CN116362622B - Power grid power supply capacity assessment method and device under extreme meteorological conditions - Google Patents

Abstract

The invention belongs to the field of safe operation of power grids, and particularly relates to a power supply capacity assessment method and device for a power grid under extreme meteorological conditions. The evaluation method comprises the following steps: analyzing the running state of the power grid under extreme meteorological conditions, and establishing a fault rate hybrid model; calculating a mixed fault rate, judging whether important loads need to be transferred or not, and determining transfer priority; and constructing a power grid evaluation function under extreme meteorological conditions, taking the minimum electric energy shortage of the important load as a target, establishing an objective function, and carrying out electric energy transfer on the important load according to the transfer priority. The invention not only can determine the mixed fault rate of the important load, but also can realize the electric energy supply of the important load, ensure the normal electricity utilization of the important load in the power grid, provide a novel guiding method for the safe operation of the power grid and improve the operation reliability of the power grid.

Description

Power grid power supply capacity assessment method and device under extreme meteorological conditions

Technical Field

The invention belongs to the field of safe operation of power grids, and particularly relates to a power supply capacity assessment method and device for a power grid under extreme meteorological conditions.

Background

The safe operation of the power grid can not only improve the operation efficiency of the power system and ensure the sharing of high-quality power users, but also promote the economic development and maximize the benefit. However, in recent years, various small-probability extreme weather seriously threatens the normal operation of the power grid, and causes great loss to national economy, so that the operation capability of the power grid under the extreme weather condition is improved, and the method has very important significance for the safe operation of a power system and the development of the national economy. The probability of the outage of the important load close to the extreme weather is far greater than that of the important load far from the extreme weather, and how to measure the outage probability of the important load under the extreme weather is an important premise for ensuring the power supply of the important load.

Disclosure of Invention

Aiming at the defects of the existing method, the invention provides a power supply capacity evaluation method and device for a power grid under extreme meteorological conditions.

In order to achieve the above purpose, the invention adopts the following technical scheme:

a power supply capacity evaluation method for a power grid under extreme meteorological conditions comprises the following steps:

analyzing the running state of the power grid under extreme meteorological conditions, and establishing a fault rate hybrid model;

calculating a mixed fault rate, judging whether important loads need to be transferred or not, and determining transfer priority;

and constructing a power grid evaluation function under extreme meteorological conditions, taking the minimum electric energy shortage of the important load as a target, establishing an objective function, and carrying out electric energy transfer on the important load according to the transfer priority.

Preferably, the fault rate hybrid model includes a wind speed impact power grid outage fault rate model, an overload fault rate model, a line fault rate model and other fault rate models, and the definitions are respectively as follows:

the wind speed influences the power grid to shut down the fault rate model:

wherein f _w The wind speed influences the outage fault rate of the power grid, V represents the wind speed, and V represents the design wind speed;

the overload fault rate model is as follows:

f _g ＝f _g1 +f _g2

wherein f _g Indicating overload failure rate, f _g1 Indicating the current overload rate of the branch, f _g2 Representing a voltage threshold crossing rate;

the line fault rate model is as follows:

f _x ＝f _x1 +f _x2

wherein f _x Representing the failure rate of the line, f _x1 Represents the broken line fault rate, f _x2 Representing the reverse tower fault rate;

other failure rate models are:

wherein f _q Representing other failure rate, x _q Representing the variable, mu _q Mean value, sigma _q Representing standard deviation.

Preferably, the calculating the hybrid fault rate, determining whether the important load needs to be diverted, includes:

the mixed failure rate P _f The calculation is performed according to the following formula:

P _f ＝1-(1-f _w )(1-f _g )(1-f _x )(1-f _q )

determining a mixed failure rate P _f Whether C is satisfied or not, C represents a critical value, and if so, important loads are determined to need transferring; if not, it indicates that the important load does not need to be transferred.

