Power transmission line anti-icing scheme optimization method, device, equipment, medium and product

Abstract

The application discloses a power transmission line anti-icing scheme optimization method, device, equipment, medium and product, relates to the electric power transportation field, and the method comprises the following steps: calculating the failure rate of each ice period of the line according to design standards, operating states, the environment and historical fault data; calculating the failure rate distribution function of the overhead power transmission line in multiple ice periods by using the Nelson-Aalen estimation method according to the failure rate of each ice period of the line; calculating the local power loss load value according to local power data; calculating the residual risk cost of the line adopting the anti-icing scheme according to the power loss load value and the failure rate; taking the sum of the residual risk cost of the line adopting the anti-icing scheme and the line risk control cost as an objective function, taking the reliability and economy of the anti-icing scheme implementation as constraint conditions, optimizing the anti-icing scheme, and obtaining the optimal anti-icing scheme. The application can reduce the power system investment cost under the premise of guaranteeing the safe operation of the power system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of electric power transmission, and in particular to a power transmission line anti-icing scheme optimization method, device, equipment, medium and product. BACKGROUND

[0002] Overhead transmission lines are important equipment for long-distance and high-power power transmission of power systems, and their failure will cause large-scale power outages. Due to the frequent occurrence of extreme disaster weather, the freezing rain zone is moving northward, and the icing and dancing phenomenon of overhead transmission lines is increasing, leading to an increase in tower collapse and line breakage accidents and regional power outages, causing great economic losses. Power grid enterprises pay more attention to anti-icing and disaster management work, taking into account the reliability of power grid operation and the cost control needs of power enterprises, and need to consider risk management and input costs to develop overhead transmission line anti-icing and disaster reduction strategies. Therefore, an anti-icing scheme optimization method that takes into account anti-icing reliability and cost reduction is needed. SUMMARY

[0003] The purpose of the present application is to provide a power transmission line anti-icing scheme optimization method, device, equipment, medium and product, which can reduce the input cost of the power system under the premise of ensuring the safe operation of the power system.

[0004] To achieve the above-mentioned purpose, the present application provides the following solutions:

[0005] In a first aspect, the present application provides a power transmission line anti-icing scheme optimization method, comprising:

[0006] obtaining the design standard, operating state, environment, historical failure data, implementation cost of various anti-icing schemes and local power data of an overhead transmission line;

[0007] calculating the failure rate of the line in each ice period according to the design standard, operating state, environment and historical failure data;

[0008] calculating the failure rate distribution function of the overhead transmission line in multiple ice periods using the Nelson-Aalen estimation method according to the failure rate of the line in each ice period;

[0009] calculating the value of power loss of load in the local area according to the local power data;

[0010] calculating the residual risk cost of the line using the anti-icing scheme according to the value of power loss of load and the failure rate;

[0011] The objective function is to minimize the sum of the residual risk cost and the risk control cost of the line using the anti-icing scheme. The anti-icing scheme is optimized under the constraints of reliability and economy of implementation to obtain the optimal anti-icing scheme. The line risk control cost is calculated based on the implementation costs of various anti-icing schemes.

[0012] Optionally, the step of calculating the failure rate of the line during each ice period based on the design standards, the operating status, the environment, and the historical fault data specifically includes:

[0013] The combined ice and wind load is calculated based on the line diameter of the design standard, the icing density of the environment, the average wind speed of the environment, and the operating status.

[0014] The failure rate of the line during each ice period is calculated based on the combined ice and wind load, the operating status, and the historical fault data.

[0015] Optionally, the calculation formula for the combined ice and wind load is as follows:

[0016]

[0017] in, For the combined ice and wind load, l I (T0) represents the ice load on the line in year T0. W (T0) represents the wind load on the line in year T0, g is the acceleration due to gravity, and ρ i d(T0) represents the icing density, d(T0) represents the icing thickness of the line in year T0, D is the line diameter, k is the wind pressure coefficient, v is the average wind speed, a is the wind speed non-uniformity coefficient, C is the wind shape coefficient, and n is the nth icing period in a year.

[0018] Optionally, the step of calculating the fault rate distribution function of the overhead transmission line in multiple glacial periods using the Nelson-Aalen estimation method based on the fault rate in each glacial period specifically includes:

[0019] The cumulative failure rate of the line over multiple ice periods is obtained by summing up the failure rates during each ice period.

[0020] The Nelson-Aalen estimation method is used to calculate the fault rate distribution function of overhead transmission lines during multiple glacial periods based on the cumulative fault rate of the lines.

