A parameter optimization method for a wind turbine generator system and a related device

Abstract

The application discloses a parameter optimization method and related device of a wind turbine generator set, comprising: determining m environment parameter intervals according to a parameter range of an environment parameter, and determining n wind speed parameter intervals according to a parameter range of a wind speed parameter; determining a joint state probability of a target wind turbine generator set under different interval combinations, and obtaining power generation loss of the target wind turbine generator set corresponding to different environment parameter intervals based on the joint state probability under the different interval combinations; determining a reference parameter interval of an environment parameter suitable for the target wind turbine generator set, in a case that the power generation loss satisfies a power generation threshold condition; and optimizing the target wind turbine generator set according to the reference parameter interval. Whether the power generation loss satisfies the power generation threshold condition can reduce the parameter range of the environment parameter to the reference parameter interval, and the target wind turbine generator set is optimized based on the smaller reference parameter interval, which is more targeted and reduces the overall cost of the target wind turbine generator set.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wind power generation, in particular to a parameter optimization method of a wind turbine generator system and a related device. BACKGROUND

[0002] The working principle of a wind turbine generator system is to drive a generator to generate electricity by rotating a rotor driven by wind, and then driving the generator to generate electricity by increasing the speed of the generator through an electrical transmission system, so as to convert wind energy into electrical energy. Wind turbine generator system manufacturers, owners and operators are looking for ideal electrical transmission system solutions to improve annual power generation, minimize life cycle costs and meet the most stringent grid connection requirements.

[0003] When manufacturing a wind turbine generator system, the design boundary of the electrical transmission system is generally determined based on the relevant provisions of the International Electrotechnical Commission (IEC) or the People's Republic of China National Standard (GB), such as the environmental parameter design boundary suitable for the wind turbine generator system, the wind speed design boundary, etc.

[0004] However, the design boundary determined according to the IEC or GB is relatively conservative in most cases, or the determined design boundary is relatively wide, resulting in a higher overall cost of the wind turbine generator system. SUMMARY

[0005] To solve the above problems, the present application provides a parameter optimization method of a wind turbine generator system and a related device for narrowing the design boundary of the electrical transmission system and reducing the overall cost of the wind turbine generator system.

[0006] In one aspect, the present application provides a parameter optimization method of a wind turbine generator system, the method comprising:

[0007] obtaining an environmental parameter of a target wind turbine generator system varying with time, and a wind speed parameter of a target wind farm where the target wind turbine generator system is located varying with time;

[0008] determining m environmental parameter intervals according to a parameter range of the environmental parameter, and determining n wind speed parameter intervals according to a parameter range of the wind speed parameter;

[0009] determining a joint state probability of the target wind turbine generator system under different interval combinations, the joint state probability being used to identify a proportion of an accumulated time length of the target wind turbine generator system running under different interval combinations to a total time length of the target wind turbine generator system, the interval combination being determined according to different combinations of the m environmental parameter intervals and the n wind speed parameter intervals;

[0010] obtain power generation loss of the target wind turbine generator set corresponding to different environmental parameter intervals based on the joint state probability under the different interval combinations;

[0011] determine a reference parameter interval of the environmental parameter applicable to the target wind turbine generator set, if the environmental parameter interval corresponding to the power generation loss satisfying the power generation threshold condition;

[0012] optimize the target wind turbine generator set according to the reference parameter interval.

[0013] Optionally, the optimizing the target wind turbine generator set according to the reference parameter interval comprises:

[0014] determine the reference parameter interval as an optimization parameter range of the target wind turbine generator set, and optimize the target wind turbine generator set according to the optimization parameter range.

[0015] Optionally, the optimizing the target wind turbine generator set according to the reference parameter interval comprises:

[0016] determine a levelized electricity cost corresponding to the kth environmental parameter interval according to the power generation loss of the kth environmental parameter interval and the construction cost of the target wind turbine generator set in the kth environmental parameter interval, the levelized electricity cost being used to identify the power generation cost of the target wind turbine generator set after the levelized cost and the power generation loss;

[0017] determine an optimization parameter range according to the difference between the levelized electricity costs of two adjacent environmental parameter intervals, and optimize the target wind turbine generator set through the optimization parameter range.

[0018] Optionally, the determining the levelized electricity cost according to the power generation loss of the kth environmental parameter interval and the construction cost of the target wind turbine generator set in the kth environmental parameter interval comprises:

[0019] determine the levelized electricity cost according to the power generation loss of the kth environmental parameter interval, the construction cost of the target wind turbine generator set in the kth environmental parameter interval, a discount rate of the target wind turbine generator set, a discount tax of the target wind turbine generator set, a residual value of the target wind turbine generator set and an operation and maintenance cost of the target wind turbine generator set.

