Transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraint

Abstract

The invention relates to the field of power equipment maintenance methods, in particular to a transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints, which comprises the following steps of: performing quantitative modeling on the influence of power failure overhaul and maintenance measures frequently adopted by transformer and circuit breaker equipment; quantitative modeling is carried out on the influence of periodic inspection measures frequently adopted by the transformer and the circuit breaker equipment; based on the equipment three-state model, modeling equipment fault probability maintenance after considering two maintenance strategies of power-off maintenance and periodic inspection, and providing data input for the reliability index evaluation model in the step 4; obtaining all possible states of the substation system based on a state enumeration method, and calculating performance indexes of the system in each state; and building an in-station transformer and circuit breaker maintenance strategy collaborative optimization model considering the system reliability constraint. According to the invention, a more reasonable reference basis is provided for system operation and maintenance personnel to carry out maintenance strategy decision-making of the transformer and the circuit breaker in the station.

Description

Technical Field

[0001] The present invention relates to the field of power equipment maintenance methods, and in particular to a transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints. Background Art

[0002] Substations are key hubs for power transmission and distribution, responsible for reliably delivering electricity from power plants to users. Transformers and circuit breakers are key in-station equipment to ensure power supply. They usually require huge investments, have long service lives, and are complex to manage. They are an important part of the infrastructure and operations management of power companies. As their service life continues to grow, a large number of in-station transformers and circuit breakers invested in the early stage have entered the aging period under the long-term effects of various factors, which not only affects the performance of the equipment itself, but also potentially threatens the reliability and safety of the entire substation.

[0003] Equipment maintenance of transformers and circuit breakers in stations is a common tool to ensure the operating efficiency and reliability of power assets and extend the service life of equipment. It is essential for power companies to achieve continuous power supply in a more economical and reliable manner. Unplanned power outages can lead to huge economic losses due to the impact of power outages and subsequent maintenance costs. Maintaining transformers and circuit breakers in stations before the probability of failure exceeds an acceptable level (due to normal aging or long-term exposure to adverse environmental conditions) can reduce the frequency and impact of such power outages.

[0004] For the problem of unplanned power outages, the traditional method is to proceed from the economic and reliability level of the equipment itself, ignoring the role of power equipment in the entire power grid and its impact on the reliability of the power grid, making it impossible to determine a maintenance plan that meets the system reliability requirements. In addition, the traditional method focuses on the predetermined maintenance action plan, which may not fully consider the actual degradation state of the equipment, and fails to take into account the impact of different maintenance strategies, making it impossible to determine a more cost-effective maintenance plan. In addition, the traditional method usually optimizes the maintenance strategy independently for two types of equipment, transformers or circuit breakers in the station, and fails to consider the decision-making dependence between the maintenance strategies of the two types of equipment, and does not make collaborative decisions on maintenance strategies, which cannot achieve full-perspective resource optimization. Summary of the invention

[0005] The present invention aims to provide a collaborative optimization method for transformer and circuit breaker maintenance strategies taking into account reliability constraints, so as to solve the problem that traditional methods cannot achieve full-view resource optimization when performing maintenance separately.

[0006] The collaborative optimization method of transformer and circuit breaker maintenance strategies considering reliability constraints in this scheme includes the following steps:

[0007] Step 1: Quantitative modeling of the impact of power outage maintenance measures commonly used for transformer and circuit breaker equipment, including quantitative models of aging state recovery after power outage maintenance of transformer and circuit breaker, aging failure rate of equipment after power outage maintenance, future aging failure rate after power outage maintenance, and random incidental random failure rate after power outage maintenance;

[0008] Step 2: quantitatively model the impact of periodic inspection measures commonly used for transformer and circuit breaker equipment;

[0009] Step 3: Based on the equipment three-state model, the equipment failure probability maintenance model is established after considering the two maintenance strategies of power outage maintenance and periodic inspection, providing data input for the reliability index evaluation model in step 4;

[0010] Step 4: Establish a substation reliability index evaluation model based on the state enumeration method. The probability of the equipment in the substation being in each state is calculated through the three-state model of the equipment established in step 3. Then, all possible operating states of the substation system are obtained by enumerating one by one, and the performance index of the system in each state is calculated. Finally, the reliability index of the substation system is obtained.

[0011] Step 5: Build a collaborative optimization model for in-station transformer and circuit breaker maintenance strategies that considers system reliability constraints.

