Power equipment optimal operation life decision-making method based on technical economy

Abstract

The invention relates to the technical field of power equipment operation management, and particularly discloses a power equipment optimal operation life decision-making method based on technical economy, which can greatly reduce the cost income accounting deviation through dynamic fusion, improve the accuracy of economy evaluation in life decision-making, and improve the power equipment optimal operation life decision-making efficiency. A real-time linkage mechanism solves the problem of insufficient dynamic matching of the whole-cycle cost income, adapts to the change rule of the safety state and the economic performance of the power equipment in the whole life cycle through two-dimensional linkage of the health value and the cost income, dynamic weight calibration and a decision-making mechanism, avoids insufficient safety or economic waste caused by single-dimensional decision-making, and improves the safety of the power equipment. And meanwhile, safety and economic balance of the equipment in different operation stages is ensured, and stable and accurate optimal operation life decision is kept in the whole life cycle of the equipment.

Description

Technical Field

[0001] This invention relates to the field of power equipment operation and management technology, and in particular to a method for determining the optimal service life of power equipment based on techno-economic factors. Background Technology

[0002] The economic life of equipment is related to the economic benefits and operational efficiency of the power grid. Economic life is the period when the average annual cost of equipment is the lowest. When calculating the economic life of equipment, it is necessary to apply the whole life cycle theory. By calculating the total life cycle cost and total cost of ownership of the equipment, the economic efficiency of the equipment is improved. In addition, by combining the technical performance degradation law of the equipment and operation and maintenance data, a comprehensive technical and economic evaluation model is established. By analyzing the failure rate, maintenance cost and efficiency changes of the equipment in different operating stages, its economic indicators are quantified, the optimal replacement or decommissioning time is determined, thereby maximizing the comprehensive benefits of the equipment throughout its entire life cycle and improving the level of power grid asset management.

[0003] However, existing technologies lack dynamic integration of total lifecycle costs and real-time benefits, and maintenance cost accounting does not reflect the increasing effect of equipment aging, making it difficult to balance safety and economy in lifecycle decisions. Summary of the Invention

[0004] The purpose of this invention is to provide a technically and economically sound method for determining the optimal service life of power equipment. This method aims to address the technical problems in existing technologies, such as the lack of dynamic integration of total life cycle costs and real-time benefits, the failure of maintenance cost accounting to reflect the increasing effect of equipment aging, and the difficulty in balancing safety and economy in lifespan decision-making.

[0005] To achieve the above objectives, the present invention employs a techno-economic-based method for determining the optimal operating life of power equipment, comprising the following steps: Collect the cumulative operating time T, real-time voltage D, and real-time ambient temperature W of the power equipment to obtain the wear parameters M of the power equipment; Calculate the real-time health value J of the power equipment, the cumulative percentage of maintenance costs Y, and the hourly revenue-cost ratio S; Calculate the remaining lifespan L of the power equipment based on its real-time health value. The decision is made based on the cumulative maintenance cost percentage Y, the hourly revenue-cost ratio S, and the remaining lifespan L. The decision includes continuing operation, optimizing maintenance, and terminating operation.