[0020] Optionally, if the wind speed parameter is obtained through a wind measurement tower of the target wind farm, the determining the joint state probability of the target wind turbine generator set under different interval combinations comprises:

[0021] obtaining a first cumulative duration of the target wind turbine operating in the ith environmental parameter interval and a second cumulative duration of the wind measurement tower operating in the jth wind speed parameter interval, i < m, j < n;

[0022] determining a total duration of the target wind turbine operating according to the start and end time, the data missing duration and the data abnormal duration corresponding to the parameter range of the environmental parameter, and determining a total duration of the wind measurement tower operating according to the start and end time, the data missing duration and the data abnormal duration corresponding to the parameter range of the wind speed parameter;

[0023] determining a joint state probability of the target wind turbine under a target interval combination according to the first cumulative duration, the second cumulative duration, the total duration of the target wind turbine operating and the total duration of the wind measurement tower operating, the target interval combination being a combination of the ith environmental parameter interval and the jth wind speed parameter interval.

[0024] Optionally, the determining the joint state probability of the target wind turbine under different interval combinations comprises:

[0025] determining an interval combination corresponding to the full-load wind speed of the target wind turbine according to the full-load wind speed of the target wind turbine;

[0026] determining a joint state probability of the target wind turbine under the interval combination corresponding to the full-load wind speed of the target wind turbine;

[0027] The obtaining the power generation loss of the target wind turbine corresponding to different environmental parameter intervals based on the joint state probability under the different interval combinations comprises:

[0028] The obtaining the power generation loss of the target wind turbine corresponding to different environmental parameter intervals based on the joint state probability under the interval combination corresponding to the full-load wind speed of the target wind turbine.

[0029] Optionally, the obtaining the power generation loss of the target wind turbine corresponding to different environmental parameter intervals based on the joint state probability under the interval combination corresponding to the full-load wind speed of the target wind turbine comprises:

[0030] The obtaining the power generation loss of the target wind turbine corresponding to different environmental parameter intervals based on the joint state probability under the interval combination corresponding to the full-load wind speed of the target wind turbine, the single-machine rated capacity of the target wind turbine, the de-rating operation ratio of the target wind turbine and the availability of the target wind turbine.

[0031] In another aspect, an embodiment of the present application provides a parameter optimization device for a wind turbine, the device comprising:

[0032] The parameter acquisition unit is configured to acquire an environmental parameter of a target wind turbine generator set changing over time and a wind speed parameter of a target wind farm where the target wind turbine generator set is located changing over time;

[0033] The parameter interval determination unit is configured to determine m environmental parameter intervals according to a parameter range of the environmental parameter and n wind speed parameter intervals according to a parameter range of the wind speed parameter;

[0034] The joint state probability determination unit is configured to determine a joint state probability of the target wind turbine generator set under different interval combinations, the joint state probability being used to identify a proportion of a cumulative running time of the target wind turbine generator set under the different interval combinations to a total running time of the target wind turbine generator set, the interval combinations being determined according to different combinations of the m environmental parameter intervals and the n wind speed parameter intervals;

[0035] The power generation loss determination unit is configured to obtain a power generation loss of the target wind turbine generator set corresponding to different environmental parameter intervals based on the joint state probability under the different interval combinations;

[0036] The reference parameter interval determination unit is configured to determine a reference parameter interval of the environmental parameter suitable for the target wind turbine generator set according to an environmental parameter interval corresponding to a power generation threshold condition satisfied by the power generation loss;

[0037] The optimization unit is configured to optimize the target wind turbine generator set according to the reference parameter interval.

[0038] In another aspect, the present application provides a computer device, the device comprising a processor and a memory:

[0039] The memory is configured to store program code and transmit the program code to the processor;

[0040] The processor is configured to execute the method according to the instructions in the program code.

[0041] In another aspect, the present application provides a computer readable storage medium for storing a computer program, the computer program being used to execute the method according to the above aspect.

