A power grid safety control device opportunity maintenance decision method based on multi-layer random optimization

Abstract

The present application relates to the technical field of power grid and electrical equipment operation and maintenance, and discloses a power grid safety control device opportunity maintenance decision method based on multi-layer random optimization. The method comprises the following steps: according to the state transition process after the safety control device is put into operation, the correlation between the internal hardware of the safety control device, between the safety control devices, and between the safety control device and the primary equipment is considered, the functional correlation, the economic correlation and the random correlation of the safety control device are planned from three levels, a nested compound objective function is first constructed, a multi-level safety control device opportunity maintenance decision model is established, and thus the best maintenance strategy of the safety control device is formulated, the maintenance efficiency of the safety control device can be improved, and the effective balance between the safety control device maintenance and the power system operation is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid and electrical equipment operation and maintenance, and particularly relates to a power grid safety control device opportunity maintenance decision method based on multi-layer random optimization. BACKGROUND

[0002] The power grid safety and stability control system is the second line of defense for ensuring the safety of the power grid. In order to ensure the safe operation of the large power grid, a large number of safety and stability control systems are generally constructed in support. With the increase of transmission distance and capacity, the development and construction of new energy and direct current transmission, and the increasing complexity of the power grid structure, the reliability requirements of the power grid for the safety and stability control system are becoming higher and higher. It is of great significance to master the potential risk faults of the safety and stability control system and develop effective and economic maintenance schemes for improving the reliability of the power grid operation.

[0003] The existing power system maintenance is mainly divided into three types of post-maintenance, periodic maintenance and condition-based maintenance. Post-maintenance is to carry out maintenance after the fault occurs, which is very passive and cannot prevent the occurrence of faults. Periodic maintenance is a planned maintenance with time intervals, but often causes the consequences of insufficient maintenance or excessive maintenance. Compared with the planned maintenance of post-maintenance and periodic maintenance, condition-based maintenance not only prolongs the service life of the device, but also significantly improves the reliability and economy of the system operation. The condition-based maintenance of the power system is increasingly valued, and some documents have proposed a relay protection condition-based maintenance model based on fault rate calculation. Some researchers have developed an annual maintenance decision method with the goal of maximizing the maintenance risk benefit of the power system. Some documents have proposed a transmission equipment maintenance method considering the total risk and fault risk of maintenance, and on this basis, some researchers have proposed a power grid condition-based maintenance decision method with the goal of minimizing the fault risk of power grid equipment and the total operation risk of power grid.

[0004] However, the existing condition-based maintenance methods above mainly focus on switches, transformers and other primary equipment or relay protection equipment, and few studies focus on the maintenance decision problem of the safety control system. The composition of the safety control system is essentially different from the primary equipment, so the condition-based maintenance method of the primary equipment cannot be applied to the safety control system. Although there is some similarity compared with the relay protection equipment, there are also great differences in the operation principle and configuration method, and the condition-based maintenance method of the relay protection equipment is also difficult to be directly applied to the safety control system. In addition, there are complex functional associations, economic associations and random associations under disturbance between the devices of the large safety control system, and the existing condition-based maintenance methods usually take a single independent device as the object, only focus on the individual performance of the device, and do not consider the association of the system devices and the influence on the system operation, but there is a contradiction between the system performance and the device performance, so the above condition-based maintenance method cannot solve the problem of condition-based maintenance of the safety control device.

[0005] Opportunity maintenance can solve the contradiction between equipment maintenance and system operation, and has become a hot spot of equipment maintenance research at home and abroad. Opportunity maintenance refers to the maintenance of other devices to be maintained at the same time when a device of the system fails or preventive maintenance is performed, so as to reasonably utilize the maintenance resources and improve the reliability and economy. At present, the research on opportunity maintenance mainly focuses on the combination of preventive maintenance of different devices. The existing research quantifies the individual loss of the device and the risk of system operation caused by the change of the device maintenance time, and establishes a device opportunity maintenance model taking the association set as the basic unit. The research establishes a device opportunity maintenance decision-making model for minimizing the system maintenance risk and failure risk, and realizes the compromise decision-making of the device state maintenance time at the system level. However, the existing research has not involved the opportunity maintenance decision-making problem of safety control devices. SUMMARY

[0006] In view of the above problems of the prior art, the application provides a power grid safety control device opportunity maintenance decision-making method based on multi-layer random optimization, which compromises the difference of safety control device maintenance time from the overall perspective of the safety control system, and reduces unnecessary maintenance cost and system outage loss.

[0007] To solve the above technical problems, the power grid safety control device opportunity maintenance decision-making method based on multi-layer random optimization adopts the following technical scheme:

[0008] Through the state transition process of the safety control device after being put into operation, the correlation between the internal hardware of the safety control device, between the safety control devices, and between the safety control device and the primary equipment is considered, the functional correlation, economic correlation and random correlation of the safety control device are planned from three levels, and the reliability and economy of the safety control device maintenance are considered, a multi-layer nested compound objective function is constructed, and then the power safety and stability control device opportunity maintenance decision-making method based on multi-layer random optimization is proposed.

