CN111852788B

CN111852788B - Method and device for diagnosing power loss abnormity of wind turbine generator

Info

Publication number: CN111852788B
Application number: CN201910361898.8A
Authority: CN
Inventors: 欧发顺
Original assignee: Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
Current assignee: Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
Priority date: 2019-04-30
Filing date: 2019-04-30
Publication date: 2022-07-15
Anticipated expiration: 2039-04-30
Also published as: CN111852788A

Abstract

The invention provides a method and a device for diagnosing power loss abnormity of a wind turbine generator, wherein the method comprises the following steps: acquiring the internet power of the wind turbine generator in a preset time period; determining an actual total loss power value of the wind turbine generator based on the internet power in the preset time period; and calculating a conformity index of the actual total loss power value and the corresponding standard total loss power value, and diagnosing the power loss condition of the wind turbine generator based on the calculated conformity index. By adopting the method and the device for diagnosing the power loss abnormality of the wind turbine generator, the deviation condition of the wind turbine generator relative to the standard loss can be accurately determined, and the effective evaluation of the output level of the wind turbine generator is facilitated.

Description

Method and device for diagnosing power loss abnormity of wind turbine generator

Technical Field

The present invention relates generally to the field of wind power technology, and more particularly, to a method and an apparatus for diagnosing power loss abnormality of a wind turbine.

Background

In the operation process of the wind turbine generator, wind energy is absorbed through the blades and converted into mechanical energy, and then the mechanical energy is converted into electric energy. Due to the complexity of modern large wind turbines, there are a lot of losses in the generation process of the wind turbines, and these losses mainly come from the following aspects:

(1) mechanical losses. Taking a permanent-magnet direct-drive wind driven generator as an example, the mechanical loss exists in the rotation process of an impeller-main shaft-generator mechanical transmission system.

(2) The generator itself is lost. Similarly, taking a permanent-magnet direct-drive wind driven generator as an example, the generator loss includes iron loss, copper loss and the like.

(3) Power cable losses. The wind driven generator is generally positioned in an engine room, electric energy is transmitted to a transformer outside a wind turbine generator through a three-phase power cable, and the electric energy is boosted by the transformer and then input into a power grid. Generally, the length of the power cable is about 100 meters, and the larger the rated power of the wind turbine generator is, the larger the diameter of the power cable is, and the larger the power consumption is.

(4) The converter itself loses. The converter can be divided into air cooling and water cooling according to the cooling mode, and the water-cooled converter is taken as an example, and the converter loss at least comprises: the heat generated by the power components in the working process, the electric energy consumed by the water-cooling heat-radiating fan, the electric energy consumed by the water-cooling system driving pump and the like.

(5) And electric energy consumed by each electric component of the wind turbine generator in the working process. The part of electric energy mainly comprises: a) the pitch control motor is used for controlling the electric energy consumed by the yaw motor in the working process; b) the generator cooling system consumes electric energy in the working process; c) other electrical components consume electrical energy during operation.

In the normal power generation process of the wind turbine generator, the loss of the wind turbine generator changes along with the change of different operation conditions and seasonal conditions of the wind turbine generator.

However, at present, the influence of the operating condition and the seasonal condition of the wind turbine generator on the power loss of the wind turbine generator is not considered, so that the diagnosis of the power loss condition of the wind turbine generator is not accurate enough, and a large deviation exists.

In addition, when the loss of the wind turbine generator is abnormal (generally, the loss of the wind turbine generator is higher), the grid-connection power curve of the wind turbine generator is affected, and the specific expression is that the SCADA power curve of the wind turbine generator in a certain time period is obviously lower than that of other wind turbine generators with the same configuration. For the diagnosis deviation of the power loss condition of the wind turbine generator, the reason of poor online power curve may not be quickly located.

Disclosure of Invention

An object of an exemplary embodiment of the present invention is to provide a method and an apparatus for diagnosing power loss abnormality of a wind turbine generator, so as to overcome at least one of the above-mentioned disadvantages.

In one general aspect, there is provided a method for diagnosing a power loss abnormality of a wind turbine generator, including: acquiring the internet power of the wind turbine generator in a preset time period; determining an actual total loss power value of the wind turbine generator based on the internet power in the preset time period; and calculating a conformity index of the actual total loss power value and the corresponding standard total loss power value, and diagnosing the power loss condition of the wind turbine generator based on the calculated conformity index.

Optionally, the step of obtaining the internet power of the wind turbine generator in a predetermined time period includes: performing data binning according to the air density of the position of the wind turbine generator in a preset time period to obtain a plurality of air density intervals, and acquiring the internet surfing power corresponding to each air density in each air density interval; and aiming at each air density interval, performing data binning according to all internet power in the air density interval to obtain a plurality of internet power intervals.

Optionally, an actual total loss power value corresponding to each grid power interval of the wind turbine generator and each air density interval is determined, wherein the diagnosis method further includes: and determining a standard total loss power value corresponding to each internet power interval of the wind turbine generator and each air density interval.

Optionally, an actual total loss power value corresponding to any internet access power interval of the wind turbine generator and any air density interval may be determined according to an actual estimated loss power value and an actual measured loss power value corresponding to any internet access power interval of any air density interval, and a standard total loss power value corresponding to any internet access power interval of the wind turbine generator and any air density interval may be determined according to a standard estimated loss power value and a standard measured loss power value corresponding to any internet access power interval of any air density interval.

Optionally, the actual measured loss power value corresponding to any internet power interval in any air density interval may include an actual power cable loss value corresponding to any internet power interval in any air density interval during operation of the wind turbine generator and an actual loss value of each electrical component included in the wind turbine generator, where the actual power cable loss value may be determined based on a generator terminal voltage value and a total resistance value of the power cable, and the actual loss value of each electrical component may be determined based on a power coefficient and a rated power of each electrical component.

Optionally, the actual estimated loss power value corresponding to the any internet power interval in the any air density interval may be determined by: and determining an actual estimated loss power value corresponding to any one of the internet access power intervals under any one of the air density intervals based on a predetermined corresponding relationship between the internet access power intervals and the estimated loss power values under the air density intervals.

Optionally, the corresponding relationship between the plurality of internet power intervals and the plurality of estimated loss power values under the plurality of air density intervals may be determined by: acquiring historical operating data of the wind turbine generator, determining an air density interval to which the air density in the historical operating data belongs, executing the following steps aiming at each air density interval, according to the electromagnetic power and the internet power of the wind turbine generator corresponding to each air density in the air density interval, determining a theoretical total loss power value corresponding to each internet power of the wind turbine generator, determining an actual measurement loss power value corresponding to each internet power of the wind turbine generator, obtaining an estimated loss power value corresponding to each internet power according to the determined theoretical total loss power value and the determined actual loss power value, determining an internet power interval to which each internet power belongs, calculating an estimated loss average value of the estimated loss power values corresponding to the internet powers in the internet power interval aiming at each internet power interval, and taking the calculated estimated loss average value as the estimated loss power value corresponding to the internet power interval.

Alternatively, the theoretical total loss power value may be a difference between the electromagnetic power and the power on the grid, and the electromagnetic power may be a product of the electromagnetic torque corresponding to each air density and the rotational speed of the generator.

