Transformer maintenance strategy making method and device, storage medium and equipment

Abstract

The invention discloses a method and device for formulating a transformer maintenance strategy, a storage medium and equipment, relates to the technical field of transformer maintenance, and mainly aims to solve the problems that overall planning of the health state of parts is lacked and the service life of a transformer cannot be dynamically evaluated in the formulating process of an existing transformer maintenance strategy. Comprising the following steps: acquiring monitoring or test data based on state parameters corresponding to each key component in a transformer, and determining a state score of each state parameter based on the monitoring or test data; obtaining a parameter weight corresponding to the state parameter and a component weight corresponding to the key component, and determining an overall health index of the transformer based on the parameter weight, the component weight and the state score; determining a transformer failure rate based on the overall health index, and establishing a target function of a transformer maintenance strategy based on the overall health index and the transformer failure rate; and performing optimization solution on the target function of the transformer maintenance strategy by adopting the intelligent optimization model to obtain a target maintenance strategy of the transformer.

Description

Technical Field

[0001] The present invention relates to the technical field of transformer maintenance, and in particular to a method and device for formulating a transformer maintenance strategy, a storage medium, and equipment. Background Art

[0002] In a substation, the transformer is the core device for energy transmission and distribution, and its performance is directly related to the operating efficiency and reliability of the entire substation. In order to ensure the normal operation of the substation and even the entire power system, the formulation of the maintenance strategy for the power transformer is particularly critical.

[0003] At present, the formulation of transformer maintenance strategies is usually based on an in-depth understanding of its structure and fault causes, combined with condition monitoring technology to evaluate the operating status. Regular and conditional maintenance are combined, based on risk assessment and life prediction models to ensure economy and efficiency. However, the existing transformer maintenance strategy has not yet comprehensively considered the health status of different components of the power transformer when it was formulated, and the evaluation of the transformer's performance such as life lacks dynamism, which cannot effectively realize the full utilization of transformer equipment. Summary of the invention

[0004] In view of this, the present invention provides a method and device for formulating a transformer maintenance strategy, a storage medium, and equipment, the main purpose of which is to solve the problems of lack of overall consideration of component health status and inability to dynamically evaluate transformer life in the process of formulating existing transformer maintenance strategies.

[0005] According to one aspect of the present invention, a method for formulating a transformer maintenance strategy is provided, comprising:

[0006] Acquire monitoring or experimental data based on the state parameters corresponding to each key component in the transformer, and determine the state score of each state parameter based on the monitoring or experimental data;

[0007] Obtaining parameter weights corresponding to the state parameters and component weights corresponding to the key components, and determining an overall health index of the transformer based on the parameter weights, the component weights and the state score;

[0008] Determining a transformer failure rate based on the overall health index, and establishing an objective function of a transformer maintenance strategy based on the overall health index and the transformer failure rate;

[0009] An intelligent optimization model is used to optimize and solve the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer.

[0010] Furthermore, the key components include a body, a bushing, a cooling system, a tap changer and a non-electrical protection device;

[0011] The determining of the state score of each state parameter based on the monitoring or experimental data comprises:

[0012] Respectively acquiring the monitoring or experimental data corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device;

[0013] The monitoring or experimental data are normalized to obtain status scores corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device.

[0014] Further, determining the overall health index of the transformer based on the parameter weight, the component weight and the status score includes:

[0015] Obtaining target parameter weights and target status scores corresponding to each of the key components;

[0016] Performing weighted summation processing based on the target parameter weight and the target state score to obtain a component health index corresponding to each of the key components;

[0017] A weighted summation process is performed based on the component health index and the component weight to obtain an overall health index of the transformer.

[0018] Further, determining the transformer failure rate based on the overall health index includes:

[0019] Using an exponential function to simulate the exponential distribution relationship between the overall health index and the transformer failure rate;

[0020] The proportionality coefficient and the curvature coefficient in the exponential function are solved to obtain the transformer failure rate.

[0021] Furthermore, the objective function of the transformer maintenance strategy is established based on the overall health index and the transformer failure rate, including:

[0022] Determining a transformer health index objective function based on the overall health index;

[0023] Determine the transformer risk assessment objective function based on the power grid operation loss and fault recovery cost generated after the transformer fault occurs and the transformer failure rate;

[0024] The transformer maintenance cost objective function is determined based on the linear relationship between the transformer failure rate and the transformer maintenance cost.

[0025] Furthermore, before optimizing and solving the objective function of the transformer maintenance strategy by using the intelligent optimization model, the method further includes:

[0026] Obtain the factory value of the health index of the transformer, the expected life, and the termination value of the health index when the expected life is reached, and calculate the equipment aging coefficient of the transformer;

[0027] The relationship between the health status of the transformer and time is simulated based on the equipment aging coefficient and the overall health index to obtain a time-varying function of the health index.

[0028] Furthermore, the intelligent optimization model is used to optimize and solve the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer, including:

[0029] Initializing the maintenance strategy, and using the intelligent optimization model to adjust the initialized maintenance strategy to obtain an intermediate maintenance strategy;

[0030] Determine an equivalent service age corresponding to the intermediate maintenance strategy based on the service age regression factor, and determine an intermediate health index corresponding to the intermediate maintenance strategy based on the equivalent service age and a health index time-varying function;

[0031] Based on the intermediate health index, the transformer failure rate is updated to obtain an intermediate failure rate corresponding to the intermediate maintenance strategy;

[0032] An optimization solution is performed based on the intermediate failure rate, the intermediate health index and the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer.

