Method and system for evaluating and deciding full-life periodic performance of transformer in coastal region

Abstract

The invention relates to a coastal region transformer full-life periodic performance evaluation and decision-making method and system, and belongs to the technical field of power system asset management and reliability evaluation. The method comprises the steps of collecting multi-source data of a transformer and performing standardization processing; constructing an environment equivalent strength index according to the environment data, fusing the operation load and the state monitoring data, and constructing a comprehensive degradation index reflecting thermal aging and corrosion damage; determining a reference failure rate based on the service life, and correcting the reference failure rate by using the comprehensive degradation index to obtain a time-varying failure rate; calculating the whole life cycle cost and carbon emission based on the time-varying failure rate and the economic data; and solving an optimal replacement strategy by taking the lowest cost and carbon emission as targets. According to the method, the problems that the traditional method is difficult to quantify the coastal environment influence, and cannot dynamically evaluate the equipment health state and perform multi-objective optimization decision making are solved, and lean and green low-carbon management of the whole life cycle of the transformer is realized.

Description

Technical Field

[0001] This application relates to the field of power system asset management and reliability assessment technology, and more specifically, to a method and system for performance assessment and decision-making of transformers throughout their entire life cycle in coastal areas. Background Technology

[0002] In coastal power grids, large-capacity oil-immersed transformers operate under complex environments characterized by high humidity, high salt spray, strong winds, and pollutant deposits. The aging and corrosion processes of their insulation systems, metal components, and sealing structures are significantly faster than in inland areas, increasing the risk of leaks, discharges, and short circuits. With the continuous construction of new energy bases, power grid interconnection projects, and important load centers in coastal areas, the combined effects of high-load operation, frequent power flow fluctuations, and extreme weather on transformers exacerbate the discrepancy between their actual and designed lifespans. Traditional lifespan assumptions and static maintenance strategies based on experience curves or periodic test results are insufficient to reflect the true health status and failure trends of equipment in coastal environments. This introduces significant uncertainty and risk to power grid safety and asset planning. Current transformer condition assessments primarily rely on single-point testing results such as oil chromatography, electrical testing, and partial discharge detection, supplemented by expert scoring, fuzzy evaluation, or simple lifespan reduction coefficients for comprehensive judgment. These methods often lack systematic utilization of multi-source data on coastal environmental intensity, operating load, thermal aging, and corrosion degradation, and rarely quantify the coupling relationship between failure rate evolution, outage risk, maintenance costs, and losses from a full life-cycle perspective. Meanwhile, existing operation and maintenance and replacement decision-making methods mostly adopt rough rules based on the expiration of service life or the number of failures exceeding the limit. They fail to make a unified balance between equipment degradation status, reliability level and economic efficiency and carbon emission constraints throughout the entire life cycle, which restricts the realization of lean management of transformer assets and green and low-carbon goals in coastal areas.

[0003] Therefore, it is necessary to propose a transformer life-cycle performance assessment and decision-making method that simultaneously considers coastal environmental intensity, operating conditions, maintenance behavior, and economic constraints, linking degradation mechanisms, reliability indicators, and life-cycle costs to provide quantifiable, optimizable, and traceable decision-making basis for the reinforcement, maintenance, and replacement of transformers in coastal areas. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a method and system for evaluating and making decisions on the full life-cycle performance of transformers in coastal areas.

[0005] The technical solution of this invention is as follows: This invention proposes a method for evaluating and making decisions on the full life-cycle performance of transformers in coastal areas, comprising the following steps: Multi-source data of transformers in coastal areas are collected and standardized; the multi-source data includes environmental data, operating load data, condition monitoring data, and economic data. An environmental equivalent intensity index is constructed based on environmental data. Based on the environmental equivalent intensity index, operating load data, and condition monitoring data, a comprehensive degradation index reflecting thermal aging damage and corrosion damage is constructed. The baseline failure rate is determined based on the service life of the transformer, and then corrected using comprehensive degradation index and operating load data to obtain the time-varying failure rate. Based on time-varying failure rates and economic data, calculate the total life cycle cost and carbon emissions of transformers. With the goal of minimizing life-cycle costs and carbon emissions, we seek the optimal transformer replacement strategy for coastal areas.