[0042] Compared with the prior art, the above technical solutions of the present application have the following advantages:

[0043] Obtain the environmental parameters of the target wind turbine changing over time and the wind speed parameters of the target wind farm where the target wind turbine is located changing over time, divide the parameter range of the environmental parameters into m environmental parameter intervals, divide the parameter range of the wind speed parameters into n wind speed parameter intervals, combine the m environmental parameter intervals and the n wind speed parameter intervals into a plurality of interval combinations respectively, determine the joint state probability of the target wind turbine under different interval combinations, the joint state probability is used to identify the proportion of the cumulative running time of the target wind turbine under different interval combinations in the total running time of the target wind turbine, obtain the power generation loss of the target wind turbine corresponding to different environmental parameter intervals based on the joint state probability under different interval combinations, determine the environmental parameter reference interval suitable for the target wind turbine as the environmental parameter interval corresponding to the power generation loss meeting the power generation threshold condition, determine the optimization parameter range of the target wind turbine according to the reference parameter interval, and optimize the target wind turbine through the optimization parameter range. Therefore, whether the power generation loss meets the power generation threshold condition can reduce the parameter range of the environmental parameters to the reference parameter interval, optimize the target wind turbine based on the smaller reference parameter interval, which is more targeted, so that the target wind turbine is suitable for the target wind farm while reducing the overall cost of the target wind turbine. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0045] Figure 1 A flow chart of a parameter optimization method of a wind turbine provided by the present application;

[0046] Figure 2 A schematic diagram of a parameter optimization device of a wind turbine provided by the present application;

[0047] Figure 3 A structural diagram of a computer device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0048] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application, so that those skilled in the art can better understand the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0049] Referring to Figure 1 , Figure 1 is a flowchart of a parameter optimization method of a wind turbine generator set provided by the present application. The method can include the following steps S101-S106.

[0050] S101: Obtain an environmental parameter of a target wind turbine generator set changing over time, and a wind speed parameter of a target wind field where the target wind turbine generator set is located changing over time.

[0051] The environmental parameter and the wind speed parameter can be obtained from a wind resource data set, which includes historical data of wind turbine generators and a wind measurement tower. The wind measurement tower is a newly emerging tower type for data collection of wind resources. The wind measurement tower is erected in the target wind field to analyze the actual situation of wind energy resources in the wind field. The number of wind turbines in the target wind turbine generator set is greater than or equal to 1.

[0052] It should be noted that the environmental parameter can be a temperature parameter, a pressure parameter, a humidity parameter, etc. The present application does not make specific limitations on this.

[0053] As a possible implementation manner, if no wind turbine generator set has been built in the wind field, the environmental parameter of the wind field changing over time can be obtained, and the environmental parameter of the wind field changing over time is taken as the environmental parameter of the target wind turbine generator set to be built changing over time.

[0054] S102: Determine m environmental parameter intervals according to the parameter range of the environmental parameter, and determine n wind speed parameter intervals according to the parameter range of the wind speed parameter.

[0055] According to the environmental parameter, the wind speed parameter, and IEC (such as IEC60034-1) or GB, the parameter range of the environmental parameter of the target wind turbine generator set and the range of the wind speed parameter can be determined.

[0056] The parameter range of the environmental parameter can be represented as , wherein, min represents a lower limit value of the environmental parameter, max represents an upper limit value of the environmental parameter. The parameter range of the wind speed parameter can be represented as , ​a lower limit value of the wind speed parameter, an upper limit value of the wind speed parameter.

[0057] After determining the parameter range, the parameter range of the environmental parameter is divided into n environmental parameter intervals, and n wind speed parameter intervals are determined according to the parameter range of the wind speed parameter. Specifically:

[0058] The interval of the environmental parameter can be represented as wherein, , is a design interval of the environmental parameter, is a lower limit value of the environmental parameter interval, is an upper limit value of the environmental parameter interval.

[0059] The interval of the wind speed parameter can be represented as wherein, , is a design interval of the wind speed parameter, is a lower limit value of the wind speed parameter interval, is an upper limit value of the wind speed parameter interval.

[0060] S103: Determine the joint state probability of the target wind turbine under different interval combinations.

[0061] The ith environmental parameter interval and the jth wind speed parameter interval can be determined as an interval combination, and different interval combinations can be determined according to different combinations of the m environmental parameter intervals and the n wind speed parameter intervals. The joint state probability of the wind turbine under different interval combinations can be different, wherein the joint state probability is used to identify the proportion of the cumulative length of the target wind turbine running under different interval combinations to the total length of the target wind turbine running.

[0062] When the wind speed parameter is obtained through a wind measurement tower in the target wind farm, the manner of obtaining the joint state probability can refer to S201-S203:

[0063] S201: Obtain a first cumulative length of the target wind turbine running in the ith environmental parameter interval, and a second cumulative length of the wind measurement tower running in the jth wind speed parameter interval, wherein i

[0064] S202: Determine the total length of the target wind turbine running according to the start time, the data missing length and the data abnormal length corresponding to the parameter range of the environmental parameter, and determine the total length of the wind measurement tower running according to the end time, the data missing length and the data abnormal length corresponding to the parameter range of the wind speed parameter.

