Power transmission investment decision model construction method and device based on risk and cost

Abstract

The invention provides a power transmission investment decision model construction method and device based on risks and cost. The power transmission investment decision model construction method based on the risk and the cost comprises the following steps: calculating the operation and maintenance cost of the power grid power transmission equipment after maintenance according to the remaining service life of the power grid power transmission equipment, the failure rate expected value of the remaining service life and the single maintenance cost; calculating the replacement cost of the power grid power transmission equipment according to the single maintenance cost and the initial value of the power grid power transmission equipment; and determining a maintenance strategy of the power transmission equipment of the power grid according to the operation and maintenance cost and the replacement cost. According to the method, the internal relation between the power transmission line equipment state information and the equipment failure rate is utilized to construct the equipment failure rate model before and after maintenance, the equipment operation and maintenance cost and the equipment risk hazard are accurately evaluated in combination with the power transmission line equipment defect data and the state evaluation information, and intelligent decision-making of the power transmission line maintenance production investment strategy is realized.

Description

Technical Field

[0001] This application belongs to the field of transmission line operation and maintenance technology, specifically involving a method and apparatus for constructing a transmission investment decision-making model based on risk and cost. Background Technology

[0002] Current technologies rely heavily on manual experience in the development of transmission line maintenance plans, lacking scientific and quantifiable decision-making tools, which makes it difficult to meet the increasingly demanding requirements of transmission line operation and maintenance. Therefore, there is an urgent need for a decision-making tool for transmission line production investment to assist in the scientific, economical, and efficient development of transmission equipment maintenance plans. Summary of the Invention

[0003] The present invention discloses a method and apparatus for constructing a power transmission investment decision-making model based on risk and cost. It utilizes the inherent relationship between the status information of transmission line equipment and the equipment failure rate to construct a model of equipment failure rate before and after maintenance. By combining the defect data and status evaluation information of transmission line equipment, it accurately assesses the equipment operation and maintenance costs and equipment risks, and realizes intelligent decision-making for transmission line maintenance and production investment strategies.

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0005] In a first aspect, the present invention provides a method for constructing a power transmission investment decision-making model based on risk and cost, comprising:

[0006] The operation and maintenance cost of the power grid transmission equipment after maintenance is calculated based on the remaining service life of the equipment, the expected failure rate during the remaining service life, and the cost of a single maintenance.

[0007] The replacement cost of the power grid transmission equipment is calculated based on the cost of a single maintenance and the initial value of the power grid transmission equipment.

[0008] The maintenance strategy for the power grid transmission equipment is determined based on the operation and maintenance costs and the replacement costs.

[0009] In one embodiment, the method for constructing a transmission investment decision-making model based on risk and cost further includes:

[0010] A failure rate model is established based on the state parameters of the power grid transmission equipment.

[0011] The equivalent service life after maintenance is calculated based on the failure rate model.

[0012] In one embodiment, establishing a failure rate model based on the state parameters of the power grid transmission equipment includes:

[0013] The correlation coefficients in the failure rate model are derived by inversely using historical equipment failure data and their corresponding state parameters.

[0014] The failure rate model is established based on the correlation coefficient and the state parameters of the power grid transmission equipment.

[0015] In one embodiment, the method for constructing a power transmission investment decision model based on risk and cost further includes: checking the failure rate of the power grid transmission equipment.

[0016] In one embodiment, checking the failure rate of the power grid transmission equipment includes:

[0017] Check whether the failure rate conforms to a Weibull distribution;

[0018] When the failure rate conforms to the Weibull distribution, the failure rate is considered acceptable.

[0019] Otherwise, the failure rate is considered unacceptable.

[0020] In one embodiment, the method for constructing a transmission investment decision-making model based on risk and cost further includes:

[0021] The fault risk hazard value of the power grid transmission equipment is calculated based on the hazard score of the power grid when the power grid transmission equipment fails and the importance level factor of the power grid.

[0022] The risk value of the power grid when the power transmission equipment fails is calculated based on the fault risk hazard value and the failure rate after equipment maintenance.

[0023] Secondly, the present invention provides a device for constructing a power transmission investment decision-making model based on risk and cost, the device comprising:

[0024] The operation and maintenance cost calculation module is used to calculate the operation and maintenance cost of the power grid transmission equipment after maintenance based on the remaining service life of the power grid transmission equipment, the expected failure rate of the remaining service life, and the cost of a single maintenance.

[0025] The replacement cost calculation module is used to calculate the replacement cost of the power grid transmission equipment based on the single maintenance cost and the initial value of the power grid transmission equipment.

[0026] The maintenance strategy determination module is used to determine the maintenance strategy for the power grid transmission equipment based on the operation and maintenance cost and the replacement cost.