[0021] Optionally, the formula for calculating the residual risk cost of the line using the anti-icing scheme based on the power loss value and the failure rate is as follows:

[0022] RI(T0+T)=V L(T0+T)×P(T0+T)×t out ×F N (T0+T)

[0023] Where T0 is the year the anti-icing plan is implemented, T is the Tth year after the implementation of the anti-icing plan, RI(T0+T) is the remaining risk cost in the Tth year after the implementation of the anti-icing plan, and V L (T0+T) represents the energy loss value in year T after the implementation of the anti-icing plan, P(T0+T) represents the average load of overhead transmission lines during the ice period in year T after the implementation of the anti-icing plan, and t out F represents the average fault repair time. N (T0+T) is the failure rate distribution function during N ice periods in year T after the implementation of the anti-icing plan.

[0024] Optionally, the objective function is to minimize the sum of the residual risk cost and the risk control cost of the line using the anti-icing scheme. The optimization of the anti-icing scheme is then performed under constraints of reliability and economy, yielding the following formula for the optimal anti-icing scheme:

[0025]

[0026] Among them, TC-RCRR i (T0+T) represents the sum of the line risk control cost and the line residual risk cost of anti-icing scheme i; RI i (T0+T) represents the residual risk cost of the line using anti-icing scheme i; C i (T0+T) represents the implementation cost of using anti-icing solution i, RI th For reliability constraints; C th For economic constraints, I represents the set of all anti-icing schemes, T0 represents the year in which the anti-icing scheme is implemented, and T represents the Tth year after the implementation of the anti-icing scheme. The sum of the remaining risk costs from the year of implementation of anti-icing scheme i to the year T is given, where t is a variable in the summation formula.

[0027] Secondly, this application provides an optimization device for transmission line anti-icing schemes, comprising:

[0028] The acquisition module is used to acquire the design standards, operating status, environment, historical fault data, implementation costs of various anti-icing schemes, and local power data of overhead transmission lines.

[0029] The failure rate calculation module is used to calculate the failure rate of the line during each ice period based on the design standards, the operating status, the environment, and the historical failure data.

[0030] The fault rate distribution function calculation module is used to calculate the fault rate distribution function of overhead transmission lines in multiple ice periods based on the fault rate of the line in each ice period using the Nelson-Aalen estimation method;

[0031] The power loss load value calculation module is used to calculate the local power loss load value based on the local power data.

[0032] The residual risk cost calculation module for lines employing anti-icing schemes is used to calculate the residual risk cost of lines employing anti-icing schemes based on the power loss value and the failure rate.

[0033] The optimization module is used to minimize the sum of the residual risk cost and the line risk control cost of the line using the anti-icing scheme as the objective function, and to optimize the anti-icing scheme under the constraints of the reliability and economy of the anti-icing scheme implementation, so as to obtain the optimal anti-icing scheme; the line risk control cost is calculated based on the implementation costs of multiple anti-icing schemes.

[0034] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the transmission line anti-icing scheme optimization method described in any one of the above-mentioned methods.

[0035] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the transmission line anti-icing scheme optimization method described in any one of the above-mentioned methods.

[0036] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the transmission line anti-icing scheme optimization method described in any one of the above-mentioned methods.

[0037] According to the specific embodiments provided in this application, this application has the following technical effects:

[0038] This application provides a method, device, equipment, medium, and product for optimizing anti-icing schemes for transmission lines. By calculating the fault rate of the line during each ice period, the fault distribution function of the line during multiple ice periods, and the value of power loss, and utilizing the time evolution effect of the line's current state and its environment for time correction, it solves the problems of not considering implementation costs and the impact of time evolution on persistence factors. The objective function is to minimize the sum of the residual risk cost and the risk control cost of the line using the anti-icing scheme. With the reliability and economy of the anti-icing scheme as constraints, the anti-icing scheme is optimized to obtain the optimal anti-icing scheme that balances the reliability and economy of the power system, thereby reducing the investment cost of the power system while ensuring its safe operation. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating an optimization method for an anti-icing scheme of a transmission line in one embodiment of this application;

[0041] Figure 2 This is a flowchart illustrating the calculation of line icing risk cost in one embodiment of this application;

[0042] Figure 3 This is a detailed block diagram of the transmission line anti-icing scheme optimization method in one embodiment of this application;

[0043] Figure 4 This is a performance comparison chart of the transmission line anti-icing scheme optimization method (strategy 1), Weibull curve method (strategy 2), and line condition assessment method (strategy 3) in one embodiment of this application;

[0044] Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0045] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0046] In recent years, most research on transmission line anti-icing strategies has focused on technical aspects, without considering the costs of implementing these strategies, the residual risks after implementation, or optimizing the strategies for specific line operating conditions. Therefore, this application provides a method for optimizing transmission line anti-icing schemes, which is urgently needed by power grid companies. This method aims to maximize the economic efficiency of investment while ensuring power supply reliability during ice periods, enabling power grid companies to better cope with increasingly fierce market competition.