[0033] According to another aspect of the present invention, a device for formulating a transformer maintenance strategy is provided, comprising:

[0034] A state scoring module, used to obtain monitoring or experimental data based on the state parameters corresponding to each key component in the transformer, and determine the state score of each state parameter based on the monitoring or experimental data;

[0035] A health index evaluation module, used to obtain parameter weights corresponding to the state parameters and component weights corresponding to the key components, and determine the overall health index of the transformer based on the parameter weights, the component weights and the state score;

[0036] A target determination module, used to determine the transformer failure rate based on the overall health index, and establish an objective function of the transformer maintenance strategy based on the overall health index and the transformer failure rate;

[0037] The optimization solution module is used to optimize and solve the objective function of the transformer maintenance strategy using an intelligent optimization model to obtain a target maintenance strategy for the transformer.

[0038] Furthermore, the key components include a body, a bushing, a cooling system, a tap changer and a non-electrical protection device; the status scoring module is also used for:

[0039] Respectively acquiring the monitoring or experimental data corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device;

[0040] The monitoring or experimental data are normalized to obtain status scores corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device.

[0041] Furthermore, the health index assessment module is also used for:

[0042] Obtaining target parameter weights and target status scores corresponding to each of the key components;

[0043] Performing weighted summation processing based on the target parameter weight and the target state score to obtain a component health index corresponding to each of the key components;

[0044] A weighted summation process is performed based on the component health index and the component weight to obtain an overall health index of the transformer.

[0045] Further, the target determination module includes a failure rate determination unit and an objective function determination unit;

[0046] The failure rate determination unit is used to:

[0047] Using an exponential function to simulate the exponential distribution relationship between the overall health index and the transformer failure rate;

[0048] The proportionality coefficient and the curvature coefficient in the exponential function are solved to obtain the transformer failure rate.

[0049] The objective function determination unit is used to:

[0050] Determining a transformer health index objective function based on the overall health index;

[0051] Determine the transformer risk assessment objective function based on the power grid operation loss and fault recovery cost generated after the transformer fault occurs and the transformer failure rate;

[0052] The transformer maintenance cost objective function is determined based on the linear relationship between the transformer failure rate and the transformer maintenance cost.

[0053] Furthermore, the device also includes a time-varying module, which is used to:

[0054] Obtain the factory value of the health index of the transformer, the expected life, and the termination value of the health index when the expected life is reached, and calculate the equipment aging coefficient of the transformer;

[0055] The relationship between the health status of the transformer and time is simulated based on the equipment aging coefficient and the overall health index to obtain a time-varying function of the health index.

[0056] Furthermore, the optimization solution module is also used for:

[0057] Initializing the maintenance strategy, and using the intelligent optimization model to adjust the initialized maintenance strategy to obtain an intermediate maintenance strategy;

[0058] Determine an equivalent service age corresponding to the intermediate maintenance strategy based on the service age regression factor, and determine an intermediate health index corresponding to the intermediate maintenance strategy based on the equivalent service age and a health index time-varying function;

[0059] Based on the intermediate health index, the transformer failure rate is updated to obtain an intermediate failure rate corresponding to the intermediate maintenance strategy;

[0060] An optimization solution is performed based on the intermediate failure rate, the intermediate health index and the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer.

[0061] According to another aspect of the present invention, a storage medium is provided, wherein the storage medium stores at least one executable instruction, wherein the executable instruction enables a processor to execute operations corresponding to the above-mentioned method for formulating a transformer maintenance strategy.

[0062] According to another aspect of the present invention, there is provided a device, comprising a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0063] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the method for formulating the transformer maintenance strategy as described above.

[0064] By means of the above technical solution, the technical solution provided by the embodiment of the present invention has at least the following advantages:

[0065] The present invention provides a method and device, storage medium, and equipment for formulating a transformer maintenance strategy. Compared with the prior art, the present invention obtains monitoring or experimental data based on the state parameters corresponding to each key component in the transformer, and determines the state score of each state parameter based on the monitoring or experimental data; obtains the parameter weight corresponding to the state parameter and the component weight corresponding to the key component, and determines the overall health index of the transformer based on the parameter weight, the component weight, and the state score; determines the transformer failure rate based on the overall health index, and establishes the objective function of the transformer maintenance strategy based on the overall health index and the transformer failure rate; uses an intelligent optimization model to optimize and solve the objective function of the transformer maintenance strategy, obtains the target maintenance strategy of the transformer, and realizes the formulation of the transformer maintenance strategy. In the process of formulating the maintenance strategy, the present invention not only comprehensively considers the health status of different components of the power transformer, but also considers the impact of maintenance on the life of the transformer, so that the formulated transformer maintenance strategy can effectively realize the full utilization of the transformer equipment while ensuring economy.

[0066] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0068] Figure 1 A schematic diagram of a process for formulating a transformer maintenance strategy provided by an embodiment of the present invention is shown;

[0069] Figure 2 A schematic flow chart of another method for formulating a transformer maintenance strategy provided by an embodiment of the present invention is shown;

[0070] Figure 3 A schematic flow chart of another method for formulating a transformer maintenance strategy provided by an embodiment of the present invention is shown;

[0071] Figure 4 A schematic flow chart of another method for formulating a transformer maintenance strategy provided by an embodiment of the present invention is shown;

[0072] Figure 5A schematic diagram of the structure of a transformer maintenance strategy formulation device provided by an embodiment of the present invention is shown;

[0073] Figure 6 A schematic structural diagram of a device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0074] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0075] The embodiment of the present invention provides a method for formulating a transformer maintenance strategy, such as Figure 1 As shown, the method includes:

[0076] 101. Acquire monitoring or experimental data based on state parameters corresponding to each key component in the transformer, and determine a state score of each state parameter based on the monitoring or experimental data;