[0012] Furthermore, the quantitative modeling in step 1 includes the following sub-steps:

[0013] Sub-step 1.1, based on the uniform distribution model, a quantitative model for the recovery of the aging state of transformers and circuit breakers after power outage maintenance is constructed, which is expressed as:

[0014]

[0015] Where, f(·) represents the probability distribution of each aging index of the equipment; t repair Indicates the equipment power outage maintenance time; x i Indicates the various post-maintenance acceptance indicators of the equipment; for transformer equipment, x i is the ratio of the aging characteristic gas in the transformer oil chromatographic monitoring data, which are C2H2 / C2H4, CH4 / H2 and C2H4 / C2H6 respectively, at this time i = 3; for circuit breaker equipment, x i is the score of the four sub-components of the circuit breaker body structure, operating mechanism, shunt capacitor and closing resistor, in this case i=4;

[0016] Sub-step 1.2, construct a time-varying aging failure rate model for equipment taking into account the impact of power outages and maintenance. The aging characteristic indicators of the equipment after power outages and maintenance are:

[0017]

[0018] The equipment aging failure process maintenance model is built through the two-parameter Weibull distribution, and the aging failure rate of power equipment after power outage maintenance is obtained as follows:

[0019]

[0020] Where β and η are the shape parameter and scale parameter in the Weibull distribution model, respectively, DI(t) is the covariate reflecting the aging degree of individual equipment; DI aver (t) is a covariate reflecting the average aging degree of the entire group of equipment of the same type;

[0021] Sub-step 1.3, using the historical data of the equipment to model the future aging failure rate of the equipment after power outage maintenance;

[0022] Sub-step 1.4, quantifying the random incidental failure rate of equipment due to power outage maintenance, includes: determining the reduction in the repairable random failure rate after maintenance based on historical statistical data and determining the duration of the reduced repairable random failure rate based on historical statistical data.

[0023] Furthermore, the quantitative modeling in step 2 includes:

[0024] Assuming that the sporadic random failure rate changes linearly with the inspection period, the impact of periodic inspection on the sporadic random failure rate can be expressed as:

[0025]

[0026] In the formula, T0 is the reference inspection cycle; and λ0 are the repairable random failure rates with / without the influence of power outage maintenance under the reference inspection cycle, and both are constant parameters obtained from engineering statistics; T new is the new inspection cycle; rm is the random failure rate of equipment under the new inspection cycle.

[0027] Furthermore, the equipment failure probability maintenance modeling in step 3 includes the following sub-steps:

[0028] Sub-step 3.1, the failure probability model of transformers and circuit breakers in the station considering the maintenance strategy includes repairable occasional random failures and irreparable aging failures, and the three-state model of the equipment includes the normal operation state of the equipment, the random failure state of the equipment and the irreparable failure state caused by aging;

[0029] Sub-step 3.2, power outage frequency and duration method, construct a given λ ag , rm , μ ag and μ rm Under four parameters, the steady-state probability equation of the device in three states is:

[0030]

[0031] Where P1 is the probability of normal operation, P2 is the probability of random failure, and P3 is the probability of aging failure;

[0032] Sub-step 3.3, solve the steady-state probability equation to obtain the steady-state probabilities of the three states, which are:

[0033]

[0034] Further, the step 4 specifically includes the following sub-steps:

[0035] Step 4.1, combining the three-state model of station transformer and circuit breaker, enumerate all possible states of the substation;

[0036] Step 4.2, λ based on equipment failure probability model ag and λ rm The two parameters and the solution of the steady-state probability equation determine the probability of the substation being in each state;

[0037] Step 4.3, by traversing each system state, calculate the load loss of the substation under different states, which is used to calculate the expected power shortage EENS;

[0038] Step 4.4, calculate the two main reliability indicators of the substation system load side, the expected power shortage EENS and the expected loss cost EDC, which are expressed as:

[0039]

[0040] Where P ik is the probability of state i occurring at load point k with load loss; N k is the total number of states where load loss at load point k occurs; LC ik is the load loss at load point k under state i, T is the load loss duration;

[0041] EDC k = b × EENS k ;

[0042] Where: EDC k is the expected loss cost of load point k, and b is the average power outage loss cost.

[0043] Furthermore, the collaborative optimization model building process in step 5 includes the following sub-steps:

[0044] Sub-step 5.1: The goal of the maintenance strategy collaborative optimization model is to minimize the total maintenance cost TC during the planning period. The objective function of the optimization model is:

[0045]

[0046] Where: EDC k is the cumulative expected loss cost of load point k during the planning period; C T is the total cost of the equipment maintenance strategy. N L is the total number of load points in the power station system;

[0047] Sub-step 5.2: the total cost C of the equipment maintenance strategy T Perform detailed calculations to calculate the total cost of equipment maintenance strategy C T Includes: Power outage maintenance cost C m , downtime load loss cost C loss and periodic inspection cost C I ;

[0048] Sub-step 5.3, total cost of maintenance strategy C T The calculation formula is:

[0049]

[0050] In the formula, α i is the number of power outages for maintenance of the i-th equipment during the planning period T; p0 is the probability of accidental load loss caused by power outage, which is given by expert experience; K is the number of periodic inspections. Obviously, given a set of [α1, α2, …, α Na ] T After obtaining the K parameters, the expected total maintenance cost of transformers and circuit breakers in the station can be calculated;

[0051] Sub-step 5.4: The constraints satisfied by the maintenance strategy collaborative optimization model include:

[0052] The periodic inspection frequency constraint is expressed as:

[0053]

[0054] Where Tp is the total duration of the planning period, in months; R max is the maximum acceptable inspection cycle;