[0065] S203: Determine a joint state probability of the target wind turbine generator set under a target interval combination according to the first cumulative time length, the second cumulative time length, a total time length of the target wind turbine generator set running, and a total time length of the wind measurement tower running.

[0066] The target interval combination is a combination of the i th environment parameter interval and the j th wind speed parameter interval.

[0067] The above process can be specifically referred to formula (1):

[0068] (1)

[0069] Wherein:

[0070] The joint state probability is represented by P (i, j) ;

[0071] k1 is the number of wind turbine generators in the target wind turbine generator set, and k2 is the number of wind measurement towers in the target wind farm;

[0072] is a cumulative time length of the target wind turbine generator set running under the interval combination determined by the i th environment parameter interval and the j th wind speed parameter interval, is a cumulative time length of the wind measurement tower running in the target wind farm under the interval combination determined by the i th environment parameter interval and the j th wind speed parameter interval;

[0073] is a correction parameter of the target wind turbine generator set, is a correction parameter of the wind measurement tower;

[0074] is a start and end time of the target wind turbine generator set, is a start and end time of the wind measurement tower;

[0075] is a data missing time length of the target wind turbine generator set, is a data missing time length of the wind measurement tower;

[0076] is a data abnormal time length of the target wind turbine generator set, is a data abnormal time length of the wind measurement tower.

[0077] As a possible implementation manner, The value range of is [1, 5], The value range of is [1, 3].

[0078] As a possible implementation manner, each pair of adjacent interval of the environmental parameter interval and the wind speed parameter interval can be determined as an interval combination, and the joint state probability of the interval combination is determined. According to formula (1), the probability matrix corresponding to the joint state probability can be obtained, and the size of the probability matrix is .

[0079] In S104, the power generation loss of the target wind turbine corresponding to different environmental parameter intervals is obtained based on the joint state probability under different interval combinations.

[0080] The power generation loss can measure the whole machine cost of the target wind turbine under the corresponding interval combination, and thus the power generation loss can be used as a basis for reducing the parameter range, so as to reduce the whole machine cost.

[0081] As a possible implementation manner, for the selected target wind farm, the full-load wind speed is theoretically the same, and the corresponding full-load wind speed interval is fixed, which can be expressed as wherein, Thus, according to the full-load wind speed interval, the probability matrix corresponding to the joint state probability obtained in S103 can be changed from to At this time, the target wind turbine is at the full-load wind speed, that is, in a relatively harsh power generation condition, and the interval combination corresponding to the target wind turbine can be determined from the m-1 environmental parameter intervals.

[0082] The following is described by S301-S303.

[0083] In S301, the interval combination corresponding to the full-load wind speed is determined according to the full-load wind speed of the target wind turbine.

[0084] In S302, the joint state probability of the target wind turbine under the interval combination corresponding to the full-load wind speed is determined.

[0085] In S303, the power generation loss of the target wind turbine corresponding to different environmental parameter intervals is obtained based on the joint state probability under the interval combination corresponding to the full-load wind speed.

[0086] In the following, the power generation loss is taken as an example of the annual power generation loss, and the above process can be specifically referred to formula (2):

[0087] (2)

[0088] wherein,

[0089] represents the annual power generation loss of the target wind turbine;

[0090] a single-machine rated capacity of the target wind turbine generator set;

[0091] a joint state probability under the interval combination corresponding to the full-load wind speed;

[0092] a derating operation ratio;

[0093] a proportion of the wind turbine generator set that can be utilized for power generation in the target wind turbine generator set.

[0094] S105: determining, as a reference parameter interval of the environmental parameter applicable to the target wind turbine generator set, an environmental parameter interval corresponding to a power generation loss satisfying a power generation threshold condition.

[0095] The power generation loss corresponding to different interval combinations can be different. The power generation loss is taken as a basis for narrowing the parameter range. The environmental parameter interval that does not satisfy the power generation threshold condition is deleted, thereby narrowing the design boundary determined based on IEC or GB, so that the determined environmental parameter interval is more targeted, and the purpose of reducing the overall cost is achieved.

[0096] For example, the annual power generation loss corresponding to each of the aforementioned m-1 environmental parameter intervals is determined according to formula (2). The environmental parameter interval that does not satisfy the power generation threshold condition is deleted, and the reference parameter interval is further narrowed.

[0097] As a possible implementation manner, when the power generation loss is determined according to formula (2), i can be taken from the maximum value m-1. If the corresponding power generation loss satisfies the power generation threshold condition, i continues to be taken as m-2, and the judgment continues until the corresponding environmental parameter interval does not satisfy the power generation threshold condition. If i the corresponding environmental parameter interval does not satisfy the power generation threshold condition, the interval corresponding to i is narrowed from to At this time, the parameter range of the environmental parameter is narrowed from to .