[0006] The formula for calculating the real-time health value is as follows: In the formula, A1 is the impact of runtime attenuation; A2 is the impact of electrical parameter deviation; A3 is the impact of environmental coupling; A4 is the impact of equipment wear; A5 is the impact of accumulated maintenance costs; and K1+K2+K3+K4+K5=1, where K1, K2, K3, K4, and K5 are all weighting coefficients. A1 is calculated as follows: In the formula, The total design life of the equipment; A2 is calculated as follows: Calculate now A1 represents one data point, and A2 represents the sum of multiple data points. When the power equipment is continuously operating, the monitoring cycle is 24 hours, and the real-time voltage D is collected once per hour, for a total of 24 data points. When the power equipment is intermittently operating, the monitoring cycle is a cumulative 10 hours of operation, and the real-time voltage D is collected once per hour of operation, for a total of 10 data points. In the formula, This is the voltage deviation value; Standard voltage; For voltage weighting, when the power equipment is classified as mechanical... When the power equipment is electronic ; A3 is calculated as follows: In the formula, This is the temperature deviation value; The environmental impact factor is 0.8 to 1.5. When the actual temperature is higher than the suitable working temperature, it is 1.5; when the actual temperature is lower than the suitable working temperature, it is 0.8; and when the actual temperature is at the suitable working temperature, it is 1.0. The average real-time ambient temperature W during the monitoring cycle of the power equipment; Suitable operating temperature for electrical equipment; A4 is calculated as follows: In the formula, This represents the maximum allowable wear of electrical equipment; when the electrical equipment is mechanical, the wear parameter M decreases by 5% per year; when the electrical equipment is electronic, the wear parameter M decreases by 3% per year. A5 is calculated as follows: In the formula, N1 is the cumulative maintenance cost; N2 is the total initial investment. To maintain the efficiency coefficient, hour, It is 1.4. hour, It is 0.6. If the value is between 0.8 and 1.2, then the actual calculated value should be used. This represents the actual increase in health value. The expected health value improvement is the industry average health value improvement corresponding to this type of maintenance process. The health value for the first stable monitoring cycle after equipment maintenance; To maintain the average health value of the previous monitoring period, the monitoring period is 24 hours for power equipment that is operating continuously and 10 hours for power equipment that is operating intermittently.

[0007] In this process, A1, A2, A3, A4, and A5 are used as input features for calibration, and the output weight coefficients are K1, K2, K3, K4, and K5. During the calibration process, the health value changes before and after maintenance, the maintenance cost data, and the remaining lifespan L are used as training samples. The BP neural network is trained using the training samples. The training samples are no less than 100 sets of valid data. The valid data are the historical dataset after removing outliers by three times the standard deviation. The valid historical data includes the operating cycle of the past 3 years, and the sample size of each year is no less than 30 sets. Each set of samples must include the impact of time decay, the impact of electrical parameter deviation, the impact of environmental coupling, the impact of equipment wear, and the impact of accumulated maintenance costs.

[0008] Wherein, α is the operating time attenuation coefficient, with a value range of 0.01~0.03. It is determined by the equipment's factory design parameters and historical operating data according to "α = (60% of the factory design attenuation coefficient + 40% of the average attenuation coefficient of the same model of equipment over 5 years)". The factory design attenuation coefficient is provided by the equipment manufacturer, and the average attenuation coefficient of the same model of equipment over 5 years is taken from the industry shared database.

[0009] The remaining lifetime L is calculated as follows: In the formula, The safe operating time corresponding to the health value; The total design life of the power equipment; For power equipment, E is a correction factor. For mechanical power equipment, E is 0.9~1.0 when the load rate is ≥80% and E is 1.0~1.1 when the load rate is <80%. For electronic power equipment, E is 0.8~0.9 when the load rate is ≥80% and E is 0.9~1.0 when the load rate is <80%.

[0010] The calculation method for the cumulative maintenance cost percentage Y is as follows: In the formula, This represents the cumulative maintenance cost. This represents the total initial investment in power equipment.

[0011] The hourly revenue-cost ratio S is calculated as follows: In the formula, S1 is the net revenue per hour of the power equipment; S2 is the operation and maintenance cost per hour of the power equipment; S3 is the total revenue per hour of the power equipment; S4 is the energy consumption cost per hour of the power equipment, including the energy consumption for operation, cooling, lubrication, and dust removal; S5 is the system's hourly capacity revenue; S6 is the percentage of the total investment cost of the power equipment in the system; S7 is the total initial investment in the power equipment; and S8 is the total investment cost of the system.