[0047] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0048] In the embodiments of this application, such asFigure 1 As shown, an optimization method for anti-icing schemes of transmission lines is provided, the method including:

[0049] Step 1: Obtain the design standards, operating status, environment, historical fault data, implementation costs of various anti-icing schemes, and local power data of the overhead transmission line.

[0050] Step 2: Calculate the failure rate of the line during each ice period based on the design standards, operating status, environment, and historical fault data.

[0051] Step 3: Calculate the fault rate distribution function of the overhead transmission line in multiple ice periods using the Nelson-Aalen estimation method based on the fault rate of the line in each ice period.

[0052] Step 4: Calculate the local power loss value based on the local power data.

[0053] Step 5: Calculate the remaining risk cost of the line using the anti-icing scheme based on the power loss value and the failure rate.

[0054] Step 6: Using the minimum sum of the residual risk cost and the line risk control cost of the anti-icing scheme as the objective function, and with the reliability and economy of the anti-icing scheme as constraints, optimize the anti-icing scheme to obtain the optimal anti-icing scheme; the line risk control cost is calculated based on the implementation costs of various anti-icing schemes.

[0055] By implementing steps 1 to 6 above, the fault rate of the line during each ice period, the fault distribution function of the line during multiple ice periods, and the value of power loss are calculated. Time correction is performed using the time evolution effect of the line's current application status and its environment. This solves the problem of not considering implementation costs and the impact of time evolution on persistence factors. The objective function is to minimize the sum of the line's residual risk cost and line risk control cost using the anti-icing scheme. The anti-icing scheme is optimized under the constraints of reliability and economy, resulting in the optimal anti-icing scheme that balances the reliability and economy of the power system, thereby reducing the power system's investment costs while ensuring the safe operation of the power system.

[0056] In another exemplary embodiment of this application, the step of calculating the failure rate of the line during each ice period based on the design standards, the operating status, the environment, and the historical fault data specifically includes:

[0057] The combined ice and wind load is calculated based on the line diameter according to the design standard, the icing density of the environment, the average wind speed of the environment, and the operating status; the failure rate of the line during each ice period is calculated based on the combined ice and wind load, the operating status, and the historical fault data.

[0058] The specific formula for calculating the combined ice and wind load is as follows:

[0059]

[0060] in, For the combined ice and wind load, l I (T0) represents the ice load on the line in year T0. W (T0) represents the wind load on the line in year T0, g is the acceleration due to gravity, and ρ i d(T0) represents the icing density, d(T0) represents the icing thickness of the line in year T0, D is the line diameter, k is the wind pressure coefficient, v is the average wind speed, a is the wind speed non-uniformity coefficient, C is the wind shape coefficient, and n is the nth icing period in a year.

[0061] In another exemplary embodiment of this application, the step of calculating the fault rate distribution function of the overhead transmission line in multiple glacial periods using the Nelson-Aalen estimation method based on the fault rate of the line in each glacial period specifically includes:

[0062] The cumulative failure rate of the line over multiple ice periods is obtained by summing up the failure rates during each ice period.

[0063] The Nelson-Aalen estimation method is used to calculate the fault rate distribution function of overhead transmission lines during multiple glacial periods based on the cumulative fault rate of the lines.

[0064] In another exemplary embodiment of this application, the formula for calculating the residual risk cost of the line using the anti-icing scheme based on the power loss value and the failure rate is specifically as follows:

[0065] RI(T0+T)=V L (T0+T)×P(T0+T)×t out ×F N (T0+T)

[0066] Where T0 is the year the anti-icing plan is implemented, T is the Tth year after the implementation of the anti-icing plan, RI(T0+T) is the remaining risk cost in the Tth year after the implementation of the anti-icing plan, and V L (T0+T) represents the energy loss value in year T after the implementation of the anti-icing plan, P(T0+T) represents the average load of overhead transmission lines during the ice period in year T after the implementation of the anti-icing plan, and t out F represents the average fault repair time.N (T0+T) is the failure rate distribution function during N ice periods in year T after the implementation of the anti-icing plan.