[0027] In one embodiment, the device for constructing a transmission investment decision model based on risk and cost further includes:

[0028] The post-maintenance failure rate calculation module is used to calculate the post-maintenance failure rate of the power grid transmission equipment based on its equivalent service life after maintenance.

[0029] The expected value calculation module is used to calculate the expected value of the failure rate for the remaining service life based on the failure rate after the equipment is overhauled.

[0030] In one embodiment, the device for constructing a transmission investment decision model based on risk and cost further includes:

[0031] The failure rate model establishment module is used to establish a failure rate model for the power grid transmission equipment based on its state parameters.

[0032] The equivalent service life calculation module is used to calculate the equivalent service life after maintenance based on the failure rate model.

[0033] In one embodiment, the failure rate model building module includes:

[0034] The coefficient back-calculation unit is used to back-calculate the correlation coefficients in the failure rate model based on historical equipment failure data and its corresponding state parameters.

[0035] The failure rate model establishment unit is used to establish the failure rate model based on the correlation coefficient and the state parameters of the power grid transmission equipment.

[0036] In one embodiment, the device for constructing a transmission investment decision model based on risk and cost further includes:

[0037] The failure rate checking module is used to check the failure rate of the power grid transmission equipment.

[0038] In one embodiment, the failure rate checking module includes:

[0039] The Weibull verification unit is used to check whether the failure rate conforms to the Weibull distribution.

[0040] When the failure rate conforms to the Weibull distribution, the failure rate is considered acceptable.

[0041] Otherwise, the failure rate is considered unacceptable.

[0042] In one embodiment, the device for constructing a transmission investment decision model based on risk and cost further includes:

[0043] The hazard value calculation module is used to calculate the fault risk hazard value of the power grid transmission equipment based on the hazard score of the power grid when the power grid transmission equipment fails and the importance level factor of the power grid.

[0044] The risk value calculation module is used to calculate the risk value of the power grid when the power grid transmission equipment fails, based on the fault risk hazard value and the failure rate after equipment maintenance.

[0045] Thirdly, the present invention 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 steps of constructing a transmission investment decision model based on risk and cost.

[0046] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for constructing a transmission investment decision model based on risk and cost.

[0047] As described above, embodiments of the present invention provide a method and apparatus for constructing a power transmission investment decision-making model based on risk and cost. First, the operation and maintenance cost of the power transmission equipment after maintenance is calculated based on the remaining service life of the power grid transmission equipment, the expected failure rate of the remaining service life, and the cost of a single maintenance. Next, the replacement cost of the power grid transmission equipment is calculated based on the cost of a single maintenance and the initial value of the power grid transmission equipment. Finally, the maintenance strategy for the power grid transmission equipment is determined based on the operation and maintenance cost and the replacement cost. This invention utilizes the inherent relationship between the status information of transmission line equipment and the equipment failure rate to construct a failure rate model before and after maintenance. Combined with transmission line equipment defect data and status evaluation information, it accurately assesses the equipment operation and maintenance costs and equipment risks, achieving intelligent decision-making for power transmission line maintenance and production investment strategies. Attached Figure Description

[0048] 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 some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a flowchart illustrating the method for constructing a transmission investment decision-making model based on risk and cost in an embodiment of the present invention. Figure 1 ;

[0050] Figure 2 This is a flowchart illustrating the method for constructing a transmission investment decision-making model based on risk and cost in an embodiment of the present invention. Figure 2 ;

[0051] Figure 3 This is a flowchart illustrating the method for constructing a transmission investment decision-making model based on risk and cost in an embodiment of the present invention. Figure 3 ;

[0052] Figure 4 This is a flowchart illustrating step 600 in an embodiment of the present invention;

[0053] Figure 5This is a flowchart illustrating the method for constructing a transmission investment decision-making model based on risk and cost in an embodiment of the present invention. Figure 4 ;

[0054] Figure 6 This is a flowchart illustrating step 800 in an embodiment of the present invention;

[0055] Figure 7 This is a flowchart illustrating the method for constructing a transmission investment decision-making model based on risk and cost in an embodiment of the present invention. Figure 5 ;

[0056] Figure 8 This is a flowchart illustrating the method for constructing a power transmission investment decision-making model based on risk and cost in a specific embodiment of the present invention.