[0009] The method comprises the following steps:

[0010] S1, a first maintenance decision-making objective function of the internal hardware of the safety control device considering the economic correlation is established by taking the simultaneous maintenance of the internal hardware in the deteriorated state as the decision-making objective;

[0011] S2, a second maintenance decision-making objective function of the safety control device considering the economic, functional and random correlation between the safety control devices is established by taking the simultaneous maintenance of the safety control devices with economic, functional and random correlation as the decision-making objective;

[0012] S3, a third maintenance decision-making objective function of the safety control device considering the economic and random correlation between the safety control device and the primary equipment is established by taking the simultaneous maintenance of the safety control device in the deteriorated state as the decision-making objective when the primary equipment fails;

[0013] S4, establishing a multi-layer composite nested opportunity maintenance target function according to the first maintenance decision target function, the second maintenance decision target function and the third maintenance decision target function;

[0014] S5, establishing an opportunity maintenance decision model of the safety control device according to the multi-layer composite nested opportunity maintenance target function and the corresponding constraint conditions;

[0015] S6, solving the opportunity maintenance decision model of the safety control device according to a preset optimization algorithm to determine an optimal maintenance scheme.

[0016] Compared with the prior art, the present application has the following beneficial effects:

[0017] 1. The prior art is suitable for the maintenance decision of primary equipment and relay protection devices of a power system, and cannot be applied to the safety control device of a power grid due to different compositions and principles. The present application provides a power grid safety control device opportunity maintenance decision method based on multi-layer random optimization, which fills the gap of the condition-based maintenance of the safety control device.

[0018] 2. The prior art does not consider the correlation between devices, and it is difficult to obtain an optimal maintenance scheme. The present application considers the different degrees of functional correlation between safety control devices and the different effects on the device maintenance time, and also considers the economic correlation, random correlation and other factors that affect the maintenance time between safety control devices, which can improve the maintenance benefit of the safety control device and is beneficial to improving the reliability, flexibility and economy of the operation of the safety control system.

[0019] 3. The prior art cannot balance the contradiction between device maintenance and system maintenance. The present application effectively quantifies the correlation between the maintenance strategy and the individual maintenance of the safety control device and the operation of the safety control system from the perspectives of fault risk and maintenance cost, and realizes the effective balance between the maintenance of the safety control device and the overall operation of the power system.

[0020] 4. The opportunity maintenance is applied to the maintenance of the safety control device, and the difference in the maintenance time of the safety control device is compromised from the overall perspective of the safety control system, which can formulate a safety control device maintenance scheme with the minimum maintenance cost and system outage loss. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to make the purpose, technical scheme and advantages of the application clearer, the application will be further described in detail below with reference to the drawings, in which:

[0022] Figure 1 is a flowchart of the safety control device opportunity maintenance decision method based on multi-layer random optimization of the present application. DETAILED DESCRIPTION

[0023] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those ordinarily skilled in the art without creative work fall within the scope of the present application.

[0024] As shown in the formula (1), the present application discloses a power grid safety control device opportunity maintenance decision method based on multi-layer random optimization, comprising the following steps: Figure 1

[0025] S1, taking the simultaneous maintenance of the internal hardware in the deterioration state as the decision target, a first maintenance decision objective function f1 of the internal hardware of the safety control device considering the economic correlation is established;

[0026] S2, taking the simultaneous maintenance of the safety control device with economic, functional and random correlation as the decision target, a second maintenance decision objective function f2 of the safety control device considering the economic, functional and random correlation between the safety control devices is established;

[0027] S3, when the maintenance of the primary equipment is performed, taking the simultaneous maintenance of the safety control device in the deterioration state as the decision target, a third maintenance decision objective function f3 of the safety control device considering the economic and random correlation between the safety control device and the primary equipment is established;

[0028] S4, according to the first maintenance decision objective function, the second maintenance decision objective function and the third maintenance decision objective function, a multi-layer composite nested opportunity maintenance objective function is established;

[0029] S5, according to the multi-layer composite nested opportunity maintenance objective function T and the corresponding constraint conditions, an opportunity maintenance decision model of the safety control device is established;

[0030] S6, according to a preset optimization algorithm, the opportunity maintenance decision model of the safety control device is solved, and the best maintenance scheme is determined.

[0031] In the specific implementation, the state transition matrix of the safety control device considering the maintenance strategy in the forward-looking time of the maintenance is:

[0032]

[0033] In the formula, P 1,2 represents the transition rate of the safety control device from state S1 to state λ2, P 2,3 ​This represents the transition rate of the security control device from state S2 to state S3. Where S1 indicates the security control device is in good condition; S2 indicates the security control device is in a slightly deteriorated state; S3 indicates the security control device is in a severely deteriorated state; S4 indicates the security control device is in a functional failure state; Sm1 indicates the security control device is in maintenance state m1; Sm2 indicates the security control device is in maintenance state m2. Here, m1 represents minor preventative maintenance, and m2 represents moderate preventative maintenance. λ1 represents the transition rate of the security control device from state S1 to state S4, λ2 represents the transition rate from state S2 to state S4, and λ3 represents the transition rate from state S3 to state S4.