[0067] In another exemplary embodiment of this application, steps 2-3 specifically include:

[0068] The fault rate of the overhead transmission line during each ice period was calculated based on factors such as design standards, operating status, environment, and historical fault data. The Nelson-Aalen estimation method was then used to estimate the fault rate distribution function F of the overhead transmission line across multiple ice periods. N .

[0069] The Nelson-Aalen estimation method was used to estimate the fault rate distribution function F of overhead transmission lines during multiple glacial periods in year T0. N (T0), specifically including:

[0070] The failure rate of transmission lines during ice periods is mapped to the mortality rate in the Nelson-Aalen estimation method, and the failure rate distribution function F during ice periods is calculated based on the line failure rate during N ice periods in year T0. N (T0), the calculation formula is as follows:

[0071] F N (T0)=1-e -ΛN(T0)

[0072] Where N represents the number of ice ages that occurred in a year, Λ N (T0) represents the cumulative failure rate of the line during the Nth ice period in year T0, and its calculation method is as follows:

[0073]

[0074] Where λ n (T0) represents the line failure rate during the nth ice period in year T0, and its calculation method is as follows:

[0075]

[0076] Where λ0 is the failure rate of overhead transmission lines under normal weather conditions; l C n (T0) represents the combined ice and wind load borne by the overhead transmission line during the nth ice period in year T0; L min (T0) represents the effective value of the design load on the overhead transmission line in year T0; L max (T0) represents the ultimate load threshold that the overhead transmission line can withstand in year T0, i.e., the operating state of the overhead line. Among these, the combined ice and wind load l C n The formula for calculating (T0) is:

[0077]

[0078] In the formula, l I (T0) represents the ice load on the line in year T0. W (T0) represents the wind load on the line in year T0, g is the acceleration due to gravity, and ρ i d(T0) represents the icing density, d(T0) represents the icing thickness of the line in year T0, D is the line diameter, k is the wind pressure coefficient, v is the average wind speed, a is the wind speed non-uniformity coefficient, C is the wind shape coefficient, and n is the nth icing period in a year.

[0079] In another exemplary embodiment of this application, steps 4-5 specifically include: calculating the local power load loss value based on the economic data and power consumption data of the region to which the overhead transmission line belongs in year T0 using the production function method, and using the power load loss value V of the overhead transmission line... L (T0), load P(T0) during the ice age in year T0, mean time to repair (t) out and the line failure rate distribution function F in year T0 N (T0) Calculate the line icing risk cost RI(T0), that is:

[0080] RI(T0)=V L (T0)×P(T0)×t out ×F N (T0).

[0081] The cost of line icing risk after the implementation of the anti-icing scheme is defined as the residual risk cost of the line. Considering the periodicity of the implementation of the anti-icing scheme, the residual risk cost of the line after T years of implementation is calculated using the following formula:

[0082] RI(T0+T)=V L (T0+T)×P(T0+T)×t out ×F N (T0+T).

[0083] In the formula for calculating the remaining risk cost of the line after T years of implementing the anti-icing scheme, the failure rate distribution function F after T years is... N (T0+T) is the ice thickness d(T0+T) after T years and the effective value L of the design load of the overhead transmission line after T years. min (T0+T), the ultimate load threshold L of overhead transmission lines after T years. max (T0+T) is used to determine d(T0+T) and L. min (T0+T), L max The formula for calculating (T0+T) is:

[0084]

[0085] Where d(T0) is the icing thickness of the line in the year the scheme is implemented, and the annual increase in icing thickness Δd(t) satisfies the following conditions: mean μ and variance σ. 2 The normal distribution; ΔL min (t), ΔL max (t) represents the degradation of the transmission line's load-bearing limit threshold and load-bearing limit threshold in year t after the implementation of the scheme.

[0086] In another exemplary embodiment of this application, the objective function is to minimize the sum of the residual risk cost and the risk control cost of the line using the anti-icing scheme. The optimization of the anti-icing scheme is then performed under constraints of reliability and economy, yielding the following formula for the optimal anti-icing scheme:

[0087]

[0088] Among them, TC-RCRR i (T0+T) represents the sum of the line risk control cost and the line residual risk cost of anti-icing scheme i; RI i (T0+T) represents the residual risk cost of the line using anti-icing scheme i; C i (T0+T) represents the implementation cost of using anti-icing solution i, RI th For reliability constraints; C th For economic constraints, I represents the set of all anti-icing schemes, T0 represents the year in which the anti-icing scheme is implemented, and T represents the Tth year after the implementation of the anti-icing scheme. The sum of the remaining risk costs from the year of implementation of anti-icing scheme i to the year T is given, where t is a variable in the summation formula.