[0057] Figure 9 A mind map illustrating the method for constructing a power transmission investment decision-making model based on risk and cost in a specific embodiment of the present invention;

[0058] Figure 10 This is a block of a power transmission investment decision-making model construction device based on risk and cost, as shown in an embodiment of the present invention. Figure 1 ;

[0059] Figure 11 This is a block of a power transmission investment decision-making model construction device based on risk and cost, as shown in an embodiment of the present invention. Figure 2 ;

[0060] Figure 12 This is a block of a power transmission investment decision-making model construction device based on risk and cost, as shown in an embodiment of the present invention. Figure 3 ;

[0061] Figure 13 A block diagram of the failure rate model building module 60 in an embodiment of the present invention;

[0062] Figure 14 This is a block of a power transmission investment decision-making model construction device based on risk and cost, as shown in an embodiment of the present invention. Figure 4 ;

[0063] Figure 15 This is a block diagram of the failure rate checking module 80 in an embodiment of the present invention;

[0064] Figure 16 This is a block of a power transmission investment decision-making model construction device based on risk and cost, as shown in an embodiment of the present invention. Figure 5 ;

[0065] Figure 17 This is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, 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.

[0067] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0068] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product or device.

[0069] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0070] The embodiments of the present invention provide a specific implementation method for constructing a power transmission investment decision-making model based on risk and cost. See [link to relevant documentation]. Figure 1 The method specifically includes the following:

[0071] Step 100: Calculate the operation and maintenance cost of the power grid transmission equipment after maintenance based on the remaining service life of the power grid transmission equipment, the expected failure rate of the remaining service life, and the cost of a single maintenance.

[0072] Specifically, see the following formula:

[0073] C 检修 =C 成本 +E 故障率 ×T f ×C 成本

[0074] Among them, C 检修 It is the total cost of equipment operation and maintenance after overhaul, E 故障率It is the expected failure rate over the remaining total service life of the equipment after maintenance. T f It is the remaining total service life T f =T0-T eq C 成本 It is the maintenance cost required for a single equipment overhaul.

[0075] Step 200: Calculate the replacement cost of the power grid transmission equipment based on the single maintenance cost and the initial value of the power grid transmission equipment;

[0076] Equipment replacement cost:

[0077] C 更换 =C 成本 +L0

[0078] Where L0 is the initial value of the equipment.

[0079] Step 300: Determine the maintenance strategy for the power grid transmission equipment based on the operation and maintenance cost and the replacement cost;

[0080] First, calculate the critical value point for equipment replacement:

[0081] C 检修 =C 更换 -L 残

[0082] Among them, L 残 The residual value of the equipment is calculated using the straight-line depreciation method.

[0083] Substitute C 检修 With C 更换 The simplified calculation formula is as follows:

[0084] E 故障率 ×T f ×C 成本 =L0-L 残

[0085] Next, decisions will be made regarding equipment replacement and maintenance:

[0086] When E 故障率 ×T f ×C 成本 =L0-L 残 If necessary, choose to replace the equipment;

[0087] When E 故障率 ×T f ×C 成本 <L0-L 残 At that time, further evaluation of the maintenance methods will be conducted.

[0088] Equipment maintenance method selection in cases where equipment replacement is not required:

[0089] C * =min{C 大修 C 小修}

[0090] Among them, C 大修 To determine the required overhaul cost for selecting a major repair plan, C 小修 The maintenance cost required to select a minor repair plan.

[0091] As described above, this invention provides a method for constructing a power transmission investment decision-making model based on risk and cost. First, it calculates the operation and maintenance cost of the power transmission equipment after maintenance based on the remaining service life, expected failure rate of the remaining service life, and cost of a single maintenance. Next, it calculates the replacement cost of the power transmission equipment based on the cost of a single maintenance and the initial value of the power transmission equipment. Finally, it determines the maintenance strategy for the power transmission equipment based on the operation and maintenance cost and the replacement cost. This invention utilizes the inherent relationship between the status information of transmission line equipment and the equipment failure rate to construct a failure rate model before and after maintenance. Combined with transmission line equipment defect data and status evaluation information, it accurately assesses equipment operation and maintenance costs and equipment risks, achieving intelligent decision-making for power transmission line maintenance and production investment strategies.

[0092] In one embodiment, see Figure 2 The method for constructing a transmission investment decision-making model based on risk and cost further includes:

[0093] Step 400: Calculate the equipment failure rate after maintenance based on the equivalent service life of the power grid transmission equipment after maintenance;

[0094] Specifically:

[0095]

[0096] Where m is the shape parameter, η is the scale parameter, and t is time.

[0097] Step 500: Calculate the expected failure rate for the remaining service life based on the failure rate after equipment maintenance.

[0098] Expected failure rate over the remaining total service life of the equipment after maintenance:

[0099]

[0100] In one embodiment, see Figure 3 The method for constructing a transmission investment decision-making model based on risk and cost further includes:

[0101] Step 600: Establish a failure rate model for the power grid transmission equipment based on its state parameters;

[0102] Specifically, a device failure rate model based on device condition evaluation scores is constructed:

[0103] λ=K·e A·S

[0104] Where λ is the equipment failure rate, K is the proportional coefficient, A is the curvature coefficient, and S is the equipment condition evaluation score.