[0034] When the security control device is in state S1, no maintenance is required; when the security control device is in state S2 or S3, maintenance can be performed. The maintenance levels of the two states are represented by m1 and m2, respectively, and both maintenance methods can restore the security control device to state S1. The transition rate from fault state S4 to state S1 of the safety control device; The transition rate from maintenance status Sm1 and Sm2 to status S1 of the safety control device.

[0035] As an example, safety control device A is selected as a substation of the 220kV regional stability control system, whose function is high-frequency switching and low-frequency disconnection. The corresponding primary equipment in the same area is D, E, and F. Safety control device B is the main device of the 500kV safety and stability control station and the backup automatic transfer auxiliary device C, whose function is regional stability control. The corresponding primary equipment in the same area protection is G and H. These are used as examples for calculation.

[0036] Table 1 shows the state probabilities of each security control device in the future time in the example:

[0037] Table 1 Hardware Status of Security Control Devices

[0038]

[0039] In Table 1, A1, A2, A3, A4, A5, and A6 represent the hardware of security control device A, B1 and B2 represent the hardware of security control device B, and C1 and C2 represent the hardware of automatic transfer switch (ATS) device C. For example, the probability of hardware A1 of security control device A being in state S1 is 0.90, the probability of being in state S2 is 0.10, the probability of being in state S3 is 0, and the probability of being in state S4 is 0.

[0040] As shown in Table 1, the state probabilities of security control device hardware A2, A5, and B1 are basically distributed in states S2 and S3, which require preventive maintenance, while the state probabilities of other security control device hardware are almost all distributed in state S1, which does not require preventive maintenance. Therefore, the security control device hardware that requires preventive maintenance are A2, A5, and B1.

[0041] Substituting the future state probabilities of the security control device into the state transition matrix of the security control device, the state transition rates of the security control device are obtained as shown in Table 2:

[0042] Table 2 State transition data of security control device hardware

[0043]

[0044] Table 2 shows the transition values ​​between different states of the hardware A2, A5, and B1 of the security control device to be inspected.

[0045] In specific implementation, in step S1, the maintenance cost functions for the internal hardware A2, A5, and B1 of the security control device are calculated using the following formula, expressed as:

[0046] f1 = c M,1 -ΔC W1

[0047] In the formula, c M,1 ΔC represents the total cost of repairing the hardware of the security control device in a deteriorated state. W1 Cost savings for security control devices that are in a deteriorated state, due to simultaneous maintenance.

[0048] The total cost of repairing the hardware of the security control device in a deteriorated state is calculated using the following formula:

[0049]

[0050] In the formula, N T The number of time periods divided for the forward-looking period; N α b is the number of security control devices to be inspected within the foreseeable timeframe; α (t) represents whether the hardware α to be repaired starts repair within time period t. α (t) = 1 indicates that hardware α has started maintenance, otherwise b α (t) = 0; p α,S2 (t), p α,S3 (t) represents the probability that hardware α is in state S2 or S3 during time period t; The cost required to repair hardware α, specifically m1 and m2.

[0051] The cost savings due to simultaneous maintenance of the security control device hardware are calculated using the following formula:

[0052]

[0053] In the formula, C D (α,β) represents the increased maintenance cost due to simultaneous maintenance of hardware α and β. When the value is negative, it indicates the reduced maintenance cost due to simultaneous maintenance of hardware. respectively, are the probabilities of hardware α, β being in the maintenance outage state Sm1 at time period t; respectively, are the probabilities of hardware α, β being in the maintenance outage state Sm2 at time period t.

[0054] According to the above cost calculation, it can be concluded that c M,1 = 398.2 / ten thousand yuan, ΔC W1 = 124.3 / ten thousand yuan; therefore, the internal hardware maintenance cost of the safety control device is:

[0055] f1= c M,1 - ΔC W1 = 398.2-124.3 = 273.9 / ten thousand yuan

[0056] In the specific implementation, in step S2, the safety control device maintenance decision objective function considering the economic, functional and organizational association of the safety control device is calculated as:

[0057] Maxf2= Max(f 2.1 +f 2.2 -f 2.3 )

[0058] In the formula, f 2.1 is the maintenance objective function considering the organizational association of the safety control device, f 2.2 is the maintenance objective function considering the functional association of the safety control device, and f 2.3 is the maintenance objective function considering the economic association of the safety control device.

[0059] The maintenance objective considering the organizational association of the safety control device is:

[0060]

[0061] In the formula, N M is the number of safety control devices to be maintained, b i (t) = 1 indicates that the safety control device i to be maintained starts maintenance at time period t, and otherwise b i (t) = 0; p i,S2 (t) and p i,S3 (t) are the probabilities of the safety control device i being in the states S2 and S3 at time period t; η lost is the system operation risk that can be avoided by the safety control device maintenance, which can be calculated by the following formula:

[0062] η lost = k1·P im +k2·P lost +k3·P cust

[0063] In the formula, P im is the importance index of the safety control device; P lostP is an indicator of the potential loss level of the security control device. cust The number of users affected by security control devices; k8, k9, k 10 P respectively im P lost P cust The weighting coefficients. Specifically, weighting coefficients k8 and k9 are set to 0.3, and weighting coefficient k... 10 The value is set to 0.4.