[0055] The power outage maintenance constraint is that if a certain equipment has two or more power outage maintenance during the planning period, the maintenance time should be separated by a period D period , expressed as:

[0056] |diff(t i )|>D period ,if numel(t i )>1;

[0057] Maintenance resource constraints meet:

[0058]

[0059] In the formula, num repair An upper limit on the number of equipment outages that can be sustained by available maintenance resources in a year;

[0060] The mandatory power outage maintenance constraint is satisfied when the aging failure probability of the equipment reaches the maintenance standard:

[0061] t i ←t p ,if failure t p >failure rated ;

[0062] Where: failure t p is the aging failure probability of the i-th device in the tp-th month, calculated in step 4; rated It is the minimum allowable value for equipment aging that should be repaired;

[0063] The reliability constraint is the expected reliability index of each load point of the substation every year during the planning period, satisfying:

[0064] EENS k ≤EENS pre ;

[0065] In the formula: EENS pre is the acceptable reliability constraint value of each load point;

[0066] Sub-step 5.5, input substation system topology parameters, operation parameters, equipment reliability parameters, and load curve parameters; use the genetic algorithm intelligent optimization algorithm to complete the model solution.

[0067] Furthermore, in the sub-step 5.2, the calculation formulas for the total cost of the equipment maintenance strategy are:

[0068] The power outage maintenance cost of each month in the planning period is converted into a certain discount rate by the present value method. The discount rate is θ, and the power outage maintenance cost C is calculated. m for:

[0069]

[0070] In the formula, represents the power outage maintenance cost of the i-th equipment in the k-th month during the planning period; is the average maintenance cost, is the average aging failure rate;

[0071] pass Represents the outage load loss cost C of the i-th equipment loss ;

[0072] Cost of a single periodic inspection of equipment C I It includes three parts: equipment inspection cost ε, transportation cost of equipment inspection τ, transportation cost of inspection personnel from maintenance center to substation κ, and equipment single periodic inspection cost C I for:

[0073] C I =ε+τ+κ=(A1×N a )+(A2×d interval )+(A3×d trip );

[0074] Where A1 represents the cost of testing a single device; N a is the total number of devices in the specified area; A2 represents the transportation cost per kilometer required by the inspection personnel when moving between devices, which is related to the relative position of the devices; d interval It refers to the total distance between equipment in the area; A3 represents the transportation cost per kilometer required by the inspection team from the maintenance center to the substation; d trip is the distance from the maintenance center to the substation.

[0075] Furthermore, in the sub-step 5.4, if the system reliability requirement is not met, a load loss penalty cost PU will be generated, and the calculation formula is:

[0076]

[0077] Where: is the penalty cost factor.

[0078] The beneficial effects of this program are:

[0079] The mapping relationship between the influence of power outage maintenance and periodic inspection on the random failure rate and aging failure rate of two types of equipment, transformers and circuit breakers, was constructed; however, taking the month as the unit, the steady-state probability equation was constructed, and the failure probability calculation model of the equipment in the station was established by considering both the random failure and aging failure states. Then, the calculation method of the EENS reliability index of the substation based on the state enumeration method was proposed; finally, with the reliability expected power outage loss and the minimum maintenance cost as the objective function, the collaborative optimization model of the maintenance strategy of the transformer and circuit breaker in the station was proposed, and the solution process based on the genetic algorithm was given. The results of this method can provide a more reasonable reference for system operation and maintenance personnel to make decisions on the maintenance strategy of transformers and circuit breakers in the station. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1A flowchart of an embodiment of a transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints of the present invention;

[0081] Figure 2 A diagram showing the change in aging failure rate of equipment after power outage and maintenance in an embodiment of a transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints of the present invention;

[0082] Figure 3 A graph showing the change in the sporadic random failure rate of equipment after power outage and maintenance in an embodiment of the transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints of the present invention;

[0083] Figure 4 A flowchart of solving a collaborative optimization model of transformer and circuit breaker maintenance strategies in a station in an embodiment of a collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints of the present invention;

[0084] Figure 5 A structural diagram of a main connection system of a substation in an embodiment of a collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints of the present invention;

[0085] Figure 6 A transformer and circuit breaker outage maintenance decision plan diagram in an embodiment of a transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints of the present invention;

[0086] Figure 7 A comparison chart of the expected costs in each year within the planning period between the strategy proposed in the embodiment of the transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints of the present invention and the strategy of only executing periodic inspections;

[0087] Figure 8 A comparison chart of the expected costs in each year within the planning period of the strategy proposed in the embodiment of the transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints of the present invention and the strategy of only executing power outage maintenance;

[0088] Fig. 9 This is a three-state model diagram of equipment in an embodiment of the collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints of the present invention. DETAILED DESCRIPTION

[0089] The following is further explained in detail through specific implementation methods.