[0077] In an embodiment of the present invention, the current execution end obtains monitoring or experimental data based on the state parameters corresponding to each key component in the transformer, wherein the key components are components that affect the health status of the transformer, such as the transformer body, bushing, cooling system, tap changer, and non-electrical protection device, etc., which are not specifically limited in the embodiment of the present invention. The current execution end selects the state parameters that have a significant impact on the health status of each key component as the evaluation index of the key component. For example, when the key components include the body, the monitoring or experimental data of the state parameters such as the winding absorption ratio, winding dielectric loss factor, furfural content, acetylene content, water content in oil, and total hydrocarbon content corresponding to the body can be obtained; when the key components include the bushing, the monitoring or experimental data of the state parameters such as the methane content, insulation resistance of the bushing end screen, initial value difference of capacitance, hydrogen content, and hot spot temperature of the bushing column can be obtained; when the key components include the cooling system, the monitoring or experimental data of the state parameters corresponding to the cooling system can be obtained. The monitoring or experimental data of the corresponding state parameters such as the oil pump temperature, the periodic switching of the cooler power supply, the operation of the fan, and the contamination of the cooler can be obtained; when the key components include a tap switch, the monitoring or experimental data of the state parameters such as the DC resistance difference, oil breakdown voltage, winding DC leakage current, and the number of tap switch operations corresponding to the tap switch can be obtained; when the key components include a non-electrical protection device, the monitoring or experimental data of the state parameters such as the insulation resistance of the pressure relief valve signal circuit, the insulation resistance of the heavy gas signal circuit, and the insulation resistance of the thermometer signal circuit corresponding to the non-electrical protection device can be obtained, and the embodiments of the present invention do not make specific limitations. After obtaining the monitoring or experimental data, the current execution end determines the state score of each state parameter based on the monitoring or experimental data. Among them, the state score reflects the state of each state parameter during monitoring.

[0078] 102. Obtain parameter weights corresponding to the state parameters and component weights corresponding to the key components, and determine an overall health index of the transformer based on the parameter weights, the component weights and the state score;

[0079] In an embodiment of the present invention, the current execution end obtains parameter weights corresponding to state parameters, wherein the parameter weights reflect the degree of influence of each state parameter on the health state of the corresponding key component, and the higher the value of the parameter weight, the greater the influence of the corresponding state parameter on the health state of the key component. In addition, the current execution end also obtains component weights corresponding to key components, wherein the component weights reflect the degree of influence of each key component on the health state of the transformer, and the higher the value of the component weight, the greater the influence of the corresponding key component on the health state of the transformer. After the current execution end obtains the parameter weights and component weights, it also determines the overall health index of the transformer based on the obtained parameter weights, component weights, and the state score obtained in step 101. The overall health index reflects the overall health state of the transformer and is obtained by comprehensively considering the health states of different components of the transformer.

[0080] It should be noted that the above-mentioned parameter weights and component weights can be set according to empirical values, and the parameter weights of each state parameter in the health status assessment of each key component and the component weights of each key component in the overall health status assessment of the transformer can also be obtained through the analytic hierarchy process (AHP), which is not specifically limited in the embodiment of the present invention.

[0081] In the embodiment of the present invention, a 500kV, 250MV·A main transformer of a substation is taken as an example for example analysis. The parameter weights of various state parameters of the transformer in the health status evaluation of each key component and the component weights of each key component in the overall health status evaluation of the transformer are shown in Tables 1 to 5 below.

[0082] Table 1 Parameter weights and component weights corresponding to the transformer body

[0083]

[0084] Table 2 Parameter weights and component weights corresponding to the transformer bushing

[0085]

[0086] Table 3 Parameter weights and component weights corresponding to the transformer cooling system

[0087]

[0088] Table 4 Parameter weights and component weights corresponding to the transformer tap changer

[0089]

[0090]

[0091] Table 5 Parameter weights and component weights corresponding to the non-electrical protection devices of transformers

[0092]

[0093] 103. Determine a transformer failure rate based on the overall health index, and establish an objective function of a transformer maintenance strategy based on the overall health index and the transformer failure rate;

[0094] In the embodiment of the present invention, since there is a correlation between the overall health status of the transformer and the transformer failure, the current execution end determines the transformer failure rate based on the overall health index. After obtaining the transformer failure rate, the current execution end establishes the objective function of the transformer maintenance strategy based on the overall health index and the transformer failure rate. Among them, the objective function of the transformer maintenance strategy not only comprehensively considers the health status of different components of the power transformer, but also considers the economy of maintenance and the risk of failure.

[0095] 104. Use an intelligent optimization model to optimize and solve the objective function of the transformer maintenance strategy to obtain a target maintenance strategy for the transformer.

[0096] In the embodiment of the present invention, the current execution end uses an intelligent optimization model to optimize and solve the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer. Among them, the intelligent optimization model represents a mathematical model of the process of seeking the optimal solution to a problem using certain steps, and does not have idempotence. In the embodiment of the present invention, the intelligent optimization model can adopt models such as gradient descent method, genetic algorithm, simulated annealing algorithm, ant colony algorithm and particle swarm optimization algorithm, as well as improved models of the above models, etc., which are not specifically limited in the embodiment of the present invention.