[0105] Step 700: Calculate the equivalent service life after maintenance based on the failure rate model.

[0106] Specifically, the failure rate calculation method based on equipment condition evaluation is used to estimate the current equivalent service life of the equipment.

[0107]

[0108] Among them, t eq The equivalent service life of the equipment.

[0109] In one embodiment, see Figure 4 Step 600 includes:

[0110] Step 601: Based on historical equipment failure data and their corresponding state parameters, deduce the correlation coefficients in the failure rate model;

[0111] Step 602: Establish the failure rate model based on the correlation coefficient and the state parameters of the power grid transmission equipment.

[0112] In steps 601 and 602, the correlation coefficients in step 601 are calculated based on historical equipment failure data and condition evaluation scores. Paired data of equipment failure rate and equipment condition evaluation score are statistically analyzed on an annual basis, and coefficients K and A are inversely calculated.

[0113] Formula for determining coefficients based on statistical and extrapolation concepts:

[0114]

[0115] Where n is the number of faulty devices, N is the total number of devices of this type, and S i For the condition evaluation score of the i-th type of equipment in the statistical classification, N i For S i The total number of corresponding devices.

[0116] Obtain paired data for equipment failure rates and equipment operating status evaluation scores from two years or more. Substitute the historical data into the inversion formula to calculate K and A respectively.

[0117] In one embodiment, see Figure 5The method for constructing a transmission investment decision-making model based on risk and cost further includes:

[0118] Step 800: Check the failure rate of the power grid transmission equipment.

[0119] In one embodiment, see Figure 6 Step 800 includes:

[0120] Step 801: Check whether the failure rate conforms to the Weibull distribution;

[0121] When the failure rate conforms to the Weibull distribution, the failure rate is considered acceptable.

[0122] Otherwise, the failure rate is considered unacceptable.

[0123] Specifically, when filtering data distribution characteristics, the Weibull distribution, which describes the distribution of equipment failure rates, is preferred:

[0124]

[0125] Where λ(t) is the equipment failure rate at service age t, m is the shape parameter, and η is the scale parameter. Verification of whether the failure rate distribution of transmission equipment conforms to the Weibull distribution: Randomly sample historical fault maintenance time data of transmission lines and organize them into an ascending time sequence {t1, t2, t3…t}. n}

[0126] Calculate T i and y i (i = 1, 2, ..., n), the calculation formula is as follows:

[0127] T i =ln(t) i ′);

[0128]

[0129] Draw according to the point plotting method (t) i ,y i The system can be used to determine whether the coordinate points are roughly distributed along a straight line. If they are distributed along a straight line, it proves that the failure rate distribution of the power transmission equipment basically conforms to the Weibull distribution; otherwise, it does not.

[0130] In one embodiment, see Figure 7 The method for constructing a transmission investment decision-making model based on risk and cost further includes:

[0131] Step 900: Calculate the fault risk hazard value of the power grid transmission equipment based on the hazard score of the power grid when the power grid transmission equipment fails and the importance level factor of the power grid;

[0132] Step 1000: Calculate the risk value of the power grid when the power grid transmission equipment fails, based on the fault risk hazard value and the failure rate after equipment maintenance.

[0133] First, quantitatively assess the risk hazard value of equipment maintenance, F = y. t ×n where y t Let t be the hazard score of a component failure on the overall operation of the line, and n be the line importance level factor. The specific process is as follows:

[0134] Next, determine the severity score y for component failure. t Based on equipment ledgers and marketing user files, and taking the power line as the main body, the power load curves of the equipment / towers and power users are associated. By accumulating the power load curves of similar equipment / towers and associated power users, the power load curves of the equipment / towers are obtained, and thus the y-value is calculated. t .

[0135] Determine the importance level n. Based on the amount of power outage / shortage caused by the equipment failure to be repaired, design the importance factor n.

[0136] Finally, based on the equipment failure risk d = F × λ t Prioritize equipment maintenance items and optimize investment plans.

[0137] In one specific implementation, see Figure 8 as well as Figure 9 The present invention also provides specific implementation methods for constructing a power transmission investment decision-making model based on risk and cost.

[0138] S1: Construct a failure rate calculation method based on equipment condition evaluation;

[0139] Specifically, step S1 includes:

[0140] S11: Construct a device failure rate model based on device condition evaluation scores:

[0141] λ=K·e A·S

[0142] Where λ is the equipment failure rate, K is the proportional coefficient, A is the curvature coefficient, and S is the equipment status evaluation score obtained according to the power grid transmission equipment operation status evaluation standard (the value range is 0 to 100).