[0090] Example

[0091] The collaborative optimization method of transformer and circuit breaker maintenance strategy considering reliability constraints, such as Figure 1 As shown, the following steps are included:

[0092] Step 1: Quantitatively model the impact of power outage maintenance measures commonly used for transformer and circuit breaker equipment. The resulting model includes a quantitative model of the recovery of the aging state of transformers and circuit breakers after power outage maintenance, the aging failure rate of equipment after power outage maintenance, the future aging failure rate after power outage maintenance, and the random incidental random failure rate after power outage maintenance. Quantitative modeling includes the following sub-steps:

[0093] Sub-step 1.1: Since the acceptance indicators of transformers and circuit breakers in the station after power outage maintenance should meet the requirements of the grid guidelines, a quantitative model for the recovery of the aging state of transformers and circuit breakers after power outage maintenance is constructed based on the uniform distribution model, which is expressed as:

[0094]

[0095] In the formula, f(·) represents the probability distribution of each aging index of the equipment. Due to the uncertainty of maintenance and human factors, the aging characteristic indexes of the equipment after power outage and maintenance are uniformly distributed within the upper and lower limits; t repair Indicates the equipment power outage maintenance time; x i Indicates the various post-maintenance acceptance indicators of the equipment; for transformer equipment, x i is the ratio of the aging characteristic gases in the transformer oil chromatogram monitoring data. The aging characteristic gases are C2H2 / C2H4, CH4 / H2 and C2H4 / C2H6. The slash in the middle represents the content of the two gases divided by each other. At this time, i=3. For circuit breaker equipment, x i is the score of the four sub-components of the circuit breaker body structure, operating mechanism, shunt capacitor and closing resistor, and i = 4. After the power outage, the equipment status will get better, that is, x will get smaller, so the failure rate will be lower than before the non-power outage.

[0096] Sub-step 1.2, quantify the impact of power outage maintenance on equipment aging failure rate, and construct a time-varying aging failure rate model for equipment taking into account the impact of power outage maintenance. Since the reliability assessment result of the substation is the expected value, and it is known that the aging characteristic indicators of the equipment after the power outage maintenance follow a uniform distribution, in order to eliminate uncertainty, the aging characteristic indicators of the equipment after the power outage maintenance are:

[0097]

[0098] The equipment aging failure process maintenance model is built through the two-parameter Weibull distribution, and the aging failure rate of power equipment after power outage maintenance is obtained as follows:

[0099]

[0100] In the formula, x i That is x i (t repair), β and η are the shape parameter and scale parameter in the Weibull distribution model respectively. The shape parameter and scale parameter are estimated by the least square method based on the historical statistical equipment aging failure data. DI(t) is a covariate reflecting the aging degree of individual equipment; DI aver (t) is a covariate reflecting the average aging degree of the entire group of equipment of the same type. The aging failure rate of power equipment after power outage maintenance indicates that the greater the aging degree of individual equipment relative to the average aging degree of the same type of equipment group, the greater its aging failure rate.

[0101] Sub-step 1.3, such as Figure 2 As shown in the figure, for the transformer or circuit breaker equipment in the station after maintenance, the future time-varying aging failure rate in the planning period is calculated by assuming that the prediction result of the future aging state of the equipment after power outage maintenance should be consistent with the historical aging evolution of the equipment. Since the transformer oil chromatographic data or circuit breaker status data is monitored online, its degradation path is relatively complete, so the future aging failure rate of the equipment after power outage maintenance is modeled based on the historical data of the equipment.

[0102] Sub-step 1.4, quantify the random incidental failure rate of the equipment caused by power outage maintenance, including: determining the reduction of the repairable random failure rate after maintenance based on historical statistical data and determining the duration of the reduced repairable random failure rate based on historical statistical data. Since the random incidental failure rate has nothing to do with the operating time of the equipment, it is replaced by a constant. Therefore, the trend of the random incidental failure rate of the equipment in the future after the power outage maintenance is as follows: Figure 3 shown.

[0103] Step 2: quantitatively model the impact of periodic inspection measures commonly used for transformer and circuit breaker equipment, which specifically includes the following sub-steps:

[0104] In engineering, it is generally believed that the more frequent the inspection cycle, the lower the probability of occasional random failures, that is, the random failure rate is positively correlated with the inspection cycle. Assuming that the occasional random failure rate changes linearly with the inspection cycle, the impact of periodic inspection on the occasional random failure rate is expressed as:

[0105]

[0106] In the formula, T0 is the reference inspection cycle; and λ0 are the repairable random failure rates with / without the influence of power outage maintenance under the reference inspection cycle, and both are constant parameters obtained from engineering statistics; T new is the new inspection cycle; rm is the random failure rate of equipment under the new inspection cycle.

[0107] Step 3: Based on the equipment three-state model, the equipment failure probability maintenance model is constructed after considering the two maintenance strategies of power outage maintenance and periodic inspection, providing data input for the reliability index evaluation model in step 4. The equipment failure probability maintenance model includes the following sub-steps:

[0108] Sub-step 3.1, the failure probability model of transformers and circuit breakers in the station considering the maintenance strategy includes repairable occasional random failures and irreparable aging failures. When the power equipment encounters an occasional random failure, it can be restored to normal through corrective maintenance; and when the equipment fails due to aging, the normal operation of the system can also be achieved through equipment replacement. Fig. 9 As shown in FIG, the three-state model of the equipment includes the normal operation state of the equipment, the random failure state of the equipment, and the irreparable failure state caused by aging.