[0097] Further, as a refinement and extension of the specific implementation of the above embodiment, in order to unify the numerical range of the status score, another method for formulating the transformer maintenance strategy is provided, such as Figure 2 As shown, the step of determining the state score of each state parameter based on the monitoring or experimental data includes:

[0098] 201. Acquire the monitoring or experimental data corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device respectively;

[0099] In an embodiment of the present invention, the current execution end respectively obtains the monitoring or experimental data corresponding to the main body, the bushing, the cooling system, the tap switch and the non-electrical protection device; for example, the monitoring or experimental data of the state parameters such as the winding absorption ratio, the winding dielectric loss factor, the furfural content, the acetylene content, the water content in the oil, the total hydrocarbon content, etc. corresponding to the main body are obtained; the monitoring or experimental data of the state parameters such as the methane content, the insulation resistance of the bushing end screen, the initial value difference of the capacitance, the hydrogen content, the hot spot temperature of the bushing column, etc. corresponding to the bushing are obtained, and the embodiment of the present invention does not make specific limitations.

[0100] 202. Normalize the monitoring or experimental data to obtain status scores corresponding to the body, the bushing, the cooling system, the tap changer, and the non-electrical protection device, respectively.

[0101] In an embodiment of the present invention, the current execution end performs normalization processing on the monitoring or experimental data obtained in step 201, such as normalizing the monitoring or experimental data of state parameters such as the winding absorption ratio, winding dielectric loss factor, furfural content, acetylene content, water content in oil, and total hydrocarbon content corresponding to the main body to obtain a state score corresponding to the main body; normalizing the monitoring or experimental data of state parameters such as the methane content, insulation resistance of the end screen of the casing, initial value difference of capacitance, hydrogen content, hot spot temperature of the casing column, etc. corresponding to the casing to obtain a state score corresponding to the casing, etc., which is not specifically limited in the embodiment of the present invention.

[0102] The normalization formula is as follows:

[0103]

[0104] Among them, y n is the state score of the state parameter n (when y n >100, let y n =100; when y n <0, let y n =0); x0 is the initial value of the state parameter, i.e., the factory or acceptance test value; x n is the monitoring or experimental data of the state parameter; x N It is the warning value of the status parameter.

[0105] In the embodiment of the present invention, a 500kV, 250MV·A main transformer of a certain substation is taken as an example for calculation analysis. The monitoring or experimental data of the state parameters corresponding to each key component of the transformer and the corresponding state scores are shown in Tables 6 to 10 below.

[0106] Table 6 Monitoring or experimental data and status scores of state parameters corresponding to the main body

[0107]

[0108]

[0109] Table 7 Monitoring or experimental data and status scores of casing corresponding status parameters

[0110] Status parameters Monitoring or experimental data Initial Value Note Value Status score Methane content 43.2 0.46 100 (upper limit) 42.94 Bushing end screen insulation resistance 1326 1500 1000MΩ(lower limit) 34.8 Initial capacitance difference 2.73％ 0％ 5% (upper limit) 54.6 Hydrogen content 238 2.95 500 (upper limit) 47.29 Hot spot temperature of casing column 42 35 55℃(Upper limit) 35

[0111] Table 8 Status scores relative to cooling system

[0112] Status parameters Status score Oil pump temperature 25.3 Cooler power supply periodically switched 31.5 Fan operation status 27.4 Cooler Dirty 23.7

[0113] Table 9 Monitoring or experimental data and status scores of the state parameters corresponding to the tap changer

[0114] Status parameters Monitoring or experimental data Initial Value Note Value Status score DC resistance difference 0.84 0.14 2% (upper limit) 37.63 Oil breakdown voltage 58 65 55kV (lower limit) 70 Winding DC leakage current 26 5 60μA (upper limit) 38.18 Number of tap changer operations 1376 100 5000 (upper limit) 26.04

[0115] Table 10 Monitoring or experimental data and status scores of state parameters corresponding to non-electrical protection devices

[0116]

[0117] Among them, the corresponding status score of the cooling system can also be determined by professional staff based on experience.

[0118] Further, as a refinement and extension of the specific implementation of the above embodiment, in order to comprehensively consider the impact of key components of the transformer on the overall health status of the transformer, another method for formulating a transformer maintenance strategy is provided, such as Figure 3 As shown, the step of determining the overall health index of the transformer based on the parameter weights, the component weights and the status score includes:

[0119] 301. Obtain target parameter weights and target status scores corresponding to each of the key components;

[0120] In the embodiment of the present invention, when the current execution end analyzes the health status of each key component, the target parameter weight and target status score corresponding to each key component are first obtained. For example, when analyzing the health status of the casing, the target parameter weights such as the methane content, the insulation resistance of the casing end screen, the initial value difference of the capacitance, the hydrogen content, and the hot spot temperature of the casing column corresponding to the casing are obtained. According to Table 2 in step 102, 0.0909, 0.3028, 0.1516, 0.2425, and 0.2122 are obtained. And the corresponding target status scores such as the methane content, the insulation resistance of the casing end screen, the initial value difference of the capacitance, the hydrogen content, and the hot spot temperature of the casing column are obtained. According to Table 7 in step 202, 42.94, 34.8, 54.6, 47.29, and 35 are obtained. The embodiment of the present invention does not make specific limitations.

[0121] 302. Perform weighted summation processing based on the target parameter weight and the target state score to obtain a component health index corresponding to each of the key components;

[0122] In the embodiment of the present invention, the current execution end performs weighted summation based on the obtained target parameter weight and target status score to obtain the component health index corresponding to each key component. The formula for weighted summation in this step is as follows:

[0123]

[0124] Among them, TH i represents the component health index of each key component (i = 1, 2, 3, 4, 5), P represents the number of status parameters related to the health status of each key component, and Z ij represents the parameter weight of the jth state parameter of the i-th key component, y ij Represents the status score of the jth status parameter of the ith key component.

[0125] 303. Perform weighted summation processing based on the component health index and the component weight to obtain an overall health index of the transformer.

[0126] In the embodiment of the present invention, the current execution end performs weighted summation processing based on the component health index and the component weight to obtain the overall health index of the transformer. The formula for the weighted summation processing in this step is as follows:

[0127]

[0128] Among them, TH represents the overall health index of the transformer, Z i It represents the component weight of the i-th key component in the overall health assessment of the transformer.