Optionally, a standard total loss power value corresponding to each internet access power interval under each air density interval is searched from a loss standard library, wherein a plurality of standard total loss power values corresponding to different internet access power intervals under different air density intervals of the wind turbine generator are stored in the loss standard library.

Alternatively, the loss criteria library may be constructed by: acquiring historical operating data of the wind turbine generator; performing data binning according to the air density and the internet power in the acquired historical operating data respectively, and calculating an actually measured loss power value corresponding to each internet power interval under each air density interval; determining an estimated loss power value corresponding to each internet access power interval under each air density interval; and determining the sum of the estimated loss power value and the actually measured loss power value corresponding to the internet power interval under the air density interval as the standard total loss power value corresponding to the internet power interval under the air density interval aiming at each internet power interval under each air density interval.

Optionally, the step of calculating a conformity index of the actual total loss power value with the corresponding standard total loss power value may include: and aiming at each air density interval, calculating a conformity index corresponding to the air density interval according to the sum of the ratio of the actual total loss power value corresponding to each internet power interval under the air density interval to the standard total loss power value.

Alternatively, the conformity index corresponding to any one of the air density intervals may be calculated by: and respectively calculating the ratio of the actual total loss power value corresponding to each internet power interval in any air density interval to the standard total loss power value, calculating the ratio of the sum of all the ratios to the number of the internet power intervals, and determining the difference between the calculated ratio and 1 as the conformity index corresponding to any air density interval.

Optionally, the step of diagnosing the power loss condition of the wind turbine generator based on the calculated conformity index may include: and for each air density interval, if the calculated conformity index is greater than a set threshold, determining that the power loss of the wind turbine generator in the air density interval is abnormal, and if the calculated conformity index is less than or equal to the set threshold, determining that the power loss of the wind turbine generator in the air density interval is not abnormal.

In another general aspect, there is provided a diagnosis apparatus for power loss abnormality of a wind turbine, including: the power acquisition module is used for acquiring the internet power of the wind turbine generator within a preset time period; the actual total loss determining module is used for determining an actual total loss power value of the wind turbine generator based on the internet power in the preset time period; and the conformity degree determining module is used for calculating a conformity degree index of the actual total loss power value and the standard total loss power value and diagnosing the power loss condition of the wind turbine generator based on the calculated conformity degree index.

Optionally, the power obtaining module comprises: the density data binning submodule is used for performing data binning according to the air density of the position of the wind turbine generator in a preset time period to obtain a plurality of air density intervals and acquiring the internet power corresponding to each air density in each air density interval; and the power data binning submodule is used for performing data binning according to all the internet access power in each air density interval to obtain a plurality of internet access power intervals.

Optionally, the actual total loss determining module determines an actual total loss power value corresponding to each grid power interval of the wind turbine generator and each air density interval, where the diagnostic apparatus may further include: and the standard total loss determining module is used for determining a standard total loss power value corresponding to each grid power interval of the wind turbine generator and each air density interval.

Optionally, the actual total loss power value of the wind turbine generator corresponding to any internet power interval in any air density interval may be determined according to the actual estimated loss power value and the actual measured loss power value corresponding to any internet power interval in any air density interval, and the standard total loss power value of the wind turbine generator corresponding to any internet power interval in any air density interval may be determined according to the standard estimated loss power value and the standard measured loss power value corresponding to any internet power interval in any air density interval.

Optionally, the actual total loss determining module may determine an actual estimated loss power value corresponding to the any internet power interval in the any air density interval by: and determining an actual estimated loss power value corresponding to any one of the internet access power intervals under any one of the air density intervals based on a predetermined corresponding relationship between the internet access power intervals and the estimated loss power values under the air density intervals.

Optionally, the diagnostic apparatus may further include a correspondence relationship establishing module, where the correspondence relationship establishing module may determine correspondence relationships between a plurality of internet power intervals and a plurality of estimated loss power values under a plurality of air density intervals by: acquiring historical operating data of the wind turbine generator, determining an air density interval to which the air density in the historical operating data belongs, executing the following processing aiming at each air density interval, according to the electromagnetic power and the internet power of the wind turbine generator corresponding to each air density in the air density interval, determining a theoretical total loss power value corresponding to each internet power of the wind turbine generator, determining an actual measurement loss power value corresponding to each internet power of the wind turbine generator, obtaining an estimated loss power value corresponding to each internet power according to the determined theoretical total loss power value and the determined actual loss power value, determining an internet power interval to which each internet power belongs, calculating an estimated loss average value of the estimated loss power values corresponding to each internet power in the internet power interval aiming at each internet power interval, and taking the calculated estimated loss average value as the estimated loss power value corresponding to the internet power interval.

Alternatively, the theoretical total loss power value may be a difference between the electromagnetic power and the grid power, and the electromagnetic power may be a product of the electromagnetic torque corresponding to each air density and the generator rotation speed.

Optionally, the standard total loss determining module may search a loss standard library for a standard total loss power value corresponding to each internet power interval in each air density interval, where the loss standard library stores a plurality of standard total loss power values corresponding to different internet power intervals in different air density intervals for the wind turbine generator.

Optionally, the diagnostic apparatus may further include a loss criteria library building module that may build a loss criteria library by: acquiring historical operating data of the wind turbine generator; performing data binning according to the air density and the internet power in the acquired historical operating data respectively, and calculating an actually measured loss power value corresponding to each internet power interval under each air density interval; determining an estimated loss power value corresponding to each internet power interval under each air density interval; and determining the sum of the estimated loss power value and the actually measured loss power value corresponding to the internet power interval under the air density interval as the standard total loss power value corresponding to the internet power interval under the air density interval aiming at each internet power interval under each air density interval.

Optionally, the conformity determining module may calculate, for each air density interval, a conformity index corresponding to the air density interval according to a sum of ratios of an actual total loss power value and a standard total loss power value corresponding to each internet power interval in the air density interval.

Optionally, the conformity determination module may calculate the conformity index corresponding to any air density interval by: and respectively calculating the ratio of the actual total loss power value corresponding to each internet power interval in any air density interval to the standard total loss power value, calculating the ratio of the sum of all the ratios to the number of the internet power intervals, and determining the difference between the calculated ratio and 1 as the conformity index corresponding to any air density interval.

Optionally, for each air density interval, if the calculated conformity index is greater than a set threshold, the conformity determination module may determine that the power loss of the wind turbine generator in the air density interval is abnormal, and if the calculated conformity index is less than or equal to the set threshold, the conformity determination module may determine that the power loss of the wind turbine generator in the air density interval is not abnormal.

In another general aspect, there is provided a computer readable storage medium storing a computer program which, when executed by a processor, implements the above-described method for diagnosing a power loss abnormality of a wind turbine.

In another general aspect, there is provided a computing device, comprising: a processor; and a memory storing a computer program which, when executed by the processor, implements the above-described method for diagnosing a power loss abnormality of a wind turbine generator.

By adopting the method and the device for diagnosing the power loss abnormality of the wind turbine generator, the deviation condition of the wind turbine generator relative to the standard loss can be accurately determined, and the effective evaluation of the output level of the wind turbine generator is facilitated.