Preferably, the determining the priority of forwarding includes:

all disaster scenes are simulated in advance by using a Monte Carlo method, all possible transfer success paths are analyzed, and the running time of each possible transfer success path is recorded as (l, t) = { (l) _i ,t _i ) I=1, 2, …, n, where L represents the path set, T represents the run-time set, and transfer priority is determined from the run-time.

Preferably, the power grid evaluation function under the extreme meteorological conditions is:

F(λ,P,f)＝λ _w P _w f _w +λ _g P _g f _g +λ _x P _x f _x +λ _q P _q f _q

wherein F (λ, P, F) represents an evaluation function, λ _w Representing the coefficient of failure rate of wind speed influencing power grid outage, P _w Indicating that important loads lack of electric energy value when wind speed influences power grid outage, f _w The wind speed is expressed to influence the outage fault rate of the power grid; lambda (lambda) _g Representing the overload failure rate coefficient, P _g Indicating that the important load lacks an electric energy value when in overload fault, f _g Indicating an overload failure rate; lambda (lambda) _x Representing the line fault rate coefficient, P _x Indicating the lack of electric energy value of important load during line fault, f _x Representing line faultsA rate; lambda (lambda) _q Representing other failure rate coefficients, P _q Indicating that the important load lacks power values at other faults, and fq indicates other fault rates.

Preferably, the objective function is:

minF(λ,P,f)

s.t.λ _i ∈[0,1]and (2) and

P _i ∈[0,P _i ^max ]

f _i ∈[0,1]

wherein F (lambda, P, F) represents an evaluation function, lambda i represents a power grid outage fault rate coefficient caused by an ith scene, nF represents the total number of scenes, pi represents an important load lack electric energy value when the fault of the ith scene occurs, and P _i ^max Indicating the lack of the maximum power value of the important load in the ith scene, f _i Indicating the i-th scene failure rate.

An apparatus for evaluating power supply capacity of a power grid under extreme meteorological conditions, comprising:

the model construction module is used for analyzing the running state of the power grid under the extreme meteorological conditions and establishing a fault rate hybrid model;

the transfer supply determining module calculates the mixed fault rate, judges whether important loads need transfer supply or not, and determines transfer supply priority;

and the electric energy transfer module is used for constructing a power grid evaluation function under extreme weather conditions, taking the minimum electric energy shortage of the important load as a target, establishing an objective function, and carrying out electric energy transfer on the important load according to transfer priority.

The invention has the positive beneficial effects that:

1. although extreme weather is a small probability event, the probability of occurrence still exists, and once the occurrence happens, the safety operation of the power grid is seriously influenced, the normal development of national economy is influenced, and how to measure the probability of the shutdown of an important load under the extreme weather condition is an important premise for ensuring the power supply of the important load. The invention provides a power supply capacity assessment method of a power grid under extreme weather conditions, which comprises the steps of analyzing the running state of the power grid under the extreme weather conditions, establishing a fault rate mixing model, calculating each fault rate according to the fault rate mixing model, calculating to obtain a mixed fault rate, judging whether important loads in the power grid under the extreme weather conditions need to be supplied or not according to the magnitude of the mixed fault rate, if the mixed fault rate is larger than a critical value, indicating that the possibility of the important loads to be shut down is larger, and if the mixed fault rate is larger than the critical value, considering that the important loads need to be supplied, otherwise, indicating that the possibility of the important loads to be shut down is smaller, and then further determining the priority of the supply. According to the invention, through constructing an evaluation function, the outage probability of important loads in the power grid when extreme weather conditions occur is evaluated, an objective function which aims at minimizing the electric energy shortage of the important loads is established, and electric energy transfer is carried out on the important loads according to transfer priority.

The method can not only determine the mixed fault rate of the important load, but also realize the electric energy supply of the important load, ensure the normal operation of the important load in the power grid, provide a new method for evaluating the fault rate of the power grid under extreme meteorological conditions, and improve the operation reliability of the power grid.