[0012] The decision-making process is based on the cumulative maintenance cost percentage Y, the hourly revenue-cost ratio S, and the remaining lifespan L. When the hourly revenue-cost ratio S is lower than a preset threshold for three consecutive monitoring cycles, the operation is triggered to terminate the power equipment when any of the following conditions are met: Condition 1: Remaining life L ≤ Total design life of power equipment 30%; Condition 2: Cumulative value of maintenance costs ≥60% of the total initial investment in equipment S7; Optimized maintenance is triggered when the remaining lifespan L ≥ 50% and the maintenance cost ≥ 40%. The maintenance and optimization strategy process is as follows: Mechanical equipment: The initial maintenance cycle is 1 year. When the health value is 60-70, the maintenance cycle is shortened by 50%; when the health value is 50-60, the maintenance cycle is shortened by 70%. Electronic equipment: The initial maintenance cycle is 2 years. When the health value is 60-70, the maintenance cycle is shortened by 50%; when the health value is 50-60, the maintenance cycle is shortened by 75%.

[0013] When the decision-making criteria do not meet the requirements of either terminating operation or optimizing maintenance, the power equipment shall continue to operate.

[0014] The preset threshold is 80% of the average revenue-cost ratio of similar equipment in the same industry.

[0015] Specifically, when the cumulative maintenance cost accounts for Y > 30% and the health value J < 70, the calculated health value J is reduced by 2 for correction. The expected increase in health value The minimum is not less than 5, and the expected increase in health value is... The maximum value should not exceed 25, and the expected increase in health value is [not specified]. The sum of the health value J before maintenance should not exceed 100; The maximum expected increase in health value is calculated as follows: Maximum expected increase in health value = (100-U)×80%, where U is the health value before maintenance; When the accumulated maintenance cost value If the health value J increases but there is no significant improvement (meaning the increase in health value J after maintenance is ≤5) and there is no increase for two consecutive monitoring cycles, the remaining lifespan L will be reduced according to the actual change in health value J, with the reduction being: ( - ) / × (50%~80%).

[0016] The present invention provides a method for determining the optimal operating life of power equipment based on techno-economic efficiency, which has the following beneficial effects: 1. Overcome the limitations of static separation between full life cycle cost and real-time benefits in existing technologies, cover the cost and benefit relationship characteristics of equipment from commissioning to retirement, dynamic integration can significantly reduce cost and benefit accounting deviation, improve the accuracy of economic assessment in life cycle decision-making, and the real-time linkage mechanism solves the problem of insufficient dynamic matching of full life cycle cost and benefit. 2. By quantifying the aging-increase effect of maintenance costs, maintenance cost accounting is deeply linked to the aging status of equipment. Through the dynamic correlation of multiple factors with changes in maintenance efficiency coefficient and health value, the distortion of maintenance cost accounting caused by the failure to reflect the aging-increase effect of equipment can be avoided, ensuring the accuracy of maintenance cost accounting at different aging stages. 3. By linking health values ​​and cost-benefit in a dual-dimensional manner, and through dynamic weight calibration and decision-making mechanisms, the system adapts to the changing patterns of safety status and economic performance throughout the entire life cycle of power equipment. This avoids insufficient safety or economic waste caused by single-dimensional decision-making, while ensuring a balance between safety and economy at different operating stages. It maintains stable and accurate optimal operating life decisions throughout the entire life cycle of the equipment, preventing the equipment from operating beyond its optimal operating life, which could lead to sudden damage during operation and cause a chain reaction of system failures, affecting the normal service life of other equipment and preventing additional losses. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the method steps for a techno-economic-based decision-making method for the optimal service life of power equipment according to the present invention. Detailed Implementation

[0019] Please see Figure 1 This invention provides a method for determining the optimal operating life of power equipment based on techno-economic efficiency, comprising the following steps: S1: Collect the cumulative operating time T, real-time voltage D, and real-time ambient temperature W of the power equipment to obtain the wear parameters M of the power equipment; S2: Calculate the real-time health value J of the power equipment, the cumulative percentage of maintenance costs Y, and the hourly revenue-cost ratio S; S3: Calculate the remaining lifespan L of the power equipment based on its real-time health value; S4: Make a decision based on the cumulative maintenance cost percentage Y, the hourly revenue-cost ratio S, and the remaining lifespan L. The decision includes continuing operation, optimizing maintenance, and terminating operation.

