CN110942218B

CN110942218B - Method, device and system for calculating online electric quantity of wind power plant

Info

Publication number: CN110942218B
Application number: CN201811114113.9A
Authority: CN
Inventors: 李鸿秀; 赵长全; 丛宇辰
Original assignee: Beijing Tianrun Xinneng Investment Co ltd
Current assignee: Beijing Tianrun Xinneng Investment Co ltd
Priority date: 2018-09-25
Filing date: 2018-09-25
Publication date: 2023-10-10
Anticipated expiration: 2038-09-25
Also published as: CN110942218A

Abstract

A method, a device and a system for calculating the online electric quantity of a wind power plant are provided. The method may include: calculating a comprehensive reduction coefficient according to at least one generating capacity reduction term; the comprehensive uncertainty coefficient is obtained by classifying the generating capacity uncertainty factors; and calculating the Internet surfing electric quantity of the wind power plant by using the comprehensive reduction coefficient and the comprehensive uncertainty coefficient. The method can standardize the industry power generation amount calculation rules, improve the accuracy of power generation amount prediction, and improve the early working efficiency of wind power projects.

Description

Method, device and system for calculating online electric quantity of wind power plant

Technical Field

The invention relates to the technical field of wind power generation, in particular to a method, a device and a system for calculating the online electric quantity of a wind power plant.

Background

The determination of the online electric quantity is one of basic tasks of a wind power plant feasibility research stage, and the annual online electric quantity directly relates to the benefit level and the risk degree of the wind power plant, and influences and determines investment decisions of the wind power plant. The assessment electric quantity of the grid point gateway table on the wind power plant is the basis for the industry to assess the online electric quantity of the wind power plant. In fact, the online electric quantity is always less than the theoretical electric quantity, and in order to evaluate the benefit level and the risk degree of the wind power plant more accurately, the difference between the theoretical and actual generated energy needs to be calculated accurately, and the reduction of the generated energy needs to be analyzed.

The national modification Committee (for the description of the problem of reduction of the amount of wind power generation in China) documents give official definitions: the reduction of the generated energy of the wind power plant means that the factors influencing the actual output of the wind power plant are analyzed one by one to obtain the value of the reduction of the generated energy of the wind power plant caused by the factors. The reference reduction terms and typical value ranges given therein are given in table 1 below.

TABLE 1

Sequence number	Reduction category	Typical value range
			1	Wake reduction	Software computation
2	Air density reduction	Software computation
			3	Control and turbulence reduction	About 5%
4	Blade pollution reduction	Within 6%
			5	Wind turbine generator system availability ratio reduction	5％-10％
6	Power curve guarantee rate reduction of wind turbine generator	5％
			7	Reduction of field power consumption, line loss and the like	3％-10％
8	Climate influence reduction	3％-7％
			9	Software calculation error reduction	5％-10％
10	Power grid frequency fluctuation and electricity limiting equivalent reduction	3％-5％
			11	Large-scale wind farm wake reduction	In the exploration
	Totals to	30％-45％

The reference reduction items and the values thereof are easily seen from the table, and the total reduction coefficient can be obtained by continuously multiplying the values of each item. However, these reference compromises and their values are one empirical reference value at the current state of the wind power technology.

In addition, in the process of calculating the online electric quantity, not only electric quantity reduction is considered, but also an uncertainty factor of the generated energy is needed to be considered, however, the current wind farm design in China generally adopts comprehensive reduction method to convert the online electric quantity, and the uncertainty factor and the reduction factor are considered together in the process of calculating the generated energy and are uniformly used as the reduction factor to take the value, so that the reduction and the uncertainty are not explicitly separated. However, trade-off and uncertainty are essentially two concepts, the former being an absolute loss of project power generation; the latter is a measure of project power generation risk, and there is uncertainty in links such as anemometer tower measurement, CFD modeling, model selection, etc.

At present, the estimation of the online electric quantity mainly depends on enterprise experience, and there is no clear explanation for calculating the reduction term and uncertainty of the online electric quantity and an evaluation system for giving the value of each reduction term coefficient in detail.

Disclosure of Invention

The exemplary embodiments of the present invention provide a method, apparatus and system for calculating the online power of a wind farm, which at least solve the above technical problems and other technical problems not mentioned above, and provide the following advantages.

An aspect of the present invention is to provide a method for calculating an online power of a wind farm, where the method may include: calculating a comprehensive reduction coefficient according to at least one generating capacity reduction term; the comprehensive uncertainty coefficient is obtained by classifying the generating capacity uncertainty factors; and the comprehensive reduction coefficient and the comprehensive uncertainty coefficient are used for calculating the internet power of the wind power plant.

The power generation amount reduction term may include at least one of the following parameter terms: air density reduction terms, wake flow reduction terms, wind turbine generator set utilization reduction terms, wind turbine generator set power curve reduction terms, blade pollution loss reduction terms, line loss self-electricity consumption reduction terms, control and turbulence effect loss reduction terms, climate effect reduction terms, icing reduction terms, surrounding wind farm effect reduction terms and limiting factor reduction terms.

The step of calculating the integrated reduction coefficient may include: determining a reduction coefficient of each of the at least one power generation amount reduction term; and multiplying the determined reduction coefficients of each term to obtain a comprehensive reduction coefficient.

The step of obtaining the integrated uncertainty coefficient by classifying the power generation amount uncertainty factor may include: classifying the generating capacity uncertainty factors into wind data source uncertainty, wind flow modeling uncertainty and loss uncertainty; calculating the generating capacity uncertainty coefficient of each type of uncertainty by using the uncertainty factors of each type; and the integrated uncertainty coefficient is calculated using the generated energy uncertainty coefficient of each class.

Wind data source uncertainty factors may include site wind data uncertainty factors and long term extrapolation uncertainty factors. Wind flow modeling uncertainty factors may include input data uncertainty factors, horizontal extrapolation uncertainty factors, and vertical extrapolation uncertainty factors. The loss uncertainty factors may include wake uncertainty factors, fan performance uncertainty factors, environmental uncertainty factors, and other technical loss uncertainty factors.

The step of separately calculating the power generation amount uncertainty coefficient of each type of uncertainty may include: determining coefficients of various uncertainty factors in each type of uncertainty factors; calculating a sensitivity coefficient from the anemometry data; obtaining a first power generation amount uncertainty coefficient using the sensitivity coefficient and a coefficient of the determined wind data source uncertainty factor; obtaining a second power generation amount uncertainty coefficient using the sensitivity coefficient and the coefficient of the determined wind flow modeling uncertainty factor; and obtaining a third power generation amount uncertainty coefficient using the coefficient of the determined loss uncertainty factor.