[0089] In practical applications, the implementation cost of an anti-icing scheme is defined as the line risk control cost. The sum of the line risk control cost and the line residual risk cost in year T of the anti-icing scheme implementation is defined as TC-RCRR (Total Cost of Risk Control and Residual Risk). The optimization objective of the line anti-icing strategy is to minimize TC-RCRR, and the reliability and economy of the scheme implementation are used as constraints to optimize the anti-icing strategy for overhead transmission lines. The formula for calculating TC-RCRR is as follows:

[0090]

[0091] Among them, TC-RCRR i (T0+T) represents the sum of the line risk control cost and the line residual risk cost of anti-icing scheme i; RI i (T0+T) represents the residual risk cost of the line using anti-icing scheme i; Ci (T0+T) represents the implementation cost of using anti-icing scheme i.

[0092] The formula for calculating the line risk control cost of implementing the anti-icing plan in year T is as follows:

[0093]

[0094] Among them, C i (t) represents the implementation cost of the anti-icing plan i in year t; r represents the social discount rate.

[0095] This application provides several embodiments that simultaneously reduce the anti-icing investment costs for power grid companies while ensuring the safe operation of the power system. It utilizes the Nelson-Aalen estimation method and the value of load shedding to calculate the outage risk cost of overhead transmission lines during icing periods. Time corrections are made based on the time evolution effects of the line's condition and its environment. The optimization objective is to minimize the TC-RCRR value of each anti-icing scheme, while constraints are power grid operational reliability and the economic viability of anti-icing investment. This optimizes the anti-icing strategy for overhead transmission lines. On the one hand, it solves the problem that past anti-icing strategies did not calculate implementation costs and residual risk costs; on the other hand, it considers the impact of time evolution on persistence factors. The proposed method balances power system reliability and economy compared to existing anti-icing strategies, improving the market competitiveness of power grid companies.

[0096] In another exemplary embodiment of this application, a more specific optimization method is provided, which specifically includes the following steps:

[0097] The combined ice and wind load borne by overhead transmission lines during the nth ice period in year T0 Effective value L of the design load of the overhead transmission line in year T0 min (T0); The ultimate load threshold L of an overhead transmission line in year T0. max (T0) Calculate the failure rate λ(n) of the line during each ice period, using the following formula:

[0098]

[0099] in, The calculation method is to use the line ice load during the nth glacial period in year T0. Wind load on the line during the nth glacial period in year T0 The calculation is as follows:

[0100]

[0101] In the formula, l I (T0) represents the ice load on the line in year T0. W(T0) represents the wind load on the line in year T0, g is the acceleration due to gravity, and ρ i d(T0) represents the icing density, d(T0) represents the icing thickness of the line in year T0, D is the line diameter, k is the wind pressure coefficient, v is the average wind speed, a is the wind speed non-uniformity coefficient, C is the wind shape coefficient, and n is the nth icing period in a year.

[0102] Based on historical data, the formula is as follows to estimate the increased severity of ice storms and the decreased load-bearing capacity of power lines in year T:

[0103]

[0104] Calculate the combined ice and wind load using data on increased icing thickness in the next T years and data on decreased line load-bearing capacity. The specific formula is as follows:

[0105]

[0106] Calculate the failure rate of the nth ice period after T years using the combined ice and wind load of overhead transmission lines during the nth ice period in the future year T:

[0107]

[0108] The failure rate distribution function F of overhead transmission lines in the next T years during multiple glacial periods was calculated using the Nelson-Aalen estimation method. N (T0+T), the specific formula is:

[0109]

[0110] Among them Λ N (T0) represents the cumulative failure rate of the line during the nth round of ice season N in year T0. Its calculation method is as follows:

[0111]

[0112] Where λ n (T0+T) represents the line failure rate during the nth ice period in the next T years.

[0113] The formula for calculating the energy loss value of the area covered by the overhead transmission line using macroeconomic methods is as follows:

[0114]

[0115] Where V L The unload value of the observed region; GVA (Gross Value Added) is the total added value of the observed region, which is equivalent to the region's GDP; ELC is the electricity consumption of the observed region.

[0116] like Figure 2 As shown, based on the energy loss value V of overhead transmission lines... L Load P during the ice period, and repair time t after failure. out and the line failure rate distribution function F N The specific formula for calculating the risk cost RI of line icing is as follows:

[0117] RI(T0+T)=V L (T0+T)×P(T0+T)×t out ×F N (T0+T).