[0020] Furthermore, the formula for calculating the real-time health value is as follows: In the formula, A1 is the impact of runtime attenuation; A2 is the impact of electrical parameter deviation; A3 is the impact of environmental coupling; A4 is the impact of equipment wear; A5 is the impact of accumulated maintenance costs; and K1+K2+K3+K4+K5=1, where K1, K2, K3, K4, and K5 are all weighting coefficients. A1 is calculated as follows: In the formula, The total design life of the equipment; A2 is calculated as follows: Calculate now A1 represents one data point, and A2 represents the sum of multiple data points. When the power equipment is continuously operating, the monitoring cycle is 24 hours, and the real-time voltage D is collected once per hour, for a total of 24 data points. When the power equipment is intermittently operating, the monitoring cycle is a cumulative 10 hours of operation, and the real-time voltage D is collected once per hour of operation, for a total of 10 data points. In the formula, This is the voltage deviation value; Standard voltage; For voltage weighting, when the power equipment is classified as mechanical... When the power equipment is electronic ; A3 is calculated as follows: In the formula, This is the temperature deviation value; The environmental impact factor is 0.8 to 1.5. When the actual temperature is higher than the suitable working temperature, it is 1.5; when the actual temperature is lower than the suitable working temperature, it is 0.8; and when the actual temperature is at the suitable working temperature, it is 1.0. The average real-time ambient temperature W during the monitoring cycle of the power equipment; Suitable operating temperature for electrical equipment; A4 is calculated as follows: In the formula, This represents the maximum allowable wear of electrical equipment; when the electrical equipment is mechanical, the wear parameter M decreases by 5% per year; when the electrical equipment is electronic, the wear parameter M decreases by 3% per year. A5 is calculated as follows: In the formula, N1 is the cumulative maintenance cost; N2 is the total initial investment. To maintain the efficiency coefficient, hour, It is 1.4. hour, It is 0.6. If the value is between 0.8 and 1.2, then the actual calculated value should be used. This represents the actual increase in health value. The expected health value improvement is the industry average health value improvement corresponding to this type of maintenance process. The health value for the first stable monitoring cycle after equipment maintenance; To maintain the average health value of the previous monitoring period, the monitoring period is 24 hours for power equipment that is operating continuously and 10 hours for power equipment that is operating intermittently.

[0021] Furthermore, A1, A2, A3, A4, and A5 are used as input features for calibration, and the output weight coefficients K1, K2, K3, K4, and K5 are used. During the calibration process, the health value changes before and after maintenance, the maintenance cost data, and the remaining lifespan L are used as training samples. The BP neural network is trained using the training samples. The training samples are no less than 100 sets of valid data. The valid data are the historical dataset after removing outliers by three times the standard deviation. The valid historical data includes the operating cycle of the past 3 years, and the sample size of each year is no less than 30 sets. Each set of samples must include the influence of time decay, the influence of electrical parameter deviation, the influence of environmental coupling, the influence of equipment wear, and the cumulative influence of maintenance cost.

[0022] Furthermore, α is the operating time attenuation coefficient, with a value range of 0.01 to 0.03. It is determined by the equipment's factory design parameters and historical operating data according to "α = (60% of the factory design attenuation coefficient + 40% of the average attenuation coefficient of the same model equipment over 5 years)". The factory design attenuation coefficient is provided by the equipment manufacturer, and the average attenuation coefficient of the same model equipment over 5 years is taken from an industry shared database.

[0023] Furthermore, the remaining lifetime L is calculated as follows: In the formula, The safe operating time corresponding to the health value; The total design life of the power equipment; For power equipment, E is a correction factor. For mechanical power equipment, E is 0.9~1.0 when the load rate is ≥80% and E is 1.0~1.1 when the load rate is <80%. For electronic power equipment, E is 0.8~0.9 when the load rate is ≥80% and E is 0.9~1.0 when the load rate is <80%.

[0024] Furthermore, the calculation method for the cumulative maintenance cost percentage Y is as follows: In the formula, This represents the cumulative maintenance cost. This represents the total initial investment in power equipment.

