil temperature prediction value.
[0010] The matrix representation of the oil temperature historical data is:
[0011]
[0012] in, is the oil temperature historical data matrix, is the corresponding element, and n is the number of elements. The matrix of the winding temperature history data is expressed as:
[0013]
[0014] in, is the oil temperature historical data matrix, For the corresponding elements.
[0015] The cumulative series of the oil temperature is expressed as:
[0016]
[0017] in, is the oil temperature accumulation sequence matrix, For the corresponding elements.
[0018] The cumulative series of the winding temperature is expressed as:
[0019]
[0020] in, is the winding temperature accumulation sequence matrix, For the corresponding elements.
[0021] The first coefficient matrix, the second coefficient matrix, and the third coefficient matrix are:
[0022]
[0023] Wherein, B1 is the first coefficient matrix, B2 is the second coefficient matrix, and B3 is the third coefficient matrix. The calculation formula of the first prediction coefficient is expressed as:
[0024]
[0025] Among them, W1 is the first prediction coefficient.
[0026] The calculation formula of the second prediction coefficient is expressed as:
[0027]
[0028] Wherein, W2 is the second prediction coefficient.
[0029] The calculation formula of the predicted value is:
[0030]
[0031] in, is the predicted value of the oil temperature data.
[0032] A transformer oil temperature prediction system, comprising:
[0033] Input data definition module: used to define input data;
[0034] Cumulative sequence calculation module: used to calculate the cumulative sequence corresponding to the input data;
[0035] Prediction coefficient calculation module: used to calculate the prediction coefficient;
[0036] Prediction value calculation module: used to calculate the prediction value.
[0037] Beneficial effect: The present invention constructs oil temperature and winding temperature input data, calculates the cumulative sequence, calculates the prediction coefficient based on the above data, and finally calculates the predicted value, which effectively improves the prediction accuracy of transformer oil temperature. It has important theoretical and practical significance for guiding the predictive operation and maintenance of transformers and reducing the probability of failure. BRIEF DESCRIPTION OF THE DRAWINGS
[0038] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION
[0039] The present invention will be further described below in conjunction with the accompanying drawings.
[0040] like Figure 1 As shown, the transformer oil temperature prediction method of the present invention comprises the following steps:
[0041] S1. Input data definition: extract oil temperature history data and winding temperature history data, and convert them into corresponding matrix forms to construct oil temperature input data and winding temperature input data.
[0042] Transformer oil temperature prediction requires two types of data, namely oil temperature history data and winding temperature history data. The matrix of oil temperature history data is expressed as:
[0043]
[0044] in, is the oil temperature historical data matrix, is the corresponding element, and n is the number of elements.
[0045] The matrix representation of the winding temperature history data is:
[0046]
[0047] in, is the oil temperature historical data matrix, For the corresponding elements.
[0048] S2. Cumulative sequence calculation: Based on the original historical data, the oil temperature data and the winding temperature historical data are accumulated respectively to generate a corresponding cumulative sequence.
[0049] The cumulative series of oil temperature can be expressed as:
[0050]
[0051] in, is the oil temperature accumulation sequence matrix, For the corresponding elements.
[0052] The cumulative series of winding temperature can be expressed as:
[0053]
[0054] in, is the winding temperature accumulation sequence matrix, For the corresponding elements.
[0055] S3. Calculation of prediction coefficients: According to the oil temperature accumulation sequence and the winding temperature accumulation sequence, the first coefficient matrix, the second coefficient matrix and the third coefficient matrix are constructed, and matrix operations are performed on the three coefficient matrices to obtain the corresponding first prediction coefficient and second prediction coefficient. The first prediction coefficient and the second prediction coefficient are key parameters for temperature prediction.
[0056] The first coefficient matrix, the second coefficient matrix, and the third coefficient matrix are:
[0057]
[0058] Among them, B1 is the first coefficient matrix, B2 is the second coefficient matrix, and B3 is the third coefficient matrix.
[0059] The calculation formula of the first prediction coefficient can be expressed as:
[0060]
[0061] Among them, W1 is the first prediction coefficient.
[0062] The calculation formula of the second prediction coefficient can be expressed as:
[0063]
[0064] Wherein, W2 is the second prediction coefficient.
