Power distribution network operation optimization method and system based on power transformer

Abstract

The invention discloses a power transformer-based power distribution network operation optimization method and system. The method comprises the steps of simulating a parallel operation state of a plurality of power transformers in a power distribution network by establishing a power transformer simulation model; calculating load distribution of each power transformer by using a gradient descent method, and adjusting and optimizing the load distribution of each power transformer according to a calculation result; and based on a Weibull distribution analysis method, predicting the residual life of the key parts of the transformer, and performing reliability evaluation on the transformer simulation model according to a prediction result. By optimizing the operation, the electric energy loss is obviously reduced, and the operation cost is directly reduced; by means of intelligent management, the maintenance requirement and failure rate are reduced, the reliability and satisfaction degree of power supply are improved, and the stability of overall power supply is enhanced; by implementing parallel operation optimization and a timely maintenance strategy, the conditions of equipment overload, poor operation and the like can be effectively reduced, so that the service lives of the transformer and other equipment are prolonged, and the utilization rate of the equipment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution network operation optimization, and in particular to a power distribution network operation optimization method and system based on a power transformer. Background Art

[0002] A transformer is a device that uses the principle of electromagnetic induction to change AC voltage. Its main components are the primary coil, the secondary coil, and the iron core (magnetic core). In electrical equipment and wireless circuits, it is often used to increase or decrease voltage, match impedance, and provide safety isolation. In a generator, whether the coil moves through a magnetic field or the magnetic field moves through a fixed coil, an electric potential can be induced in the coil. In both cases, the value of the magnetic flux remains unchanged, but the amount of magnetic flux interlinked with the coil changes. This is the principle of mutual induction. A transformer is a device that uses electromagnetic mutual induction to transform voltage, current, and impedance.

[0003] Power transformers play a vital role in distribution networks. Their operation is based on the principle of electromagnetic induction. They are mainly responsible for the conversion of voltage levels to ensure that electric energy is efficiently and safely transmitted from power plants to users. With the development of smart grids, transformers are increasingly integrated into automated management systems, which can be remotely monitored, automatically adjusted, and even participate in the dynamic response of the power grid, such as voltage and reactive power control, to maintain the stable operation of the power grid.

[0004] When power transformers are operating in distribution networks, the optimization drawbacks that exist are mainly reflected in insulation aging and maintenance issues. After long-term operation of the transformer, the insulation material will age, shorten the life of the equipment, and increase the risk of failure; insufficient maintenance, including cooling system failures, dust accumulation, corrosion problems, etc., will also reduce the operating efficiency and safety of the transformer. Summary of the invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a distribution network operation optimization method and system based on power transformer to solve the problems of insulation material aging, shortened equipment life, increased failure risk and insufficient maintenance, including cooling system failure, dust accumulation and corrosion after long-term operation of the transformer.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a method for optimizing the operation of a distribution network based on a power transformer, comprising: simulating the parallel operation state of multiple power transformers in a distribution network by establishing a power transformer simulation model; calculating the load distribution of each power transformer using a gradient descent method, and adjusting and optimizing the load distribution of each power transformer according to the calculation results; predicting the remaining life of key components of the power transformer based on the Weibull distribution analysis method, and performing reliability evaluation on the power transformer simulation model according to the prediction results.

[0009] As a preferred solution of the power transformer-based distribution network operation optimization method described in the present invention, the prediction of the remaining life of key components of the power transformer based on the Weibull distribution analysis method includes:

[0010] Collect historical operation data of the transformer, screen valid life data in the historical operation data of the transformer, remove abnormal values, and determine failure events;

[0011] Use the maximum likelihood estimation method to estimate the parameters of the Weibull distribution, and determine the distribution type that best fits the data by fitting the data to the Weibull distribution model;

[0012] The reliability function R(t) at a specific time point is calculated, and the possibility of failure over time is evaluated through the failure rate function h(t). The median life, mean life and confidence interval of the transformer are calculated according to the required confidence level, and the failure mode is analyzed using the shape parameter k of the Weibull distribution.

[0013] As a preferred solution of the power transformer-based distribution network operation optimization method of the present invention, the method of analyzing the fault mode using the shape parameter k of the Weibull distribution includes:

[0014] If the shape parameter k of the Weibull distribution is less than 1, it indicates that the risk of early failure of the power transformer is high; if the shape parameter k of the Weibull distribution is 1, it indicates that the failure rate of the power transformer corresponds to an exponential distribution, which means a constant failure rate; if the shape parameter k of the Weibull distribution is greater than 1, it indicates that the failure rate gradually increases with the aging of the equipment.

[0015] As a preferred solution of the power transformer-based distribution network operation optimization method of the present invention, the reliability evaluation of the power transformer simulation model includes:

[0016] The number of failures and mean repair time of power transformers and systems before and after optimization as well as the reduction in unplanned downtime are statistically analyzed, and it is evaluated whether the continuous power supply capability of the system is improved in the event of a single component failure.