[0064] In practical implementation, the importance index P of each stability control device can be evaluated using the fuzzy comprehensive evaluation method. im The potential loss index P of the device lost Impact on user numbers (P) cust In this example, the device importance index P im The statistics are shown in Table 3:

[0065] Table 3. Importance Index of the Device (P) im

[0066]

[0067] The potential loss index P of the device lost The calculations are shown in Table 4:

[0068] Table 4. Potential Loss Index P of the Equipment lost

[0069]

[0070] Impact on user count metric P cust The calculations are shown in Table 5:

[0071] Table 5. Indicators affecting the number of users (P) cust

[0072] Impact on the number of users and importance Importance P cust ]]> Significant fluctuation of network voltage or frequency Very important 10 Collapse of local network voltage or frequency Very important 9 Significant fluctuation of local network voltage or frequency Very important 8 Partial or complete loss of voltage at 500 kV substation Very important 8 Partial or complete loss of voltage at 220 kV substation More important 7.5 Partial or complete loss of voltage at 110 kV substation More important 7 Loss of load accounting for 80% or more of total load at substation More important 7 Loss of load accounting for 50% to 80% of total load at substation Generally important 6.5 Loss of load accounting for 49% or less of total load at substation Generally important 6

[0073] The degree of failure loss η after a failure is calculated based on the statistical risk indicators of various stability control devices. lost It is used to describe the impact of a device malfunctioning or failing to operate on the power grid, the device, and users.

[0074] From the table above, we can see that P in this example im =9.6, P lost =8.7, P cust =7.5, therefore, the degree of damage caused by the failure of this device is:

[0075] η lost =k8·P im +k9·P lost +k 10 ·Pcust = 8.49

[0076] According to the obtained fault loss degree η after the device failure lost , the total risk of maintenance avoidance considering the association of the safety control device with the shutdown is calculated as:

[0077]

[0078] In the implementation, the maintenance objective function considering the association of the safety control device function is:

[0079]

[0080] In the formula, v is the maintenance benefit of the safety control device, v max is the maximum value of the maintenance benefit of the safety control device.

[0081] The maintenance benefit of the safety control device can be determined by the ratio of the risk difference before and after the maintenance of the safety control device and the total risk of the safety control system operation:

[0082]

[0083] In the formula, R is the total risk of the safety control system operation, ΔR F is the risk difference before and after the maintenance of the safety control device, which is calculated by the following formula:

[0084]

[0085] R i,t = R 1i,t + R 2i,t = ΔT i,l P i · c F + C i,l ΔT i,l

[0086] In the formula, N g is the total number of associated safety control devices of the maintenance decision; f i,t and f′ i,t are the failure probabilities of the safety control device i before and after the maintenance at the t period; R i,t is the failure risk of the safety control device i at the t period, including the loss of load S 1i,t caused by the device failure and the maintenance loss S 2i,t caused by the device failure, wherein the maintenance loss caused by the failure of the safety control device is determined by the failure severity of the safety control device, and the failure severity can be described by the failure maintenance level l of the safety control device; ΔT i,l is the maintenance time of the device i adopting the failure maintenance level l; P i is the load loss caused by the failure of the safety control device i; c F is the unit load loss cost caused by the failure of the safety control device i, and Ci,l The maintenance cost of the safety control device i.

[0087] The operation risk of the safety control device includes planned load loss and unplanned load loss, which is calculated by the following formula:

[0088]

[0089] In the formula, s(t) is the set of devices that need to be maintained in period t. The probability that the safety control device i is in state S2 or S3 in period t.

[0090] In the implementation, in step S2, the maintenance objective function considering the economic correlation of the safety control device is:

[0091] f 2.3 = c M,2 - ΔC W2

[0092] In the formula, c M,2 is the total maintenance cost of the safety control device in the deterioration state, and ΔC W2 is the cost saved by simultaneous maintenance of the safety control device.

[0093] Selecting the maintenance safety control device {A, B, C}, the total maintenance cost of the safety control device in the deterioration state is calculated by the following formula:

[0094]

[0095] In the formula: is the maintenance cost of the safety control device i in the maintenance state m1, m2.

[0096] The cost saved due to simultaneous maintenance of the safety control devices is calculated by the following formula:

[0097]

[0098] In the formula, C D (i, j) is the maintenance cost increased by the simultaneous maintenance of the safety control devices i, j, and when the value is negative, it represents the maintenance cost reduced by the simultaneous maintenance of the safety control devices; are respectively the probabilities that the safety control devices i, j are in the maintenance shutdown state Sm1 in period t; are respectively the probabilities that the safety control devices i, j are in the maintenance shutdown state Sm2 in period t.