[0143] S12: Calculate the two types of coefficients in S11 based on historical equipment failure data and condition evaluation scores. Collect paired data of equipment failure rate and equipment condition evaluation score on an annual basis, and inversely calculate coefficients K and A.

[0144] Step S12 includes:

[0145] S121: The calculation formula obtained based on statistical significance and mathematical definition is as follows:

[0146]

[0147] Where n is the number of faulty devices, N is the total number of devices of this type, and S i For the condition evaluation score of the i-th type of equipment in the statistical classification, N i For S i The total number of corresponding devices.

[0148] S122: Obtain paired data of equipment failure rate and equipment operation status evaluation score for two years or more. Taking insulators as an example, obtain equipment status information for 2019 and 2020, see Table 1.

[0149] Table 1

[0150]

[0151] S123: Substituting N, n, and P from the table into the calculation formula, we obtain K = 1.65e -1 A = 0.473.

[0152] S124: The current state failure rate model for the equipment is λ = 1.65e -0.527S .

[0153] S2: Construct a method for estimating the probability of equipment failure after maintenance;

[0154] Specifically, step S2 includes:

[0155] S21: Filter data distribution characteristics and select the Weibull distribution, which is commonly used to describe the distribution of equipment failure rates:

[0156]

[0157] Where λ(t) is the equipment failure rate at service age t, m is the shape parameter, and η is the scale parameter.

[0158] S22: Verify whether the failure rate distribution of power transmission equipment conforms to the Weibull distribution;

[0159] Specifically, step S22 includes:

[0160] S221: Randomly extract historical fault maintenance time data of transmission lines and organize them into an ascending time sequence {t1,t2,t3……t}. n} consists of n random sample data.

[0161] S222: Calculate T i and y i (i = 1, 2, ..., n), the calculation formula is as follows:

[0162] T i =ln(t) i ′);

[0163]

[0164] S223: Draw according to the point-plotting method (t) i ,y i The coordinate points are roughly distributed along a straight line, proving that the distribution characteristics of the power transmission equipment failure rate basically conform to the Weibull distribution.

[0165] S224: Substitute historical data of insulators to obtain the relationship between the failure rate of transmission line insulator equipment and the service life of the equipment.

[0166] λ(t) = 32.65t 0.38

[0167] S23: Based on the equipment failure rate model in step S1, calculate the current equivalent service life of the equipment.

[0168]

[0169] Among them, t eq The equivalent service life of the equipment.

[0170] S24: Calculate the equivalent service life of the equipment after maintenance.

[0171] The specific steps are as follows:

[0172] S241: Calculate the post-maintenance service life (major overhaul, minor overhaul) for each maintenance method based on the current equivalent service life of the equipment:

[0173] t af =t eq ×(1-α j )

[0174] Among them, t af α is the equivalent service age returned after maintenance. j The equivalent coefficient for maintenance rollback.

[0175] S242: Extract historical data on failure rates after various maintenance procedures of power transmission equipment, substitute them into the Weibull distributed failure rate shown in S21, and calculate the equipment's equivalent service life reduction rate after major and minor repairs (taking the average of the data samples):

[0176]

[0177] S243: Substitute the equivalent service life calculation formula in S23 into the post-maintenance equivalent service life calculation formula in S241:

[0178]

[0179] S244: Calculating the equipment failure rate after maintenance based on the equivalent service life after different maintenance methods:

[0180]

[0181] S3: Construct a formula for estimating equipment failure repair costs based on failure rates;

[0182] Step S3 includes:

[0183] S31: Calculate the total cost of equipment operation and maintenance after overhaul.

[0184] C 检修 =C 成本 +E 故障率 ×T f ×C 成本

[0185] Among them, C 检修 It is the total cost of equipment operation and maintenance after overhaul, E 故障率 It is the expected failure rate over the remaining total service life of the equipment after maintenance. T f It is the remaining total service life T f =T0-T eq C 成本 It is the maintenance cost required for a single equipment overhaul.

[0186] S32: Select the maintenance method;

[0187] The specific steps are as follows:

[0188] S321: Calculate equipment replacement costs:

[0189] C 更换 =C 成本 +L0

[0190] Where L0 is the initial value of the equipment.

[0191] S322: Value Criterion for Computing Equipment Replacement:

[0192] C 检修 =C 更换 -L 残

[0193] Among them, L 残 The residual value of the equipment is calculated using the straight-line depreciation method.