Drawings

FIG. 1 is a flow chart of a method for evaluating power supply capacity of a power grid under extreme meteorological conditions.

Fig. 2 is a 14-node grid system diagram.

FIG. 3 is a graph of the mixed failure rate of each significant load node shutdown as typhoons pass.

FIG. 4 is a graph of power supplied from each load node.

Detailed Description

The invention will be further illustrated with reference to a few specific examples.

Example 1

The power supply capacity evaluation method for the power grid under the extreme meteorological conditions, referring to fig. 1, comprises the following steps:

step one: analyzing the running state of the power grid under extreme meteorological conditions, and establishing a fault rate hybrid model;

the fault rate hybrid model comprises a wind speed influence power grid outage fault rate model, an overload fault rate model, a line fault rate model and other fault rate models, and is defined as follows:

the wind speed influences the power grid to shut down the fault rate model:

wherein f _w The wind speed affects the failure rate of the power grid, V represents the wind speed, and V represents the design wind speed.

The overload fault rate model is as follows:

f _g ＝f _g1 +f _g2

wherein f _g Indicating overload failure rate, f _g1 Indicating the current overload rate of the branch, f _g2 Represents the voltage out-of-limit rate, n _I And n _U Respectively representing the number of overload branches and the number of out-of-limit voltage buses, I _i Representing the current in the branch i,represents the maximum value, U _j The j-th bus voltage value is shown.

The line fault rate model is as follows:

f _x ＝f _x1 +f _x2

wherein f _x Representing the failure rate of the line, f _x1 Represents the broken line fault rate, f _x2 Indicating the reverse tower failure rate.

During meteorological disasters, the main reason for the disconnection of the line is that the acting force of disaster causing factors on the line exceeds the self-bearing limit. The wind load born by the wire in the horizontal direction corresponding to any wind speed v acting on the wire is as follows:

H _s ＝0.61275ημ _z μ _sc β _c dLbv ² sin ² α

wherein eta represents the wind pressure non-uniformity coefficient of the wire and mu _z Represents the coefficient of variation, mu, of the wind pressure altitude _sc Representing the body form factor, beta _c The wind load adjusting coefficient of the wire is represented by d, the outer diameter of the wire is represented by L, the horizontal span of the tower is represented by b, the wind load increasing coefficient during icing is represented by v, the horizontal wind speed is represented by v, and the included angle between the wire and the wind direction is represented by alpha.

The dead weight of the wire is as follows:

H _g ＝Ψm _g Lg

wherein ψ represents the wire division number, m _g The mass of the wire per unit length is shown, and g is the gravitational acceleration.

The total load of the lead is as follows:

the specific load of the lead is as follows:

the broken line fault rate is as follows:

wherein K is _fx1 Representing the fault parameters of broken lines, F _hs Represents the horizontal stress of the wire under wind load, l represents the line span,representing the overhead line elevation angle.

The unbalanced force born by the two sides of the pole tower is as follows:

wherein n is _D Indicating the number of wires on the tower, F ₁ And F ₂ Respectively representing horizontal stress of wires at two ends of the tower, wherein theta represents an included angle of the wires at two ends of the tower, and for a right-angle pole theta=0.

The wind load born by the tower in the horizontal direction is as follows:

wherein A is _gs Representing the body form factor of the tower and ρ _gs Representing the wind vibration coefficient.

The failure rate of the inverted tower is as follows:

other failure rate models are:

wherein f _q Representing other failure rate, x _q Representing the variable, mu _q Mean value, sigma _q Representing standard deviation.