[0099] According to the above cost calculation, c M,2 = 808.6 / 10,000 yuan, and ΔC W2 = 95.8 / 10,000 yuan, so the cost of the economic correlation maintenance of the safety control device is:

[0100] f2.3 =c M,2 -ΔC W2 =808.6-95.8=712.8 / 10,000 yuan

[0101] In specific implementation, in step S3, the objective function for the maintenance decision of the security control device, considering the economic and stochastic correlation between the security control device and the primary equipment, is as follows:

[0102] Maxf3=f 3.1 -f 3.2

[0103] In the formula, f 3.1 To consider the objective function of the random association between the security control device and the primary equipment, f 3.2 The objective function is to consider the random association between the security control device and the primary equipment.

[0104] The objective function considering the random association between security control devices and primary equipment is:

[0105] f 3.1 =f 2.1 -ΔR W3

[0106] In the formula, ΔR W3 The risk that a safety control device can avoid when primary equipment and safety control devices in the same area are under maintenance simultaneously can be calculated using the following formula:

[0107]

[0108] In the formula, N W This represents the number of primary equipment items awaiting maintenance within the forward timeframe. Let Sm1 be the probability that security control device i and primary equipment k in the same area are in a maintenance shutdown state during time period t. Let r be the probability that security control device i and primary equipment k in the same area are in a maintenance shutdown state Sm2 during time period t. D (i,k) represents the reduced operational risk resulting from the simultaneous maintenance of safety control device i and primary equipment k, which can be calculated using the following formula:

[0109] r D (i,k)=(θ+δ)(W1+W2+γW3)

[0110] In the formula, θ is the probability of load shedding caused by normal operation of the safety control device; δ is the probability of load shedding caused by malfunction of the safety control device; γ is the power safety accident liability cost adjustment factor, which is determined according to the accident level range and affordability; W1 is the conventional economic loss cost; W2 is the power safety accident liability cost; and W3 is the administrative penalty cost.

[0111] The cost of conventional economic losses is:

[0112] W1=f(X=pΔPt

[0113] In the formula, ΔP is the load shedding amount of the safety control device; t is the power outage time when the safety control system cuts off the load; and p is the unit power outage cost loss.

[0114] The consequences of liability for power safety accidents are:

[0115]

[0116] In the formula, λ is the load loss ratio, that is, the ratio of the lost load to the total load.

[0117] The cost of administrative penalties is:

[0118]

[0119] In the formula: P is the total load within the assessment area.

[0120] In specific implementation, in step S3, the objective function considering the economic relationship between the security control device and the primary equipment is:

[0121] f 3.2 =c M,3 -ΔC W3

[0122] In the formula, c M,3 ΔC represents the total cost of overhauling safety control devices and primary equipment in a deteriorated state. W3 Cost savings from simultaneous maintenance of safety control devices and primary equipment.

[0123] The set of primary equipment selected for maintenance is {D,H}. The total maintenance cost for safety control devices and primary equipment in a deteriorated state is calculated using the following formula:

[0124]

[0125] In the formula, p i,S2 (t), p i,S3 (t) represents the probability that security control device i is in state S2 or S3 during time period t; The cost required to repair hardware α separately for m1 and m2; C k,m The maintenance cost for primary equipment k under maintenance conditions m1 or m2; p k,sm (t)=p k,sm1 (t)+p k,sm2 (t), p k,sm (t) represents the probability that security control device i and primary equipment k in the same area are in maintenance and shutdown state Sm during time period t; here Sm can correspond to two states, namely Sm1 and Sm2 respectively.

[0126] The cost saved by the simultaneous maintenance of the safety control device and the primary equipment is calculated by the following formula:

[0127]

[0128] According to the cost calculation, c M,3 = 370.3 / (ten thousand yuan), and ΔC W3 = 88.2 / (ten thousand yuan), so the maintenance cost considering the economic correlation between the safety control device and the primary equipment is:

[0129] f 3.2 = c M,3 - ΔC W3 = 370.3-88.2 = 282.1 / (ten thousand yuan)

[0130] In the implementation, in step S4, the multi-layer composite opportunity maintenance target function of the safety control device is:

[0131] T = Maxf3[Maxf2(Minf1), y]

[0132] In the formula, y is the primary equipment to be maintained.

[0133] In the embodiment of the present application, the multi-layer composite opportunity maintenance target function contains three-layer nested decisions, the first layer is the internal maintenance decision of the safety control device, the first maintenance decision target function is minimized to select the hardware in the deterioration state for simultaneous maintenance to reduce the maintenance times and the maintenance cost; the second layer is the associated maintenance decision of the safety control device, on the basis of the first layer, the second maintenance decision target function is maximized to select the safety control device with functional, economic and random association for simultaneous maintenance; the third layer is the associated maintenance decision of the safety control device and the primary equipment, on the basis of the second layer, when the primary equipment y with fault is maintained, the third maintenance decision target function is maximized to select the safety control device in the deterioration state for maintenance, through the layer-by-layer selection, the correlation between the individual maintenance of the safety control device and the operation of the safety control system is quantified from the multiple angles of the internal maintenance of the safety control device, the inter-safety control device and the external safety control device, and the difference of the maintenance time of the safety control device is compromised, so that the safety control device maintenance scheme with the minimum maintenance cost and system outage loss is formulated, and the power grid operation reliability can be effectively improved.