Drawings

The above and other objects and features of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings, in which:

fig. 1 shows a flowchart of a method for diagnosing power loss abnormality of a wind turbine generator according to an exemplary embodiment of the present invention;

FIG. 2 shows a flowchart of the steps of determining an actual total loss power value for a wind park according to an exemplary embodiment of the present invention;

fig. 3 is a flowchart illustrating a step of determining a correspondence relationship between a plurality of internet power intervals and a plurality of estimated loss power values at any air density interval according to an exemplary embodiment of the present invention;

FIG. 4 shows a flowchart of the steps of building a wear criteria library in accordance with an exemplary embodiment of the present invention;

fig. 5 shows a block diagram of a diagnosis apparatus of a power loss abnormality of a wind turbine generator according to an exemplary embodiment of the present invention.

Detailed Description

Various example embodiments will now be described more fully with reference to the accompanying drawings, in which some example embodiments are shown.

Fig. 1 shows a flowchart of a method for diagnosing a power loss abnormality of a wind turbine generator according to an exemplary embodiment of the present invention.

Referring to fig. 1, in step S10, the grid power of the wind turbine generator in a predetermined time period is obtained.

In step S20, an actual total loss power value of the wind turbine is determined based on the grid power within a predetermined time period.

Here, an actual total power loss value of the wind turbine corresponding to the acquired grid power may be determined. In a preferred embodiment, the air density of the position where the wind turbine is located within the predetermined time period may be further obtained, in which case the actual power loss value of the wind turbine corresponding to the obtained air density and the power on grid may be determined.

That is to say, the acquired air density and the acquired internet power within the predetermined time period can be respectively binned, so that the actual power loss value of the wind turbine generator in each air density interval and each internet power interval is determined.

The step of determining the actual total power loss value of the wind turbine by binning the air density and the grid power is described below with reference to fig. 2.

Fig. 2 shows a flow chart of the steps of determining an actual total loss power value of a wind park according to an exemplary embodiment of the invention.

Referring to fig. 2, in step S101, data is binned according to the air density of the position where the wind turbine generator is located within a predetermined time period to obtain a plurality of air density intervals, and the internet power corresponding to each air density within each air density interval is obtained.

For example, it may be based on the air density p from the minimum_minTo maximum air density ρ_maxThe air density bin distribution is carried out by taking a preset density step as an interval to obtain a plurality of air density intervals.

As an example, the air density at the location of the wind turbine may be determined based on the ambient temperature and altitude at the location of the wind turbine.

For example, the air density at the location of the wind turbine can be approximated using the following formula:

in the formula (1), ρ is the air density at the position of the wind turbine, T is the ambient temperature at the position of the wind turbine, generally, T can be the average value of the ambient temperatures acquired within a sampling period (e.g., 10 minutes), and H is the altitude at the position of the wind turbine.

Here, in an exemplary embodiment of the present invention, the operation data of the wind turbine generator in a predetermined period of time may be acquired, and the acquired operation data may include an air density of a location where the wind turbine generator is located, or the acquired operation data may include an ambient temperature and an altitude of the location where the wind turbine generator is located, and the air density may be determined from the ambient temperature and the altitude. In addition, the acquired operational data may further include, but is not limited to, at least one of: the system comprises the wind turbine generator, a wind turbine generator terminal voltage, a yaw speed, a pitch, a state flag bit and a cooling fan state flag bit.

The operation data of the wind turbine generator for diagnosing the power loss abnormality is the operation data of the wind turbine generator in a normal power generation state and in a non-power-limiting state. Data in other states than these, for example, in the shutdown state, in the standby state or in other states specified in standard IEC6400-12-1, are not used as data for diagnosing power loss anomalies.

As an example, each data in the exemplary embodiment of the present invention may refer to mean data of each sampling time within one sampling period (e.g., 10 minutes or 20 minutes), but the present invention is not limited thereto.

In step S102, for each air density interval, data binning is performed according to all internet power in the air density interval to obtain a plurality of internet power intervals.

For example, it may be based on power p from a minimum power on-line_minTo rated power p_ratedIn predetermined power steps p_stepAnd carrying out power binning for intervals to obtain a plurality of internet power intervals.

As an example, the number of the plurality of internet power intervals may be obtained by using the following formula:

in the formula (2), n_stepThe number of the power intervals of the internet.

In step S103, an actual total power loss value corresponding to each grid power interval of the wind turbine generator and each air density interval is determined.

Here, the total power loss of the wind turbine refers to energy lost by cooling and heat dissipation, power consumption of the electrical components themselves, and the like during operation of the wind turbine.

As an example, the actual total loss power value of the wind turbine generator corresponding to any internet power interval in any air density interval may be determined according to the actual estimated loss power value and the actual measured loss power value corresponding to any internet power interval in any air density interval.

For example, the sum of the actual estimated loss power value corresponding to any internet power interval in any air density interval and the actual measured loss power value corresponding to any internet power interval in any air density interval may be determined as the actual total loss power value corresponding to any internet power interval in any air density interval of the wind turbine generator set.

The process of determining the actual measured loss power value of a wind turbine is described below.

As an example, the actual measured loss power value corresponding to any one of the internet power intervals under any one of the air density intervals may include an actual power cable loss value corresponding to any one of the internet power intervals under any one of the air density intervals and an actual loss value of each electrical component included in the wind turbine corresponding to any one of the internet power intervals under any one of the air density intervals during the operation of the wind turbine.

For example, the actual power cable loss value may be determined based on the generator terminal voltage value and the total resistance value of the power cable, and the actual loss value of each electrical component may be determined based on the power factor and the power rating of each electrical component. The specific manner of determining the actual power cable loss value and the actual loss values of the electrical components will be described later, and the present invention will not be described herein again.

The process of determining the actual estimated loss power value of the wind turbine is described below.

For example, the actual estimated loss power value corresponding to any one of the internet power intervals under any one of the air density intervals can be determined in the following manner.

And determining an actual estimated loss power value corresponding to any one of the internet power intervals under any one of the air density intervals based on the corresponding relation between the plurality of internet power intervals and the plurality of estimated loss power values under the plurality of air density intervals.

Here, to obtain the corresponding relationship between the plurality of internet power intervals and the plurality of estimated loss power values under the plurality of air density intervals, historical operation data of the wind turbine generator may be obtained first, an air density interval to which the air density in the historical operation data belongs is determined, and then, for each air density interval, the corresponding relationship between the plurality of internet power intervals and the plurality of estimated loss power values under the air density interval is determined, so as to obtain the corresponding relationship between the plurality of internet power intervals and the plurality of estimated loss power values under the plurality of air density intervals.

The following describes the steps of determining the corresponding relationship between the plurality of internet power intervals and the plurality of estimated loss power values in any air density interval with reference to fig. 3.

Fig. 3 is a flowchart illustrating a step of determining a correspondence relationship between a plurality of internet power intervals and a plurality of estimated loss power values for any air density interval according to an exemplary embodiment of the present invention.