Step two: calculating a mixed fault rate, judging whether important loads need to be transferred or not, and determining transfer priority;

calculating a hybrid failure rate P _f ：

P _f ＝1-(1-f _w )(1-f _g )(1-f _x )(1-f _q )

Determining a mixed failure rate P _f Whether the value of C is more than C is met or not, wherein C represents a critical value, if the value is met, the important load is determined to need to be transferred according to experience, and if the value is not met, the important load is not required to be transferred;

simulating all disaster scenes in advance by using a Monte Carlo method, analyzing all possible transfer success paths and each possible transfer success pathRadial run time, noted as (l, t) = { (l) _i ,t _i )/l _i E L, ti e T, i=1, 2, …, n, where L represents the path set and T represents the run-time set; the transfer priority is determined according to the running time, and the smaller t is, the higher the priority is.

Thirdly, constructing a power grid evaluation function under extreme meteorological conditions, taking the minimum of important load electric energy deficiency as a target, establishing an objective function, and carrying out electric energy transfer on important loads according to transfer priority;

the power grid evaluation function is:

F(λ,P,f)＝λ _w P _w f _w +λ _g P _g f _g +λ _x P _x f _x +λ _q P _q f _q

wherein F (λ, P, F) represents the constructed evaluation function, λ _w Representing the coefficient of failure rate of wind speed influencing power grid outage, P _w Indicating that important loads lack of electric energy value when wind speed influences power grid outage, f _w The wind speed is expressed to influence the outage fault rate of the power grid; lambda (lambda) _g Representing the overload failure rate coefficient, P _g The method comprises the steps that when an overload fault occurs, an important load lacks an electric energy value, and fg represents an overload fault rate; lambda (lambda) _x Representing the line fault rate coefficient, P _x The method comprises the steps that when a line fails, an important load lacks an electric energy value, and fx represents the line failure rate; lambda (lambda) _q Representing other failure rate coefficients, P _q Indicating the lack of power value of important load in other faults, f _q Indicating other failure rates.

The objective function is:

minF(λ,P,f)

s.t.λ _i ∈[0,1]and (2) and

P _i ∈[0,P _i ^max ]

f _i ∈[0,1]

wherein F (λ, P, F) represents an evaluation function, λ _i Representing the power failure rate coefficient of the power grid caused by the ith scene, n _F Representing the total number of scenes, P _i Indicating the lack of electric energy value, P, of important load when the ith scene fault occurs _i ^max Indicating the lack of the maximum power value of the important load in the ith scene, f _i Indicating the i-th scene failure rate.

An evaluation device for power supply capacity of a power grid under extreme meteorological conditions, which realizes the above evaluation method, comprises the following steps:

the model construction module is used for analyzing the running state of the power grid under the extreme meteorological conditions and establishing a fault rate hybrid model;

the transfer supply determining module calculates the mixed fault rate, judges whether important loads need transfer supply or not, and determines transfer supply priority;

and the electric energy transfer module is used for constructing a power grid evaluation function under extreme weather conditions, taking the minimum electric energy shortage of the important load as a target, establishing an objective function, and carrying out electric energy transfer on the important load according to the transfer priority.

The following description will take a 14-node power grid system diagram shown in fig. 2 as an example, where node 1, node 8 and node 10 are transformer nodes; node 12, node 6, node 4 are important load nodes. The typhoon is taken as an extreme weather to explain, when the typhoon moves according to a blue double solid line, the wind speed is set to be 25km/s when the typhoon arrives at a power grid, the wind speed is set to be 15km/s when the typhoon leaves the power grid, the design wind speed of the power grid is 14km/s, C takes 0.5, the total load value of a node 12 is 12MW, the total load of a node 6 is 10MW, the total load of a node 4 is 8MW, and the probability that the typhoon stops running through important load nodes 12, 6 and 4 of the power grid is obtained by constructing a fault rate hybrid model as shown in figure 3.

As can be seen from fig. 3, the outage probability of the important load node 12 is 0.7017, the outage probability of the important load node 6 is 0.5506, and the values of the two nodes are both greater than C, which indicates that the outage probability of the two nodes is relatively high; the outage probability of the important load node 4 is 0.3395, which is smaller than C, and the outage probability is smaller. Because the outage probability of the important load node 12 and the important load node 6 is high, two important loads need to be transferred; the transfer priority is then determined and the results are shown in table 1.