The step of calculating the amount of power to wind farm using the integrated reduction coefficient and the integrated uncertainty coefficient may comprise: the comprehensive correction coefficient is obtained by using the comprehensive reduction coefficient and the comprehensive uncertainty coefficient, and the online electric quantity of the wind power plant is calculated based on the theoretical net generating capacity and the comprehensive correction coefficient.

Another aspect of the present invention is to provide an apparatus for calculating an amount of electricity for surfing the wind farm, the apparatus may include: the reduction coefficient calculation module is used for calculating a comprehensive reduction coefficient according to at least one generating capacity reduction item; the uncertainty coefficient calculation module is used for obtaining a comprehensive uncertainty coefficient by classifying the generating capacity uncertainty factors; and the online electric quantity calculation module is used for calculating the online electric quantity of the wind power plant by using the comprehensive reduction coefficient and the comprehensive uncertainty coefficient.

The power generation amount reducing term includes at least one of the following reference terms: air density reduction terms, wake flow reduction terms, wind turbine generator set utilization reduction terms, wind turbine generator set power curve reduction terms, blade pollution loss reduction terms, line loss self-electricity consumption reduction terms, control and turbulence effect loss reduction terms, climate effect reduction terms, icing reduction terms, surrounding wind farm effect reduction terms and limiting factor reduction terms.

The reduction coefficient calculation module may be configured to: a reduction coefficient of each of the at least one power generation amount reduction term is determined, and the determined reduction coefficient of each term is multiplied to obtain a comprehensive reduction coefficient.

The uncertainty coefficient calculation module may be configured to: classifying the generating capacity uncertainty factors into wind data source uncertainty, wind flow modeling uncertainty and loss uncertainty; calculating the generating capacity uncertainty coefficient of each type of uncertainty by using the uncertainty factors of each type; and the integrated uncertainty coefficient is calculated using the generated energy uncertainty coefficient of each class.

The uncertainty coefficient calculation module may also be configured to: determining coefficients of various uncertainty factors in each type of uncertainty factors; calculating a sensitivity coefficient from the anemometry data; obtaining a first power generation amount uncertainty coefficient using the sensitivity coefficient and a coefficient of the determined wind data source uncertainty factor; obtaining a second power generation amount uncertainty coefficient using the sensitivity coefficient and the coefficient of the determined wind flow modeling uncertainty factor; a third power generation amount uncertainty coefficient is obtained using the coefficient of the determined loss uncertainty factor.

The internet power calculation module may be configured to: the comprehensive correction coefficient is obtained by using the comprehensive reduction coefficient and the comprehensive uncertainty coefficient, and the online electric quantity of the wind power plant is calculated based on the theoretical net generating capacity and the comprehensive correction coefficient.

Another aspect of the present invention is to provide a system for calculating a wind farm internet surfing power, the system may include: a display for displaying a plurality of user interfaces for respectively inputting reduction coefficients of at least one power generation amount reduction term and coefficients of a plurality of uncertainty factors; and a controller for calculating a comprehensive reduction coefficient using the reduction coefficients of the plurality of input power generation amount reduction items; calculating a comprehensive uncertainty coefficient using the coefficients of the plurality of uncertainty factors input; and calculating the on-line electricity quantity of the wind power plant based on the calculated comprehensive reduction coefficient and the comprehensive uncertainty coefficient.

The controller may calculate the sensitivity coefficient using the anemometry data input through the first user interface of the plurality of user interfaces.

The controller may also calculate a first power generation amount uncertainty coefficient using the sensitivity coefficient and a coefficient of a wind data source uncertainty factor input through a second user interface of the plurality of user interfaces.

The controller may also calculate a second power generation amount uncertainty coefficient using the sensitivity coefficient and a coefficient of a wind flow modeling uncertainty factor input through a third user interface of the plurality of user interfaces.

The controller may also calculate the third power generation amount uncertainty coefficient using a coefficient of the loss uncertainty factor input through a fourth user interface of the plurality of user interfaces.

The controller may calculate the integrated uncertainty coefficient based on the first power generation amount uncertainty coefficient, the second power generation amount uncertainty coefficient, and the third power generation amount uncertainty coefficient.

The controller may use the integrated reduction coefficient and the integrated uncertainty coefficient to obtain an integrated correction coefficient, and calculate an online capacity of the wind farm based on the theoretical net power generation and the integrated correction coefficient.

An aspect of the present invention provides a computer readable storage medium storing a program, wherein the program may include instructions for performing the above-described method of calculating a wind farm internet power.

An aspect of the present invention provides a computer comprising a readable medium storing a computer program, characterized in that the computer program comprises instructions for performing the above-described method of calculating the amount of power on a wind farm.

Based on the method, the device and the system for calculating the online electric quantity of the wind power plant, the generated energy reduction item and the uncertainty item can be clearly distinguished, and the value ranges of all the related reduction items and the uncertainty factors under different conditions are provided, so that the calculation method of the online electric quantity is standardized, and the working efficiency of practitioners is improved.

Drawings

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

FIG. 1 is a flowchart of a method of calculating wind farm Internet surfing power according to an example embodiment of the present disclosure;

FIG. 2 is a flowchart of a method of calculating wind farm Internet surfing power according to another example embodiment of the present disclosure;

FIG. 3 is a block diagram of a system for calculating wind farm Internet surfing power according to an example embodiment of the present disclosure;

FIG. 4 is a diagram of a user interface for calculating an integrated reduction coefficient, according to an example embodiment of the present disclosure;

FIG. 5 is a diagram of a user interface for calculating sensitivity coefficients according to an example embodiment of the present disclosure;

fig. 6 is a block diagram of an apparatus for calculating wind farm internet power according to an example embodiment of the present disclosure.

Detailed Description

Reference will now be made in detail to the exemplary embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout. The embodiments will be described below in order to explain the present application by referring to the figures. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present disclosure. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present disclosure without making any inventive effort, are intended to be within the scope of the present application.

In this disclosure, terms including ordinal numbers such as "first," "second," and the like may be used to describe various elements, but these elements should not be construed as limited to only these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and vice versa, without departing from the scope of the present disclosure.

Before explaining the inventive concepts of the present disclosure, the terms employed in the present disclosure are explained in relation.

The reduction coefficient refers to the ratio of the loss power generation amount to the theoretical power generation amount. The integrated reduction coefficient is the product of the coefficients of the individual reduction terms. The independent single folding and subtracting items are executed according to the basic list item of the national issuing and modifying commission of the description about the problem of reducing the wind power generation capacity of China.