[0065] S4. Calculation of predicted value: Perform matrix operation based on the first prediction coefficient, the second prediction coefficient, and the winding temperature accumulation sequence to obtain the corresponding oil temperature prediction value.
[0066] The calculation formula of the predicted value can be expressed as:
[0067]
[0068] in, is the predicted value of the oil temperature data.
[0069] The method of the present invention can combine real-time monitoring data and transformer operation conditions, as well as consider the influence of environmental factors, to provide accurate and reliable oil temperature prediction. This can not only improve the accuracy of the prediction, but also help transformer health management and preventive maintenance, ultimately achieving stable operation of the power system and extending its service life.
[0070] The transformer oil temperature prediction system of the present invention comprises:
[0071] Input data definition module: used to define input data;
[0072] Cumulative sequence calculation module: used to calculate the cumulative sequence corresponding to the input data;
[0073] Prediction coefficient calculation module: used to calculate the prediction coefficient;
[0074] Prediction value calculation module: used to calculate the prediction value.
[0075] The present invention also discloses a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, and when the instructions are executed by a computing device, the computing device executes a transformer oil temperature prediction method.
[0076] Based on the same technical solution, the present invention also discloses a computing device, including one or more processors, one or more memories and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by one or more processors, and the one or more programs include instructions for executing a transformer oil temperature prediction method.
[0077] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0078] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0079] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0080] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
Claims
1. A transformer oil temperature prediction method, characterized in that: The following steps are involved: Input data definition: extract oil temperature history data and winding temperature history data, and convert them into corresponding matrix form; Cumulative sequence calculation: Based on the original historical data, the oil temperature data and winding temperature historical data are accumulated respectively to generate the corresponding cumulative sequence; Prediction coefficient calculation: According to the oil temperature accumulation sequence and the winding temperature accumulation sequence, the first coefficient matrix, the second coefficient matrix and the third coefficient matrix are constructed, and the corresponding first prediction coefficient and the second prediction coefficient are obtained by performing matrix operations on the three coefficient matrices. The first prediction coefficient and the second prediction coefficient are the key parameters for temperature prediction; A matrix operation is performed according to the first prediction coefficient, the second prediction coefficient, and the winding temperature accumulation sequence to obtain the corresponding oil temperature prediction value.
2. A transformer oil temperature prediction method according to claim 1, characterized in that: The matrix representation of the oil temperature historical data is: in, is the oil temperature historical data matrix, is the corresponding element, and n is the number of elements.
3. A transformer oil temperature prediction method according to claim 2, characterized in that: The matrix of the winding temperature history data is expressed as: in, is the oil temperature historical data matrix, For the corresponding elements.
4. A transformer oil temperature prediction method according to claim 3, characterized in that: The cumulative series of the oil temperature is expressed as: in, is the oil temperature accumulation sequence matrix, For the corresponding elements.
5. A transformer oil temperature prediction method according to claim 4, characterized in that: The cumulative series of the winding temperature is expressed as: in, is the winding temperature accumulation sequence matrix, For the corresponding elements.
6. A transformer oil temperature prediction method according to claim 5, characterized in that: The first coefficient matrix, the second coefficient matrix, and the third coefficient matrix are: Among them, B1 is the first coefficient matrix, B2 is the second coefficient matrix, and B3 is the third coefficient matrix.
7. A transformer oil temperature prediction method according to claim 6, characterized in that: The calculation formula of the first prediction coefficient is expressed as: Among them, W1 is the first prediction coefficient.
8. A transformer oil temperature prediction method according to claim 7, characterized in that: The calculation formula of the second prediction coefficient is expressed as: Wherein, W2 is the second prediction coefficient.
9. A transformer oil temperature prediction method according to claim 8, characterized in that: The calculation formula of the predicted value is: in, is the predicted value of the oil temperature data.
10. A transformer oil temperature prediction system, characterized in that: include: Input data definition module: used to define input data; Cumulative sequence calculation module: used to calculate the cumulative sequence corresponding to the input data; Prediction coefficient calculation module: used to calculate the prediction coefficient; Prediction value calculation module: used to calculate the prediction value.