[0006] Preferably, the formula for calculating the environmental equivalent intensity index is: ; In the formula: For transformer i at time point Environmental equivalent intensity index; , , , , These are the normalized ambient temperature, relative humidity, salt spray concentration, wind speed, and pollution level, respectively. , , , , These are the weighting coefficients fitted using logistic regression of historical fault data.

[0007] Preferably, the comprehensive degradation index is calculated by weighting the thermal aging damage index and the corrosion damage index, wherein: The thermal aging damage index is based on hot spot temperature data and transformer design life curve, and is obtained by accumulating the life damage increment at each time step. The corrosion damage index is obtained by estimating the corrosion depth through a corrosion model, based on the environmental equivalent intensity index and the service life of the transformer.

[0008] Preferably, the time-varying failure rate is calculated using a proportional hazards model, specifically: ; In the formula: For transformer i at time point Time-varying failure rate; , , , , These are the average values ​​of the comprehensive degradation index, environmental equivalent intensity index, load rate, preventive maintenance indicator, and overhaul indicator within the sliding time window, respectively. , , , , The coefficients for the comprehensive degradation index, environmental equivalent intensity index, load rate, preventive maintenance indicator, and overhaul indicator fitted through survival analysis.

[0009] Preferably, the survival analysis fitting step includes: Construct a historical sample set, which records the first failure time or censoring time for each transformer, as well as the feature vector at the corresponding time point. The feature vector includes the sliding window average of the comprehensive degradation index, environmental equivalent intensity index, load rate, preventive maintenance indicator, and overhaul indicator. An objective function is constructed using a partial likelihood function, and by maximizing this objective function, coefficient estimates reflecting the degree of influence of each feature on the failure risk are obtained.

[0010] Preferably, the formula for calculating the total life cycle cost is: ; In the formula: The total life-cycle cost of transformer i; The initial purchase and installation cost of transformer i; These are annual operation and maintenance costs, fault-related costs, and energy loss costs; y represents the discount factor; y represents the assessment year, which belongs to the assessment period set. .

[0011] Preferably, the standardization process includes: establishing a unified timeline, aligning multi-source data at time points, and performing missing value processing, outlier marking, and standardization transformation on numerical features.

[0012] On the other hand, the present invention also provides a transformer life-cycle performance evaluation and decision-making system for coastal areas, including: The data acquisition module collects multi-source data from transformers in coastal areas and performs standardized processing; the multi-source data includes environmental data, operating load data, condition monitoring data, and economic data. The comprehensive degradation index calculation module constructs an environmental equivalent intensity index based on environmental data. Based on the environmental equivalent intensity index, operating load data, and condition monitoring data, it constructs a comprehensive degradation index that reflects thermal aging damage and corrosion damage. The time-varying failure rate determination module determines the baseline failure rate based on the transformer's service life, and then corrects the baseline failure rate using comprehensive degradation indicators and operating load data to obtain the time-varying failure rate. The cost calculation module calculates the total life cycle cost and carbon emissions of the transformer based on time-varying failure rates and economic data. The replacement strategy optimization decision module aims to minimize the total life cycle cost and carbon emissions, and solves for the optimal transformer replacement strategy in coastal areas.

[0013] In another aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the coastal area transformer full life cycle performance evaluation and decision-making method as described in any embodiment of the present invention.

[0014] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for evaluating and making decisions on the full life-cycle performance of transformers in coastal areas as described in any embodiment of the present invention.

[0015] The present invention has the following beneficial effects: 1. By introducing the environmental equivalent intensity index and comprehensive degradation index, the multi-factor coastal environment and equipment operation status are quantified into calculable damage, which significantly improves the accuracy and pertinence of health status assessment.

[0016] 2. A proportional risk model is used to construct a time-varying failure rate, which enables failure prediction to not only reflect the bathtub curve pattern of the equipment, but also dynamically respond to actual degradation, load and maintenance behavior, which is superior to the static threshold model.