Table 1 priority of transfer for important load node 12 and node 6

Important load node	Priority of transfer 1	Priority of transfer 2	Priority of transfer 3	Priority of transfer 4
					6	L3-L4	L11-L4	L8-L6-L5	L1-L2-L7-L6-L5
12	L10-L14	L9-L14	L3-L11-L12-L13	L1-L2-L7-L8-L9-L14

As can be seen from table 1, four possible transfer paths are obtained for each of the critical load node 6 and the critical load node 12. For the important load node 6, the preferred transfer path is L3-L4, then L11-L4, again L8-L6-L5, and finally L1-L2-L7-L6-L5; for the critical load node 12, the preferred transfer paths are L10-L14, followed by L9-L14, followed by L3-L11-L12-L13, and finally followed by L1-L2-L7-L8-L9-L14.

By utilizing the evaluation function and the objective function constructed by the invention, the electric energy needed to be transferred by the important load node 12 and the node 6 is obtained as shown in the figure 4, and the node 12 can start to break down when typhoons pass through the power grid for 3.3 hours, and the electric energy minimum value is only 3.25MW; the node 6 fails when typhoons pass through the power grid for 5 hours, the minimum value of electric energy is 4.19MW, the important load nodes 12 are influenced by typhoons most, the electric energy needed to be transferred is the most, and the electric energy transfer is carried out on the important load nodes according to the transfer priority.

Finally, it is noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention, and that other modifications and equivalents thereof by those skilled in the art should be included in the scope of the claims of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims (4)

1. The power supply capacity evaluation method for the power grid under the extreme meteorological conditions is characterized by comprising the following steps of:

analyzing the running state of the power grid under extreme meteorological conditions, and establishing a fault rate hybrid model;

calculating a mixed fault rate, judging whether important loads need to be transferred or not, and determining transfer priority;

constructing a power grid evaluation function under extreme meteorological conditions, taking the minimum electric energy shortage of an important load as a target, establishing an objective function, and carrying out electric energy transfer on the important load according to transfer priority;

the fault rate hybrid model comprises a wind speed influence power grid outage fault rate model, an overload fault rate model, a line fault rate model and other fault rate models, and is defined as follows:

the wind speed influences the power grid to shut down the fault rate model:

wherein f _w The wind speed influences the outage fault rate of the power grid, V represents the wind speed, and V represents the design wind speed;

the overload fault rate model is as follows:

f _g ＝f _g1 +f _g2

wherein f _g Indicating overload failure rate, f _g1 Indicating the current overload rate of the branch, f _g2 Represents the voltage out-of-limit rate, n _I And n _U Respectively representing the number of overload branches and the number of out-of-limit voltage buses, I _i Representing the current in the branch i,represents the maximum value, U _j Representing the voltage value of the j-th bus;

the line fault rate model is as follows:

f _x ＝f _x1 +f _x2

wherein f _x Representing the failure rate of the line, f _x1 Represents the broken line fault rate, f _x2 Representing the reverse tower fault rate;

the wind load born by the wire in the horizontal direction corresponding to any wind speed v acting on the wire is as follows:

H _s ＝0.61275ημ _z μ _sc β _c dLbv ² sin ² α

wherein eta represents the wind pressure non-uniformity coefficient of the wire and mu _z Represents the coefficient of variation, mu, of the wind pressure altitude _sc Representing the body form factor, beta _c The wind load adjusting coefficient of the wire is represented by d, the outer diameter of the wire is represented by L, the horizontal span of the tower is represented by b, the wind load increasing coefficient during icing is represented by v, the horizontal wind speed is represented by v, and the included angle between the wire and the wind direction is represented by alpha;

the dead weight of the wire is as follows:

H _g ＝Ψm _g Lg

wherein ψ represents the wire division number, m _g Representing the mass of a wire per unit length, g representing the gravitational acceleration;

the total load of the lead is as follows:

the specific load of the lead is as follows:

the broken line fault rate is as follows:

wherein K is _fx1 Representing the fault parameters of broken lines, F _hs Represents the horizontal stress of the wire under wind load, l represents the line span,representing the overhead line height difference angle;

the unbalanced force born by the two sides of the pole tower is as follows:

wherein n is _D Indicating the number of wires on the tower, F ₁ And F ₂ Respectively representing horizontal stress of wires at two ends of the tower, wherein theta represents an included angle of the wires at two ends of the tower, and for a right-angle pole theta=0;

the wind load born by the tower in the horizontal direction is as follows:

wherein A is _gs Representing the body form factor of the tower and ρ _gs Representing wind vibration coefficients;

the failure rate of the inverted tower is as follows:

other failure rate models are:

wherein f _q Representing other failure rate, x _q Representing the variable, mu _q Mean value, sigma _q Representing standard deviation;

the calculating the mixed fault rate and judging whether the important load needs to be transferred or not comprises the following steps:

the mixed failure rate P _f The calculation is performed according to the following formula:

P _f ＝1-(1-f _w )(1-f _g )(1-f _x )(1-f _q )

determining a mixed failure rate P _f Whether C is satisfied or not, C represents a critical value, and if so, important loads are determined to need transferring; if the load is not satisfied, indicating that the important load is not required to be transferred;

the power grid evaluation function under the extreme meteorological conditions is as follows:

F(λ,P,f)＝λ _w P _w f _w +λ _g P _g f _g +λ _x P _x f _x +λ _q P _q f _q

wherein F (λ, P, F) represents an evaluation function, λ _w Representing the coefficient of failure rate of wind speed influencing power grid outage, P _w Indicating that important loads lack of electric energy value when wind speed influences power grid outage, f _w The wind speed is expressed to influence the outage fault rate of the power grid; lambda (lambda) _g Representing the overload failure rate coefficient, P _g Representing the critical load in the event of overload failureLack of electric energy value, f _g Indicating an overload failure rate; lambda (lambda) _x Representing the line fault rate coefficient, P _x Indicating the lack of electric energy value of important load during line fault, f _x Representing a line failure rate; lambda (lambda) _q Representing other failure rate coefficients, P _q Indicating the lack of power value of important load in other faults, f _q Representing other failure rates;

the objective function is:

minF(λ,P,f)

s.t.λ _i ∈[0,1]and (2) and

P _i ∈[0,P _i ^max ]

f _i ∈[0,1]

wherein F (λ, P, F) represents an evaluation function, λ _i Representing the power failure rate coefficient of the power grid caused by the ith scene, n _F Representing the total number of scenes, P _i Indicating the lack of electric energy value, P, of important load when the ith scene fault occurs _i ^max Indicating the lack of the maximum power value of the important load in the ith scene, f _i Indicating the i-th scene failure rate.

2. The method for evaluating power supply capacity of a power grid under extreme weather conditions as set forth in claim 1, wherein said determining a transfer priority comprises:

all disaster scenes are simulated in advance by using a Monte Carlo method, all possible transfer success paths are analyzed, and the running time of each possible transfer success path is recorded as (l, t) = { (l) _i ,t _i )/l _i ∈L,t _i E T }, i=1, 2, …, n, where L represents the set of paths, T represents the set of runtimes, and the transfer priority is determined from the runtimes.