The correction factor is 1 minus the reduction factor. The integrated correction coefficient refers to a correction coefficient in which uncertainty is taken into consideration.

The sensitivity coefficient refers to the percentage value that may cause a deviation in the amount of power generation due to a deviation of 1% in wind speed.

Uncertainty refers to the fact that the decision scheme is subject to various external factors that cannot be controlled in advance. The influence of uncertainty factors on the predicted internet power can be clarified and reduced as much as possible through uncertainty analysis, so that a predicted result is closer to reality, and a basis is provided for scientific decision.

The theoretical generating capacity is the total electric energy of the outlet end of the fan produced in one year of the wind generating set by utilizing wind generating set data and wind energy parameters such as wind speed, wind direction and the like of which the hub height represents the year. The theoretical net generating capacity is the generating capacity obtained by subtracting wake flow from the theoretical generating capacity.

The loss generating capacity refers to the difference between the theoretical generating capacity and the internet-surfing electric quantity caused by the difference between the theoretical generating capacity and the actual generating condition of the wind generating set and the difference between the electric quantity of the outlet end and the electric quantity of the electricity price metering end of the wind generating set.

The online electric quantity refers to the electric quantity input by a power plant to a power supply enterprise (power grid) at an online electric quantity metering point, namely the electric quantity sold by the power plant to the power supply enterprise.

The equivalent full load hours refers to the number of times that power is generated at full power, which is the total power generation of the wind farm divided by the installed capacity of the wind farm.

The capacity coefficient refers to the ratio of the number of hours of active use of the wind farm to the number of hours of full year.

Fig. 1 is a flowchart of a method of calculating wind farm internet power according to an example embodiment of the present disclosure.

Referring to fig. 1, in step S101, a comprehensive reduction coefficient is calculated from at least one power generation amount reduction term. According to an embodiment of the present disclosure, the power generation amount discount term may include at least one of the following parameter terms: air density reduction terms, wake flow reduction terms, wind turbine generator set utilization reduction terms, wind turbine generator set power curve reduction terms, blade pollution loss reduction terms, line loss self-electricity consumption reduction terms, control and turbulence effect loss reduction terms, climate effect reduction terms, icing reduction terms, surrounding wind farm effect reduction terms and limiting factor reduction terms. And in the calculation of the comprehensive reduction coefficient, determining the reduction coefficient of each generating capacity reduction item according to a theoretical method and the working experience of wind power staff, and multiplying the determined reduction coefficient of each item to obtain the comprehensive reduction coefficient.

According to the embodiment of the disclosure, when determining the reduction coefficient of each reduction item, a calculation method of the reduction coefficient of each reduction item or a value range of the reduction coefficient of each reduction item can be determined according to a theoretical method in combination with working experience of a worker, and then the reduction coefficient of each reduction item is determined in combination with an actual item. And the index is quantized by determining the calculation method or the value range of the reduction coefficient of each reduction item, so that the calculation method of the online electric quantity is standardized.

In step S102, a comprehensive uncertainty coefficient is obtained by classifying the power generation amount uncertainty factor. According to embodiments of the present disclosure, the power generation uncertainty factors are classified into wind data source uncertainty, wind flow modeling uncertainty, and loss uncertainty. Wind data source uncertainty factors may include, among other things, site wind data uncertainty factors and long-term extrapolation uncertainty factors. Wind flow modeling uncertainty factors may include input data uncertainty factors, horizontal extrapolation uncertainty factors, and vertical extrapolation uncertainty factors. The loss uncertainty factors may include wake uncertainty factors, fan performance uncertainty factors, environmental uncertainty factors, and other technical loss uncertainty factors.

After each type of uncertainty factors are determined, determining the value of the coefficient of each type of uncertainty factors according to a theoretical method and working experience of wind power staff, and then calculating the uncertainty coefficient of the generated energy of each type of uncertainty. When calculating each type of generating capacity uncertainty coefficient, a sensitivity coefficient is calculated according to the wind measuring data, and the sensitivity coefficient and the coefficient of the determined wind data source uncertainty factor are used for obtaining a first generating capacity uncertainty coefficient. A second power generation uncertainty coefficient is obtained using the sensitivity coefficient and the coefficient of the determined wind flow modeling uncertainty factor. A third power generation amount uncertainty coefficient is obtained using the coefficient of the determined loss uncertainty factor. Here, in calculating the uncertainty coefficient with respect to the wind data source uncertainty and the wind flow modeling uncertainty, since the uncertainty coefficients calculated by both belong to the wind speed uncertainty coefficient, it is necessary to convert the wind speed uncertainty coefficient into the power generation amount uncertainty coefficient using the sensitivity coefficient, and in calculating the coefficient with respect to the loss uncertainty, since the calculated uncertainty coefficient is the power generation amount uncertainty coefficient, it is unnecessary to use the sensitivity coefficient for conversion.

After obtaining the coefficients of each class of power generation uncertainty, the integrated uncertainty coefficients are calculated using the power generation uncertainty coefficients of each class (i.e., wind data source uncertainty, wind flow modeling uncertainty, and loss uncertainty).

In step S103, the comprehensive reduction coefficient and the comprehensive uncertainty coefficient are used to calculate the online power of the wind farm. And (3) combining the comprehensive reduction coefficient and the comprehensive uncertainty coefficient to obtain a comprehensive correction coefficient, and then calculating the on-line electric quantity of the wind power plant based on the theoretical net generating capacity and the comprehensive correction coefficient. According to the embodiment of the disclosure, the power generation values under different overrun probabilities of P50, P75, P84, P90, P99 and the like can be calculated. A flowchart of a method of calculating the amount of power on the wind farm will be described in detail below with reference to fig. 2.

Fig. 2 is a flowchart of a method of calculating wind farm internet power according to another example embodiment of the present disclosure.

Referring to fig. 2, in step S201, a reduction coefficient of each of at least one power generation amount reduction term is determined. When determining the reduction coefficient of each item, firstly, determining the value range of the reduction coefficient of each item according to theoretical data and working experience of wind power personnel, and then, determining the reduction coefficient of each item according to actual conditions. Wherein the power generation amount reduction term may include at least one of the following parameter terms: air density reduction terms, wake flow reduction terms, wind turbine generator set utilization reduction terms, wind turbine generator set power curve reduction terms, blade pollution loss reduction terms, line loss self-electricity consumption reduction terms, control and turbulence effect loss reduction terms, climate effect reduction terms, icing reduction terms, surrounding wind farm effect reduction terms and limiting factor reduction terms. When determining the reduction coefficient of each reduction item, the reduction coefficient of each reduction item can be determined according to a theoretical method and working experience of wind power staff, and meanwhile, the correction coefficient of each reduction item is determined. In the embodiment of the present disclosure, a calculation method or a value range of the reduction coefficient of each item is given, and a person skilled in the art may determine the reduction coefficient of each item according to the given calculation method or value range of the reduction coefficient of each item, in combination with an operation state and an operation environment of an actual wind turbine generator set.