[0017] As a preferred solution of the power transformer-based distribution network operation optimization method of the present invention, wherein: the use of the gradient descent method to calculate the load distribution of each power transformer includes:

[0018] Randomly select an initial point as the starting value of the parameter;

[0019] Calculate the gradient of the loss function for the current parameter value θ;

[0020] Update the parameter value according to the direction and magnitude of the calculated gradient;

[0021] Repeat the above steps until the preset maximum number of iterations is reached.

[0022] As a preferred solution of the power transformer-based distribution network operation optimization method described in the present invention, the formula for calculating the gradient of the current parameter value θ loss function is:

[0023]

[0024] Among them, θ represents the parameters of the transformer model, J(θ) represents the loss function, and α represents the learning rate. represents the gradient of the loss function with respect to the transformer model parameters θ.

[0025] As a preferred solution of the power transformer-based distribution network operation optimization method of the present invention, wherein: the establishment of a power transformer simulation model to simulate the parallel operation state of multiple power transformers in the distribution network includes:

[0026] Define the parameters of the power transformer system, including voltage level, frequency, rated capacity, rated voltage, impedance value and load type and distribution;

[0027] Based on the parameters of the power transformer system, a single transformer model is established through NEPLAN simulation software, and the connection method between the transformers is adjusted to integrate multiple single transformer models into a power transformer simulation model;

[0028] The constructed model is simulated to observe and record the parameter changes when the transformers are running in parallel.

[0029] In a second aspect, the present invention provides a distribution network operation optimization system based on a power transformer, comprising:

[0030] A simulation module is used to simulate the parallel operation status of multiple power transformers in the distribution network by establishing a power transformer simulation model;

[0031] An adjustment and optimization module is used to calculate the load distribution of each power transformer using a gradient descent method, and adjust and optimize the load distribution of each power transformer according to the calculation results;

[0032] The prediction and evaluation module is used to predict the remaining life of key components of the power transformer based on the Weibull distribution analysis method, and to perform reliability evaluation on the power transformer simulation model according to the prediction results.

[0033] In a third aspect, the present invention provides an electronic device, comprising:

[0034] Memory and processor;

[0035] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the power transformer-based distribution network operation optimization method are implemented.

[0036] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the power transformer-based distribution network operation optimization method.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a distribution network operation optimization method and system based on power transformers, which significantly reduces power loss and directly reduces costs by optimizing operation; at the same time, it reduces maintenance frequency and failure rate with the help of intelligent management, and improves the efficiency of intelligent operation and maintenance. In addition, the present invention can effectively avoid equipment overload and poor operation by implementing parallel operation optimization and timely maintenance strategies, thereby extending the service life of transformers and other equipment, improving the reliability of power supply, and enhancing the stability of the overall power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0039] Figure 1 The present invention is a schematic diagram of the overall process logic of a power transformer-based distribution network operation optimization method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0041] Example 1

[0042] Reference Figure 1 As an embodiment of the present invention, a method for optimizing the operation of a distribution network based on a power transformer is provided, such as Figure 1 The specific steps shown include:

[0043] S100: Simulate the parallel operation state of multiple power transformers in the distribution network by establishing a power transformer simulation model;

[0044] S200: Calculate the load distribution of each power transformer using a gradient descent method, and adjust and optimize the load distribution of each power transformer according to the calculation result;

[0045] S300: Predict the remaining life of key components of power transformers based on Weibull distribution analysis, and perform reliability assessment on power transformer simulation models based on the prediction results.

[0046] It should be noted that the present invention provides a distribution network operation optimization method and system based on power transformers, which significantly reduces power loss and directly reduces costs by optimizing operation; at the same time, it reduces maintenance frequency and failure rate with the help of intelligent management, and improves the efficiency of intelligent operation and maintenance. In addition, the present invention can effectively avoid equipment overload and poor operation by implementing parallel operation optimization and timely maintenance strategies, thereby extending the service life of transformers and other equipment, improving the reliability of power supply, and enhancing the stability of the overall power supply.

[0047] In the embodiment of the present application, the above step S100 simulates the parallel operation state of multiple power transformers in the distribution network by establishing a power transformer simulation model, including:

[0048] Define the parameters of the power transformer system, including voltage level, frequency, rated capacity, rated voltage, impedance value and load type and distribution;

[0049] Based on the parameters of the power transformer system, a single transformer model is established through NEPLAN simulation software, and the connection method between transformers is adjusted to integrate multiple single transformer models into a power transformer simulation model;

[0050] The constructed model is simulated to observe and record the parameter changes when the transformers are running in parallel.