[0098] S106: optimizing the target wind turbine generator set according to the reference parameter interval.

[0099] The embodiments of the present application do not specifically limit the manner of optimizing the target wind turbine generator set according to the reference parameter interval. Two manners are taken as examples for illustration below.

[0100] Manner one: determining the reference parameter interval as an optimization parameter range of the target wind turbine generator set, and optimizing the target wind turbine generator set according to the optimization parameter range.

[0101] At this time, since the parameter range of the environmental parameter can be narrowed to the reference parameter interval by whether the power generation loss meets the power generation threshold condition, optimizing the target wind turbine based on the smaller reference parameter interval makes the target wind turbine more targeted, so that the target wind turbine is suitable for the target wind field and can also reduce the overall cost of the target wind turbine.

[0102] Method two: according to the power generation loss of the kth environmental parameter interval and the construction cost of the target wind turbine in the kth environmental parameter interval, determine the levelized cost of electricity corresponding to the kth environmental parameter interval, and according to the difference value of the levelized cost of electricity of the adjacent two environmental parameter intervals, determine the environmental parameter interval corresponding to the difference value meeting the difference value threshold as the optimization parameter range, and optimize the target wind turbine through the optimization parameter range.

[0103] In order to further optimize the parameter range of the target wind power and reduce the positive electrode cost of the target wind turbine, a more accurate parameter range is further selected from the reference parameter interval according to the levelized cost of electricity. Among them, the levelized cost of electricity is used to identify the levelized cost of the target wind turbine and the power generation cost after the power generation loss.

[0104] The calculation formula of the levelized cost of electricity corresponding to the kth environmental parameter interval is formula (3):

[0105] (3)

[0106] Among them:

[0107] is the power generation loss of the kth environmental parameter interval,

[0108] is the construction cost of the target wind turbine in the kth environmental parameter interval, generally, as the environmental parameter interval is narrowed, the cost of the electric drive system will also be reduced, so that is reduced;

[0109] is the power generation loss of the target wind turbine in the kth environmental parameter interval, generally, as the environmental parameter interval is narrowed, also decreases;

[0110] is the discount rate, which is generally a constant;

[0111] is the discount tax, which is generally a constant;

[0112] is the recovery residual value, which is generally a constant; ​

[0113] For the operation and maintenance cost, it is generally a constant.

[0114] Similarly, the levelized cost of electricity corresponding to the k-1th environmental parameter interval can also be calculated, the difference between the levelized cost of electricity corresponding to the kth environmental parameter interval and the levelized cost of electricity corresponding to the k-1th environmental parameter interval is determined, the environmental parameter interval corresponding to the difference satisfying the difference threshold is determined as the optimization parameter range, see formula (4):

[0115] (4)

[0116] Wherein:

[0117] The difference between the levelized cost of electricity of the adjacent two environmental parameter intervals;

[0118] The levelized cost of electricity corresponding to the k-1th environmental parameter interval;

[0119] The levelized cost of electricity corresponding to the kth environmental parameter interval.

[0120] As a possible implementation manner, when the difference between the levelized cost of electricity of the adjacent two environmental parameter intervals is determined according to formula (4), k can be taken from the maximum value m-1, if the corresponding difference satisfies the difference threshold, k continues to take m-2, and the judgment continues until the corresponding environmental parameter interval does not satisfy the difference threshold or k= If the corresponding environmental parameter interval does not satisfy the difference threshold, the interval corresponding to k is reduced from to At this time, the parameter range of the environmental parameter is reduced from to At this time, the optimization parameter range is .

[0121] ​​According to the technical solution, the environment parameter of the target wind turbine changing over time and the wind speed parameter of the target wind farm where the target wind turbine is located changing over time are obtained, the parameter range of the environment parameter is divided into m environment parameter intervals, the parameter range of the wind speed parameter is divided into n wind speed parameter intervals, the m environment parameter intervals and the n wind speed parameter intervals are combined into multiple interval combinations respectively, the joint state probability of the target wind turbine under different interval combinations is determined, the joint state probability is used to identify the proportion of the cumulative running time of the target wind turbine under different interval combinations in the total running time of the target wind turbine, the power generation loss of the target wind turbine corresponding to different environment parameter intervals is obtained based on the joint state probability under different interval combinations, the environment parameter interval corresponding to the power generation loss satisfying the power generation threshold condition is determined as the reference interval of the environment parameter suitable for the target wind turbine, and the target wind turbine is optimized according to the reference parameter interval. Therefore, whether the power generation loss satisfies the power generation threshold condition can reduce the parameter range of the environment parameter to the reference parameter interval, the target wind turbine is optimized based on the smaller reference parameter interval, which is more targeted, so that the target wind turbine is suitable for the target wind farm and can also reduce the overall cost of the target wind turbine.