Specifically, when determining the reduction coefficient of the air density, the air density can be calculated according to the GB/T18710-2002 method, and the air density of the wind power plant is calculated according to the power curve and the thrust coefficient corresponding to the actual air density of the wind power plant, so that the air density is not required to be corrected.

When determining the wake reduction coefficient, the influence of a single fan and the wake of the full wind power plant can be checked according to the software calculation result, and then the wake reduction coefficient is calculated according to the wake of the full wind power plant.

When determining the reduction coefficient of the utilization rate of the wind generating set, the reduction coefficient can be determined according to the manufacturing level of the selected wind generating set and the actual condition of the wind farm, for example, if the availability rate of the wind generating set is generally the availability rate ensured by a wind generating set manufacturer, the reduction coefficient takes a value of 2% -5%, and the correction coefficient takes a value of 95% -98%.

When determining the reduction coefficient of the power curve of the wind generating set, the reduction coefficient can be determined according to the manufacturing level of the selected wind generating set and the actual conditions of the wind farm, for example, the correction coefficient takes on a value of 95% -98% assuming that the power curve of the wind generating set is generally the power curve guaranteed by a manufacturer of the wind generating set.

When determining the reduction coefficient of the pollution loss of the blade, the blade surface roughness is improved due to the blade pollution, so that the aerodynamic characteristics of the wing shape are reduced, and the generated energy is reduced, therefore, the reduction coefficient is 2-4% according to the statistics of the proportion of the number of sand storm days of adjacent weather stations in the whole year, and the correction coefficient is 96-98%.

When determining the line loss and the reduction coefficient of the self-electricity consumption, firstly, the electric energy consumption in the wind farm can be estimated preliminarily according to the model and the electrical arrangement scheme of the wind farm electric equipment and the length of the current collection line, wherein the resistance R=ρ (L/S) of the wind farm line represents the resistivity of the resistor, the ρ is determined by the property of the resistor, L represents the length of the resistor, and S represents the cross section area of the resistor. Loss p=i of line power is calculated according to wind power plant line current ² R, wherein P represents electric quantity loss, I represents current, and R represents resistance. The line loss (line loss) is estimated through calculation and experience, the self-power consumption is estimated or consulted at the same time, the sum of the line loss and the self-power consumption is 2% -5%, the reduction coefficient of the line loss of the conventional project and the self-power consumption is 4%, and the correction coefficient is 95% -98%.

The wind generating set continuously adjusts the running state of the wind generating set along with the change of wind speed and wind direction, but in actual running, the wind generating set is controlled to lag behind the change of wind speed and wind direction, so that the wind generating set cannot output force according to ideal wind conditions, in addition, the turbulence can cause load fluctuation of the wind generating set and tremble of the wind generating set, and the output force of the wind generating set can be reduced. In determining the reduction coefficient of the control and turbulence effect losses, the high wind speed hysteresis factor is no longer a single consideration, since the reduction term of the control and turbulence effect losses already contains the high wind speed hysteresis factor.

The reduction coefficient of the control loss can be estimated according to the wind direction of the wind farm and the wind energy distribution concentration degree, for example, when the proportion of the wind energy direction of the height of the hub concentrated in a sector (namely, a 22.5 degree interval) is respectively smaller than 10%, greater than or equal to 20%, greater than or equal to 30%, the reduction coefficients of the control loss reduction items are respectively 2.5%, 2%, 1.5% and 1%, and the corresponding correction coefficients are respectively 97.5%, 98%, 98.5% and 99%.

The turbulence intensity is the ratio of the mean square deviation of the fluctuating wind speed to the average wind speed, and the turbulence intensity correction is judged according to the turbulence intensity at the hub height of the wind power plant, for example, when the turbulence intensity is smaller than or equal to 0.12, smaller than or equal to 0.14, smaller than or equal to 0.16 and larger than 0.16, the turbulence reduction coefficients are 1%, 1.5%, 2% and 2.5%, and the turbulence correction coefficients are 99%, 98.5%, 98% and 97.5%, respectively.

Therefore, the reduction coefficient of the control and turbulence influence loss takes 2% -5%, and the correction coefficient of the control and turbulence influence loss takes 95% -98%.

When determining the reduction coefficient of the climate influence, the generating capacity of the wind generating set is affected to a certain extent due to the influence of severe climate conditions such as thunderstorm, typhoon, high and low temperature and the like, therefore, the extreme minimum and maximum air temperature of the wind power plant can be calculated according to the temperature direct reduction rate of-0.65 ℃/100m by referring to the thunderstorm days, extreme minimum and maximum air temperatures of the nearby weather stations, the shutdown reduction coefficient of the climate influence of the wind power plant is comprehensively considered, the reduction coefficient is taken as 1% -3%, and the correction coefficient is taken as 97% -99%.

When determining the reduction coefficient of icing, considering the reduction according to the wind speed proportion of the measured wind tower air temperature less than 0 for the project that the icing exists in winter and spring at the place of the wind power plant, and not considering the reduction if the icing exists on the spot, the correction should be paid special attention to in Guangxi, hunan, hubei, yunnan and Guizhou areas.

When determining the reduction coefficient of the influence of the surrounding wind power plant, considering that the surrounding wind power plant has a certain influence on the generated energy of the wind power plant after being built, at present, the coordinates of the surrounding wind power plant can be obtained and carried into software to calculate to obtain the influence rate of the surrounding wind power plant on the wind power plant, if the coordinates of the wind power plant are not taken, the reduction coefficient can be determined by estimating the influence of the surrounding wind power plant according to the current experience, the correction coefficient is 0% -5%, and the correction coefficient is 95% -100%.

When determining the reduction coefficient of the limiting factor, the reduction coefficient can take an empirical value of 0% -5% according to project conditions due to the wind power plant noise, high animal and surrounding forest length, electricity limiting and other reasons, and the shutdown or the reduction of the power generation efficiency of the wind power generation set is caused. And combining the value range of the reduction coefficient of each item, and determining the reduction coefficient of each item according to the running state and the running environment of the wind generating set.

By giving out a scientific value-taking strategy of the reduction coefficient, detailed classification can be carried out according to different conditions in the process of calculating the network electric quantity, and a specific value-taking method is formulated for each index, so that the calculation result is more accurate.