[0017] 3. Within the framework of the entire life cycle, economic costs, downtime risks, and carbon emissions are quantified simultaneously, and these are treated as multiple objectives and constraints in the optimization model, realizing the transformation from purely technical judgment to multi-dimensional scientific decision-making based on economic, risk, and environmental protection dimensions. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0021] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0022] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0023] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0024] Example 1: To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present application and with reference to the accompanying drawings.

[0025] To address the problems of existing technologies, this invention provides a method for performance evaluation and decision-making throughout the entire life cycle of transformers in coastal areas, comprising the following steps: Step S1: Collect multi-source data of transformers in coastal areas and perform standardization processing; the multi-source data includes static attribute data, environmental data, operating load data, condition monitoring data, maintenance behavior data, and economic data; In this embodiment, Static attribute data includes: rated capacity, rated voltage, equipment type, cooling method, insulation class or insulation system, year of manufacture, year of installation and commissioning, installation location identifier (geographic coordinates, Loc), and coastal region zone. Environmental data include: ambient temperature, relative humidity, salt spray deposition rate or concentration, wind speed, number of extreme wind events, and pollution level; Operating load data includes: active load, reactive load, load factor, hot spot temperature or oil temperature; Condition monitoring data includes: partial discharge characteristic quantities, oil chromatography key gas concentrations, trace water content in the oil, and condition alarm signs or frequency. Inspection behavior data includes: preventive maintenance signs, signs for overhaul or replacement of main components, and signs or number of times defects were found and eliminated; Economic data include: initial purchase and installation costs, operation and maintenance costs, average cost of a single emergency repair, unit price of power outage loss per unit of unsupplied electricity, electricity price converted from power loss, and carbon emission factor per unit of electricity in the regional power grid.

[0026] The standardization process includes the following steps: Determine the set of transformers Ω within the evaluation scope, define the time axis T for the evaluation period, and discretize time into a series of time points. And calculate the time step Δ .

[0027] Align the multi-source data on the time axis to construct a comprehensive feature vector and mark data missing or imputed cases.

[0028] Numerical features are cleaned and standardized, the mean and standard deviation are calculated, and outlier labels are defined to improve model stability.

[0029] Step S2: Construct an environmental equivalent intensity index based on environmental data. Based on the environmental equivalent intensity index, operating load data, and condition monitoring data, construct a comprehensive degradation index that reflects thermal aging damage and corrosion damage. In this embodiment, the formula for calculating the environmental equivalent intensity index is: ; In the formula: For transformer i at time point Environmental equivalent intensity index; The normalized ambient temperature represents the temperature at time point i. The normalized value of ambient temperature relative to the extreme values ​​of the entire network; Normalized relative humidity; This refers to the normalized salt spray settling rate or salt spray concentration index. Normalized average wind speed or representative wind speed; To normalize the pollution levels, they are mapped to dimensionless values ​​according to industry standard codes; , , , , To reflect the relative contribution of each environmental factor to failure risk by using weight coefficients fitted through logistic regression of historical failure data, the logistic regression fits the environmental impact weights with environmental indicators as independent variables and whether a failure occurs as the dependent variable. The specific function is as follows: ; in: ; In the formula: These are logical functions, commonly used standard functions in statistics. These are the regression coefficients obtained by fitting historical sample data using maximum likelihood estimation. Let be the estimated failure probability of transformer i in year y.

[0030] The formula for calculating the comprehensive degradation index is: ; In the formula: For transformer i at time point Comprehensive degradation index; For transformer i at time point Thermal aging damage indicators; For transformer i at time point Corrosion damage indicators; and To normalize the weights, , The coefficients are obtained by logistic regression fitting of historical failure data, reflecting the relative impact of thermal aging damage and corrosion damage on failure probability. The thermal aging damage index is calculated based on hot spot temperature data and the manufacturer's lifespan curve. The specific calculation formula is as follows: ; ; ; In the formula: For time step Increase in internal thermal aging damage; The relative lifespan consumption rate is the hotspot temperature. The function is calculated based on the life curve provided by the manufacturer or IEC / IEEE standards; The design life of transformer i at the reference hot spot temperature; For all points earlier than or equal to the current target time point during the transformer's service life... The historical time points are denoted by m, where m is the index of these historical time points.