[0129] In the embodiment of the present invention, a 500 kV, 250 MV·A main transformer of a certain substation is taken as an example for example analysis. Based on the data recorded in Tables 1 to 5 in the above step 102 and the data recorded in Tables 6 to 10 in step 202, the overall health index of the transformer is calculated as shown in Table 11 below.

[0130] Table 11 Component health index and overall health index of transformer

[0131]

[0132] Further, as a refinement and extension of the specific implementation of the above embodiment, in order to analyze the relationship between the overall health index of the transformer and the transformer failure rate, another method for formulating a transformer maintenance strategy is provided, wherein the steps of determining the transformer failure rate based on the overall health index include:

[0133] Using an exponential function to simulate the exponential distribution relationship between the overall health index and the transformer failure rate;

[0134] The proportionality coefficient and the curvature coefficient in the exponential function are solved to obtain the transformer failure rate.

[0135] In the embodiment of the present invention, the quantitative relationship between the overall health index of the transformer and the transformer failure rate is determined as an exponential distribution relationship, so the current execution end uses an exponential function to simulate the quantitative relationship between the overall health index of the transformer and the transformer failure rate, as shown in the following formula:

[0136] λ=Ke L·TH

[0137] Among them, λ represents the transformer failure rate, TH represents the overall health index of the transformer, and K and L are the proportional coefficient and curvature coefficient in the exponential function, respectively. The current execution end solves K and L in the above exponential function to obtain the exponential distribution relationship between the transformer failure rate and the overall health index of the transformer. When the overall health index of the transformer is known, the corresponding transformer failure rate can be calculated according to the exponential distribution relationship solved in the embodiment of the present invention. For example, Table 11 in step 303 shows that the overall health index of the transformer is 43.2424. According to the above exponential distribution relationship, the corresponding transformer failure rate of the transformer can be calculated to be 0.0787, which is not specifically limited in the embodiment of the present invention.

[0138] Further, as a refinement and extension of the specific implementation of the above embodiment, in order to comprehensively consider the health status of different components of the power transformer while also comprehensively considering the economy of maintenance and the risk of failure, another method for formulating a transformer maintenance strategy is provided, the steps of establishing an objective function of the transformer maintenance strategy based on the overall health index and the transformer failure rate, including:

[0139] Determining a transformer health index objective function based on the overall health index;

[0140] In the embodiment of the present invention, the current execution end determines the minimum value of the overall health index as the transformer health index objective function, as shown below:

[0141] min TH

[0142] Determine the transformer risk assessment objective function based on the power grid operation loss and fault recovery cost generated after the transformer fault occurs and the transformer failure rate;

[0143] In the embodiment of the present invention, the current execution end determines the transformer risk assessment objective function based on the power grid operation loss and fault recovery cost generated after the transformer fault occurs and the transformer failure rate. The specific formula is as follows:

[0144] Min R

[0145] R=λ·(C X +C O )

[0146]

[0147] Among them, R represents the risk value, λ represents the transformer failure rate, C X With C O They respectively represent the grid operation loss and fault recovery cost after a transformer failure occurs.

[0148] It should be noted that when a transformer fails, the load needs to be removed, which will cause losses in the operation of the power grid. This loss is mainly affected by factors such as the capacity, power factor, load rate and time required for fault repair of the transformer. N Indicates the capacity of the transformer; Indicates power factor; L indicates average load rate; R i Indicates the probability value of transformer failure of different levels; i represents the probability of load shedding after different levels of faults occur; v represents the unit power risk value, which is determined by the annual GDP value and the annual total power consumption; T c Indicates the time to remove the load; δ1 is the correction coefficient for the power grid operation loss, which depends on the substation and the importance of the load. When a transformer fails, it is necessary to carry out fault recovery work in a timely manner. During this process, costs such as materials, labor, equipment replacement, and transportation will be incurred. In the formula, C i It represents the fault recovery cost required after different levels of faults occur; δ2 is the correction coefficient of the fault recovery cost, which depends on the production place and maintenance environment of the transformer.

[0149] The transformer maintenance cost objective function is determined based on the linear relationship between the transformer failure rate and the transformer maintenance cost.

[0150] In the embodiment of the present invention, in order to improve the reliability of the equipment and extend the economic life of the equipment, it is necessary to perform maintenance to different degrees according to the equipment status during operation and maintenance (the maintenance guidelines are divided into four categories). The maintenance cost of the transformer varies due to the difference in materials, labor and required technical difficulty. Its maintenance cost and health index show a roughly linear relationship. The current execution end determines the transformer maintenance cost objective function based on the linear relationship between the transformer failure rate and the transformer maintenance cost. The specific formula is as follows:

[0151] min C M

[0152] C M =αTH+β

[0153] Among them, C M is the maintenance cost, α and β are the model coefficients.

[0154] In summary, the objective function of the transformer maintenance strategy in the embodiment of the present invention is summarized as follows:

[0155]

[0156] Further, as a refinement and extension of the specific implementation of the above embodiment, in order to dynamically evaluate the life of the transformer, another method for formulating a transformer maintenance strategy is provided. Before optimizing and solving the objective function of the transformer maintenance strategy using an intelligent optimization model, the method also includes:

[0157] Obtain the factory value of the health index of the transformer, the expected life, and the termination value of the health index when the expected life is reached, and calculate the equipment aging coefficient of the transformer;

[0158] As the transformer is put into operation for a longer time, its health status will change. Based on the aging mechanism, the relationship between the health status of the transformer and time is established. In the embodiment of the present invention, the current execution end obtains the factory value of the health index of the transformer, the expected life, and the end value of the health index when the expected life is reached, and calculates the equipment aging coefficient of the transformer. The specific formula is as follows:

[0159]

[0160] Among them, B is the equipment aging factor of the transformer, TH end With TH st are the factory value of the transformer's health index and the end value of the health index when the expected life is reached; T e is the expected life of the transformer. e The design life of the transformer is T d , Operation environment impact factor K T and load influence factor KL Jointly decided, the formula is as follows:

[0161]

[0162] The relationship between the health status of the transformer and time is simulated based on the equipment aging coefficient and the overall health index to obtain a time-varying function of the health index.