Referring to fig. 3, in step S201, a theoretical total power loss value corresponding to each internet power of the wind turbine generator is determined according to the electromagnetic power and the internet power of the wind turbine generator corresponding to each air density in the air density interval.

Here, if the theoretical total loss power value is used as the actual total loss power value of the wind turbine to diagnose the power loss condition of the wind turbine, the magnitude of the measured loss power value and the magnitude of the estimated loss power value (i.e., the unmeasurable loss power value) cannot be distinguished, and since the loss of the wind turbine has the characteristic of changing with the operation condition and the seasonal condition of the wind turbine, the determination of the total loss power value of the wind turbine is not accurate enough, which affects the accuracy of diagnosing the power loss condition of the wind turbine.

As an example, the theoretical total loss power value of the wind turbine may be a difference between the electromagnetic power and the grid power, and the electromagnetic power may be a product of the electromagnetic torque corresponding to each air density and the generator rotation speed.

For example, for any sampling period, the average value of the electromagnetic torque, the average value of the rotating speed of the generator and the power average value of the network power in any sampling period can be calculated, the electromagnetic power is obtained by the product of the average value of the electromagnetic torque and the average value of the rotating speed of the generator, and then the theoretical total power loss value is obtained by subtracting the obtained electromagnetic power and the power average value of the network power.

The sampling period may include a plurality of sampling moments, an average value of the internet power obtained at each sampling moment in the sampling period may be calculated, and the calculated average value may be determined as the power average value.

During the operation of the wind turbine generator, the blades absorb wind energy to drive the impeller to rotate so as to generate pneumatic torque, the generator electromagnetic torque given by a control system of the wind turbine generator must be matched with the pneumatic torque, and the direction of the generator electromagnetic torque is opposite to that of the pneumatic torque. When the electromagnetic torque is smaller than the aerodynamic torque, the impeller rotating speed is increased according to Newton's second law, and conversely, the impeller rotating speed is decreased. Generally, a control system of a wind turbine generator updates a given value of electromagnetic torque at a certain period according to output power of the wind turbine generator, so that the wind turbine generator can achieve optimal control at different wind speed sections as much as possible, that is, the electromagnetic power reflects wind energy absorbed by the wind turbine generator as a whole.

For example, the electromagnetic power may be calculated using the following formula:

P_e＝T_e×ω (3)

in formula (3), P_eIs electromagnetic power, T_eThe unit is electromagnetic torque, the unit is N.m, and omega is generator speed, the unit is rad/s.

The electromagnetic torque and the rotating speed of the generator of the wind turbine generator set in the operation process can be measured in various modes, and then the electromagnetic power of the wind turbine generator set can be calculated. The grid power of the wind turbine generator can also be actually measured in various ways, and under the condition, the difference value between the electromagnetic power and the grid power of the wind turbine generator is determined as the theoretical total loss power value of the wind turbine generator under different working conditions.

In step S202, an actually measured loss power value corresponding to each grid power of the wind turbine is determined.

As an example, the theoretical total loss power value may comprise a measured loss power value and an estimated loss power value. For example, the measured loss power value of the wind turbine may include a loss value of a power cable during operation of the wind turbine and a loss value of each electrical component included in the wind turbine. The loss value of the power cable can refer to the energy lost by the three-phase power cable of the generator from the cabin position to the box type transformer of the wind turbine generator in the running process of the wind turbine generator. The loss value of each electrical component mainly comprises energy lost by a heat dissipation system (such as a generator and a converter) in the operation process of the wind turbine generator, energy lost in the operation process of a yaw system and a pitch system, and self loss of each electrical component in each control cabinet.

In a preferred embodiment, the power cable loss value may be determined based on the generator terminal voltage value and the total resistance value of the power cable, and the loss value of each electrical component may be determined based on the power factor and the rated power of each electrical component.

For example, the measured loss power value of the wind turbine generator in the sampling period m may be calculated by the following formula:

in the formula (4), p_gridRepresenting the mean value of the power, P, of the real-time power on the Internet during the sampling period m₀(p_grid) To sampleThe measured loss power value within the period m,

the loss value of a power cable of the wind turbine generator is shown, u (t) is a voltage value of a terminal of the generator at a sampling moment t, r is a total resistance value of the power cable, and m is a time length of a sampling period.

p_i(t) represents the power rating of the ith electrical component at sampling time t, which may include, by way of example and not limitation, a yaw motor, a pitch motor, a radiator fan drive motor.

Representing the mean value of the power as p_gridThe power coefficient of the ith electrical component is in a value range of 0-1, when the wind turbine generator reaches rated power, the value of the power coefficient of the ith electrical component can be 1, i is not less than 1 and not more than k, and k is the number of the electrical components.

Here, the above equation (4) may be utilized to determine an actual power cable loss value and an actual loss value of each electrical component based on the generator terminal voltage value and the total resistance value of the power cable, and the power coefficient and rated power of each electrical component.

In step S203, an estimated loss power value corresponding to each internet access power is obtained according to the determined theoretical total loss power value and the determined actual loss power value.

For example, the estimated loss power value may include losses of the wind turbine in addition to the measured loss power value, and the estimated loss power value may include, as an example, a generator copper loss, which may refer to a loss generated by a copper winding of the generator during operation of the wind turbine, and a converter loss, which may be expressed as a converter efficiency.

For example, the difference between the determined theoretical total loss power value and the measured loss power value may be determined as an estimated loss power value corresponding to each internet access power in each sampling period.

For example, the estimated loss power value may be calculated using the following equation:

δ(p_grid)＝P_loss(p_grid)-P₀(p_grid) (5)

in the formula (5), δ (p)_grid) Is the average value p of power with the network_gridCorresponding estimated loss power value, P_loss(p_grid) Is the theoretical total loss power value, P, of the wind turbine₀(p_grid) Power mean value p for power on line_gridA corresponding measured loss power value.

In step S204, an internet power interval to which each internet power belongs is determined.

Here, the internet power interval to which the power average of the internet power of each sampling period belongs may be determined.

In step S205, for each internet power interval, an estimated loss average value of the estimated loss power values corresponding to the internet powers in the internet power interval is calculated, and the calculated estimated loss average value is used as the estimated loss power value corresponding to the internet power interval.

In order to ensure the accuracy of the determined corresponding relationship, the number of the estimated loss power values in each internet power interval is counted, and in order to ensure the sufficiency of the data, the number of the estimated loss power values in each internet power interval should be greater than or equal to a predetermined number.

For example, the average estimated loss corresponding to any internet power interval can be calculated by using the following formula:

in the formula (6), δ (p)_grid) To estimate the average loss value, delta_j(p_grid) The estimated loss power value is the jth estimated loss power value in any internet power interval, and n is the number of the estimated loss power values in any internet power interval.