[0031] The corrosion damage index is calculated using corrosion test data and environmental intensity. The specific calculation formula is as follows: ; ; In the formula: To estimate the corrosion depth, regression fitting was performed using historical test specimen data and inspection data. For transformer i at time point Service life; Permissible corrosion limits are derived from the manufacturer's or structural design documents; , , , is the regression coefficient.

[0032] Step S3: Determine the baseline failure rate based on the service life of the transformer, and correct the baseline failure rate using comprehensive degradation index and operating load data to obtain the time-varying failure rate. In this embodiment, the process for calculating the time-varying failure rate includes: Based on transformer type and service life range, historical fault data is collected to define a baseline failure rate: ; In the formula: For transformer i at time point The baseline failure rate; This represents the baseline failure rate of the C-type transformer within the service life range j. This refers to the number of years that a Class C transformer has been under in-service monitoring within the service life interval j. This refers to the number of transformers of type c that experience their first failure within the service life interval j.

[0033] The time-varying failure rate is calculated using a proportional risk model, incorporating correction factors such as degradation, environment, load, and maintenance. ; In the formula: , , , , These are the average values ​​of the comprehensive degradation index, environmental equivalent intensity index, load rate, preventive maintenance indicator, and overhaul indicator within the sliding time window, respectively. , , , , The coefficients obtained through survival analysis reflect the corrective effect of each factor on the failure rate. The steps of survival analysis fitting include: If the first fault occurs in each transformer i during the observation period, the fault time shall be recorded. And the corresponding feature trajectory; if no fault occurred, record the deletion time. Construct the objective using the standard partial likelihood function: ; in: ; Let i be the eigenvector of transformer i at time t; This refers to the set of transformers that experienced their first fault during the observation period. In order to be at the moment of failure The collection of risk-bearing transformers is still in operation; To calculate the risk set Transformer J at the time of fault The relative risk; by maximizing partial likelihood Obtain coefficient estimates .

[0034] Calculate the expected number of failures per year based on time-varying failure rate: ; Calculate the expected annual downtime based on the expected number of annual failures: ; In the formula: The expected number of failures per year; The expected downtime for the year; Mean time to repair (MTBT); Let be the set of indices of all discrete time points corresponding to the year y of the evaluation of transformer i.

[0035] Step S4: Calculate the transformer's total life cycle cost and carbon emissions based on time-varying failure rate and economic data; The formula for calculating total life cycle cost is: ; in: ; ; ; In the formula: The total life-cycle cost of transformer i; The initial purchase and installation cost of transformer i; The total annual cost includes operating and maintenance costs. Fault-related costs and wear and tear costs ; is the discount factor; r is the discount rate; The base year for evaluation; The average cost of emergency repair for a single fault of transformer i is obtained from historical emergency repair cost statistics. The unit price for power loss due to lack of power supply in the area supplied by transformer i is given by the company's power outage loss assessment standard. The expected annual power outage, based on And annual average active load calculation.

[0036] The formula for calculating carbon emissions over the entire life cycle is: ; in: ; In the formula: Carbon emissions throughout the entire life cycle of transformer i; Annual carbon emissions; The annual power loss is calculated based on transformer loss parameters and load factor. It is the annual average carbon emission factor per unit of electricity.

[0037] Step S5: With the goal of minimizing both total life-cycle cost and carbon emissions, solve for the optimal transformer replacement strategy for coastal areas. The specific solution steps include: Let the evaluation period be the annual set. Consider a set of candidate replacement years as follows: ; This indicates that no replacement will be made during the evaluation period, and the equipment will continue to operate as it is currently in use.

[0038] Define the decision variables as follows: ; For the planned replacement year of transformer i; if , indicates no replacement.

[0039] For each candidate replacement year This creates a scenario as follows: when To use the original equipment , , Equal amounts, from steps S3 and S4; when To recalculate S1 to S4 according to the parameters of the new equipment, and obtain new... , , And in the replacement year, Increase one-time investment .