[0122] In addition to the parameter optimization method of the wind turbine provided by the embodiments of the present application, a parameter optimization device of the wind turbine is also provided, as shown in Figure 2 The parameter optimization device comprises:

[0123] A parameter acquisition unit 201 is configured to acquire an environment parameter of a target wind turbine changing over time and a wind speed parameter of a target wind farm where the target wind turbine is located changing over time.

[0124] A parameter interval determination unit 202 is configured to determine m environment parameter intervals according to a parameter range of the environment parameter and n wind speed parameter intervals according to a parameter range of the wind speed parameter.

[0125] A joint state probability determination unit 203 is configured to determine a joint state probability of the target wind turbine under different interval combinations, the joint state probability being used to identify the proportion of the cumulative running time of the target wind turbine under different interval combinations in the total running time of the target wind turbine, the interval combination being determined according to different combinations of the m environment parameter intervals and the n wind speed parameter intervals.

[0126] A power generation loss determination unit 204 is configured to obtain the power generation loss of the target wind turbine corresponding to different environment parameter intervals based on the joint state probability under different interval combinations.

[0127] The reference parameter interval determination unit 205 is configured to determine a reference parameter interval of the environmental parameter applicable to the target wind turbine generator set, according to the environmental parameter interval corresponding to the power generation loss satisfying the power generation threshold condition.

[0128] The optimization unit 206 is configured to optimize the target wind turbine generator set according to the reference parameter interval.

[0129] As a possible implementation manner, the optimization unit 206 is configured to:

[0130] The reference parameter interval is determined as an optimization parameter range of the target wind turbine generator set, and the target wind turbine generator set is optimized according to the optimization parameter range.

[0131] As a possible implementation manner, the optimization unit 206 is configured to:

[0132] The levelized electricity cost corresponding to the kth environmental parameter interval is determined according to the power generation loss of the kth environmental parameter interval and the construction cost of the target wind turbine generator set in the kth environmental parameter interval, and the levelized electricity cost is used to identify the power generation cost after the levelized cost of the target wind turbine generator set and the power generation loss.

[0133] The optimization parameter range is determined according to the difference between the levelized electricity costs of the adjacent two environmental parameter intervals, the environmental parameter interval corresponding to the difference satisfying the difference threshold value is determined as the optimization parameter range, and the target wind turbine generator set is optimized through the optimization parameter range.

[0134] As a possible implementation manner, the optimization unit 206 is configured to:

[0135] The levelized electricity cost is determined according to the power generation loss of the kth environmental parameter interval, the construction cost of the target wind turbine generator set in the kth environmental parameter interval, the discount rate of the target wind turbine generator set, the discount tax of the target wind turbine generator set, the residual value of the target wind turbine generator set and the operation and maintenance cost of the target wind turbine generator set.

[0136] As a possible implementation manner, if the wind speed parameter is obtained through the wind measurement tower of the target wind farm, the joint state probability determination unit 203 is configured to:

[0137] The first cumulative duration of the target wind turbine generator set running in the ith environmental parameter interval and the second cumulative duration of the wind measurement tower running in the jth wind speed parameter interval are obtained, i < m, j < n.

[0138] determine the total operation duration of the target wind turbine generator set according to the start time and end time, the data missing duration and the data abnormal duration corresponding to the parameter range of the environment parameter, and determine the total operation duration of the wind measurement tower according to the start time and end time, the data missing duration and the data abnormal duration corresponding to the parameter range of the wind speed parameter;

[0139] determine the joint state probability of the target wind turbine generator set under a target interval combination according to the first cumulative duration, the second cumulative duration, the total operation duration of the target wind turbine generator set and the total operation duration of the wind measurement tower, the target interval combination being a combination of the ith environment parameter interval and the jth wind speed parameter interval.

[0140] As a possible implementation manner, the joint state probability determination unit 203 is configured to:

[0141] determine the interval combination corresponding to the full-load wind speed of the target wind turbine generator set according to the full-load wind speed of the target wind turbine generator set;

[0142] determine the joint state probability of the target wind turbine generator set under the interval combination corresponding to the full-load wind speed;

[0143] The power generation loss determination unit 204 is configured to:

[0144] obtain the power generation loss of the target wind turbine generator set corresponding to different environment parameter intervals based on the joint state probability under the interval combination corresponding to the full-load wind speed.