[0109] State 1 indicates the normal operation of the equipment; State 2 indicates the random failure of the equipment, which can be restored to state 1 through corrective maintenance; State 3 indicates the irreparable failure caused by aging, which can be restored to state 1 through equipment replacement. ag is the equipment aging failure rate, calculated in step 1; rm is the random incidental failure rate of the equipment, calculated in step 2; μ ag and μ rm It is the replacement rate and repair rate of equipment after aging and failure, which is usually a constant obtained from historical statistical data.

[0110] Sub-step 3.2, power outage frequency and duration method, construct a given λ ag , rm , μ ag and μ rm Under four parameters, the steady-state probability equation of the device in three states is:

[0111]

[0112] Where P1 is the probability of normal operation, P2 is the probability of random failure, and P3 is the probability of aging failure;

[0113] Sub-step 3.3, solve the steady-state probability equation to obtain the steady-state probabilities of the three states, which are:

[0114]

[0115] After determining the specific implementation time of the two strategies of power outage maintenance and periodic inspection of the equipment, the λ of the equipment every month during the planning period is calculated through steps 1 and 2. ag , rm , μ ag and μ rmThe four transfer rates are corrected to determine the probability steady-state constants of the equipment being in the three states within the month.

[0116] Step 4: Based on the state enumeration method, all possible states of the substation system are obtained, and the performance indicators of the system under each state are calculated to provide sufficiently accurate reliability evaluation results. Based on the method proposed in step 3, the power equipment failure probability model is established. When a set of certain maintenance strategies is given, the λ of the equipment failure probability model is ag and λ rm The two parameters are then determined. The calculation process is as follows:

[0117] Step 4.1, establish a substation reliability index evaluation model based on the state enumeration method, calculate the probability of the equipment in the substation being in each state through the three-state model of equipment established in step 3, and then enumerate all possible operating states of the substation system one by one, calculate the performance index of the system in each state, and finally obtain the reliability index of the substation system.

[0118] Take two devices A and B as an example. Each device may be in three states. The probabilities of normal operation, random failure, and aging failure are P1a, P2a, P3a; P1b, P2b, P3b. Then there are 9 combined states in total, and the probabilities are:

[0119] The probability that A operates normally and B operates normally: P1a*P1b;

[0120] The probability that A operates normally and B fails randomly is: P1a*P2b;

[0121] And so on….

[0122] Therefore, after step 4.3 determines the probability of each device being in the three states through sub-step 3.3, all possible states and their probabilities of occurrence can be calculated (that is, the work of step 4.3).

[0123] Step 4.2, λ based on equipment failure probability model ag and λ rm Based on the two parameters and the solution results of the steady-state probability equation, the busbar can adopt the traditional two-state model to calculate and determine the probability of the substation being in each state.

[0124] Step 4.3, by traversing each system state, calculate the load loss of the substation under different states, which is used to calculate the expected power shortage EENS.

[0125] Step 4.4, calculate the two main reliability indicators of the substation system load side, the expected power shortage EENS and the expected loss cost EDC, which are expressed as:

[0126]

[0127] Where P ik is the probability of state i occurring at load point k with load loss; N k is the total number of states where load loss at load point k occurs; LC ik is the load loss at load point k under state i, T is the load loss duration;

[0128] EDC k = b × EENS k ;

[0129] Where: EDC k is the expected loss cost of load point k, and b is the average power outage loss cost.

[0130] When the original data of the substation system, such as topology and load, are given, the reliability index of the system is only related to the system state probability. When the random failure of components is affected by power outages and periodic inspections, the aging of components becomes more serious over time or recovers after power outages, the system state probability will increase with the device λ. ag and λ rm The change in the state probability will change accordingly. At this time, it is only necessary to correct the state probability calculation to achieve accurate assessment of the substation system reliability.

[0131] Step 5: Build a collaborative optimization model for transformer and circuit breaker maintenance strategies within the station considering system reliability constraints. The collaborative optimization model building process includes the following sub-steps:

[0132] Sub-step 5.1: The goal of the maintenance strategy collaborative optimization model is to minimize the total maintenance cost TC during the planning period. The objective function of the optimization model is:

[0133]

[0134] Where: EDC k is the cumulative expected loss cost of load point k during the planning period; C T is the total cost of the equipment maintenance strategy. N L is the total number of load points in the power station system.