[0025] Furthermore, the hourly revenue-cost ratio S is calculated as follows: In the formula, S1 is the net revenue per hour of the power equipment; S2 is the operation and maintenance cost per hour of the power equipment; S3 is the total revenue per hour of the power equipment; S4 is the energy consumption cost per hour of the power equipment, including the energy consumption for operation, cooling, lubrication, and dust removal; S5 is the system's hourly capacity revenue; S6 is the percentage of the total investment cost of the power equipment in the system; S7 is the total initial investment in the power equipment; and S8 is the total investment cost of the system.

[0026] Furthermore, the decision-making process is based on the cumulative maintenance cost percentage Y, the hourly revenue-cost ratio S, and the remaining lifespan L. When the hourly revenue-cost ratio S is lower than a preset threshold for three consecutive monitoring cycles, the operation is triggered to terminate the operation of the power equipment if any of the following conditions are met: Condition 1: Remaining life L ≤ Total design life of power equipment 30%; Condition 2: Cumulative value of maintenance costs ≥60% of the total initial investment in equipment S7; Optimized maintenance is triggered when the remaining lifespan L ≥ 50% and the maintenance cost ≥ 40%. The maintenance and optimization strategy process is as follows: Mechanical equipment: The initial maintenance cycle is 1 year. When the health value is 60-70, the maintenance cycle is shortened by 50%; when the health value is 50-60, the maintenance cycle is shortened by 70%. Electronic equipment: The initial maintenance cycle is 2 years. When the health value is 60-70, the maintenance cycle is shortened by 50%; when the health value is 50-60, the maintenance cycle is shortened by 75%.

[0027] When the decision-making criteria do not meet the requirements of either terminating operation or optimizing maintenance, the power equipment shall continue to operate.

[0028] Furthermore, the preset threshold is 80% of the average revenue-cost ratio of similar equipment in the same industry.

[0029] Furthermore, when the cumulative maintenance cost accounts for more than 30% and the health value J is less than 70, the calculated health value J is reduced by 2 for correction. The expected increase in health value The minimum is not less than 5, and the expected increase in health value is... The maximum value should not exceed 25, and the expected increase in health value is [not specified]. The sum of the health value J before maintenance should not exceed 100; The maximum expected increase in health value is calculated as follows: Maximum expected increase in health value = (100-U)×80%, where U is the health value before maintenance; When the accumulated maintenance cost value If the health value J increases but there is no significant improvement (meaning the increase in health value J after maintenance is ≤5) and there is no increase for two consecutive monitoring cycles, the remaining lifespan L will be reduced according to the actual change in health value J, with the reduction being: ( - ) / × (50%~80%).