It should be appreciated that the losses of the wind turbine are characteristic of changes in the operating conditions and seasonal conditions of the wind turbine (e.g., changes in ambient temperature, air density). For example, the condition that the loss of the wind turbine changes with the change of the operation condition of the wind turbine is as follows: according to the current control strategy of the wind turbine generator, before the wind turbine generator reaches the rated power, a variable pitch system of the wind turbine generator is in no action, when the wind speed exceeds the rated wind speed, the wind turbine generator enters a constant power control section, and redundant wind energy is discharged through the variable pitch system, so that the output power stability of the wind turbine generator is ensured, and the load safety of the wind turbine generator is ensured. A variable pitch system of the wind turbine generator is driven by a variable pitch motor, and a part of electric energy needs to be consumed in the working process of the variable pitch motor. On the other hand, the heat dissipation system of the whole machine, for example, a wind turbine generator or a converter heat dissipation system, increases the output of the wind turbine generator with the increase of the wind speed, the power element parts of the generator and the converter generate heat which gradually rises, and when the temperature exceeds the temperature threshold, the heat dissipation system is triggered, and the loss of the wind turbine generator is further increased.

The situation that the loss of the wind turbine generator changes along with the change of seasonal conditions is as follows: in summer, the general environmental temperature is high, after the wind turbine generator reaches rated power, the self heating of a converter power component or other electrical components of the wind turbine generator is high, at the moment, the electric energy consumed by a heat dissipation system is also high, and correspondingly, the self loss of the wind turbine generator is also high. On the contrary, the general ambient temperature is lower in winter, the working time of the heat dissipation system is generally shorter, and the self loss of the wind turbine generator is also smaller. In addition, in winter, because the ambient temperature is lower, the air density is higher than that in summer, the output of the wind turbine generator is higher than that in summer, and the wind turbine generator has smaller self loss in winter and winter, so that the output power of the wind turbine generator is generally higher than that in summer above the rated wind speed in winter and winter.

Aiming at the change characteristics of the loss of the wind turbine generator, historical operation data of the wind turbine generator under different working conditions, different seasons, different air densities and different temperatures are obtained as far as possible, so that a more accurate corresponding relation is established based on the obtained historical operation data. That is to say, the statistics of the complete machine loss of the wind turbine generator can be more representative by counting the loss distribution conditions of the wind turbine generator under the different conditions.

Returning to fig. 1, in step S30, a conformity index between the actual total loss power value and the corresponding standard total loss power value is calculated, and the power loss condition of the wind turbine generator is diagnosed based on the calculated conformity index.

Preferably, the method for diagnosing the power loss abnormality of the wind turbine according to the exemplary embodiment of the present invention may further include: and determining a standard total loss power value corresponding to each internet power interval of the wind turbine generator and each air density interval.

As an example, the standard total loss power value corresponding to any one of the internet power intervals of any one of the air density intervals of the wind turbine generator may be determined according to a standard estimated loss power value corresponding to the any one of the internet power intervals of the any one of the air density intervals and a standard actually measured loss power value corresponding to the any one of the internet power intervals of the any one of the air density intervals.

For example, the sum of the standard estimated loss power value corresponding to any one of the internet access power intervals in any one of the air density intervals and the standard measured loss power value corresponding to any one of the internet access power intervals in any one of the air density intervals can be determined as the standard total loss power value corresponding to any one of the internet access power intervals in any one of the air density intervals.

In a preferred embodiment, a plurality of standard total loss power values corresponding to different internet power intervals of the wind turbine generator and different air density intervals can be stored in the loss standard library.

In this case, a standard total loss power value corresponding to each internet power interval at each air density interval may be searched from the loss standard library.

Here, the loss standard library may be established based on historical operating data of the wind turbine, and it should be understood that, in order to ensure accuracy of a power loss condition diagnosis result of the wind turbine, a plurality of standard total loss power values in the loss standard library should be obtained in the same manner as an actual total loss power value is determined according to operating data of the wind turbine within a predetermined time period. That is, the method for processing the historical operation data of the wind turbine to generate the standard total loss power value should be the same as the method for processing the operation data of the wind turbine within the predetermined time period to generate the actual total loss power value. For example, when the two total power loss values are obtained, the data binning mode of the air density and the internet power should be the same, and the duration of the sampling period for acquiring the operation data should be the same.

In a preferred embodiment, a loss standard library may be respectively established for each type of wind turbine in a wind farm, that is, the wind turbine used for collecting historical operating data for establishing the loss standard library and the wind turbine used for performing power loss condition diagnosis based on the loss standard library are the same type and the same configuration wind turbines.

The steps for constructing the wear criteria library are described below with reference to fig. 4.

Fig. 4 shows a flowchart of the steps of building a wear criteria library according to an exemplary embodiment of the present invention.

Referring to fig. 4, in step S301, historical operation data of the wind turbine generator is acquired.

In step S302, data binning is performed according to the air density and the internet power in the acquired historical operating data, and an actually measured loss power value corresponding to each internet power interval in each air density interval is calculated.

Here, the air density and the internet power of each sampling period may be respectively determined according to the acquired historical operating data, and the air density and the internet power may be subjected to data binning in the same data binning processing manner as that for the operating data in a predetermined time period.

For example, all the air densities in the historical operating data are subjected to data binning, and a plurality of air density intervals are obtained. Here, the number of the plurality of air density sections obtained by data binning all the air densities and the value range of each air density section are the same as the number of the plurality of air density sections obtained by data binning all the air densities in a predetermined time period and the value range of each air density section.

Correspondingly, for each air density interval, performing data binning on the internet power corresponding to each air density in the air density interval to obtain a plurality of internet power intervals. Here, the number of the plurality of internet power intervals obtained by binning all the internet power and the value range of each internet power interval are the same as the number of the plurality of internet power intervals obtained by binning all the internet power in each air density interval within a predetermined time period and the value range of each internet power interval.

As an example, the measured loss power value corresponding to each internet power interval in each air density interval may be calculated by using the method of determining the measured loss power value described in step S202, and the details of this part of the present invention are not repeated herein.

In step S303, an estimated loss power value corresponding to each internet power interval in each air density interval is determined.

For example, the estimated loss power value corresponding to each internet power interval in each air density interval may be determined by determining the actual estimated loss power value corresponding to each internet power interval in each air density interval, which is not described in detail herein.

In step S304, for each internet power interval in each air density interval, a sum of an estimated loss power value and an actual loss power value corresponding to the internet power interval in the air density interval is determined as a standard total loss power value corresponding to the internet power interval in the air density interval.

For example, for each air density interval, the conformity index corresponding to the air density interval may be calculated according to a sum of ratios of an actual total loss power value and a standard total loss power value corresponding to each internet power interval in the air density interval.

In a preferred embodiment, the conformity index corresponding to any air density interval may be calculated in the following manner.

And respectively calculating the ratio of the actual total loss power value corresponding to each internet power interval under any air density interval to the standard total loss power value, calculating the ratio of the sum of all the ratios to the number of the internet power intervals, and determining the difference between the calculated ratio and 1 as the conformity index corresponding to any air density interval.

For example, the conformity index corresponding to any one of the air density intervals may be calculated using the following formula:

in the formula (7), C (ρ)_a) Represents the interval ρ of the a-th air density_aCorresponding conformity index, P_loss(p_b,ρ_a) Denotes the first_aIndividual air density interval rho_aThe b-th lower internet power interval p_bCorresponding actual total loss power value, P'_loss(p_b,ρ_a) Represents the a-th air density interval ρ_aThe b-th lower internet power interval p_bB is more than or equal to 1 and less than or equal to R which is the a-th air density interval rho_aThe number of the lower internet power intervals.