[0135] Sub-step 5.2: the total cost C of the equipment maintenance strategy T Perform detailed calculations to calculate the total cost of equipment maintenance strategy C T Includes: Power outage maintenance cost C m , downtime load loss cost C loss and periodic inspection cost C I The calculation formulas for the total cost of equipment maintenance strategy are:

[0136] The power outage maintenance cost of each month in the planning period is converted into a certain discount rate by the present value method. The discount rate is θ, and the power outage maintenance cost C is calculated. m for:

[0137]

[0138] In the formula, represents the power outage maintenance cost of the i-th equipment in the k-th month during the planning period; is the average maintenance cost, is the average aging failure rate;

[0139] pass Represents the outage load loss cost C of the i-th equipment loss ;

[0140] Cost of a single periodic inspection of equipment C I It includes three parts: equipment inspection cost ε, transportation cost of equipment inspection τ, transportation cost of inspection personnel from maintenance center to substation κ, and equipment single periodic inspection cost C I for:

[0141] C I =ε+τ+κ=(A1×N a )+(A2×d interval )+(A3×d trip );

[0142] Where A1 represents the cost of testing a single device; N a is the total number of devices in the specified area; A2 represents the transportation cost per kilometer required by the inspection personnel when moving between devices, which is related to the relative position of the devices; d interval It refers to the total distance between equipment in the area; A3 represents the transportation cost per kilometer required by the inspection team from the maintenance center to the substation; d trip is the distance from the maintenance center to the substation.

[0143] Sub-step 5.3, the total cost C of the equipment maintenance strategy T Perform detailed calculations to calculate the total cost of equipment maintenance strategy C T Includes: Power outage maintenance cost C m , downtime load loss cost C loss and periodic inspection cost C I , the calculation formula is:

[0144]

[0145] In the formula, α iis the number of power outages for maintenance of the i-th equipment during the planning period T; p0 is the probability of accidental load loss caused by power outage, which is given by expert experience; K is the number of periodic inspections. Obviously, given a set of [α1, α2, …, α Na ] T After determining the K parameters, the expected total maintenance cost of transformers and circuit breakers in the station can be calculated.

[0146] Since the maintenance time contains the information to determine the number of maintenance times, the decision variables [α1, α2, …, α Na ] T is [t1,t2,…,t Na ] T And parameter K. Among them, the power outage maintenance time t i The vector representing the months when the i-th equipment will be shut down for maintenance during the planning period.

[0147] Sub-step 5.4: The constraints satisfied by the maintenance strategy collaborative optimization model include:

[0148] The inspection cycle is a discrete value with equal time intervals (1 month), with a minimum of 1 (month). The periodic inspection frequency constraint is expressed as:

[0149]

[0150] Where Tp is the total duration of the planning period, in months; R max is the maximum acceptable inspection cycle;

[0151] There are requirements for the number of power outages for equipment maintenance during the planning period. It is generally believed that it is unnecessary to repeat power outages for maintenance for a period of time after the equipment is overhauled. The power outage maintenance constraint is that if a certain equipment has two or more power outages for maintenance during the planning period, the maintenance time should be separated by a period of time D period , expressed as:

[0152] |diff(t i )|>D period ,if numel(t i )>1;

[0153] Due to the limitations of maintenance personnel and available resources, the maintenance resource constraints satisfy:

[0154]

[0155] In the formula, num repair An upper limit on the number of equipment outages that can be sustained by available maintenance resources in a year;

[0156] The mandatory power outage maintenance constraint is satisfied when the aging failure probability of the equipment reaches the maintenance standard:

[0157] t i ←t p ,if failure t p >failure rated ;

[0158] Where: failure t p is the aging failure probability of the i-th device in the tp-th month, calculated in step 4; rated It is the minimum allowable value for equipment aging that should be repaired;

[0159] The reliability constraint is the expected reliability index of each load point of the substation every year during the planning period, satisfying:

[0160] EENS k ≤EENS pre ;

[0161] In the formula: EENS pre is the acceptable reliability constraint value of each load point.

[0162] If the system reliability requirements are not met, a load loss penalty cost PU will be generated, and the calculation formula is:

[0163]

[0164] Where: is the penalty cost factor.

[0165] Sub-step 5.5, input substation system topology parameters, operation parameters, equipment reliability parameters, and load curve parameters; use the genetic algorithm intelligent optimization algorithm to complete the model solution, as follows Figure 4 shown.

[0166] Taking the main wiring system of a power station actually implemented as an example, the specific structure is as follows Figure 5 As shown, the effectiveness of the method of this embodiment is explained. The high-voltage side of the main connection system of the substation adopts a half-circuit breaker connection, and the low-voltage side is a double bus connection. The substation includes two transformers T1 and T2, and 15 circuit breakers CB1-CB15. The six load points are distributed on two parallel buses, and the load values ​​are 20.57, 21.23, 99.44, 100.21, 37.07 and 35.53MW respectively.

[0167] Assuming the planning period is 3 years (i.e. 36 months), the maintenance plans of T1-T2 and CB1-CB15 in the station are collaboratively optimized within the planning period. The optimal equipment inspection cycle is 2 months, and the optimal equipment power outage maintenance plan is as follows: Figure 6 shown.