[0194] Substituting C into S31 and S321 检修 With C 更换 The simplified calculation formula is as follows:

[0195] E 故障率 ×T f ×C 成本 =L0-L 残

[0196] S323: Equipment Replacement and Maintenance Decisions

[0197] Based on the calculation results of S322, the decision-making criteria are as follows:

[0198] When E 故障率 ×T f ×C 成本 =L0-L 残 If necessary, choose to replace the equipment;

[0199] When E 故障率 ×T f ×C 成本 <L0-L 残 At that time, further evaluation of the maintenance method will be conducted. Here, K represents the cost required to replace the equipment, and L represents the residual value of the old equipment. The residual value is calculated using the straight-line depreciation method.

[0200] S324: Equipment maintenance method selection in non-equipment replacement cases:

[0201] C * =min{C 大修 C 小修}

[0202] Among them, C 大修 To determine the required overhaul cost for selecting a major repair plan, C 小修 The maintenance cost required to select a minor repair plan.

[0203] S4: Design investment plan optimization rules.

[0204] Step S4 includes:

[0205] S41: Quantitatively assess the hazard value of equipment failure risk:

[0206] F = y t ×n

[0207] Where F is the hazard value of equipment failure risk, y t Let t be the hazard score of a component failure on the overall operation of the line, and n be the line importance level factor. The specific steps are as follows:

[0208] S411: Determine the severity score of component failure y t .

[0209] Based on equipment ledgers and marketing user files, and taking the power lines as the main body, the power load curves of similar equipment / towers and associated power users are obtained by cumulatively analyzing the power load curves of the equipment / towers and associated power users. This allows for the calculation of y. t .

[0210] S412: Determine the importance level n.

[0211] The importance factor n is determined based on the line grade of the equipment to be inspected. The ranges for importance factors for various line grades are as follows (see Table 2):

[0212] Table 2

[0213] Line type Category III lines Category II lines Class I lines N 1 1<＝n<1.2 1.2<＝n<2.5

[0214] S42: Develop an equipment maintenance plan:

[0215] d=F×λ t

[0216] S43: Based on the power grid risk value of equipment failure, prioritize equipment maintenance items to further optimize the investment plan.

[0217] Based on the same inventive concept, this application also provides a risk and cost-based transmission investment decision-making model construction apparatus, which can be used to implement the method described in the above embodiments, as shown in the following embodiments. Since the principle of the risk and cost-based transmission investment decision-making model construction apparatus in solving the problem is similar to that of the risk and cost-based transmission investment decision-making model construction method, the implementation of the risk and cost-based transmission investment decision-making model construction apparatus can refer to the implementation of the risk and cost-based transmission investment decision-making model construction method, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0218] Embodiments of the present invention provide a specific implementation of a risk- and cost-based transmission investment decision-making model construction device capable of implementing a risk- and cost-based transmission investment decision-making model construction method. See [link to specific implementation details]. Figure 10 The device for constructing a power transmission investment decision-making model based on risk and cost specifically includes the following:

[0219] The operation and maintenance cost calculation module 10 is used to calculate the operation and maintenance cost of the power grid transmission equipment after maintenance based on the remaining service life of the power grid transmission equipment, the expected failure rate of the remaining service life, and the cost of a single maintenance.

[0220] The replacement cost calculation module 20 is used to calculate the replacement cost of the power grid transmission equipment based on the single maintenance cost and the initial value of the power grid transmission equipment.

[0221] The maintenance strategy determination module 30 is used to determine the maintenance strategy of the power grid transmission equipment based on the operation and maintenance cost and the replacement cost.

[0222] In one embodiment, see Figure 11 The device for constructing a transmission investment decision-making model based on risk and cost also includes:

[0223] The post-maintenance failure rate calculation module 40 is used to calculate the post-maintenance failure rate of the power grid transmission equipment based on its equivalent service life after maintenance.

[0224] The expected value calculation module 50 is used to calculate the expected value of the failure rate for the remaining service life based on the failure rate after the equipment is overhauled.

[0225] In one embodiment, see Figure 12 The device for constructing a transmission investment decision-making model based on risk and cost also includes:

[0226] The failure rate model establishment module 60 is used to establish a failure rate model for the power grid transmission equipment based on its state parameters.

[0227] The equivalent service life calculation module 70 is used to calculate the equivalent service life after maintenance based on the failure rate model.

[0228] In one embodiment, see Figure 13 The failure rate model establishment module 60 includes:

[0229] The coefficient back-calculation unit 601 is used to back-calculate the correlation coefficients in the failure rate model based on historical equipment failure data and its corresponding state parameters.

[0230] The failure rate model establishment unit 602 is used to establish the failure rate model based on the correlation coefficient and the state parameters of the power grid transmission equipment.

[0231] In one embodiment, see Figure 14 The device for constructing a transmission investment decision-making model based on risk and cost also includes:

[0232] The failure rate checking module 80 is used to check the failure rate of the power grid transmission equipment.