[0040] S5.2 Costs and Risks, Carbon Emission Objective Function For a given candidate replacement year The following three performance metrics are defined as follows: Present value of total life cycle cost: ; In the formula: For the historical investment of the original transformer, The cost of purchasing and installing a new transformer for replacement is provided in the procurement / estimated cost data. For a given replacement year The total annual cost is obtained by combining the calculations for the old equipment phase and the new equipment phase using the formula in step S4.

[0041] The value is 1 if the condition is true, and 0 otherwise.

[0042] Lifecycle downtime risks: ; In the formula, The expected annual downtime for the original and new equipment in a given replacement year is obtained by combining the calculations performed in step S3 for the old equipment phase and the new equipment phase.

[0043] Present value of carbon emissions over the entire life cycle: ; The annual carbon emissions from the loss in a given replacement year are calculated separately for the old equipment and the new equipment in step S4 and then combined.

[0044] S5.3 Constraints Based on the company's current reliability and carbon emission constraints, the following limits are given: Annual maximum unavailability limit This stems from power supply reliability requirements; Life-cycle carbon emission discount cap These come from emission reduction targets or quotas; The corresponding constraints are: ; in: In the plan Unavailable for the next year.

[0045] S5.4 Solution Method and Selection of Optimal Replacement Year This step uses a finite number of candidate years enumeration and filtering method to solve the problem. The process is clear and reproducible. The specific steps are as follows: Enumerate all candidate replacement years: For each Using the formulas in steps S3 and S4, calculate the costs for the old equipment stage and the new equipment stage, respectively. , , , Equal amounts were combined and concatenated to obtain the complete evaluation period sequence; the corresponding... , , ; Eliminate solutions that do not meet the constraints: For each If there is a certain year ,or If the above conditions are not met, the proposed solution will be considered infeasible and eliminated.

[0046] Select the optimal solution from the feasible options: For the set of remaining feasible solutions A simple rule of minimum cost plus suboptimal risk can be adopted for selection; The solution with the lowest cost is: ; If multiple solutions with similar costs exist, then select from these solutions. The smallest option will be used as the final recommended replacement year.

[0047] The final output is: Optimal replacement year for each transformer i ; The corresponding present value of the whole life cycle cost ; The corresponding total discounted amount of downtime over the entire life cycle and total discounted carbon emissions .

[0048] Example 2: This embodiment provides a transformer lifecycle performance evaluation and decision-making system for coastal areas, including: The data acquisition module collects multi-source data from transformers in coastal areas and performs standardized processing; the multi-source data includes environmental data, operating load data, condition monitoring data, and economic data. The comprehensive degradation index calculation module constructs an environmental equivalent intensity index based on environmental data. Based on the environmental equivalent intensity index, operating load data, and condition monitoring data, it constructs a comprehensive degradation index that reflects thermal aging damage and corrosion damage. The time-varying failure rate determination module determines the baseline failure rate based on the transformer's service life, and then corrects the baseline failure rate using comprehensive degradation indicators and operating load data to obtain the time-varying failure rate. The cost calculation module calculates the total life cycle cost and carbon emissions of the transformer based on time-varying failure rates and economic data. The replacement strategy optimization decision module aims to minimize the total life cycle cost and carbon emissions, and solves for the optimal transformer replacement strategy in coastal areas.

[0049] Example 3: This embodiment proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the coastal area transformer full life cycle performance evaluation and decision-making method as described in any embodiment of the present invention.

[0050] Example 4: This embodiment proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the coastal area transformer full life cycle performance evaluation and decision-making method as described in any embodiment of the present invention.

[0051] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0052] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0053] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0054] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0055] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for evaluating and making decisions on the full life-cycle performance of transformers in coastal areas, characterized in that, Including the following: Multi-source data of transformers in coastal areas are collected and standardized; the multi-source data includes environmental data, operating load data, condition monitoring data, and economic data. An environmental equivalent intensity index is constructed based on environmental data. Based on the environmental equivalent intensity index, operating load data, and condition monitoring data, a comprehensive degradation index reflecting thermal aging damage and corrosion damage is constructed. The baseline failure rate is determined based on the service life of the transformer, and then corrected using comprehensive degradation index and operating load data to obtain the time-varying failure rate. Based on time-varying failure rates and economic data, calculate the total life cycle cost and carbon emissions of transformers. With the goal of minimizing life-cycle costs and carbon emissions, we seek the optimal transformer replacement strategy for coastal areas.