[0030] In this embodiment, the improvement in the industry average health value refers to the DL / T series regulations (e.g., DL / T1870-2018 Technical Specification for Power System Grid-Source Coordination; DL / T 593-2016 Common Technical Requirements for High Voltage Switchgear and Control Equipment), the industry shared database refers to either the China Electricity Council database or the State Grid equipment database, the total design life of the equipment is provided by the equipment manufacturer, and the total equipment life data complies with the requirements of GB / 17215.211-2021, the average revenue-cost ratio of similar equipment in the same industry is calibrated by industry statistical data from the past 3 years, and the use of the 3x standard deviation method to remove outliers is a very common and mature outlier removal method in the existing technical field, so it will not be described in detail here; Example 1: This embodiment takes a 10kV mechanical vacuum circuit breaker as the research object. The basic parameters of the power equipment are set as shown in the table below: The decision-making time point was set at 5 years of equipment operation, and the following data was collected: Total runtime: 5 years, totaling 43,800 hours; Real-time electrical parameters: Continuous monitoring for 24 hours, with data collected once per hour. The real-time voltage fluctuation range is 9.98kV~10.02kV. The average value of the 24 voltage deviations is calculated to be 0.005 (with a weight of 0.4 for mechanical voltages). Environmental parameters: The average temperature during the monitoring period was 25℃, which deviated from the suitable operating temperature of 20℃ by 5℃; Equipment wear parameters: Mechanical equipment wears down by 5% annually, with a cumulative wear of 25% over 5 years; Cumulative maintenance costs: Three scheduled maintenance sessions were conducted within 5 years, with each maintenance costing 10,000 yuan, for a total maintenance cost of 30,000 yuan; The impact of runtime decay = cumulative runtime / total design life of the equipment × 10 = 43800 / 175200 × 10 ≈ 2.5; The influence of electrical parameter deviation = the sum of 24 data points = 24 × 0.005 = 0.12; Environmental coupling effect = 5 × 1 = 5; The impact of equipment wear = 25 / 100 × 15 = 3.75; Cumulative impact of maintenance costs: After each maintenance, the health value increases by 6 (90 before maintenance, 96 after maintenance), with an expected increase of 7 (industry average). The maintenance efficiency coefficient is approximately 0.857 (between 0.8 and 1.2, with a maintenance efficiency coefficient of 0.857). The cumulative impact of maintenance costs = (3 / 15) × 10 × 0.857 ≈ 1.714; A backpropagation neural network was trained using 120 sets of valid historical data from the past 3 years (after removing outliers) to obtain the weight coefficients of each influencing factor: K1=0.2, K2=0.1, K3=0.3, K4=0.25, K5=0.15; The factory-designed attenuation coefficient is 0.02 (provided by the manufacturer), and the average attenuation coefficient of the same model of equipment over 5 years is 0.018 (taken from the China Electricity Council database). = (0.02 × 0.6 + 0.018 × 0.4) = 0.0192; (-0.0192×5)≈0.908; ( = 0.2×2.5+0.1×0.12+0.3×5+0.25×3.75+0.15×1.714≈3.2066; Health score = 100 × 0.908 - 3.2066 ≈ 87.6; Health value correction judgment: The cumulative maintenance cost percentage = 3 / 15 × 100% = 20% < 30%, which does not meet the correction condition of "cumulative maintenance cost percentage Y > 30% and health value J < 70". The final health value is 87.6. The safe operating time corresponding to the health value = 20 × (87.6 / 100) × 1.05 ≈ 13.7 years; Remaining lifespan = 13.7 × (1 - 20% × 0.3) ≈ 12.9 years; In DL / T 593-2016 "Common Technical Requirements for High Voltage Switchgear and Controlgear", Article 7.3 of the standard stipulates that the health status qualification line for mechanical high voltage equipment is a health value ≥80. The current health value of the power equipment is 87.6 (no warning), the cumulative maintenance cost accounts for 20% (no warning), and the remaining lifespan is 12.9 years (no warning). The system's hourly revenue is 12,000 yuan; The equipment accounts for 15% of the total cost of the system; Total revenue per hour from the equipment = 1.2 × 15% = 0.18 million yuan = 1800 yuan; The total energy consumption of the equipment is 50 kWh / hour, and the electricity price is 0.6 yuan / kWh (industrial electricity price). The hourly energy cost of the equipment = 50 × 0.6 = 30 yuan; The hourly operation and maintenance cost is 120 yuan; Hourly revenue-cost ratio = (1800-30) / 120 ≈ 14.75; Preset threshold = 12 × 0.8 = 9.6; 14.75 > 9.6, which does not meet the requirement of "when the hourly revenue-cost ratio S is lower than the preset threshold for three consecutive monitoring cycles", so it will not trigger the termination of operation or the optimization and maintenance. The remaining lifespan of 12.9 years does not meet the requirement that "remaining lifespan L ≤ total design lifespan of the power equipment". "30% (6 years)" will not trigger termination of operation; "Remaining lifetime L≥50%" must be satisfied; The cumulative maintenance cost percentage is 20%, which does not meet the "cumulative maintenance cost value" requirement. The operation will not be terminated if the initial investment of equipment S7 is ≥60% (90,000 yuan); the maintenance plan optimization process will not be triggered if the maintenance cost is not ≥40% (60,000 yuan). Based on the above assessment, the 10kV vacuum circuit breaker is currently operating safely and economically, and there is no need to terminate its operation or optimize its maintenance; therefore, the decision is to continue its operation.