After the conformity index corresponding to each air density interval is calculated and obtained for each air density interval, the power loss condition of the wind turbine generator in each air density interval can be diagnosed in the following way.

For example, for each air density interval, if the calculated conformity index is greater than a set threshold, it is determined that the power loss of the wind turbine generator in the air density interval is abnormal, and if the calculated conformity index is less than or equal to the set threshold, it is determined that the power loss of the wind turbine generator in the air density interval is not abnormal.

As an example, when C (ρ)_a) And when the power loss is more than 0, the actual total loss power value of the wind turbine generator is higher than the standard total loss power value, namely, the power loss of the wind turbine generator is higher and abnormal. When C (ρ)_a) When the total loss power value is equal to 0, the actual total loss power value and the standard total loss of the wind turbine generator are expressedThe power consumption values are equal and no anomalies exist. When C (ρ)_a) When the power loss is less than 0, the actual total loss power value of the wind turbine generator is lower than the standard total loss power value, namely, the power loss of the wind turbine generator is low and no abnormity exists.

In a preferred embodiment, the conformity indexes of all the wind power sets in the wind power plant can be calculated through the method, and the wind power sets are arranged in a descending order according to the conformity indexes, so that the wind power set with the worst power loss performance or the best performance in the wind power plant is determined.

As shown in fig. 5, the apparatus for diagnosing a power loss abnormality of a wind turbine according to an exemplary embodiment of the present invention includes: a power acquisition module 10, an actual total loss determination module 20 and a compliance determination module 30.

Specifically, the power obtaining module 10 obtains the power of the wind turbine generator during a predetermined time period.

The actual total loss determining module 20 determines an actual total loss power value of the wind turbine generator based on the power of the grid during a predetermined time period.

Here, the actual total loss determining module 20 may determine an actual total loss power value corresponding to the acquired grid power of the wind turbine generator. In a preferred embodiment, the diagnostic apparatus may further include a density obtaining module (not shown in the figure) for obtaining an air density of a location where the wind turbine is located within a predetermined time period, in which case the actual total loss determining module 20 may determine an actual loss power value of the wind turbine corresponding to the obtained air density and the grid power.

That is to say, the power obtaining module 10 may separately bin the obtained air density and the obtained internet power within the predetermined time period, so that the actual total loss determining module 20 determines the actual loss power value of the wind turbine generator in each air density interval and each internet power interval.

In a preferred embodiment, the power harvesting module 10 may include: a density data binning sub-module 101 and a power data binning sub-module 102.

Specifically, the density data binning submodule 101 performs data binning according to the air density of the position of the wind turbine generator in a predetermined time period to obtain a plurality of air density intervals, and obtains the internet access power corresponding to each air density in each air density interval.

The power data binning submodule 102 performs data binning on each air density interval according to all internet power in the air density interval to obtain a plurality of internet power intervals.

In this case, the actual total loss determining module 20 may determine an actual total loss power value corresponding to each internet power interval of the wind turbine generator and each air density interval.

As an example, the actual total loss determining module 20 may determine the actual total loss power value corresponding to any internet access power interval of the wind turbine generator and any air density interval according to the actual estimated loss power value and the actual measured loss power value corresponding to any internet access power interval of any air density interval.

For example, the actual total loss determining module 20 may determine the sum of the actual estimated loss power value corresponding to any one of the internet power intervals in any one of the air density intervals and the actual measured loss power value corresponding to any one of the internet power intervals in any one of the air density intervals as the actual total loss power value corresponding to any one of the internet power intervals in any one of the air density intervals.

In a preferred example, the actual measured loss power value corresponding to any one of the internet power intervals under any one of the air density intervals may include an actual power cable loss value corresponding to any one of the internet power intervals under any one of the air density intervals during the operation of the wind turbine generator and an actual loss value of each electrical component included in the wind turbine generator.

As an example, the actual power cable loss value may be determined based on the generator terminal voltage value and the total resistance value of the power cable, and the actual loss value of each electrical component may be determined based on the power factor and the rated power of each electrical component.

The actual total loss determining module 20 may determine the actual estimated loss power value corresponding to any internet access power interval in any air density interval in the following manner.

The actual total loss determining module 20 determines an actual estimated loss power value corresponding to any internet access power interval in any air density interval based on a predetermined correspondence relationship between the internet access power intervals and the estimated loss power values in the air density intervals.

In a preferred embodiment, the apparatus for diagnosing power loss abnormality of a wind turbine generator according to an exemplary embodiment of the present invention may further include: the correspondence relationship establishing module 50 is configured to determine correspondence relationships between a plurality of internet power intervals and a plurality of estimated loss power values under a plurality of air density intervals.

For example, the correspondence relationship establishing module 50 may determine the above correspondence relationship in the following manner.

Acquiring historical operating data of the wind turbine generator, determining an air density interval to which the air density in the historical operating data belongs, and executing the following processing for each air density interval: according to the electromagnetic power and the internet power of the wind turbine generator corresponding to each air density in the air density interval, determining a theoretical total loss power value corresponding to each internet power of the wind turbine generator, determining an actual loss power value corresponding to each internet power of the wind turbine generator, obtaining an estimated loss power value corresponding to each internet power according to the determined theoretical total loss power value and the actual loss power value, determining an internet power interval to which each internet power belongs, calculating an estimated loss average value of the estimated loss power values corresponding to each internet power in the internet power interval aiming at each internet power interval, and taking the calculated estimated loss average value as the estimated loss power value corresponding to the internet power interval.

As an example, the theoretical total loss power value may be a difference between the electromagnetic power, which may be a product of the electromagnetic torque corresponding to each air density and the generator speed, and the grid power.

The conformity determining module 30 calculates a conformity index between the actual total loss power value and the corresponding standard total loss power value, and diagnoses the power loss condition of the wind turbine generator based on the calculated conformity index.

Preferably, the apparatus for diagnosing power loss abnormality of a wind turbine generator according to an exemplary embodiment of the present invention may further include: and the standard total loss determining module 40 is used for acquiring a standard total loss power value corresponding to each internet power interval of the wind turbine generator and each air density interval.

As an example, the standard total loss determining module 40 may determine a standard total loss power value corresponding to any internet power interval of the wind turbine generator and any internet power interval of any air density interval according to a standard estimated loss power value corresponding to any internet power interval of any air density interval and a standard actually measured loss power value corresponding to any internet power interval of any air density interval.

For example, the standard total loss determining module 40 may determine a sum of a standard estimated loss power value corresponding to any one of the internet power intervals in any one of the air density intervals and a standard measured loss power value corresponding to any one of the internet power intervals in any one of the air density intervals as a standard total loss power value corresponding to any one of the internet power intervals in any one of the air density intervals for the wind turbine generator system.

In this case, the standard total loss determination module 40 may search the loss standard library for a standard total loss power value corresponding to each internet power interval at each air density interval.

Optionally, the apparatus for diagnosing power loss abnormality of a wind turbine generator according to an exemplary embodiment of the present invention may further include: and a loss standard library establishing module 60 for establishing a loss standard library.