[0134] The constraint conditions of the safety control device opportunity maintenance decision model include:

[0135] (1) Hardware maintenance time constraint of the safety control device:

[0136]

[0137] In the formula, b i , e i , si , d i are the earliest time, the latest time, the starting time of maintenance, the period of condition-based maintenance of the i-th safety control device, respectively, i (t) represents the state of the i-th safety control device at time period t, i (t) = 1 means maintenance at time period t, i (t) = 0 means no maintenance at time period t, i (t) = {0, 1} means that maintenance or no maintenance is possible at time period t.

[0138] (2) Safety control device maintenance resource constraints:

[0139]

[0140] In the formula, m i represents the resources required for maintenance of the i-th safety control device; S t represents the upper limit of maintenance resources at time period t.

[0141] (3) The power grid safety constraint is:

[0142] P l ≤ P lmax

[0143] In the formula, P l is the actual transmission power of line l; P lmax is the maximum power allowed to be transmitted by line l.

[0144] (4) Loss of load limit constraint:

[0145] 0 ≤ P d ≤ P c

[0146] In the formula, P d , P c are the node load and the maximum allowed loss of load, respectively.

[0147] Therefore, based on the multi-layer composite nested opportunity maintenance objective function and the corresponding constraints described above, the safety control device opportunity maintenance decision model can be represented as follows:

[0148] T = Maxf3[Maxf2(Minf1), y]

[0149]

[0150]

[0151] C3: P l ≤ P lmax

[0152] C4: 0≤P d ≤P c

[0153] The safety control device opportunity maintenance decision model considers the relevance between internal hardware of the safety control device, between the safety control devices, and between the safety control device and primary equipment through the state transition process after the safety control device is put into operation, plans the functional relevance, economic relevance and random relevance of the safety control device from three levels, and can take into account the reliability and economy of the safety control device maintenance, can improve the maintenance efficiency of the safety control device, and is conducive to improving the reliability, flexibility and economy of the operation of the safety control system.

[0154] The preset optimization algorithm adopted in the embodiment can be a genetic algorithm, which is a common optimization algorithm. In fact, solving the safety control device opportunity maintenance decision model is to solve the multi-layer composite nested opportunity maintenance objective function according to the optimization algorithm and the constraint condition, and determine the best maintenance scheme.

[0155] In the solving process, the state transition rate of the safety control device is solved according to the state transition equation of the safety control device hardware after being put into operation; the solved state transition rate of the safety control device hardware is substituted into the internal hardware maintenance objective function f1 of the safety control device to solve; then the most suitable maintenance safety control device hardware set and maintenance time solved by the objective function f1 are substituted into the maintenance objective function f2 between the safety control devices; the most suitable maintenance safety control device set and the primary equipment set to be maintained solved by the objective function f2 are substituted into the maintenance objective function f3 between the safety control device and the primary equipment; finally, the most suitable maintenance safety control device and primary equipment set and maintenance time solved by the objective function f3 based on the constraint condition are determined, and the best maintenance decision, that is, the best maintenance scheme is determined.

[0156] The solving result of the objective function f3 by the genetic algorithm is: the maintenance safety control device is selected as {A, B, C}, the maintenance hardware set is {A2, A5, A6, B1, C1}, and the maintenance primary equipment set is {D, H}.

[0157] The corresponding simulation calculation data is shown in Table 6.

[0158] Table 6 Simulation calculation data

[0159]

[0160] In the specific implementation, in step S5, the best strategy selected by the genetic algorithm for maintenance is in the period of [20 25], and the allowed maintenance interval of the safety control device is consistent.

[0161] Table 7 gives the allowed maintenance time table of the safety control devices A, B and C.

[0162] Table 7 Allowed maintenance interval of safety control device

[0163]

[0164] The optimal maintenance strategy obtained by the target function is used to test whether the constraints of the safety control device maintenance decision are met:

[0165] (1) Safety control device maintenance time constraint:

[0166]

[0167] After testing x i (20-25) = 1, so the device state is available for maintenance.

[0168] (2) Safety control device maintenance resource constraint:

[0169]

[0170] After testing x i (20-25) m i ≤ S 20～25 , so the maintenance resource of this period meets the maintenance demand.

[0171] (3) Power grid safety constraint:

[0172] P l ≤ P l max

[0173] After testing P l ≤ P l max , so the devices in the maintenance device set meet the power grid safety constraint.

[0174] (4) Loss of load limit constraint:

[0175] 0 ≤ P d ≤ P c

[0176] After testing P l ≤ P l max , so the devices in the maintenance device set meet the power grid safety constraint.

[0177] In summary, the period [20 25] and the optimal maintenance device set obtained by the multi-layer composite nested opportunity maintenance target function meet all the constraints, so it is determined as the optimal maintenance scheme.