[0051] It should be noted that the above step S100 can not only accurately reflect the working characteristics of the power transformer and their mutual influence under actual operating conditions, but also provide a solid data foundation for subsequent load distribution optimization and reliability evaluation, ensuring that the analysis and optimization of the entire system can be carried out in a close to real environment, thereby improving the effectiveness and feasibility of the final solution.

[0052] In the embodiment of the present application, the step S200 of calculating the load distribution of each power transformer by using the gradient descent method includes:

[0053] Randomly select an initial point as the starting value of the parameter;

[0054] Calculate the gradient of the loss function for the current parameter value θ;

[0055] Update the parameter value according to the direction and magnitude of the calculated gradient;

[0056] Repeat the above steps until the preset maximum number of iterations is reached.

[0057] Specifically, the formula for calculating the gradient of the loss function for the current parameter value θ is:

[0058]

[0059] Among them, θ represents the parameters of the transformer model, J(θ) represents the loss function, and α represents the learning rate. represents the gradient of the loss function with respect to the transformer model parameters θ.

[0060] It should be noted that in the calculation of the gradient descent method, the gradient descent may converge to a local minimum rather than a global minimum, especially in the optimization of non-convex functions. For this situation, there are many strategies that can be tried, such as using different initialization strategies, adjusting the learning rate, using momentum or more advanced optimization algorithms such as Adam, RMSprop, etc. There are three common forms of Weibull distribution: one parameter (exponential distribution), two parameters, and three parameters. By fitting the data to the Weibull distribution model, determine the distribution type that best suits the data. The maximum likelihood estimation (MLE) method is usually used to estimate the parameters of the Weibull distribution (shape parameter k, scale parameter α, and sometimes location parameter β). The two-parameter Weibull distribution (shape parameter k and scale parameter α) is most common in the life analysis of power equipment because it can describe multiple modes of equipment aging over time.

[0061] It should be noted that the above step S200 can effectively find the optimal or nearly optimal load distribution plan, ensuring that each transformer operates within its most efficient or safest operating range, which not only helps to improve the operating efficiency of the entire distribution network and reduce energy consumption, but also reduces the risk of equipment damage due to overload, extends the service life of the equipment, and at the same time ensures the stability and reliability of the power supply.

[0062] In the embodiment of the present application, the above step S300 includes:

[0063] In a feasible implementation, predicting the remaining life of key components of a power transformer based on the Weibull distribution analysis method includes:

[0064] Collect historical operation data of transformers, filter valid life data in the historical operation data of transformers, remove abnormal values, and identify failure events;

[0065] Use the maximum likelihood estimation method to estimate the parameters of the Weibull distribution, and determine the distribution type that best fits the data by fitting the data to the Weibull distribution model;

[0066] The reliability function R(t) at a specific time point is calculated, and the possibility of failure over time is evaluated through the failure rate function h(t). The median life, mean life and confidence interval of the transformer are calculated according to the required confidence level, and the failure mode is analyzed using the shape parameter k of the Weibull distribution.

[0067] In a feasible implementation, if the shape parameter k of the Weibull distribution is less than 1, it indicates that the risk of early failure of the power transformer is high; if the shape parameter k of the Weibull distribution is 1, it indicates that the failure rate of the power transformer corresponds to an exponential distribution, which means a constant failure rate; if the shape parameter k of the Weibull distribution is greater than 1, it indicates that the failure rate gradually increases as the equipment ages.

[0068] In a feasible implementation, reliability assessment of the power transformer simulation model includes: statistically analyzing the number of failures and average repair time of the power transformer and system before and after optimization, as well as the reduction in unplanned downtime, and evaluating whether the system's continuous power supply capability is improved in the event of a single component failure.

[0069] It should be noted that the above step S300 can not only detect potential failure risks in advance and provide a scientific basis for formulating preventive maintenance plans, but also accurately evaluate the reliability and life of power transformers under different operating conditions, thereby helping power companies optimize asset management, reduce unexpected downtime and maintenance costs, and improve the overall operating efficiency and economy of the power system.

[0070] Example 2

[0071] This embodiment provides a distribution network operation optimization system based on power transformers, including a simulation module, an adjustment and optimization module, and a prediction and evaluation module;

[0072] Specifically, the simulation module is used to simulate the parallel operation state of multiple power transformers in the distribution network by establishing a power transformer simulation model;

[0073] Specifically, the adjustment and optimization module is used to calculate the load distribution of each power transformer using the gradient descent method, and adjust and optimize the load distribution of each power transformer according to the calculation results;

[0074] Specifically, the prediction and evaluation module is used to predict the remaining life of key components of the power transformer based on the Weibull distribution analysis method, and to perform reliability evaluation on the power transformer simulation model according to the prediction results.