[0145] As a possible implementation manner, the power generation loss determination unit 204 is configured to:

[0146] obtain the power generation loss of the target wind turbine generator set corresponding to different environment parameter intervals according to the joint state probability under the interval combination corresponding to the full-load wind speed, the single-machine rated capacity of the target wind turbine generator set, the derating operation ratio of the target wind turbine generator set and the availability of the target wind turbine generator set.

[0147] The embodiment of the present application provides a parameter optimization device of a wind turbine generator set, obtains an environment parameter of a target wind turbine generator set changing over time and a wind speed parameter of a target wind field where the target wind turbine generator set is located changing over time, divides a parameter range of the environment parameter into m environment parameter intervals, divides a parameter range of the wind speed parameter into n wind speed parameter intervals, combines the m environment parameter intervals and the n wind speed parameter intervals into a plurality of interval combinations respectively, determines a joint state probability of the target wind turbine generator set under different interval combinations, the joint state probability is used for identifying a proportion of accumulated running time of the target wind turbine generator set under different interval combinations in total running time of the target wind turbine generator set, obtains power generation loss of the target wind turbine generator set corresponding to different environment parameter intervals based on the joint state probability under different interval combinations, determines an environment parameter reference interval suitable for the target wind turbine generator set as an environment parameter interval corresponding to the power generation loss meeting a power generation threshold condition, and optimizes the target wind turbine generator set according to the reference parameter interval. Therefore, whether the power generation loss meets the power generation threshold condition can reduce the parameter range of the environment parameter to the reference parameter interval, optimize the target wind turbine generator set based on the reference parameter interval with a smaller range, and make the target wind turbine generator set suitable for the target wind field and reduce the overall cost of the target wind turbine generator set.

[0148] The embodiment of the present application also provides a computer device, referring to Figure 3 The figure shows a structure diagram of a computer device provided by the embodiment of the present application, as Figure 3 The device comprises a processor 310 and a memory 320:

[0149] The memory 310 is used for storing program code and transmitting the program code to the processor;

[0150] The processor 320 is used for executing any one of the interface calling methods provided by the above-mentioned embodiments according to the instructions in the program code.

[0151] The embodiment of the present application provides a computer readable storage medium, which is used for storing a computer program, and the computer program is used for executing any one of the interface calling methods provided by the above-mentioned embodiments.

[0152] The various embodiments described in this specification are intended to be exemplary only. The same elements having the same reference numerals designate the same elements throughout the several embodiments. The various embodiments set forth in the specification are described with respect to the exemplary methods and apparatuses of the embodiments, but the embodiments are not limited to these specific embodiments, and indeed many options exist for adapting the embodiments to different applications. Those skilled in the art will recognize, or be able to ascertain, using no more than routine experimentation, many equivalents to the specific embodiments described herein. Such equivalents are considered to be within the scope of this application. In addition, it is contemplated that individuals skilled in the art will be able to devise their own implementation that, although not explicitly described herein, embody the principles of the application and, thus, are within the spirit and scope of the application.

[0153] The specific embodiments described herein are examples of the application and it is contemplated that those skilled in the art upon considering this disclosure will be able to devise their own implementations that, although not explicitly described herein, embody the principles of the application and, thus, are within the spirit and scope of the application.

Claims

1. A method of parameter optimization of a wind turbine, characterized in that, The method comprises: acquiring an environmental parameter of a target wind turbine generator set changing over time and a wind speed parameter of a target wind farm where the target wind turbine generator set is located changing over time; determining m environmental parameter intervals according to a parameter range of the environmental parameter and n wind speed parameter intervals according to a parameter range of the wind speed parameter; determining a joint state probability of the target wind turbine generator set under different interval combinations, the joint state probability being used to identify a proportion of a cumulative time length of the target wind turbine generator set running under different interval combinations in a total time length of the target wind turbine generator set running, the interval combinations being determined according to different combinations of the m environmental parameter intervals and the n wind speed parameter intervals; obtaining a power generation loss of the target wind turbine generator set corresponding to different environmental parameter intervals based on the joint state probability under the different interval combinations; determining a reference parameter interval of an environmental parameter suitable for the target wind turbine generator set based on an environmental parameter interval corresponding to which the power generation loss satisfies a power generation threshold condition; optimizing the target wind turbine generator set according to the reference parameter interval.

2. The method of claim 1, wherein, The optimization of the target wind turbine generator set according to the reference parameter interval comprises: determining the reference parameter interval as an optimization parameter range of the target wind turbine generator set and optimizing the target wind turbine generator set according to the optimization parameter range.