In step S202, the determined reduction coefficient of each term is multiplied to obtain a comprehensive reduction coefficient. After obtaining the reduction coefficient of each term determined in step S201, the reduction coefficient of each term is multiplied, and a comprehensive reduction coefficient can be obtained.

In step S203, the power generation amount uncertainty factor is classified. According to embodiments of the present disclosure, the power generation amount uncertainty factors may be classified into wind data source uncertainty, wind flow modeling uncertainty, and loss uncertainty. Wind data source uncertainty factors may include, among other things, site wind data uncertainty factors and long-term extrapolation uncertainty factors. Site wind data uncertainty factors may include anemometer calibration, anemometer grading, instrument installation/installation impact, and year-round of valid data; the long-term extrapolation uncertainty factor may include factors such as annual changes, correlations, etc.

Wind flow modeling uncertainty factors may include input data uncertainty factors, horizontal extrapolation uncertainty factors, and vertical extrapolation uncertainty factors, among others.

The loss uncertainty factors may include wake uncertainty factors, fan performance uncertainty factors, environmental uncertainty factors, and other technical loss uncertainty factors.

In step S204, coefficients of respective ones of the uncertainty factors in each of the classes of uncertainty factors are determined. The coefficient of each uncertainty factor in each type of uncertainty factors can be determined according to theoretical basis and working experience of wind power personnel. In the embodiment of the present disclosure, a calculation method or a value range of the uncertainty coefficient of each term is given, and a person skilled in the art may determine the uncertainty coefficient of each term according to the given calculation method or value range of the uncertainty coefficient of each term, in combination with an operation state and an operation environment of an actual wind turbine generator set.

Specifically, the anemometer calibrated by the known calibration mechanism typically takes 1% uncertainty in determining the uncertainty coefficient for the anemometer calibration. If the anemometer is not calibrated, a further 1% uncertainty is added to the default. In determining the uncertainty factor for the anemometer rating, the uncertainty factor is determined according to the International Universal Standard, which is shown in Table 2, where Table 2 is rated according to ACCUWIND-Classification of Five Cup Anemometers According to IEC 61400-12-1.

TABLE 2

In determining the uncertainty factor for the instrument installation/installation impact, the uncertainty factor is in the range of 0% to 3%, and if the anemometer is installed without violating the relevant standard (e.g., IEC standard cylindrical anemometer installation struts should be at 45 degrees to main wind direction and truss anemometer needs to be perpendicular to main wind direction), the uncertainty factor is determined to be 0% and if the anemometer installation severely violates the relevant standard, the uncertainty factor is increased by 1%.

In determining the uncertainty coefficient of the effective data integrity rate, the uncertainty coefficient of the effective data integrity rate may be calculated from (1-effective data integrity rate) x 20%.

In determining the uncertainty coefficient of the internationally variation, whether the representative year is accurate or not is determined, and in general, the data uncertainty coefficient ly of taking only one year of anemometry data takes 6%, the uncertainty coefficient of taking five years of anemometry data is 1y/sqrt (5), and the uncertainty coefficient of the internationally variation of twenty years is 1y/sqrt (20), for example, 1 y=6%; 6%/sqrt (20) =1.3%.

When determining the uncertainty coefficient of the correlation, the correlation coefficient R of the representative year reference data source indicates that the data does not reach the standard if R is less than or equal to 0.6, the data source is not adopted, and if R is more than 0.6, the uncertainty coefficient is (1-R) x 10%.

Geographic data factors, such as topography, roughness, etc., are primarily considered in determining the input data uncertainty coefficients. For example, when the topographic map scales are 1:2000, 1:5000, 1:1 ten thousand, and 1:5 ten thousand, respectively, the uncertainty coefficients take values of 0.25%, 0.5%, 0.75%, and 1%, respectively; when no map is available, the flat terrain has a value of 2% and the mountain terrain has a value of 5%.

In determining the uncertainty coefficient of the horizontal extrapolation, the uncertainty of the horizontal extrapolation is mainly related to the distance of the dead reckoning position and the distance of the anemometer tower, and the uncertainty of the horizontal extrapolation can be classified and defined from the following two aspects: uncertainty coefficient y=0.5% x for simple terrain, uncertainty coefficient y=1.5% x for complex terrain, where,d _ij the horizontal distance between the ith fan and the jth wind measuring tower is represented, and the X unit is km.

In determining the uncertainty coefficient of the vertical extrapolation, the wind speed under ideal conditions is vertically extrapolatedUncertainty of the derivative as the difference in extrapolated height increases, the uncertainty of the vertical extrapolation mainly arises from two aspects: altitude and wind altitude. This term uncertainty can follow an empirical formula, and altitude extrapolation uncertainty can be classified and defined from two aspects: uncertainty coefficient y=0.005% q for simple terrain, uncertainty coefficient y=0.03% q for complex terrain; the wind altitude extrapolation uncertainty can be categorized and defined from two aspects: uncertainty coefficient y=0.03% q for simple terrain, uncertainty coefficient y=0.1% q for complex terrain, where, q _ij The vertical distance between the ith fan and the jth wind measuring tower is represented, and the Q unit is m.

In determining the uncertainty coefficient of the wake, the uncertainty coefficient Y of the flat terrain=5% of the wind farm row number, and the uncertainty coefficient Y of the hills and mountains=30% of the wake.

In determining the uncertainty coefficients of the fan performance (power curve), if the first line manufacturer function curve assurance rates are 95%, 96%, 97% and 98%, respectively, the uncertainty coefficients take values of 0, 1%, 2% and 3%, respectively. In special cases, items with a power curve guarantee rate below 95% may be considered with an uncertainty of 5%.

When determining the uncertainty coefficient of the environment, factors such as forest, animal, noise, flicker and the like are considered, and according to experience, the uncertainty coefficient takes a value of 0% -5%.

When determining the uncertainty coefficient of other technical losses, for example, consider factors such as fan availability, electrical losses and the like, according to experience, the uncertainty coefficient takes a value of 0% -1.5%.

By giving out an uncertainty scientific value-taking strategy, detailed classification can be carried out according to different conditions in the process of calculating the network-surfing electric quantity, and a specific value-taking method is formulated for each index, so that a calculation result is more accurate.