[0031] The above description discloses only one preferred embodiment of the present invention, and should not be construed as limiting the scope of the present invention. Those skilled in the art will understand that all or part of the processes of the above embodiments can be implemented, and equivalent changes made in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A method for optimal operation life decision of power equipment based on techno-economic efficiency, characterized in that, It comprises the following steps: Collecting the cumulative running time T, real-time voltage D and real-time environment temperature W of the power equipment, and obtaining the wear parameter M of the power equipment; Calculating the real-time health value J, cumulative maintenance cost ratio Y and hourly income cost ratio S of the power equipment; Calculating the remaining life L of the power equipment according to the real-time health value of the power equipment; Making a decision according to the cumulative maintenance cost ratio Y, hourly income cost ratio S and remaining life L, which includes continuing operation, optimizing maintenance and terminating operation.

2. The optimal operation life decision method of the power equipment based on technical economy according to claim 1, characterized in that, The calculation formula of the real-time health value is as follows: In the formula, A1 is the running time attenuation influence quantity; A2 is the electrical parameter deviation influence quantity; A3 is the environmental coupling influence quantity; A4 is the equipment wear influence quantity; A5 is the cumulative maintenance cost influence quantity; and K1+K2+K3+K4+K5=1, K1, K2, K3, K4 and K5 are weight coefficients; The A1 calculation method is as follows: In the formula, is the total length of the design life of the device; A2 calculation method is: present calculation The value is a data point, A2 is the sum of multiple data points, and the power equipment is a continuous operation equipment: the monitoring period is 24h, the real-time voltage D is collected once every hour, and there are 24 data points in total; When the power equipment is an intermittent operation equipment, the monitoring period is 10h of cumulative operation, and the real-time voltage D is collected once every 1h, with a total of 10 data points; In the formula, is a voltage deviation value; is a standard voltage; is a voltage weight, when the power equipment is mechanical , when the power equipment is electronic ; The A3 calculation method is as follows: In the formula, is a temperature deviation value; is an environmental influence coefficient, the environmental influence coefficient is 0.8-1.5, 1.5 when the actual temperature is higher than the suitable working temperature, 0.8 when the actual temperature is lower than the suitable working temperature, and 1.0 when the actual temperature is at the suitable working temperature; is an average value of the real-time temperature W of the environment in the monitoring period of the power equipment; is a suitable working temperature of the power equipment; The A4 calculation method is as follows: In the formula, is the maximum wear allowed for the electric device; the wear parameter M is reduced by 5% per year for mechanical electric devices and by 3% per year for electronic electric devices. The A5 calculation method is as follows: In the formula, N1 is the cumulative maintenance cost; N2 is the total initial investment; is the maintenance efficiency coefficient, when, is 1.4, when, is 0.6, when between 0.8 and 1.2, the actual calculated value is taken; is the actual health value improvement amount; is the expected health value improvement amount, the expected health value improvement amount being the average health value improvement amount of the industry corresponding to the maintenance process; is the health value of the first stable monitoring period after equipment maintenance; is the average health value in a monitoring period before maintenance, the monitoring period being 24 hours for a continuous operation power equipment and 10 hours for an intermittent operation power equipment.

3. The optimal operation life decision method of the power equipment based on technical economy according to claim 2, characterized in that, A1, A2, A3, A4 and A5 are taken as input characteristics for calibration, and the weight coefficients K1, K2, K3, K4 and K5 are output, the health value change data before and after maintenance, the maintained cost data and the remaining life L are taken as training samples in the calibration process, the BP neural network is trained through the training samples, the training samples are not less than 100 groups of effective data, the effective data are the data set after the 3 times standard deviation of the historical data set is removed, the effective historical data include the operation period of the last 3 years, and the sample amount of each year is not less than 30 groups, each group of samples needs to include the time length attenuation influence quantity, the electrical parameter deviation influence quantity, the environmental coupling influence quantity, the equipment wear influence quantity and the cumulative maintenance cost influence quantity.