[0178] It can be seen that the application considers that the influence effect of the maintenance time of the device is different due to the different functional correlation degrees between the safety control devices, and there are also factors such as economic correlation, association with the safety control device, which affect the maintenance time, so that the maintenance time of the device state maintenance needs to be compromised and decided. The correlation and coordination degree between the individual maintenance of the safety control device and the operation of the safety control system is effectively quantified from the two aspects of failure and maintenance, and the effective balance between the maintenance of the safety control device and the overall operation of the power system is realized. The individual maintenance decision of the safety control device is refined to the specific maintenance decision of the internal hardware of the safety control device, and then extended to the global maintenance decision level of the safety control device and the primary equipment, which is beneficial to improve the reliability, flexibility and economy of the operation of the safety control system. The application of opportunity maintenance to the maintenance of the safety control device can improve the maintenance benefit of the safety control device, but opportunity maintenance is a complex optimization decision problem, and the opportunity maintenance decision of the safety control device still needs to be further improved and developed.

[0179] In the description of the application, it should be understood that the orientation or positional relationship indicated by the terms "coaxial", "bottom", "one end", "top", "middle", "the other end", "upper", "one side", "top", "inner", "outer", "front", "central", "both ends" and the like is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the application and simplifying the description, and does not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the application.

[0180] In the application, unless otherwise explicitly specified and limited, the terms "mounting", "setting", "connection", "fixing", "rotation" and the like should be understood broadly, for example, it can be fixed connection, or detachable connection, or integrated; it can be mechanical connection, or electrical connection; it can be direct connection, or indirect connection through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements, unless otherwise explicitly limited, the above-mentioned terms in the application can be understood according to the specific meaning in the specific situation by those skilled in the art.

[0181] Although the embodiments of the application have been shown and described, those skilled in the art can understand that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the application, and the scope of the application is defined by the appended claims and their equivalents.

Claims

1. A method for grid security control device condition-based maintenance decision based on multi-layer stochastic optimization, characterized in that, Comprise the following steps: S1, with the decision goal of selecting the internal hardware in the deterioration state for simultaneous maintenance, a first maintenance decision objective function of the internal hardware of the safety control device considering economic association is established; The first maintenance decision objective function is: Maxf1 = Max(c M,1 - ΔC W1 ) wherein c M,1 is the total cost of the hardware maintenance of the safety control device in the deteriorated state, ΔC W1 is the cost saved by the hardware maintenance of the safety control device in the deteriorated state due to simultaneous maintenance; The total maintenance cost of the safety control device hardware in the deterioration state is calculated by the following formula: In the formula, N T is the number of time periods for the look-ahead time; N α is the number of hardware devices of the safety control device to be maintained in the look-ahead time; b α (t) is whether the hardware α to be maintained starts to be maintained in the time period t, b α (t)=1 indicates that the hardware α starts to be maintained, otherwise b α (t)=0; p α,S2 (t), p α,S3 (t) is the probability of the hardware α being in the state S2, S3 in the time period t; is the required cost of the hardware α to be maintained m1, m2, respectively; The cost saved due to the simultaneous maintenance of the safety control device hardware is calculated by the following formula: In the formula, C D (α, β) is the increased maintenance cost of hardware α and β simultaneous maintenance, and is negative when the maintenance cost of hardware α and β simultaneous maintenance is reduced; respectively, are the probabilities of hardware α and β being in the maintenance outage state Sm1 at time period t; respectively, are the probabilities of hardware α and β being in the maintenance outage state Sm2 at time period t; S2, with the decision goal of selecting the safety control device with economic, functional and random association for simultaneous maintenance, a second maintenance decision objective function of the safety control device considering the economic, functional and random association between the safety control devices is established; The second maintenance decision objective function is: Maxf2 = Max(f 2.1 +f 2.2 -f 2.3 ) In the formula, f 2.1 As the maintenance target function considering the association of safety control devices with the system, f 2.2 As the maintenance target function considering the association of safety control device functions, f 2.3 As the maintenance target function considering the association of safety control device economy The maintenance objective function considering the random association of the safety control device is: wherein: N T is the number of time intervals for the look-ahead time; N M is the number of safety control devices to be maintained, b i (t) = 1 indicates that the safety control device i to be maintained starts maintenance in the time interval t, otherwise b i (t) = 0; p i,S2 (t), p i,S3 (t) is the probability that the safety control device i is in state S2, S3 in the time interval t; η lost To avoid the system operation risk for the maintenance of the safety control device; The maintenance objective function considering the functional association of the safety control device is: where v is the maintenance benefit of the safety control device, R is the total risk of the safety control system operation, ΔR F is the risk difference before and after the maintenance of the safety control device; v max is the maximum value of the maintenance benefit of the safety control device The maintenance objective function considering the economic association of the safety control device is: f 2.3 = c M,2 - AC W2 wherein c M,2 is the total cost of the maintenance of the security control device in the deteriorated state, ΔC W2 is the cost saved by the simultaneous maintenance of the security control device; The total maintenance cost of the safety control device in the deterioration state is calculated by the following formula: In the formula: is the maintenance cost of the maintenance state m1, m2 for the security control device i; The cost saved due to the simultaneous maintenance between the safety control devices is calculated by the following formula: In the formula, C D (i,j) is the maintenance cost increased when safety control devices i and j are simultaneously maintained, and is negative when the maintenance cost is reduced; respectively are the probabilities that safety control devices i and j are in maintenance outage state Sm1 at time period t; respectively are the probabilities that safety control devices i and j are in maintenance outage state Sm2 at time period t; S3, when the primary equipment fails, with the decision goal of selecting the safety control device in the deterioration state for simultaneous maintenance, a third maintenance decision objective function of the safety control device considering the economic and random association between the safety control device and the primary equipment is established; The third maintenance decision objective function is: Maxf3 = f 3.1 -f 3.2 In the formula, f 3.1 is the target function of the safety control device and the primary equipment associated with the target function 3.2 is the target function of the safety control device and the primary equipment associated with the target function The objective function considering the random association between the safety control device and the primary equipment is: f 3.1 = f 2.1 - ΔR W3 where ΔR W3 is the risk that the safety control device can avoid when the primary equipment and the safety control device are simultaneously maintained in the same area, and can be calculated by the following formula: wherein N W is the number of primary equipment to be repaired in the look-ahead time, is the probability that the safety control device i and the primary equipment k in the same area are in the repair outage state Sm1 at the time period t, respectively, is the probability that the safety control device i and the primary equipment k in the same area are in the repair outage state Sm2 at the time period t, respectively, r D is the reduced operation risk of the safety control device i and the primary equipment k when they are repaired simultaneously; The objective function considering the economic association between the safety control device and the primary equipment is: f 3.2 = c M,3 - AC W3 In the formula, c M,3 Total cost of maintenance of the safety control device and primary equipment in the deteriorated state, ΔC W3 Cost saved by simultaneous maintenance of the safety control device and primary equipment The total maintenance cost of the safety control device and the primary equipment in the deterioration state is calculated by the following formula: where p i,S2 (t) is the probability that the control device i is in state S2, S3 during the time period t; i,S3 (t) is the probability that the control device i is in state S2, S3 during the time period t; Cm1, m2 are the costs for the repair of hardware a in repair states m1, m2, respectively; C k,m1 , C k,m2 are the repair costs for the repair of the unit k in repair state m1 or m2, respectively; The cost saved due to the simultaneous maintenance of the safety control device and the primary equipment is calculated by the following formula: wherein C D (i, k) is the increased maintenance cost of the maintenance of the device k and the control device i simultaneously, and is negative when the maintenance cost of the simultaneous maintenance of the device is reduced. S4, according to the first maintenance decision objective function, the second maintenance decision objective function and the third maintenance decision objective function, a multi-layer composite nested opportunity maintenance objective function is established; The multi-layer composite nested opportunity maintenance objective function of the safety control device is: T=Maxf3[Maxf2(Minf1),y] In the formula, y is the primary equipment to be maintained, Minf1 represents the first maintenance decision objective function, Maxf2 represents the second maintenance decision objective function, and Maxf3 represents the third maintenance decision objective function; S5, according to the multi-layer composite nested opportunity maintenance objective function and the corresponding constraint conditions, an opportunity maintenance decision model of the safety control device is established; S6, according to a preset optimization algorithm, the opportunity maintenance decision model of the safety control device is solved, and the best maintenance scheme is determined.