[0118] Considering the time value of money, calculate the risk control cost C of the overhead transmission line anti-icing scheme implemented for year T. i (T0+T), the calculation formula is as follows:

[0119]

[0120] Where r is the social discount rate.

[0121] The implementation cost (i.e., risk control cost) of anti-icing scheme i is added to the residual risk cost to obtain the total cost of risk control and residual risk (TC-RCRR). The optimization objective of the line anti-icing strategy is to minimize TC-RCRR, and the reliability and economy of scheme implementation are used as constraints to optimize the anti-icing strategy for overhead transmission lines. The calculation formula and constraints for TC-RCRR are as follows:

[0122]

[0123] Among them, RI th For reliability constraints; C th This is an economic constraint.

[0124] In another exemplary embodiment of this application, such as Figure 3 As shown in Table 1, this paper analyzes data from railway lines in Henan Province that experienced severe icing during multiple ice periods from December 2023 to February 2024. The basic data for these lines are as follows:

[0125] Table 1 Basic Data of the Line

[0126]

[0127] Taking Line 2 as an example, the line failure rate and residual risk cost during the ice season are calculated. The icing data and meteorological data of Line 2 during the four ice seasons are shown in Table 2:

[0128] Table 22: Icing and Meteorological Data for Line 22

[0129]

[0130] The failure rate during multiple glacial periods is calculated using the theory of metal deformation. The specific formula is as follows:

[0131]

[0132] The value of gravitational acceleration is 9.8 × 10⁻⁶. -3 mm / s 2 Ice density ρ i The value is 0.9 g / cm³. 3 The wind pressure coefficient is taken as 0.613, and the wind speed non-uniformity coefficient 'a' and wind load shape coefficient 'C' are determined as follows:

[0133]

[0134] Based on historical data, estimate the ice thickness d(T0+T) in the next T years and the effective value L of the design load on the overhead transmission line after T years. min (T0+T), the ultimate load threshold L of overhead transmission lines after T years. max (T0+T), the specific calculation formula is as follows:

[0135]

[0136] Where, the mean of Δd(t) is μ = 2%d(T0), σ 2 =0.02; ΔL min (t), L max (t) takes values ​​L respectively min (T0), L max 1% of (T0).

[0137] The fault rate distribution function F of overhead transmission lines during multiple glacial periods was calculated using the Nelson-Aalen estimation method. N The specific formula is as follows:

[0138]

[0139] The formula for calculating the remaining risk cost of the line after T years of implementing the anti-icing plan is as follows:

[0140] RI(T0+T)=V L (T0+T)×P(T0+T)×t out ×F N (T0+T).

[0141] The value of power loss is determined by the GDP and electricity consumption of Henan Province, and is 15.697 yuan / kWh; the average fault repair time is obtained from historical data statistics and is 36 hours.

[0142] The cost of implementing various anti-icing schemes for line risk control in year T is calculated using the following formula:

[0143]

[0144] The anti-icing solutions are divided into three types: reconstruction, renovation, and maintenance. The implementation costs of the three solutions are shown in Table 3.

[0145] Table 3. Cost of Anti-icing Solutions for Each Voltage Level

[0146]

[0147] The implementation cost (i.e., risk control cost) of anti-icing scheme i is added to the residual risk cost to obtain the total cost of risk control and residual risk (TC-RCRR). The optimization objective of the line anti-icing strategy is to minimize TC-RCRR, and the reliability and economy of scheme implementation are used as constraints to optimize the anti-icing strategy for overhead transmission lines. The calculation formula and constraints for TC-RCRR are as follows:

[0148]

[0149] To demonstrate the superior performance of this application, the performance of the transmission line anti-icing scheme optimization method (strategy 1) is compared with that of the Weibull curve method (strategy 2) and the line condition assessment method (strategy 3). The results are as follows: Figure 4 As shown.

[0150] Strategy 2 determines the anti-icing strategy based on the correlation between the service life of the overhead transmission line and the Weibull curve. Maintenance is implemented during the stable period of the Weibull curve; retrofitting is implemented during the first 50% of the period of loss failure on the Weibull curve; and reconstruction is implemented during the last 50% of the period of loss failure on the Weibull curve. Strategy 3 determines the anti-icing strategy based on the line's health index. Maintenance is implemented when the line's health index is in the range [80, 100); retrofitting is implemented when the line's health index is in the range [50, 80); and reconstruction is implemented when the health index is below 50.