[0233] In one embodiment, see Figure 15 The failure rate checking module 80 includes:

[0234] The Weibull verification unit 801 is used to check whether the failure rate conforms to the Weibull distribution;

[0235] When the failure rate conforms to the Weibull distribution, the failure rate is considered acceptable.

[0236] Otherwise, the failure rate is considered unacceptable.

[0237] In one embodiment, see Figure 16 The device for constructing a transmission investment decision-making model based on risk and cost also includes:

[0238] The hazard value calculation module 90 is used to calculate the fault risk hazard value of the power grid transmission equipment based on the hazard score of the power grid when the power grid transmission equipment fails and the importance level factor of the power grid.

[0239] The risk value calculation module 91 is used to calculate the risk value of the power grid when the power grid transmission equipment fails, based on the fault risk hazard value and the failure rate after equipment maintenance.

[0240] As described above, this invention provides a risk and cost-based power transmission investment decision-making model construction device. First, it calculates the operation and maintenance cost of the power transmission equipment after maintenance based on the remaining service life, expected failure rate of the remaining service life, and cost of a single maintenance. Next, it calculates the replacement cost of the power transmission equipment based on the cost of a single maintenance and the initial value of the power transmission equipment. Finally, it determines the maintenance strategy for the power transmission equipment based on the operation and maintenance cost and the replacement cost. This invention utilizes the inherent relationship between the status information of transmission line equipment and the equipment failure rate to construct a failure rate model before and after maintenance. Combined with transmission line equipment defect data and status evaluation information, it accurately assesses equipment operation and maintenance costs and equipment risks, achieving intelligent decision-making for power transmission line maintenance and production investment strategies.

[0241] The embodiments of this application also provide a specific implementation of an electronic device capable of implementing all steps in the risk and cost-based power transmission investment decision-making model construction method described in the above embodiments. See [link to implementation details]. Figure 17 The electronic devices specifically include the following:

[0242] Processor 1201, memory 1202, communications interface 1203, and bus 1204;

[0243] The processor 1201, memory 1202, and communication interface 1203 communicate with each other via bus 1204; the communication interface 1203 is used to realize information transmission between server-side devices and client-side devices and other related devices.

[0244] The processor 1201 is used to call the computer program in the memory 1202. When the processor executes the computer program, it implements all the steps in the risk and cost-based power transmission investment decision-making model construction method in the above embodiments. For example, when the processor executes the computer program, it implements the following steps:

[0245] Step 100: Calculate the operation and maintenance cost of the power grid transmission equipment after maintenance based on the remaining service life of the power grid transmission equipment, the expected failure rate of the remaining service life, and the cost of a single maintenance.

[0246] Step 200: Calculate the replacement cost of the power grid transmission equipment based on the single maintenance cost and the initial value of the power grid transmission equipment;

[0247] Step 300: Determine the maintenance strategy for the power grid transmission equipment based on the operation and maintenance cost and the replacement cost.

[0248] Embodiments of this application also provide a computer-readable storage medium capable of implementing all steps of the risk- and cost-based power transmission investment decision-making model construction method in the above embodiments. The computer-readable storage medium stores a computer program that, when executed by a processor, implements all steps of the risk- and cost-based power transmission investment decision-making model construction method in the above embodiments. For example, when the processor executes the computer program, it implements the following steps:

[0249] Step 100: Calculate the operation and maintenance cost of the power grid transmission equipment after maintenance based on the remaining service life of the power grid transmission equipment, the expected failure rate of the remaining service life, and the cost of a single maintenance.

[0250] Step 200: Calculate the replacement cost of the power grid transmission equipment based on the single maintenance cost and the initial value of the power grid transmission equipment;

[0251] Step 300: Determine the maintenance strategy for the power grid transmission equipment based on the operation and maintenance cost and the replacement cost.

[0252] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are relatively simple in description because they are fundamentally similar to method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0253] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

[0254] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0255] While this application provides method operation steps as shown in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual device or client product execution, the method can be executed sequentially as shown in the embodiments or drawings, or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0256] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing the embodiments of this specification, the functions of each module can be implemented in one or more software and / or hardware components, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0257] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0258] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0259] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0260] The embodiments described in this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0261] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, system embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. In the description of this specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments in this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0262] The above description is merely an embodiment of the present specification and is not intended to limit the embodiments of the present specification. For those skilled in the art, various modifications and variations can be made to the embodiments of the present specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of the present specification should be included within the scope of the claims of the embodiments of the present specification.

Claims

1. A method for constructing a power transmission investment decision-making model based on risk and cost, characterized in that, include: The operation and maintenance cost of the power grid transmission equipment after maintenance is calculated based on the remaining service life of the equipment, the expected failure rate during the remaining service life, and the cost of a single maintenance. The replacement cost of the power grid transmission equipment is calculated based on the cost of a single maintenance and the initial value of the power grid transmission equipment. The maintenance strategy for the power grid transmission equipment is determined based on the operation and maintenance costs and the replacement costs.