For example, the loss criteria library creation module 60 may construct the loss criteria library in the following manner.

Acquiring historical operating data of the wind turbine generator; performing data binning according to the air density and the internet power in the acquired historical operating data respectively, and calculating an actually measured loss power value corresponding to each internet power interval under each air density interval; determining an estimated loss power value corresponding to each internet access power interval under each air density interval; and determining the sum of the estimated loss power value and the actually measured loss power value corresponding to the internet power interval under the air density interval as the standard total loss power value corresponding to the internet power interval under the air density interval aiming at each internet power interval under each air density interval.

For example, the conformity determining module 30 may calculate, for each air density interval, a conformity index corresponding to the air density interval according to a sum of ratios of an actual total loss power value and a standard total loss power value corresponding to each internet power interval in the air density interval.

In a preferred embodiment, the conformity determination module 30 may calculate the conformity index corresponding to any air density interval in the following manner.

Respectively calculating the ratio of the actual total loss power value corresponding to each internet power interval in any air density interval to the standard total loss power value, calculating the ratio of the sum of all the ratios to the number of the internet power intervals, and determining the difference between the calculated ratio and 1 as the conformity index corresponding to any air density interval.

After calculating the conformity index corresponding to each air density interval for each air density interval, the conformity determining module 30 may diagnose the power loss condition of the wind turbine generator in each air density interval in the following manner.

For each air density interval, if the calculated conformity index is greater than a set threshold, the conformity determination module 30 determines that the power loss of the wind turbine generator in the air density interval is abnormal, and if the calculated conformity index is less than or equal to the set threshold, the conformity determination module 30 determines that the power loss of the wind turbine generator in the air density interval is not abnormal.

In a preferred embodiment, the apparatus for diagnosing power loss abnormality of wind turbines according to an exemplary embodiment of the present invention may further include a sorting module (not shown in the drawings), where the sorting module obtains the conformity indexes of all wind turbines in the wind farm, and performs descending sorting on all wind turbines according to the conformity indexes, so as to determine a wind turbine with the worst power loss performance or the best performance in the wind farm.

There is also provided, in accordance with an exemplary embodiment of the present invention, a computing device. The computing device includes a processor and a memory. The memory is for storing a computer program. The computer program is executed by a processor to cause the processor to execute the above-described method for diagnosing a power loss abnormality of a wind turbine generator.

There is also provided, in accordance with an exemplary embodiment of the present invention, a computer-readable storage medium storing a computer program. The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to execute the above-described method of diagnosing a power loss abnormality of a wind turbine generator. The computer readable recording medium is any data storage device that can store data read by a computer system. Examples of the computer-readable recording medium include: read-only memory, random access memory, read-only optical disks, magnetic tapes, floppy disks, optical data storage devices, and carrier waves (such as data transmission through the internet via wired or wireless transmission paths).

According to the method and the device for diagnosing the power loss abnormality of the wind turbine generator, the power loss abnormality condition is diagnosed based on the complete machine loss of the wind turbine generator, so that the power loss diagnosis of each wind turbine generator in the wind power plant can be accurately based, and the problem of inaccurate diagnosis of the existing power loss condition is solved.

In addition, according to the diagnosis method and the diagnosis device for the power loss abnormality of the wind turbine generator, the power loss of the wind turbine generator can be diagnosed more accurately by considering the difference of the loss power values in different internet power intervals in different air density intervals.

In addition, by adopting the method and the device for diagnosing the abnormal power loss of the wind turbine generator, the influence of the actual operation condition of the wind turbine generator and the seasonal condition change on the complete machine loss is considered, and the complete machine loss of the wind turbine generator under different working conditions and different seasonal conditions can be accurately estimated.

In addition, by adopting the method and the device for diagnosing the abnormal power loss of the wind turbine generator, which are provided by the exemplary embodiment of the invention, the accuracy of the obtained diagnosis result of the power loss condition of the wind turbine generator is higher, so that whether the reason influencing the power curve deterioration of the wind turbine generator is caused by the abnormal self-loss of the wind turbine generator or not can be rapidly positioned. In other words, the diagnosis result of the power loss condition of the wind turbine generator can be used as one of the means for diagnosing the power curve problem.

While the invention has been shown and described with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes and modifications may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims

1. A method for diagnosing power loss abnormality of a wind turbine generator is characterized by comprising the following steps:

acquiring the internet surfing power of the wind turbine generator in a preset time period;

determining an actual total loss power value of the wind turbine generator based on the internet power in the preset time period;

calculating the conformity index of the actual total loss power value and the corresponding standard total loss power value, diagnosing the power loss condition of the wind turbine generator based on the calculated conformity index,

the method for acquiring the internet power of the wind turbine generator in the preset time period comprises the following steps:

performing data binning according to the air density of the position of the wind turbine generator in a preset time period to obtain a plurality of air density intervals, and acquiring the internet surfing power corresponding to each air density in each air density interval;

and aiming at each air density interval, performing data binning according to all internet power in the air density interval to obtain a plurality of internet power intervals.

2. The diagnostic method of claim 1, wherein an actual total power loss value of the wind turbine corresponding to each grid power interval under each air density interval is determined,

wherein the diagnostic method further comprises: and determining a standard total loss power value corresponding to each internet power interval of the wind turbine generator and each air density interval.

3. The diagnosis method according to claim 1 or 2, wherein the actual total loss power value of the wind turbine corresponding to any one of the Internet power intervals in any one of the air density intervals is determined according to the actual estimated loss power value and the actual measured loss power value corresponding to the any one of the Internet power intervals in the any one of the air density intervals,

the standard total loss power value corresponding to any internet power interval of the wind turbine generator and any air density interval is determined according to a standard estimated loss power value and a standard actual measurement loss power value corresponding to any internet power interval of any air density interval.

4. The diagnosis method according to claim 3, wherein the actual measured loss power value corresponding to any one of the Internet power intervals in any one of the air density intervals comprises an actual power cable loss value corresponding to any one of the Internet power intervals in any one of the air density intervals during the operation of the wind turbine generator and an actual loss value of each electrical component included in the wind turbine generator,

wherein the actual power cable loss value is determined based on the generator terminal voltage value and the total resistance value of the power cable, and the actual loss value of each electrical component is determined based on the power coefficient and the rated power of each electrical component.

5. The diagnostic method of claim 3, wherein the actual estimated loss power value corresponding to the any Internet power interval at the any air density interval is determined by:

and determining an actual estimated loss power value corresponding to any internet power interval in any air density interval based on the corresponding relationship between a plurality of internet power intervals and a plurality of estimated loss power values in a plurality of predetermined air density intervals.