[0151] Figure 4In this paper, the sum of residual risk cost and implementation cost is the TC-RCRR value under the corresponding strategy. Under Strategy 1, the implementation cost of the anti-icing scheme for lines 1-5, 7, and 10 is significantly higher than that under Strategy 2. However, the residual risk cost and TC-RCRR for these lines under Strategy 1 are significantly lower than those under Strategy 2, indicating that Strategy 1 is superior to Strategy 2. The reason for this is that the Weibull curve of Strategy 2 only considers the change in failure rate caused by the increase in the service life of overhead transmission lines, but does not consider the increase in line failure rate caused by icing disasters.

[0152] Strategy 3 considers the impact of icing disasters on line failure rates, but does not consider the impact of line load on residual risk costs. Figure 4 For some lines, the TC-RCRR values ​​are similar under both Strategy 1 and Strategy 3, but their cost distributions differ. Strategy 1 significantly reduces the residual risk cost compared to Strategy 3, thus better ensuring the safe and stable operation of the power grid. For example, the TC-RCRR of Line 7 differs by only 0.4% under the two strategies, but the residual risk cost of this line is reduced by 37.8% under Strategy 1 compared to Strategy 3.

[0153] Based on the same inventive concept, this application also provides a device for implementing the above-mentioned transmission line anti-icing scheme optimization. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the transmission line anti-icing scheme optimization device provided below can be found in the limitations of the transmission line anti-icing scheme optimization method above, and will not be repeated here.

[0154] In one exemplary embodiment, a transmission line anti-icing scheme optimization device is provided, comprising:

[0155] The acquisition module is used to acquire design standards, operating status, environment, historical fault data, implementation costs of various anti-icing schemes, and local power data of overhead transmission lines.

[0156] The failure rate calculation module is used to calculate the failure rate of the line during each ice period based on the design standards, the operating status, the environment, and the historical failure data.

[0157] The fault rate distribution function calculation module is used to calculate the fault rate distribution function of overhead transmission lines in multiple ice periods based on the fault rate of the line in each ice period using the Nelson-Aalen estimation method.

[0158] The power loss value calculation module is used to calculate the local power loss value based on the local power data.

[0159] The residual risk cost calculation module for lines employing anti-icing schemes is used to calculate the residual risk cost of lines employing anti-icing schemes based on the power loss value and the failure rate.

[0160] The optimization module is used to minimize the sum of the residual risk cost and the line risk control cost of the line using the anti-icing scheme as the objective function, and to optimize the anti-icing scheme under the constraints of the reliability and economy of the anti-icing scheme implementation, so as to obtain the optimal anti-icing scheme; the line risk control cost is calculated based on the implementation costs of multiple anti-icing schemes.

[0161] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 5 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores optimization data for transmission line anti-icing schemes. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for optimizing transmission line anti-icing schemes.

[0162] Those skilled in the art will understand that Figure 5 The structures shown are merely block diagrams of some structures related to the present application and do not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method embodiments.

[0163] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the above-described method embodiments.

[0164] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described method embodiments.

[0165] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0166] In this application, all actions to acquire signals, information, or data are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with the authorization granted by the owner of the relevant device.

[0167] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0168] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchain. The processors involved in the embodiments provided in this application may be, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc.

[0169] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0170] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An optimization method for anti-icing schemes of transmission lines, characterized in that, The optimization method for the anti-icing scheme of the transmission line includes: Obtain information on the design standards, operating status, environment, historical fault data, implementation costs of various anti-icing schemes, and local power data of overhead transmission lines; The failure rate of the line during each ice period is calculated based on the design standards, the operating status, the environment, and the historical fault data. The fault rate distribution function of overhead transmission lines during multiple ice periods is calculated using the Nelson-Aalen estimation method based on the fault rate during each ice period. Calculate the local power loss value based on the local power data; Calculate the remaining risk cost of the line using the anti-icing scheme based on the power loss value and the failure rate; The objective function is to minimize the sum of the residual risk cost and the risk control cost of the line using the anti-icing scheme. The anti-icing scheme is optimized under the constraints of reliability and economy of implementation to obtain the optimal anti-icing scheme. The line risk control cost is calculated based on the implementation costs of various anti-icing schemes.

2. The method for optimizing the anti-icing scheme of transmission lines according to claim 1, characterized in that, The calculation of the fault rate of the line during each ice period based on the design standards, the operating status, the environment, and the historical fault data specifically includes: The combined ice and wind load is calculated based on the line diameter of the design standard, the icing density of the environment, the average wind speed of the environment, and the operating status. The failure rate of the line during each ice period is calculated based on the combined ice and wind load, the operating status, and the historical fault data.