[0168] In order to verify the superiority of the proposed collaborative optimization method, the proposed method is compared with the maintenance strategy of only conducting inspections without any power outage maintenance and the maintenance strategy of only conducting power outage maintenance without performing inspections. The expected total costs of each year under different strategies are analyzed. Figure 7 and Figure 8 shown.

[0169] As can be seen from the figure, the proposed strategy effectively improves the reliability of the substation system during the planning period and effectively reduces the expected total cost value. In contrast, the strategy of only considering inspections without executing any power outage maintenance plan will result in the failure to meet the reliability of the substation system, resulting in a higher reliability penalty cost (the proposed method can reduce the load loss cost and total cost by 60.46% and 47.31% respectively). Considering only the regular maintenance strategy will result in high maintenance costs in the first two years of the planning period, and the load loss costs are still significantly higher than the proposed strategy.

[0170] The above is only an embodiment of the present invention, and the common knowledge such as the known specific structure and characteristics in the scheme is not described in detail here. It should be pointed out that for those skilled in the art, several deformations and improvements can be made without departing from the structure of the present invention, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints, characterized in that: The following steps are involved: Step 1: Quantitative modeling of the impact of power outage maintenance measures commonly used for transformer and circuit breaker equipment, including quantitative models of aging state recovery after power outage maintenance of transformer and circuit breaker, aging failure rate of equipment after power outage maintenance, future aging failure rate after power outage maintenance, and random incidental random failure rate after power outage maintenance; Step 2: quantitatively model the impact of periodic inspection measures commonly used for transformer and circuit breaker equipment; Step 3: Based on the equipment three-state model, the equipment failure probability maintenance model is established after considering the two maintenance strategies of power outage maintenance and periodic inspection, providing data input for the reliability index evaluation model in step 4; Step 4: Establish a substation reliability index evaluation model based on the state enumeration method. The probability of the equipment in the substation being in each state is calculated through the three-state model of the equipment established in step 3. Then, all possible operating states of the substation system are obtained by enumerating one by one, and the performance index of the system in each state is calculated. Finally, the reliability index of the substation system is obtained. Step 5: Build a collaborative optimization model for in-station transformer and circuit breaker maintenance strategies that considers system reliability constraints.

2. The collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints according to claim 1 is characterized in that: The quantitative modeling in step 1 includes the following sub-steps: Sub-step 1.1, based on the uniform distribution model, a quantitative model for the recovery of the aging state of transformers and circuit breakers after power outage maintenance is constructed, which is expressed as: Where, f(·) represents the probability distribution of each aging index of the equipment; t repair Indicates the equipment power outage maintenance time; x i Indicates the various post-maintenance acceptance indicators of the equipment; for transformer equipment, x i is the ratio of the aging characteristic gas in the transformer oil chromatographic monitoring data, which are C2H2 / C2H4, CH4 / H2 and C2H4 / C2H6 respectively, at this time i = 3; for circuit breaker equipment, x i is the score of the four sub-components of the circuit breaker body structure, operating mechanism, shunt capacitor and closing resistor, in this case i=4; Sub-step 1.2, construct a time-varying aging failure rate model for equipment taking into account the impact of power outages and maintenance. The aging characteristic indicators of the equipment after power outages and maintenance are: The equipment aging failure process maintenance model is built through the two-parameter Weibull distribution, and the aging failure rate of power equipment after power outage maintenance is obtained as follows: Where β and η are the shape parameter and scale parameter in the Weibull distribution model, respectively, DI(t) is the covariate reflecting the aging degree of individual equipment; DI aver (t) is a covariate reflecting the average aging degree of the entire group of equipment of the same type; Sub-step 1.3, using the historical data of the equipment to model the future aging failure rate of the equipment after power outage maintenance; Sub-step 1.4, quantifying the random incidental failure rate of equipment due to power outage maintenance, includes: determining the reduction in the repairable random failure rate after maintenance based on historical statistical data and determining the duration of the reduced repairable random failure rate based on historical statistical data.

3. The transformer and circuit breaker maintenance strategy collaborative optimization method considering reliability constraints according to claim 2 is characterized in that: The quantitative modeling in step 2 includes: Assuming that the sporadic random failure rate changes linearly with the inspection period, the impact of periodic inspection on the sporadic random failure rate can be expressed as: In the formula, T0 is the reference inspection cycle; and λ0 are the repairable random failure rates with / without the influence of power outage maintenance under the reference inspection cycle, and both are constant parameters obtained from engineering statistics; T new is the new inspection cycle; rm is the random failure rate of equipment under the new inspection cycle.