[0163] In the embodiment of the present invention, the current execution end simulates the relationship between the health status of the transformer and time based on the equipment aging coefficient and the overall health index to obtain a health index time-varying function. The specific formula is as follows:

[0164]

[0165] Among them, TH and TH0 are the health index values ​​of the device status at time T and time T0 respectively.

[0166] Furthermore, as a refinement and extension of the specific implementation of the above embodiment, in order to further consider the dynamics of transformer life, another method for formulating transformer maintenance strategy is provided, such as Figure 4 As shown, the step uses an intelligent optimization model to optimize and solve the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer, including:

[0167] 401. Initialize the maintenance strategy, and use the intelligent optimization model to adjust the initialized maintenance strategy to obtain an intermediate maintenance strategy;

[0168] 402. Determine an equivalent service age corresponding to the intermediate maintenance strategy based on the service age regression factor, and determine an intermediate health index corresponding to the intermediate maintenance strategy based on the equivalent service age and a health index time-varying function;

[0169] 403. Update the transformer failure rate based on the intermediate health index to obtain an intermediate failure rate corresponding to the intermediate maintenance strategy;

[0170] 404. Optimize and solve the objective function of the intermediate failure rate, the intermediate health index, and the transformer maintenance strategy to obtain a target maintenance strategy for the transformer.

[0171] In an embodiment of the present invention, the current execution end initializes the maintenance strategy, and uses the intelligent optimization model to adjust the initialized maintenance strategy to obtain an intermediate maintenance strategy; wherein, the intelligent optimization model includes models such as gradient descent method, genetic algorithm, simulated annealing algorithm, ant colony algorithm and particle swarm optimization algorithm, as well as improved models of the above models, etc., which are not specifically limited in the embodiment of the present invention.

[0172] When maintenance measures are taken on the transformer, the failure rate of the transformer will be positively affected, which is described by introducing the service age regression factor. In the embodiment of the present invention, the current execution end determines the equivalent service age corresponding to the intermediate maintenance strategy based on the service age regression factor, and the specific formula is as follows:

[0173] T el =T al (1-ρ)

[0174] Among them, T el With T al are the equivalent service age and actual service age of the transformer respectively, and ρ is the service age regression factor. In addition, transformer maintenance also indirectly affects the transformer failure rate through the overall health index. The specific formula is as follows:

[0175]

[0176] Among them, TH ao With λ ao Respectively represent the intermediate health index and intermediate failure rate after maintenance. The current execution end updates the transformer failure rate based on the intermediate health index to obtain the intermediate failure rate corresponding to the intermediate maintenance strategy. Afterwards, the current execution end optimizes and iterates based on the intermediate failure rate, the intermediate health index and the objective function of the transformer maintenance strategy to obtain the target maintenance strategy for the transformer.

[0177] In the embodiment of the present invention, a 500kV, 250MV·A main transformer in a substation is taken as an example for calculation analysis. The average load rate is 42%, the power factor is 0.9, the design life is 30 years, and it has been in service for 21 years. The grid operation loss and fault recovery cost are calculated to be 2.064 million yuan and 1.5289 million yuan respectively. In order to obtain the relationship between the health index of each component of the transformer and the time change, the health index of the transformer when it leaves the factory and reaches the expected life is set to 5 and 75. It is also necessary to determine the aging coefficient of each component of the transformer, and the aging coefficient is related to the operating environment and expected life of each component. The operating environment correction factor and aging coefficient of different components are shown in Table 12.

[0178] Table 12 Operating environment correction factors and aging coefficients of transformer components

[0179] Ontology casing Cooling system Tap Changer Non-electrical protection device Operating environment correction factor 1 1.5 1.3 1.6 1.2 Aging factor 0.0903 0.1354 0.1173 0.1444 0.1083

[0180] The reference transformer reaches the end of life with a health index of 75, and the maintenance threshold is set to 50. According to the health index values ​​of each component at the current moment, it is found that only the transformer body reaches the maintenance threshold, while the tap changer reaches the maintenance threshold in the 22.2994th year, the bushing in the 22.3561th year, the non-electrical protection device in the 23.6903th year, and the cooling system in the 26.2462th year. Referring to the setting of the maintenance cycle of "1 year to 3 years or when necessary" in the "Guidelines for the Maintenance of Power Transformers", taking the maintenance interval of 3 years as an example, the appropriate time is selected to perform maintenance on different components during the 21st to 24th year of service to form the optimal maintenance sequence, among which the components to be maintained are the transformer body, tap changer, bushing, and non-electrical protection device. In the next first maintenance interval, considering the restriction that the risk value after maintenance is less than 20, the maintenance time sequence of the transformer body, tap changer, bushing, and non-electrical protection device obtained by optimization is [21.52 years, 22.3 years, 23.3 years, 23.78 years]. This process continues in this way until the transformer reaches its expected lifespan, and an optimal maintenance decision sequence is formed at each stage, taking into account maintenance cost, reliability, and risk-benefit.