In step S205, a sensitivity coefficient is calculated from the anemometry data. According to an embodiment of the present disclosure, the sensitivity coefficient SF may be calculated according to equation (1):

wherein AEP _-100％ Represents the power generation amount calculated by the hourly or ten-minute wind speed series when the wind data is wind-100% _-105％ AEP representing the calculated power generation amount of hour-by-hour or ten-minute wind speed series when wind data is wind-105% _-95％ Representing the calculated power generation amount of the hour-by-hour or ten-minute wind speed series when the wind data is wind-95% _-100％ Mean wind speed representing hour-by-hour or ten-minute wind speed series for measuring power generation _-105％ Mean wind speed after 105% of hour or ten minute wind speed series for measuring and calculating generated energy is shown _-95％ Mean wind speeds after 95% of the hour-by-hour or ten minute wind speed series for measuring power generation are shown. Therefore, the sensitivity coefficient calculated according to the wind measurement data is more suitable for the wind generating set to be used and is closer to the actual demand.

In step S206, the power generation amount uncertainty coefficients of each type of uncertainty are calculated separately using the uncertainty coefficients of the uncertainty factors in each type. Specifically, a first power generation amount uncertainty coefficient is obtained using the sensitivity coefficient and a coefficient of the determined wind data source uncertainty factor; obtaining a second power generation amount uncertainty coefficient using the sensitivity coefficient and the coefficient of the determined wind flow modeling uncertainty factor; a third power generation amount uncertainty coefficient is obtained using the coefficient of the determined loss uncertainty factor.

For example, when calculating the first power generation amount uncertainty coefficient, multiplying the coefficient of each factor of the determined wind data source uncertainty by the sensitivity coefficient, then squaring and summing the coefficients of each factor multiplied by the sensitivity coefficient, and opening the root number of the sum result to obtain the first power generation amount uncertainty coefficient. When the second generating capacity uncertainty coefficient is calculated, multiplying the coefficient of each factor of the determined wind flow modeling uncertainty by the sensitivity coefficient, then respectively squaring and summing the coefficients of each factor multiplied by the sensitivity coefficient, and opening the root number of the sum result to obtain the first generating capacity uncertainty coefficient.

And when the third generating capacity uncertainty coefficient is calculated, the coefficients of the determined factors of the loss uncertainty are directly used for respectively squaring and summing, and the obtained summing result is provided with a root number to obtain the third generating capacity uncertainty coefficient.

In the method, the concept of sensitivity is introduced in uncertainty calculation, the sensitivity coefficient is not simply set as an empirical constant, but a more accurate sensitivity coefficient is obtained according to wind measurement data, and the result of calculating the online electric quantity is more accurate.

In step S207, the integrated uncertainty coefficient is calculated using the power generation amount uncertainty coefficient of each class. Specifically, the integrated uncertainty coefficient is calculated using the first power generation amount uncertainty coefficient, the second power generation amount uncertainty coefficient, and the third power generation amount uncertainty coefficient to calculate the integrated uncertainty coefficient. The integrated uncertainty coefficient S can be calculated according to equation (2):

wherein S is ₁ Represents a first power generation uncertainty coefficient, S ₂ Represents a second power generation uncertainty coefficient, S ₃ And represents a third power generation amount uncertainty coefficient.

In step S208, the integrated reduction coefficient and the integrated uncertainty coefficient are used to obtain an integrated correction coefficient. According to the embodiment of the present disclosure, the P50 comprehensive correction coefficient is calculated according to the comprehensive reduction coefficient calculated in step S202, and the P75 comprehensive correction coefficient, the P84 comprehensive correction coefficient, the P90 comprehensive correction coefficient, the P95 comprehensive correction coefficient, and the P99 comprehensive correction coefficient are calculated according to the P50 comprehensive correction coefficient, the comprehensive uncertainty coefficient S, respectively.

Specifically, the P50 integrated correction coefficient is 1 minus the integrated reduction coefficient; the P75 comprehensive correction coefficient is multiplied by (1-0.67 x S) the P50 comprehensive correction coefficient; the P84 comprehensive correction coefficient is multiplied by (1-S) by the P50 comprehensive correction coefficient; the P90 comprehensive correction coefficient is multiplied by (1-1.28 x S) the P50 comprehensive correction coefficient; the P95 comprehensive correction coefficient is multiplied by (1-1.64 x S) the P50 comprehensive correction coefficient; the P99 integrated correction factor is the P50 integrated correction factor multiplied by (1-2.33 x s).

In step S209, the online capacity of the wind farm is calculated based on the theoretical net power generation and the comprehensive correction coefficient. After the comprehensive correction coefficients under different override probabilities are obtained, the theoretical net power generation amount and the comprehensive correction coefficients under different override probabilities can be used for calculating the internet power under different override probabilities. Specifically, the P50 internet power is the theoretical net power generation amount multiplied by the P50 comprehensive correction coefficient; the power on the P75 network is the theoretical net power generation amount multiplied by the P75 comprehensive correction coefficient; the power on the P84 network is the theoretical net power generation amount multiplied by the P84 comprehensive correction coefficient; the P90 network-surfing electric quantity is the theoretical net generating capacity multiplied by the P90 comprehensive correction coefficient; the P95 network electric quantity is the theoretical net generating capacity multiplied by the P95 comprehensive correction coefficient; the P99 network electric quantity is the theoretical net generating capacity multiplied by the P99 comprehensive correction coefficient.

In addition, the equivalent full load hours and capacity coefficient can be calculated according to the internet power and the installed capacity, namely the equivalent full load hours are the ratio of the internet power to the installed capacity (the internet power/the installed capacity); the capacity coefficient is the ratio of the number of equivalent full load hours to 8760 (or 8784) (the number of equivalent full load hours/8760 (or 8784)).

Fig. 3 is a block diagram of a system for calculating wind farm internet power according to an example embodiment of the present disclosure.

Referring to fig. 3, a system 300 for calculating wind farm internet power may include a display 301 and a controller 302.

The display 301 may display a plurality of user interfaces. One user interface 3011 of the plurality of user interfaces may be used to input reduction coefficients of a plurality of power generation amount reduction items. For example, as shown in FIG. 4, a user may set an air density reduction factor, a wake reduction factor, a wind turbine generator system utilization reduction factor, a wind turbine generator system power curve reduction factor, a blade pollution loss reduction factor, a line loss and self-electricity consumption loss reduction factor, a control and turbulence effect loss reduction factor, a climate effect reduction factor (not shown), an icing reduction factor (not shown), a surrounding wind farm effect reduction factor (not shown), a limiting factor reduction factor (not shown) according to a theoretical method and a working experience. The method for setting the reduction coefficient of each reduction term is the same as the procedure of step S201, and will not be described here again.

After a plurality of reduction coefficients are input to the system 300 through the user interface 3011, the controller 302 may calculate the integrated reduction coefficient using the reduction coefficients of the input individual reduction items. Specifically, the controller 302 multiplies the reduction coefficients of the respective reduction items inputted to obtain an integrated reduction coefficient, and then displays the obtained integrated reduction coefficient to the user through the user interface 3011.