2. The method for evaluating and deciding on the full life-cycle performance of transformers in coastal areas according to claim 1, characterized in that: The formula for calculating the environmental equivalent intensity index is as follows: ； In the formula: For transformer i at time point Environmental equivalent intensity index; , , , , These are the normalized ambient temperature, relative humidity, salt spray concentration, wind speed, and pollution level, respectively. , , , , These are the weighting coefficients fitted using logistic regression of historical fault data.

3. The method for evaluating and deciding on the full life-cycle performance of transformers in coastal areas according to claim 2, characterized in that: The comprehensive degradation index is calculated by weighting the thermal aging damage index and the corrosion damage index, wherein: The thermal aging damage index is based on hot spot temperature data and transformer design life curve, and is obtained by accumulating the life damage increment at each time step. The corrosion damage index is obtained by estimating the corrosion depth through a corrosion model, based on the environmental equivalent intensity index and the service life of the transformer.

4. The method for evaluating and deciding on the full life-cycle performance of transformers in coastal areas according to claim 3, characterized in that: The time-varying failure rate is calculated using a proportional hazards model, specifically: ； In the formula: For transformer i at time point Time-varying failure rate; , , , , These are the average values ​​of the comprehensive degradation index, environmental equivalent intensity index, load rate, preventive maintenance indicator, and overhaul indicator within the sliding time window, respectively. , , , , The coefficients for the comprehensive degradation index, environmental equivalent intensity index, load rate, preventive maintenance indicator, and overhaul indicator fitted through survival analysis.

5. The method for evaluating and deciding on the full life-cycle performance of transformers in coastal areas according to claim 4, characterized in that: The steps of the survival analysis fitting include: Construct a historical sample set, which records the first failure time or censoring time for each transformer, as well as the feature vector at the corresponding time point. The feature vector includes the sliding window average of the comprehensive degradation index, environmental equivalent intensity index, load rate, preventive maintenance indicator, and overhaul indicator. An objective function is constructed using a partial likelihood function, and by maximizing this objective function, coefficient estimates reflecting the degree of influence of each feature on the failure risk are obtained.

6. The method for evaluating and deciding on the full life-cycle performance of transformers in coastal areas according to claim 1, characterized in that: The formula for calculating the total life cycle cost is as follows: ； In the formula: The total life-cycle cost of transformer i; The initial purchase and installation cost of transformer i; These are annual operation and maintenance costs, fault-related costs, and energy loss costs; y represents the discount factor; y represents the assessment year, which belongs to the assessment period set. .

7. The method for evaluating and deciding on the full life-cycle performance of transformers in coastal areas according to claim 1, characterized in that: The standardization process includes: establishing a unified timeline, aligning multi-source data at time points, and performing missing value processing, outlier marking, and standardization transformation on numerical features.

8. A transformer life-cycle performance evaluation and decision-making system for coastal areas, characterized in that, include: The data acquisition module collects multi-source data from transformers in coastal areas and performs standardized processing; the multi-source data includes environmental data, operating load data, condition monitoring data, and economic data. The comprehensive degradation index calculation module constructs an environmental equivalent intensity index based on environmental data. Based on the environmental equivalent intensity index, operating load data, and condition monitoring data, it constructs a comprehensive degradation index that reflects thermal aging damage and corrosion damage. The time-varying failure rate determination module determines the baseline failure rate based on the transformer's service life, and then corrects the baseline failure rate using comprehensive degradation indicators and operating load data to obtain the time-varying failure rate. The cost calculation module calculates the total life cycle cost and carbon emissions of the transformer based on time-varying failure rates and economic data. The replacement strategy optimization decision module aims to minimize the total life cycle cost and carbon emissions, and solves for the optimal transformer replacement strategy in coastal areas.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for evaluating and making decisions on the full life cycle performance of transformers in coastal areas as described in claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for evaluating and making decisions on the full life cycle performance of transformers in coastal areas as described in claims 1-7.

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