6. The diagnostic method of claim 5, wherein the correspondence between the plurality of Internet power intervals and the plurality of estimated loss power values for the plurality of air density intervals is determined by:

acquiring historical operating data of the wind turbine generator, determining an air density interval to which the air density in the historical operating data belongs, executing the following steps aiming at each air density interval,

determining theoretical total power loss values of the wind turbine generator set corresponding to the internet power according to the electromagnetic power and the internet power of the wind turbine generator set corresponding to each air density in the air density interval,

determining the actually measured loss power value of the wind turbine generator corresponding to each internet power,

obtaining an estimated loss power value corresponding to each internet access power according to the determined theoretical total loss power value and the actually measured loss power value,

determining the internet power interval to which each internet power belongs,

and calculating the estimated loss average value of the estimated loss power value corresponding to each internet power in the internet power interval aiming at each internet power interval, and taking the calculated estimated loss average value as the estimated loss power value corresponding to the internet power interval.

7. The diagnostic method of claim 6, wherein the theoretical total loss power value is a difference between an electromagnetic power and an on-grid power, and the electromagnetic power is a product of an electromagnetic torque corresponding to each air density and a generator speed.

8. The diagnostic method of claim 3, wherein a standard total loss power value corresponding to each of the power-on-grid intervals at each of the air density intervals is searched from a loss standard library,

the loss standard library stores a plurality of standard total loss power values corresponding to different internet power intervals of the wind turbine generator and different air density intervals.

9. The diagnostic method of claim 8, wherein the library of attrition criteria is constructed by:

acquiring historical operating data of the wind turbine generator;

performing data binning according to the air density and the internet power in the acquired historical operating data respectively, and calculating an actually measured loss power value corresponding to each internet power interval under each air density interval;

determining an estimated loss power value corresponding to each internet access power interval under each air density interval;

and determining the sum of the estimated loss power value and the actually measured loss power value corresponding to the internet power interval under each air density interval as the standard total loss power value corresponding to the internet power interval under the air density interval aiming at each internet power interval under each air density interval.

10. The diagnostic method of claim 1, wherein the step of calculating an index of compliance of the actual total loss power value with the corresponding standard total loss power value comprises:

and aiming at each air density interval, calculating a conformity index corresponding to the air density interval according to the sum of the ratio of the actual total loss power value corresponding to each internet power interval under the air density interval to the standard total loss power value.

11. The diagnostic method of claim 10, wherein the conformity index corresponding to any one of the air density intervals is calculated by:

respectively calculating the ratio of the actual total loss power value corresponding to each internet power interval in any air density interval to the standard total loss power value,

and calculating the ratio of the sum of all the ratios to the number of the internet power intervals, and determining the difference between the calculated ratio and 1 as a conformity index corresponding to any air density interval.

12. The diagnostic method of claim 10, wherein the step of diagnosing the power loss of the wind turbine based on the calculated conformity index comprises:

and for each air density interval, if the calculated conformity index is greater than a set threshold, determining that the power loss of the wind turbine generator in the air density interval is abnormal, and if the calculated conformity index is less than or equal to the set threshold, determining that the power loss of the wind turbine generator in the air density interval is not abnormal.

13. A diagnostic device for power loss abnormality of a wind turbine generator, characterized by comprising:

the power acquisition module is used for acquiring the internet power of the wind turbine generator within a preset time period;

the actual total loss determining module is used for determining an actual total loss power value of the wind turbine generator based on the internet power in the preset time period;

a conformity determining module for calculating conformity index of the actual total loss power value and the standard total loss power value and diagnosing the power loss condition of the wind turbine generator based on the calculated conformity index,

wherein, the power acquisition module includes:

the density data binning submodule is used for performing data binning according to the air density of the position of the wind turbine generator in a preset time period to obtain a plurality of air density intervals and acquiring the internet power corresponding to each air density in each air density interval;

and the power data binning submodule is used for performing data binning according to all the internet access power in each air density interval to obtain a plurality of internet access power intervals.

14. The diagnostic apparatus of claim 13, wherein the actual total loss determination module determines an actual total loss power value for the wind turbine corresponding to each of the grid power intervals for each of the air density intervals,

wherein the diagnostic device further comprises: and the standard total loss determining module is used for determining a standard total loss power value corresponding to each grid power interval of the wind turbine generator and each air density interval.

15. The diagnostic apparatus according to claim 13 or 14, wherein the actual total loss power value of the wind turbine corresponding to any one of the grid-connected power intervals in any one of the air density intervals is determined according to the actual estimated loss power value and the actual measured loss power value corresponding to said any one of the grid-connected power intervals in said any one of the air density intervals,

16. The diagnostic apparatus according to claim 15, wherein the actual measured power loss value corresponding to any one of the power grid sections in any one of the air density sections includes an actual power cable loss value corresponding to any one of the power grid sections in any one of the air density sections during operation of the wind turbine generator and an actual loss value of each electrical component included in the wind turbine generator,

17. The diagnostic apparatus of claim 15, wherein the actual total loss determining module determines the actual estimated loss power value corresponding to the any one of the internet power intervals at the any one of the air density intervals by:

and determining an actual estimated loss power value corresponding to any one of the internet access power intervals under any one of the air density intervals based on a predetermined corresponding relationship between the internet access power intervals and the estimated loss power values under the air density intervals.

18. The diagnostic apparatus according to claim 17, further comprising a correspondence relationship establishing module that determines correspondence relationships between a plurality of internet power intervals and a plurality of estimated loss power values for a plurality of air density intervals by:

acquiring historical operating data of the wind turbine generator, determining an air density interval to which the air density in the historical operating data belongs, executing the following processing aiming at each air density interval,

according to the electromagnetic power and the internet power of the wind turbine generator corresponding to each air density in the air density interval, determining the theoretical total loss power value of the wind turbine generator corresponding to each internet power,

determining the internet power interval to which each internet power belongs,

19. The diagnostic apparatus of claim 18, wherein the theoretical total loss power value is a difference between an electromagnetic power and an on-grid power, and the electromagnetic power is a product of an electromagnetic torque corresponding to each air density and a generator speed.

20. The diagnostic apparatus of claim 15, wherein the standard total loss determination module searches a standard total loss power value corresponding to each of the power-on-grid intervals at each of the air density intervals from a loss standard library,

21. The diagnostic apparatus of claim 20, further comprising a wear criteria library building module that builds a wear criteria library by:

acquiring historical operating data of the wind turbine generator;

determining an estimated loss power value corresponding to each internet power interval under each air density interval;

22. The diagnostic apparatus as claimed in claim 13, wherein the conformity determining module calculates, for each air density interval, a conformity index corresponding to the air density interval according to a sum of ratios of an actual total loss power value and a standard total loss power value corresponding to each internet power interval in the air density interval.

23. The diagnostic device of claim 22, wherein the conformity determining module calculates the conformity index corresponding to any air density interval by:

24. The diagnostic apparatus according to claim 22, wherein for each air density interval, the conformity determination module determines that there is an abnormality in the power loss of the wind turbine generator in the air density interval if the calculated conformity index is greater than a set threshold value, and determines that there is no abnormality in the power loss of the wind turbine generator in the air density interval if the calculated conformity index is less than or equal to the set threshold value.

25. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the method for diagnosing a power loss abnormality of a wind turbine generator set according to any one of claims 1 to 12.

26. A computing device, wherein the computing device comprises:

a processor;

a memory storing a computer program which, when executed by the processor, implements the method of diagnosing a power loss anomaly of a wind turbine generator as set forth in any one of claims 1 to 12.