The plurality of anemometry data may be input using a first user interface 3012 of the plurality of user interfaces. For example, as shown in FIG. 5, the user may calculate the power generation amount AEP of the hour-by-hour or ten-minute wind speed series at wind data of wind-100% through the first user interface 3012 _-100％ Calculated power generation amount AEP of hour-by-hour or ten-minute wind speed series when wind data is wind-105% _-105％ Calculated power generation amount AEP of hour-by-hour or ten-minute wind speed series when wind data is wind-95% _-95％ Average wind speed wind for measuring and calculating hour-by-hour or ten-minute wind speed series of generated energy _-100％ Average wind speed wind after 105% of hour-by-hour or ten-minute wind speed series for measuring and calculating generated energy _-105％ Average wind speed wind after 95% of hour-by-hour or ten-minute wind speed series for measuring and calculating generated energy _-95％ Respectively into the system 300. Then, the controller 302 calculates the sensitivity coefficient using equation (1) according to the parameter value input through the first user interface 3012. After the sensitivity coefficient is calculated, the calculated sensitivity coefficient value may be displayed to a user via the first user interface 3012 by the display 301.

In calculating the integrated uncertainty coefficients, the coefficients of wind data source uncertainty factors may be input through a second user interface (not shown) of the plurality of user interfaces, the coefficients of wind flow modeling uncertainty factors may be input through a third user interface (not shown) of the plurality of user interfaces, and the coefficients of loss uncertainty factors may be input through a fourth user interface (not shown) of the plurality of user interfaces.

The controller 302 may calculate a first power generation amount uncertainty coefficient using the sensitivity coefficient and the coefficient of the wind data source uncertainty factor input through the second user interface, and display the calculated first power generation amount uncertainty coefficient to the user through the display 301 via the second user interface. The controller 302 may also calculate a second power generation amount uncertainty coefficient using the sensitivity coefficient and a coefficient of a wind flow modeling uncertainty factor input through a third user interface of the plurality of user interfaces, and display the calculated second power generation amount uncertainty coefficient to the user through the display 301 via the third user interface.

The controller 302 may also calculate the third power generation amount uncertainty coefficient using the coefficient of the loss uncertainty factor input through the fourth user interface among the plurality of user interfaces, and display the calculated second power generation amount uncertainty coefficient to the user through the display 301 via the fourth user interface.

After obtaining the first, second, and third power generation amount uncertainty coefficients, the controller 302 may calculate the integrated uncertainty coefficient according to equation (2), and may display the result of the integrated uncertainty coefficient to the user through the fourth user interface, however, the present disclosure is not limited thereto.

The controller 302 may use the integrated reduction coefficient and the integrated uncertainty coefficient to obtain an integrated correction coefficient and calculate the wind farm's online capacity based on the theoretical net power generation and the integrated correction coefficient. According to the embodiment of the present disclosure, the controller 302 may calculate the internet power under different override probabilities, and the calculation process is the same as the process of step S208 and step S209, and will not be described again. The amount of power to surf the internet at different overrun probabilities may be displayed to the user via a fifth user interface (not shown) of the plurality of user interfaces via the display 301.

Referring to fig. 6, an apparatus 600 for calculating a wind farm internet power may include a reduction coefficient calculation module 601, an uncertainty coefficient calculation module 602, and an internet power calculation module 603. Each module in the apparatus 600 according to the present disclosure may be implemented by one or more modules, and the names of the corresponding modules may vary according to the type of apparatus. In various embodiments, some modules in apparatus 600 may be omitted, or additional modules may be included. Further, modules according to various embodiments of the present disclosure may be combined to form a single entity, and thus functions of the respective modules before combination may be equivalently performed.

The reduction coefficient calculation module 601 may calculate the integrated reduction coefficient from at least one power generation amount reduction term. Specifically, after determining various reduction coefficients such as air density, wake flow, wind generating set utilization rate, wind generating set power curve, blade pollution, line loss, self-power consumption, turbulence influence, climate influence, yaw, surrounding wind farm influence, and the like, the reduction coefficient calculation module 601 multiplies the determined reduction coefficients of each item to obtain a comprehensive reduction coefficient.

The uncertainty coefficient calculation module 602 may classify the power generation uncertainty factors into wind data source uncertainty, wind flow modeling uncertainty, and loss uncertainty, and obtain a comprehensive uncertainty coefficient by calculating coefficients of each class of power generation uncertainty separately. Specifically, the uncertainty coefficient calculation module 602 may determine the coefficients of the factors included in each type of uncertainty, using the determination method of step S204.

The uncertainty coefficient calculation module 602 may also calculate the sensitivity coefficient using equation (1). After obtaining the sensitivity coefficients, the uncertainty coefficient calculation module 602 may use the sensitivity coefficients and the coefficients of the determined wind data source uncertainty factors to obtain a first power generation amount uncertainty coefficient, use the sensitivity coefficients and the coefficients of the determined wind flow modeling uncertainty factors to obtain a second power generation amount uncertainty coefficient, and use the coefficients of the determined loss uncertainty factors to obtain a third power generation amount uncertainty coefficient. The process of calculating the uncertainty coefficient of each type of power generation amount is the same as that of step S206, and will not be described here again.

After obtaining each type of uncertainty coefficient, the uncertainty coefficient calculation module 602 calculates a composite uncertainty coefficient from the generated energy uncertainty coefficient of each type using equation (2).

The online capacity calculation module 603 may use the integrated reduction coefficient, the integrated uncertainty coefficient, and the sensitivity coefficient to obtain an integrated correction coefficient, and calculate the online capacity of the wind farm based on the theoretical net power generation and the integrated correction coefficient. Specifically, the internet power calculation module 603 may obtain the P50 integrated correction coefficient by subtracting the integrated reduction coefficient from 1, obtain the P75 integrated correction coefficient by multiplying the P50 integrated correction coefficient by (1-0.67×s), obtain the P84 integrated correction coefficient by multiplying the P50 integrated correction coefficient by (1-S), obtain the P90 integrated correction coefficient by multiplying the P50 integrated correction coefficient by (1-1.28×s), obtain the P95 integrated correction coefficient by multiplying the P50 integrated correction coefficient by (1-1.64×s), and obtain the P99 integrated correction coefficient by multiplying the P50 integrated correction coefficient by (1-2.33×s), where S represents the sensitivity coefficient.

After obtaining the comprehensive correction coefficients under different override probabilities, the online power calculation module 603 may use the theoretical net power generation and the comprehensive correction coefficients under each override probability to obtain the online power under each override probability.