[0181] The embodiment of the present invention provides a method for formulating a transformer maintenance strategy. Compared with the prior art, the present invention obtains monitoring or experimental data based on the state parameters corresponding to each key component in the transformer, and determines the state score of each state parameter based on the monitoring or experimental data; obtains the parameter weight corresponding to the state parameter and the component weight corresponding to the key component, and determines the overall health index of the transformer based on the parameter weight, the component weight and the state score; determines the transformer failure rate based on the overall health index, and establishes the objective function of the transformer maintenance strategy based on the overall health index and the transformer failure rate; uses an intelligent optimization model to optimize and solve the objective function of the transformer maintenance strategy, obtains the target maintenance strategy of the transformer, and realizes the formulation of the transformer maintenance strategy. In the process of formulating the maintenance strategy, the present invention not only comprehensively considers the health status of different components of the power transformer, but also considers the impact of maintenance on the life of the transformer, so that the formulated transformer maintenance strategy can effectively realize the full utilization of the transformer equipment while ensuring economy.

[0182] As the above Figure 1 The embodiment of the present invention provides a device for formulating a transformer maintenance strategy, such as Figure 5 As shown, the device comprises:

[0183] A state scoring module 51, for acquiring monitoring or experimental data based on state parameters corresponding to each key component in the transformer, and determining a state score of each state parameter based on the monitoring or experimental data;

[0184] A health index evaluation module 52, for obtaining parameter weights corresponding to the state parameters and component weights corresponding to the key components, and determining an overall health index of the transformer based on the parameter weights, the component weights and the state score;

[0185] A target determination module 53, used to determine the transformer failure rate based on the overall health index, and to establish an objective function of the transformer maintenance strategy based on the overall health index and the transformer failure rate;

[0186] The optimization solution module 54 is used to optimize and solve the objective function of the transformer maintenance strategy using an intelligent optimization model to obtain a target maintenance strategy for the transformer.

[0187] Furthermore, the key components include a body, a bushing, a cooling system, a tap changer and a non-electrical protection device; the state scoring module 51 is also used for:

[0188] Respectively acquiring the monitoring or experimental data corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device;

[0189] The monitoring or experimental data are normalized to obtain status scores corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device.

[0190] Furthermore, the health index assessment module 52 is also used for:

[0191] Obtaining target parameter weights and target status scores corresponding to each of the key components;

[0192] Performing weighted summation processing based on the target parameter weight and the target state score to obtain a component health index corresponding to each of the key components;

[0193] A weighted summation process is performed based on the component health index and the component weight to obtain an overall health index of the transformer.

[0194] Further, the target determination module 53 includes a failure rate determination unit and a target function determination unit;

[0195] The failure rate determination unit is used to:

[0196] Using an exponential function to simulate the exponential distribution relationship between the overall health index and the transformer failure rate;

[0197] The proportionality coefficient and the curvature coefficient in the exponential function are solved to obtain the transformer failure rate.

[0198] The objective function determination unit is used to:

[0199] Determining a transformer health index objective function based on the overall health index;

[0200] Determine the transformer risk assessment objective function based on the power grid operation loss and fault recovery cost generated after the transformer fault occurs and the transformer failure rate;

[0201] The transformer maintenance cost objective function is determined based on the linear relationship between the transformer failure rate and the transformer maintenance cost.

[0202] Furthermore, the device also includes a time-varying module, which is used to:

[0203] Obtain the factory value of the health index of the transformer, the expected life, and the termination value of the health index when the expected life is reached, and calculate the equipment aging coefficient of the transformer;

[0204] The relationship between the health status of the transformer and time is simulated based on the equipment aging coefficient and the overall health index to obtain a time-varying function of the health index.

[0205] Furthermore, the optimization solution module 54 is also used for:

[0206] Initializing the maintenance strategy, and using the intelligent optimization model to adjust the initialized maintenance strategy to obtain an intermediate maintenance strategy;

[0207] Determine an equivalent service age corresponding to the intermediate maintenance strategy based on the service age regression factor, and determine an intermediate health index corresponding to the intermediate maintenance strategy based on the equivalent service age and a health index time-varying function;

[0208] Based on the intermediate health index, the transformer failure rate is updated to obtain an intermediate failure rate corresponding to the intermediate maintenance strategy;

[0209] An optimization solution is performed based on the intermediate failure rate, the intermediate health index and the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer.

[0210] The embodiment of the present invention provides a device for formulating a transformer maintenance strategy. Compared with the prior art, the present invention obtains monitoring or experimental data based on the state parameters corresponding to each key component in the transformer, and determines the state score of each state parameter based on the monitoring or experimental data; obtains the parameter weight corresponding to the state parameter and the component weight corresponding to the key component, and determines the overall health index of the transformer based on the parameter weight, the component weight and the state score; determines the transformer failure rate based on the overall health index, and establishes the objective function of the transformer maintenance strategy based on the overall health index and the transformer failure rate; uses an intelligent optimization model to optimize and solve the objective function of the transformer maintenance strategy, obtains the target maintenance strategy of the transformer, and realizes the formulation of the transformer maintenance strategy. In the process of formulating the maintenance strategy, the present invention not only comprehensively considers the health status of different components of the power transformer, but also considers the impact of maintenance on the life of the transformer, so that the formulated transformer maintenance strategy can effectively realize the full utilization of the transformer equipment while ensuring economy.

[0211] According to one embodiment of the present invention, a storage medium is provided, wherein the storage medium stores at least one executable instruction, and the computer executable instruction can execute the method for formulating a transformer maintenance strategy in any of the above method embodiments.

[0212] Figure 6 A schematic diagram of the structure of a device provided according to an embodiment of the present invention is shown, and the specific embodiment of the present invention does not limit the specific implementation of the device.