2. The power grid security control device opportunity maintenance decision method based on multi-layer random optimization according to claim 1, characterized in that, In step S4, the constraint conditions of the opportunity maintenance decision model of the safety control device include: (1) Safety control device hardware maintenance time constraint: wherein b i , e i , s i , d i are the earliest time at which the i-th safety control device can be serviced, the latest time at which the i-th safety control device can be serviced, the time at which servicing of the i-th safety control device is initiated, the period of time during which the i-th safety control device is serviced, respectively, x i (t) represents the state of the i-th safety control device at time period t, x i (t) = 1 indicates that servicing occurs at time period t, x i (t) = 0 indicates that no servicing occurs at time period t, x i (t) = {0, 1} indicates that servicing can or can not occur at time period t. (2) Safety control device maintenance resource constraint: In the formula, m i S represents the resource required for maintenance of the ith safety control device; t S represents the upper limit of the maintenance resource for the t period. (3) Power grid safety constraint: P l ≤P lmax where P l is the actual transmitted power of line l; P lmax is the maximum power allowed to be transmitted by line l; (4) Loss of load constraint: 0 < P d ≤ P c In the formula, P d , P c are the node load and the maximum allowed load loss, respectively.

3. The method of claim 1, wherein, In step S6, the solving method of the opportunity maintenance model of the safety control device is: Solving the state transition rate of the safety control device according to the state transition equation of the internal hardware of the safety control device after the safety control device is put into operation; substituting the solved state transition rate of the hardware of the safety control device into the first maintenance decision objective function to solve; then substituting the first maintenance safety control device hardware set and the maintenance time solved by the first maintenance decision objective function into the second maintenance decision objective function to solve; then substituting the second maintenance safety control device set and the primary equipment set to be maintained solved by the second maintenance decision objective function into the third maintenance decision objective function to solve; finally, judging the third maintenance safety control device and the primary equipment set and the maintenance time solved by the third maintenance decision objective function based on the constraint condition to determine the best maintenance decision.

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