4. The collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints according to claim 3 is characterized in that: The equipment failure probability maintenance modeling in step 3 includes the following sub-steps: Sub-step 3.1, the failure probability model of transformers and circuit breakers in the station considering the maintenance strategy includes repairable occasional random failures and irreparable aging failures, and the three-state model of the equipment includes the normal operation state of the equipment, the random failure state of the equipment and the irreparable failure state caused by aging; Sub-step 3.2, power outage frequency and duration method, construct a given λ ag , rm , μ ag and μ rm Under four parameters, the steady-state probability equation of the device in three states is: Where P1 is the probability of normal operation, P2 is the probability of random failure, and P3 is the probability of aging failure; Sub-step 3.3, solve the steady-state probability equation to obtain the steady-state probabilities of the three states, which are:

5. The collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints according to claim 4 is characterized in that: The step 4 specifically includes the following sub-steps: Step 4.1, combining the three-state model of station transformer and circuit breaker, enumerate all possible states of the substation; Step 4.2, λ based on equipment failure probability model ag and λ rm The two parameters and the solution of the steady-state probability equation determine the probability of the substation being in each state; Step 4.3, by traversing each system state, calculate the load loss of the substation under different states, which is used to calculate the expected power shortage EENS; Step 4.4, calculate the two main reliability indicators of the substation system load side, the expected power shortage EENS and the expected loss cost EDC, which are expressed as: Where P ik is the probability of state i occurring at load point k with load loss; N k is the total number of states where load loss at load point k occurs; LC ik is the load loss at load point k under state i, T is the load loss duration; EDC k =b×EENS k ; Where: EDC k is the expected loss cost of load point k, and b is the average power outage loss cost.

6. The collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints according to claim 5 is characterized in that: The collaborative optimization model building process in step 5 includes the following sub-steps: Sub-step 5.1: The goal of the maintenance strategy collaborative optimization model is to minimize the total maintenance cost TC during the planning period. The objective function of the optimization model is: Where: EDC k is the cumulative expected loss cost of load point k during the planning period; C T is the total cost of the equipment maintenance strategy. N L is the total number of load points in the power station system; Sub-step 5.2: the total cost C of the equipment maintenance strategy T Perform detailed calculations to calculate the total cost of equipment maintenance strategy C T Includes: Power outage maintenance cost C m , downtime load loss cost C loss and periodic inspection cost C I ; Sub-step 5.3, total cost of maintenance strategy C T The calculation formula is: In the formula, α i is the number of power outages for maintenance of the i-th equipment during the planning period T; p0 is the probability of accidental load loss caused by power outage, which is given by expert experience; K is the number of periodic inspections. Obviously, given a set of [α1, α2, …, α Na ] T After obtaining the K parameters, the expected total maintenance cost of transformers and circuit breakers in the station can be calculated; Sub-step 5.4: The constraints satisfied by the maintenance strategy collaborative optimization model include: The periodic inspection frequency constraint is expressed as: Where Tp is the total duration of the planning period, in months; R max is the maximum acceptable inspection cycle; The power outage maintenance constraint is that if a certain equipment has two or more power outage maintenance during the planning period, the maintenance time should be separated by a period D period , expressed as: |diff(t i )|>D period ,if numel(t i )>1; Maintenance resource constraints meet: In the formula, num repair An upper limit on the number of equipment outages that can be sustained by available maintenance resources in a year; The mandatory power outage maintenance constraint is satisfied when the aging failure probability of the equipment reaches the maintenance standard: t i ←t p ,if failure t p >failure rated ; Where: failure t p is the aging failure probability of the i-th device in the tp-th month, calculated in step 4; rated It is the minimum allowable value for equipment aging that should be repaired; The reliability constraint is the expected reliability index of each load point of the substation every year during the planning period, satisfying: AT SOMETIME k ≤ONCE pre ; In the formula: EENS pre is the acceptable reliability constraint value of each load point; Sub-step 5.5, input substation system topology parameters, operation parameters, equipment reliability parameters, and load curve parameters; use the genetic algorithm intelligent optimization algorithm to complete the model solution.

7. The collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints according to claim 6 is characterized in that: In the sub-step 5.2, the calculation formulas for the total cost of the equipment maintenance strategy are: The power outage maintenance cost of each month in the planning period is converted into a certain discount rate by the present value method. The discount rate is θ, and the power outage maintenance cost C is calculated. m for: In the formula, represents the power outage maintenance cost of the i-th equipment in the k-th month during the planning period; is the average maintenance cost, is the average aging failure rate; pass Represents the outage load loss cost C of the i-th equipment loss ; Cost of a single periodic inspection of equipment C I It includes three parts: equipment inspection cost ε, transportation cost of equipment inspection τ, transportation cost of inspection personnel from maintenance center to substation κ, and equipment single periodic inspection cost C I for: C I =ε+τ+κ=(A1×N a )+(A2×d interval )+(A3×d trip ); Where A1 represents the cost of testing a single device; N a is the total number of devices in the specified area; A2 represents the transportation cost per kilometer required by the inspection personnel when moving between devices, which is related to the relative position of the devices; d interval It refers to the total distance between equipment in the area; A3 represents the transportation cost per kilometer required by the inspection team from the maintenance center to the substation; d trip is the distance from the maintenance center to the substation.

8. The collaborative optimization method for transformer and circuit breaker maintenance strategies considering reliability constraints according to claim 6 is characterized in that: In the sub-step 5.4, if the system reliability requirement is not met, a load loss penalty cost PU will be generated, and the calculation formula is: Where: is the penalty cost factor.

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