[0213] like Figure 6 As shown, the device may include: a processor (processor) 602 , a communication interface (Communications Interface) 604 , a memory (memory) 606 , and a communication bus 608 .

[0214] The processor 602 , the communication interface 604 , and the memory 606 communicate with each other via a communication bus 608 .

[0215] The communication interface 604 is used to communicate with other devices such as clients or other servers.

[0216] The processor 602 is used to execute the program 610, and specifically can execute the relevant steps of the method for formulating the above-mentioned transformer maintenance strategy.

[0217] Specifically, the program 610 may include program codes, which include computer operation instructions.

[0218] The processor 602 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0219] The memory 606 is used to store the program 610. The memory 606 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0220] The program 610 may be specifically configured to enable the processor 602 to perform the following operations:

[0221] Acquire monitoring or experimental data based on the state parameters corresponding to each key component in the transformer, and determine the state score of each state parameter based on the monitoring or experimental data;

[0222] Obtaining parameter weights corresponding to the state parameters and component weights corresponding to the key components, and determining an overall health index of the transformer based on the parameter weights, the component weights and the state score;

[0223] Determining a transformer failure rate based on the overall health index, and establishing an objective function of a transformer maintenance strategy based on the overall health index and the transformer failure rate;

[0224] An intelligent optimization model is used to optimize and solve the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer.

[0225] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0226] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for formulating a transformer maintenance strategy, characterized in that: include: Acquiring monitoring or test data based on the state parameters corresponding to each key component in the transformer, and determining the state score of each state parameter based on the monitoring or test data; Obtaining parameter weights corresponding to the state parameters and component weights corresponding to the key components, and determining an overall health index of the transformer based on the parameter weights, the component weights and the state score; Determining a transformer failure rate based on the overall health index, and establishing an objective function of a transformer maintenance strategy based on the overall health index and the transformer failure rate; An intelligent optimization model is used to optimize and solve the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer.

2. The method according to claim 1, characterized in that The key components include the body, bushing, cooling system, tap changer and non-electrical protection device; The determining of the state score of each state parameter based on the monitoring or experimental data comprises: Respectively acquiring the monitoring or experimental data corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device; The monitoring or experimental data are normalized to obtain status scores corresponding to the body, the bushing, the cooling system, the tap changer and the non-electrical protection device.

3. The method according to claim 1, characterized in that The determining the overall health index of the transformer based on the parameter weights, the component weights and the status score comprises: Obtaining target parameter weights and target status scores corresponding to each of the key components; Performing weighted summation processing based on the target parameter weight and the target state score to obtain a component health index corresponding to each of the key components; A weighted summation process is performed based on the component health index and the component weight to obtain an overall health index of the transformer.

4. The method according to claim 1, characterized in that Determining the transformer failure rate based on the overall health index includes: Using an exponential function to simulate the exponential distribution relationship between the overall health index and the transformer failure rate; The proportionality coefficient and the curvature coefficient in the exponential function are solved to obtain the transformer failure rate.

5. The method according to claim 1, characterized in that The objective function of establishing a transformer maintenance strategy based on the overall health index and the transformer failure rate includes: Determining a transformer health index objective function based on the overall health index; Determine the transformer risk assessment objective function based on the power grid operation loss and fault recovery cost generated after the transformer fault occurs and the transformer failure rate; The transformer maintenance cost objective function is determined based on the linear relationship between the transformer failure rate and the transformer maintenance cost.

6. The method according to claim 1, characterized in that Before optimizing and solving the objective function of the transformer maintenance strategy by using the intelligent optimization model, the method further includes: Obtain the factory value of the health index of the transformer, the expected life, and the termination value of the health index when the expected life is reached, and calculate the equipment aging coefficient of the transformer; The relationship between the health status of the transformer and time is simulated based on the equipment aging coefficient and the overall health index to obtain a time-varying function of the health index.

7. The method according to any one of claims 1 to 6, characterized in that: The intelligent optimization model is used to optimize and solve the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer, including: Initializing the maintenance strategy, and using the intelligent optimization model to adjust the initialized maintenance strategy to obtain an intermediate maintenance strategy; Determine an equivalent service age corresponding to the intermediate maintenance strategy based on the service age regression factor, and determine an intermediate health index corresponding to the intermediate maintenance strategy based on the equivalent service age and a health index time-varying function; Based on the intermediate health index, the transformer failure rate is updated to obtain an intermediate failure rate corresponding to the intermediate maintenance strategy; An optimization solution is performed based on the intermediate failure rate, the intermediate health index and the objective function of the transformer maintenance strategy to obtain the target maintenance strategy of the transformer.

8. A transformer maintenance strategy formulation device, characterized in that: include: A state scoring module, used to obtain monitoring or experimental data based on the state parameters corresponding to each key component in the transformer, and determine the state score of each state parameter based on the monitoring or experimental data; A health index evaluation module, used to obtain parameter weights corresponding to the state parameters and component weights corresponding to the key components, and determine the overall health index of the transformer based on the parameter weights, the component weights and the state score; A target determination module, used to determine the transformer failure rate based on the overall health index, and establish an objective function of the transformer maintenance strategy based on the overall health index and the transformer failure rate; The optimization solution module is used to optimize and solve the objective function of the transformer maintenance strategy using an intelligent optimization model to obtain a target maintenance strategy for the transformer.

9. A storage medium, wherein at least one executable instruction is stored in the storage medium, and the executable instruction executes an operation corresponding to the method for formulating a transformer maintenance strategy according to any one of claims 1 to 7.

10. A device comprising a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute an operation corresponding to the method for formulating a transformer maintenance strategy as described in any one of claims 1-7.

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