3. The method for optimizing the anti-icing scheme of transmission lines according to claim 2, characterized in that, The specific formula for calculating the combined ice and wind load is as follows: in, For the combined ice and wind load, l I (T0) represents the ice load on the line in year T0. W (T0) represents the wind load on the line in year T0, g is the acceleration due to gravity, and ρ i d(T0) represents the icing density, d(T0) represents the icing thickness of the line in year T0, D is the line diameter, k is the wind pressure coefficient, v is the average wind speed, a is the wind speed non-uniformity coefficient, C is the wind shape coefficient, and n is the nth icing period in a year.

4. The method for optimizing the anti-icing scheme of transmission lines according to claim 1, characterized in that, The calculation of the fault rate distribution function of overhead transmission lines across multiple glacial periods using the Nelson-Aalen estimation method, based on the fault rate during each glacial period, specifically includes: The cumulative failure rate of the line over multiple ice periods is obtained by summing up the failure rates during each ice period. The Nelson-Aalen estimation method is used to calculate the fault rate distribution function of overhead transmission lines during multiple glacial periods based on the cumulative fault rate of the lines.

5. The method for optimizing the anti-icing scheme of transmission lines according to claim 1, characterized in that, The formula for calculating the residual risk cost of the line using the anti-icing scheme based on the power loss value and the failure rate is as follows: RI(T0+T)=V L (T0+T)×P(T0+T)×t out ×F N (T0+T) Where T0 is the year the anti-icing plan is implemented, T is the Tth year after the implementation of the anti-icing plan, RI(T0+T) is the remaining risk cost in the Tth year after the implementation of the anti-icing plan, and V L (T0+T) represents the energy loss value in year T after the implementation of the anti-icing plan, P(T0+T) represents the average load of overhead transmission lines during the ice period in year T after the implementation of the anti-icing plan, and t out F represents the average fault repair time. N (T0+T) is the failure rate distribution function during N ice periods in year T after the implementation of the anti-icing plan.

6. The method for optimizing the anti-icing scheme of transmission lines according to claim 1, characterized in that, The objective function is to minimize the sum of the residual risk cost and the risk control cost of the line using the anti-icing scheme. With the reliability and economy of the anti-icing scheme as constraints, the anti-icing scheme is optimized, and the specific formula for obtaining the optimal anti-icing scheme is as follows: Among them, TC-RCRR i (T0+T) represents the sum of the line risk control cost and the line residual risk cost of anti-icing scheme i; RI i (T0+T) represents the residual risk cost of the line using anti-icing scheme i; C i (T0+T) represents the implementation cost of using anti-icing solution i, RI th For reliability constraints; C th For economic constraints, I represents the set of all anti-icing schemes, T0 represents the year in which the anti-icing scheme is implemented, and T represents the Tth year after the implementation of the anti-icing scheme. The sum of the remaining risk costs from the year of implementation of anti-icing scheme i to the year T is given, where t is a variable in the summation formula.

7. A device for optimizing anti-icing schemes for power transmission lines, characterized in that, The transmission line anti-icing scheme optimization device includes: The acquisition module is used to acquire the design standards, operating status, environment, historical fault data, implementation costs of various anti-icing schemes, and local power data of overhead transmission lines. The failure rate calculation module is used to calculate the failure rate of the line during each ice period based on the design standards, the operating status, the environment, and the historical failure data. The fault rate distribution function calculation module is used to calculate the fault rate distribution function of overhead transmission lines in multiple ice periods based on the fault rate of the line in each ice period using the Nelson-Aalen estimation method; The power loss load value calculation module is used to calculate the local power loss load value based on the local power data. The residual risk cost calculation module for lines employing anti-icing schemes is used to calculate the residual risk cost of lines employing anti-icing schemes based on the power loss value and the failure rate. The optimization module is used to minimize the sum of the residual risk cost and the line risk control cost of the line using the anti-icing scheme as the objective function, and to optimize the anti-icing scheme under the constraints of the reliability and economy of the anti-icing scheme implementation, so as to obtain the optimal anti-icing scheme; the line risk control cost is calculated based on the implementation costs of multiple anti-icing schemes.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the transmission line anti-icing scheme optimization method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method for optimizing the anti-icing scheme of transmission lines as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method for optimizing the anti-icing scheme of transmission lines as described in any one of claims 1-6.

Images