4. The optimal operation life decision method of the power equipment based on technical economy according to claim 2, characterized in that, The α is a running time attenuation coefficient, the value range is 0.01~0.03, and it is determined according to "α=(60% of the factory design attenuation coefficient + 40% of the 5-year average attenuation coefficient of the same type equipment)” based on the factory design parameters and historical operation data of the equipment, the factory design attenuation coefficient is provided by the equipment manufacturer, and the 5-year average attenuation coefficient of the same type equipment is taken from an industry shared database.

5. The optimal operation life decision method of the power equipment based on technical economy according to claim 1, characterized in that, The remaining life L calculation method is as follows: In the formula, is the safe operation time corresponding to the health value; is the total design life of the power equipment; is the correction coefficient of the power equipment, in mechanical power equipment, when the load rate is ≥80%, E is 0.9~1.0, when the load rate is <80%, E is 1.0~1.1, in electronic power equipment, when the load rate is ≥80%, E is 0.8~0.9, when the load rate is <80%, E is 0.9~1.

0.

6. The optimal operation life decision method of the power equipment based on technical economy according to claim 1, characterized in that, The cumulative maintenance cost ratio Y calculation method is as follows: In the formula, is the cumulative value of the maintenance cost; is the total initial investment of the power equipment.

7. The method of claim 1, wherein the hourly benefit-cost ratio S is calculated as follows: S = S1 / S2 / S3 / S4 / S5 / S6 / S7 / S8 wherein S1 is the net benefit per hour of the power equipment; S2 is the operation and maintenance cost per hour of the power equipment; S3 is the total benefit per hour of the power equipment; S4 is the energy consumption cost per hour of the power equipment, including the operation energy consumption, cooling energy consumption, lubrication energy consumption and dust removal energy consumption of the power equipment; S5 is the benefit per hour of the system capacity; S6 is the total investment cost percentage of the power equipment in the system; S7 is the total initial investment of the power equipment; and S8 is the total investment cost of the system.

8. The method of claim 1, wherein the decision is made based on the cumulative maintenance cost ratio Y, the hourly benefit-cost ratio S and the remaining life L, and wherein the decision is made as follows: when the hourly benefit-cost ratio S is lower than a preset threshold value for three consecutive monitoring periods, and any one of the following conditions is met, the power equipment is triggered to terminate operation: the remaining life L is greater than or equal to 50% and the cumulative maintenance cost is greater than or equal to 40%, the power equipment is triggered to optimize maintenance; and the maintenance optimization strategy is as follows: for mechanical equipment, the initial maintenance period is one year, when the health value is 60-70, the maintenance period is shortened by 50%, and when the health value is 50-60, the maintenance period is shortened by 70%; and for electronic equipment, the initial maintenance period is two years, when the health value is 60-70, the maintenance period is shortened by 50%, and when the health value is 50-60, the maintenance period is shortened by 75%; and when the decision does not meet the termination of operation or the optimization of maintenance, the power equipment continues to operate.

9. The method of claim 8, wherein the preset threshold value is 80% of the average benefit-cost ratio of the same type of equipment in the same industry.

10. The method of claim 1, wherein when the cumulative maintenance cost ratio Y is greater than 30% and the health value J is less than 70, the health value J is further reduced by 2 to correct the calculated health value J; and wherein the highest expected health value improvement is calculated as follows: highest expected health value improvement = (100-U) x 80%, wherein U is the health value before maintenance. ​ Condition 1: remaining lifetime L < total length of design lifetime of power equipment 30%; Condition 2: The maintenance cost cumulative value has been maintained ≥ 60% of the total initial investment of the equipment S7; ​ ​ ​ ​ ​ ​ ​ ​ ​ the expected health value increase amount the expected health value increase amount the expected health value increase amount the sum of the health values before maintenance J is not more than 100; ​ When the maintained cost cumulative value When the health value J has no obvious increase, the no obvious increase is that the health value J increase after maintenance is ≤5, and there is no increase for 2 monitoring periods, the remaining life L is adjusted according to the actual change amplitude of the health value J, and the adjustment amplitude is: - ) / × (50%-80%).

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