[0075] It should be noted that the technical solution of the system for optimizing the operation of distribution network based on power transformer and the technical solution of the above-mentioned method for optimizing the operation of distribution network based on power transformer belong to the same concept. For the details not described in detail in the technical solution of the system for optimizing the operation of distribution network based on power transformer in this embodiment, please refer to the description of the technical solution of the above-mentioned method for optimizing the operation of distribution network based on power transformer.

[0076] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0077] This embodiment also provides an electronic device, which includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a distribution network operation optimization method based on a power transformer is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0078] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method proposed in the above embodiment is implemented.

[0079] The storage medium proposed in this embodiment and the method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0080] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0081] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0082] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt 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.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0083] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0084] 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.

[0085] 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.

[0086] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0087] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for optimizing the operation of a distribution network based on a power transformer, characterized in that: include: By establishing a power transformer simulation model, the parallel operation status of multiple power transformers in the distribution network is simulated; The load distribution of each power transformer is calculated by using the gradient descent method, and the load distribution of each power transformer is adjusted and optimized according to the calculation results; The remaining life of key components of the power transformer is predicted based on the Weibull distribution analysis method, and the reliability of the power transformer simulation model is evaluated according to the prediction results.

2. The method for optimizing the operation of a power distribution network based on a power transformer according to claim 1, characterized in that: The method for predicting the remaining life of key components of power transformers based on Weibull distribution analysis includes: Collect historical operation data of the transformer, screen valid life data in the historical operation data of the transformer, remove abnormal values, and determine failure events; Use the maximum likelihood estimation method to estimate the parameters of the Weibull distribution, and determine the distribution type that best fits the data by fitting the data to the Weibull distribution model; The reliability function R(t) at a specific time point is calculated, and the possibility of failure over time is evaluated through the failure rate function h(t). The median life, mean life and confidence interval of the transformer are calculated according to the required confidence level, and the failure mode is analyzed using the shape parameter k of the Weibull distribution.

3. The method for optimizing the operation of a power distribution network based on a power transformer according to claim 2, characterized in that: The analysis of the failure mode using the shape parameter k of the Weibull distribution includes: If the shape parameter k of the Weibull distribution is less than 1, it indicates that the risk of early failure of the power transformer is high; if the shape parameter k of the Weibull distribution is 1, it indicates that the failure rate of the power transformer corresponds to an exponential distribution, which means a constant failure rate; if the shape parameter k of the Weibull distribution is greater than 1, it indicates that the failure rate gradually increases with the aging of the equipment.

4. The method for optimizing the operation of a power distribution network based on a power transformer according to claim 3, characterized in that: The reliability assessment of the power transformer simulation model comprises: The number of failures and mean repair time of power transformers and systems before and after optimization as well as the reduction in unplanned downtime are statistically analyzed, and it is evaluated whether the continuous power supply capability of the system is improved in the event of a single component failure.

5. The method for optimizing the operation of a power distribution network based on a power transformer according to claim 1, characterized in that: The method of calculating the load distribution of each power transformer by using the gradient descent method includes: Randomly select an initial point as the starting value of the parameter; Calculate the gradient of the loss function for the current parameter value θ; Update the parameter value according to the direction and magnitude of the calculated gradient; Repeat the above steps until the preset maximum number of iterations is reached.

6. The method for optimizing the operation of a power distribution network based on a power transformer according to claim 5, characterized in that: The formula for calculating the gradient of the current parameter value θ loss function is: Among them, θ represents the parameters of the transformer model, J(θ) represents the loss function, and α represents the learning rate. represents the gradient of the loss function with respect to the transformer model parameters θ.

7. The method for optimizing the operation of a power distribution network based on a power transformer according to claim 1, characterized in that: The method of simulating the parallel operation state of multiple power transformers in the distribution network by establishing a power transformer simulation model includes: Define the parameters of the power transformer system, including voltage level, frequency, rated capacity, rated voltage, impedance value and load type and distribution; Based on the parameters of the power transformer system, a single transformer model is established through NEPLAN simulation software, and the connection method between the transformers is adjusted to integrate multiple single transformer models into a power transformer simulation model; The constructed model is simulated to observe and record the parameter changes when the transformers are running in parallel.

8. A system using the power transformer-based distribution network operation optimization method according to any one of claims 1 to 7, characterized in that: include: A simulation module is used to simulate the parallel operation status of multiple power transformers in the distribution network by establishing a power transformer simulation model; An adjustment and optimization module is used to calculate the load distribution of each power transformer using a gradient descent method, and adjust and optimize the load distribution of each power transformer according to the calculation results; The prediction and evaluation module is used to predict the remaining life of key components of the power transformer based on the Weibull distribution analysis method, and to perform reliability evaluation on the power transformer simulation model according to the prediction results.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the power transformer-based distribution network operation optimization method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the power transformer-based distribution network operation optimization method according to any one of claims 1 to 7.

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