3. The method of claim 1, wherein, The optimization of the target wind turbine generator set according to the reference parameter interval comprises: determining a levelized electricity cost corresponding to a kth environmental parameter interval according to a power generation loss of the kth environmental parameter interval and a construction cost of the target wind turbine generator set in the kth environmental parameter interval, the levelized electricity cost being used to identify a levelized cost and a power generation cost after a power generation loss of the target wind turbine generator set; determining an environmental parameter interval corresponding to which a difference value of levelized electricity costs of adjacent two environmental parameter intervals satisfies a difference value threshold as an optimization parameter range and optimizing the target wind turbine generator set through the optimization parameter range.

4. The method of claim 3, wherein, The determination of the levelized electricity cost according to the power generation loss of the kth environmental parameter interval and the construction cost of the target wind turbine generator set in the kth environmental parameter interval comprises: determining the levelized electricity cost according to the power generation loss of the kth environmental parameter interval, the construction cost of the target wind turbine generator set in the kth environmental parameter interval, a discount rate of the target wind turbine generator set, a discount tax of the target wind turbine generator set, a recycling residual value of the target wind turbine generator set and an operation and maintenance cost of the target wind turbine generator set.

5. The method of claim 1, wherein, If the wind speed parameter is acquired through a wind measurement tower of the target wind farm, the determination of the joint state probability of the target wind turbine generator set under different interval combinations comprises: acquiring a first cumulative time length of the target wind turbine generator set running in an ith environmental parameter interval and a second cumulative time length of the wind measurement tower running in a jth wind speed parameter interval, i < m, j < n; determine the total operation time of the target wind turbine generator set according to the start time and end time, the data missing time length and the data abnormal time length corresponding to the parameter range of the environment parameter, and determine the total operation time of the wind measurement tower according to the start time and end time, the data missing time length and the data abnormal time length corresponding to the parameter range of the wind speed parameter; determine the joint state probability of the target wind turbine generator set under a target interval combination according to the first cumulative time length, the second cumulative time length, the total operation time of the target wind turbine generator set and the total operation time of the wind measurement tower, the target interval combination being a combination of the ith environment parameter interval and the jth wind speed parameter interval.

6. The method of claim 1, wherein, The determining the joint state probability of the target wind turbine generator set under different interval combinations comprises: determine an interval combination corresponding to the full-load wind speed of the target wind turbine generator set according to the full-load wind speed of the target wind turbine generator set; determine the joint state probability of the target wind turbine generator set under the interval combination corresponding to the full-load wind speed; The obtaining the power generation loss of the target wind turbine generator set corresponding to different environment parameter intervals based on the joint state probability under the different interval combinations comprises: obtain the power generation loss of the target wind turbine generator set corresponding to different environment parameter intervals based on the joint state probability under the interval combination corresponding to the full-load wind speed.

7. The method of claim 6, wherein, The obtaining the power generation loss of the target wind turbine generator set corresponding to different environment parameter intervals based on the joint state probability under the interval combination corresponding to the full-load wind speed comprises: obtain the power generation loss of the target wind turbine generator set corresponding to different environment parameter intervals according to the joint state probability under the interval combination corresponding to the full-load wind speed, the single-machine rated capacity of the target wind turbine generator set, the derating operation ratio of the target wind turbine generator set and the availability of the target wind turbine generator set.

8. A parameter optimization device for a wind power plant, characterized in that The device comprises: a parameter acquisition unit configured to acquire environment parameters of a target wind turbine generator set changing over time and wind speed parameters of a target wind farm in which the target wind turbine generator set is located changing over time; a parameter interval determination unit configured to determine m environment parameter intervals according to a parameter range of the environment parameters and determine n wind speed parameter intervals according to a parameter range of the wind speed parameters; a joint state probability determination unit configured to determine joint state probabilities of the target wind turbine generator set under different interval combinations, the joint state probabilities being used to identify proportions of cumulative time lengths of the target wind turbine generator set operating under different interval combinations in a total operation time of the target wind turbine generator set, the interval combinations being determined according to different combinations of the m environment parameter intervals and the n wind speed parameter intervals; a power generation loss determination unit configured to obtain power generation losses of the target wind turbine generator set corresponding to different environment parameter intervals based on the joint state probabilities under the different interval combinations; a reference parameter interval determination unit configured to determine a reference parameter interval of an environment parameter suitable for the target wind turbine generator set based on an environment parameter interval corresponding to which the power generation loss satisfies a power generation threshold condition. An optimization unit is configured to optimize the target wind turbine generator system according to the reference parameter interval.

9. A computer device, comprising: The device comprises a processor and a memory: The memory is configured to store program code and transmit the program code to the processor; The processor is configured to execute the method according to any one of claims 1-7 according to instructions in the program code.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium is configured to store a computer program, and the computer program is configured to execute the method according to any one of claims 1-7.

Images