2. The method for constructing a power transmission investment decision-making model as described in claim 1, characterized in that, Also includes: The failure rate of the equipment after maintenance is calculated based on the equivalent service life of the power grid transmission equipment after maintenance. The expected failure rate for the remaining service life is calculated based on the failure rate after the equipment is overhauled.

3. The method for constructing a power transmission investment decision-making model as described in claim 2, characterized in that, Also includes: A failure rate model is established based on the state parameters of the power grid transmission equipment. The equivalent service life after maintenance is calculated based on the failure rate model.

4. The method for constructing a power transmission investment decision-making model as described in claim 3, characterized in that, The step of establishing a failure rate model based on the state parameters of the power grid transmission equipment includes: The correlation coefficients in the failure rate model are derived by inversely using historical equipment failure data and their corresponding state parameters. The failure rate model is established based on the correlation coefficient and the state parameters of the power grid transmission equipment.

5. The method for constructing a power transmission investment decision-making model as described in claim 1, characterized in that, Also includes: The failure rate of the power grid transmission equipment is checked.

6. The method for constructing a power transmission investment decision-making model as described in claim 5, characterized in that, The failure rate check of the power grid transmission equipment includes: Check whether the failure rate conforms to a Weibull distribution; When the failure rate conforms to the Weibull distribution, the failure rate is considered acceptable. Otherwise, the failure rate is considered unacceptable.

7. The method for constructing a power transmission investment decision-making model as described in claim 1, characterized in that, Also includes: The fault risk hazard value of the power grid transmission equipment is calculated based on the hazard score of the power grid when the power grid transmission equipment fails and the importance level factor of the power grid. The risk value of the power grid when the power transmission equipment fails is calculated based on the fault risk hazard value and the failure rate after equipment maintenance.

8. A device for constructing a power transmission investment decision-making model based on risk and cost, characterized in that, include: The operation and maintenance cost calculation module is used to calculate the operation and maintenance cost of the power grid transmission equipment after maintenance based on the remaining service life of the power grid transmission equipment, the expected failure rate of the remaining service life, and the cost of a single maintenance. The replacement cost calculation module is used to calculate the replacement cost of the power grid transmission equipment based on the single maintenance cost and the initial value of the power grid transmission equipment. The maintenance strategy determination module is used to determine the maintenance strategy for the power grid transmission equipment based on the operation and maintenance cost and the replacement cost.

9. The power transmission investment decision-making model construction device as described in claim 8, characterized in that, Also includes: The post-maintenance failure rate calculation module is used to calculate the post-maintenance failure rate of the power grid transmission equipment based on its equivalent service life after maintenance. The expected value calculation module is used to calculate the expected value of the failure rate for the remaining service life based on the failure rate after the equipment is overhauled.

10. The power transmission investment decision-making model construction device as described in claim 9, characterized in that, Also includes: The failure rate model establishment module is used to establish a failure rate model for the power grid transmission equipment based on its state parameters. The equivalent service life calculation module is used to calculate the equivalent service life after maintenance based on the failure rate model.

11. The power transmission investment decision-making model construction device as described in claim 10, characterized in that, The failure rate model building module includes: The coefficient back-calculation unit is used to back-calculate the correlation coefficients in the failure rate model based on historical equipment failure data and its corresponding state parameters. The failure rate model establishment unit is used to establish the failure rate model based on the correlation coefficient and the state parameters of the power grid transmission equipment.

12. The power transmission investment decision-making model construction device as described in claim 8, characterized in that, Also includes: The failure rate checking module is used to check the failure rate of the power grid transmission equipment.

13. The power transmission investment decision-making model construction device as described in claim 12, characterized in that, The failure rate checking module includes: The Weibull verification unit is used to check whether the failure rate conforms to the Weibull distribution. When the failure rate conforms to the Weibull distribution, the failure rate is considered acceptable. Otherwise, the failure rate is considered unacceptable.

14. The power transmission investment decision-making model construction device as described in claim 8, characterized in that, Also includes: The hazard value calculation module is used to calculate the fault risk hazard value of the power grid transmission equipment based on the hazard score of the power grid when the power grid transmission equipment fails and the importance level factor of the power grid. The risk value calculation module is used to calculate the risk value of the power grid when the power grid transmission equipment fails, based on the fault risk hazard value and the failure rate after equipment maintenance.

15. 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 steps of the method for constructing a transmission investment decision model based on risk and cost as described in any one of claims 1 to 7.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method for constructing a risk and cost-based power transmission investment decision model as described in any one of claims 1 to 7.

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