3. An apparatus for evaluating power supply capacity of a power grid under extreme meteorological conditions, comprising:

the model construction module is used for analyzing the running state of the power grid under the extreme meteorological conditions and establishing a fault rate hybrid model;

the transfer supply determining module calculates the mixed fault rate, judges whether important loads need transfer supply or not, and determines transfer supply priority;

the power transfer module is used for constructing a power grid evaluation function under extreme weather conditions, taking the minimum power shortage of an important load as a target, establishing an objective function, and carrying out power transfer on the important load according to transfer priority;

the fault rate hybrid model comprises a wind speed influence power grid outage fault rate model, an overload fault rate model, a line fault rate model and other fault rate models, and is defined as follows:

the wind speed influences the power grid to shut down the fault rate model:

wherein f _w The wind speed influences the outage fault rate of the power grid, V represents the wind speed, and V represents the design wind speed;

the overload fault rate model is as follows:

f _g ＝f _g1 +f _g2

wherein f _g Indicating overload failure rate, f _g1 Indicating the current overload rate of the branch, f _g2 Represents the voltage out-of-limit rate, n _I And n _U Respectively representing the number of overload branches and the number of out-of-limit voltage buses, I _i Representing the current in the branch i,represents the maximum value, U _j Representing the voltage value of the j-th bus;

the line fault rate model is as follows:

f _x ＝f _x1 +f _x2

wherein f _x Representing the failure rate of the line, f _x1 Represents the broken line fault rate, f _x2 Representing the reverse tower fault rate;

the wind load born by the wire in the horizontal direction corresponding to any wind speed v acting on the wire is as follows:

H _s ＝0.61275ημ _z μ _sc β _c dLbv ² sin ² α

wherein eta represents the wind pressure non-uniformity coefficient of the wire and mu _z Represents the coefficient of variation, mu, of the wind pressure altitude _sc Representing the body form factor, beta _c The wind load adjusting coefficient of the wire is represented by d, the outer diameter of the wire is represented by L, the horizontal span of the tower is represented by b, the wind load increasing coefficient during icing is represented by v, the horizontal wind speed is represented by v, and the included angle between the wire and the wind direction is represented by alpha;

the dead weight of the wire is as follows:

H _g ＝Ψm _g Lg

wherein ψ represents the wire division number, m _g Representing the mass of a wire per unit length, g representing the gravitational acceleration;

the total load of the lead is as follows:

the specific load of the lead is as follows:

the broken line fault rate is as follows:

wherein K is _fx1 Representing the fault parameters of broken lines, F _hs Represents the horizontal stress of the wire under wind load, l represents the line span,representing the overhead line height difference angle;

the unbalanced force born by the two sides of the pole tower is as follows:

wherein n is _D Indicating the number of wires on the tower, F ₁ And F ₂ Respectively representing horizontal stress of wires at two ends of the tower, wherein theta represents an included angle of the wires at two ends of the tower, and for a right-angle pole theta=0;

the wind load born by the tower in the horizontal direction is as follows:

wherein A is _gs Representing the body form factor of the tower and ρ _gs Representing wind vibration coefficients;

the failure rate of the inverted tower is as follows:

other failure rate models are:

wherein f _q Representing other failure rate, x _q Representing the variable, mu _q Mean value, sigma _q Representing standard deviation;

the calculating the mixed fault rate and judging whether the important load needs to be transferred or not comprises the following steps:

the saidHybrid failure rate P _f The calculation is performed according to the following formula:

P _f ＝1-(1-f _w )(1-f _g )(1-f _x )(1-f _q )

determining a mixed failure rate P _f Whether C is satisfied or not, C represents a critical value, and if so, important loads are determined to need transferring; if not, it indicates that the important load does not need to be transferred.

4. A grid power supply capability assessment apparatus under extreme weather conditions according to claim 3, wherein said determining a transfer priority comprises:

all disaster scenes are simulated in advance by using a Monte Carlo method, all possible transfer success paths are analyzed, and the running time of each possible transfer success path is recorded as (l, t) = { (l) _i ,t _i )/l _i ∈L,t _i E T }, i=1, 2, …, n, where L represents the set of paths, T represents the set of runtimes, and the transfer priority is determined from the runtimes.