The method of calculating the amount of power to wind farm surfing according to the exemplary embodiments of the present disclosure may be implemented as computer readable instructions on a computer readable recording medium or may be transmitted through a transmission medium. The computer readable recording medium is any data storage device that can store data which can be thereafter read by a computer system. Examples of the computer readable recording medium include, but are not limited to, read-only memory (ROM), random-access memory (RAM), compact discs (CD-ROMs), digital Versatile Discs (DVDs), magnetic tapes, floppy disks, and optical data storage devices. The transmission medium may include carrier waves transmitted over a network or various types of communication channels. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable instructions are stored and executed in a distributed fashion.

In the method, all factors affecting the actual output of the wind farm are analyzed one by one and are classified into two types of comprehensive reduction coefficients and comprehensive uncertainty coefficients, and all the influence factors are not considered as reduction coefficients. When the factors influencing the actual output of the wind power plant are corrected, a scientific value strategy of the reduction term coefficient and the uncertainty coefficient is provided, indexes can be quantitatively processed for different project conditions, and a user can conveniently and rapidly make accurate judgment according to the project conditions. In addition, when the uncertainty coefficient is calculated, the sensitivity coefficient concept is introduced, and the sensitivity coefficient is not simply set as an empirical constant, so that the calculation result is more reasonable and accurate.

In the method, scientific calculation software is used to develop a digital tool for calculating comprehensive reduction coefficients, comprehensive uncertainty coefficients and Internet surfing electric quantity, and a user can automatically output physical quantities such as generated energy, internet surfing electric quantity, full load hours and capacity coefficients under each overrun probability by inputting the values of various indexes only according to the current situation of a project and combining index quantization standards. Through the system disclosed by the invention, the calculation efficiency of the generated energy of the staff is improved by at least 80%, and the workload of the staff is greatly reduced.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the following claims.

Claims

1. A method of calculating the amount of power on a wind farm, the method comprising:

calculating a comprehensive reduction coefficient according to at least one generating capacity reduction term;

the comprehensive uncertainty coefficient is obtained by classifying the generating capacity uncertainty factors;

calculating the internet power of the wind power plant by using the comprehensive reduction coefficient and the comprehensive uncertainty coefficient;

Wherein, the step of calculating the comprehensive reduction coefficient comprises the following steps:

determining a reduction coefficient of each of the at least one energy generation amount reduction term, wherein the reduction coefficient of each term is determined in combination with the operation state and the operation environment of the actual wind generating set, and the at least one energy generation amount reduction term comprises at least one of the following reference terms: air density reduction items, wake flow reduction items, wind turbine generator set utilization ratio reduction items, wind turbine generator set power curve reduction items, blade pollution loss reduction items, line loss self-power consumption reduction items, control and turbulence influence loss reduction items, climate influence reduction items, icing reduction items, surrounding wind farm influence reduction items and limiting factor reduction items;

multiplying the determined reduction coefficient of each term to obtain a comprehensive reduction coefficient;

wherein the step of obtaining the comprehensive uncertainty coefficient by classifying the power generation amount uncertainty factor includes:

classifying the generating capacity uncertainty factors into wind data source uncertainty, wind flow modeling uncertainty and loss uncertainty, wherein the wind data source uncertainty factors comprise site wind data uncertainty factors and long-term extrapolation uncertainty factors, the site wind data uncertainty factors comprise anemometer calibration, anemometer classification, instrument installation influence and effective data integrity rate, and the long-term extrapolation uncertainty factors comprise annual changes and correlations; wind flow modeling uncertainty factors include input data uncertainty factors, horizontal extrapolation uncertainty factors, and vertical extrapolation uncertainty factors; the loss uncertainty factors include wake uncertainty factors, fan performance uncertainty factors, environmental uncertainty factors, and other technical loss uncertainty factors;

Calculating the power generation amount uncertainty coefficient of each type of uncertainty by using the uncertainty factor of each type, wherein the coefficient of each uncertainty factor is determined according to the calculation method or the value range of the coefficient of each uncertainty factor given by combining the operation state and the operation environment of the actual wind generating set;

the integrated uncertainty coefficients are calculated using the generated energy uncertainty coefficients for each type of uncertainty.

2. The method of claim 1, wherein the step of separately calculating the power generation amount uncertainty coefficients for each type of uncertainty comprises:

determining coefficients of various uncertainty factors in each type of uncertainty factors;

calculating a sensitivity coefficient from the anemometry data;

obtaining a first power generation amount uncertainty coefficient using the sensitivity coefficient and a coefficient of the determined wind data source uncertainty factor;

obtaining a second power generation amount uncertainty coefficient using the sensitivity coefficient and the coefficient of the determined wind flow modeling uncertainty factor;

a third power generation amount uncertainty coefficient is obtained using the coefficient of the determined loss uncertainty factor.

3. The method of claim 1, wherein the step of calculating the amount of power to wind farm using the integrated reduction coefficient and the integrated uncertainty coefficient comprises:

Obtaining a comprehensive correction coefficient by using the comprehensive reduction coefficient and the comprehensive uncertainty coefficient;

and calculating the Internet surfing electric quantity of the wind power plant based on the theoretical net generating capacity and the comprehensive correction coefficient.

4. A device for calculating the amount of electricity on a wind farm, the device comprising:

the reduction coefficient calculation module is used for calculating a comprehensive reduction coefficient according to at least one generating capacity reduction item;

the uncertainty coefficient calculation module is used for obtaining a comprehensive uncertainty coefficient by classifying the generating capacity uncertainty factors;

the online electric quantity calculation module is used for calculating the online electric quantity of the wind power plant by using the comprehensive reduction coefficient and the comprehensive uncertainty coefficient;

the reduction coefficient calculation module is used for:

determining a reduction coefficient of each of the at least one generated energy reduction term, and multiplying the determined reduction coefficient of each term to obtain a comprehensive reduction coefficient, wherein the reduction coefficient of each term is determined in combination with the operation state and the operation environment of the actual wind generating set, and the at least one generated energy reduction term comprises at least one of the following reference terms: air density reduction items, wake flow reduction items, wind turbine generator set utilization ratio reduction items, wind turbine generator set power curve reduction items, blade pollution loss reduction items, line loss self-power consumption reduction items, control and turbulence influence loss reduction items, climate influence reduction items, icing reduction items, surrounding wind farm influence reduction items and limiting factor reduction items;

Wherein, uncertainty coefficient calculation module is used for:

The integrated uncertainty coefficient is calculated using the generated energy uncertainty coefficient of each class.

5. The apparatus of claim 4, wherein the uncertainty coefficient calculation module is further to:

calculating a sensitivity coefficient from the anemometry data;

6. The apparatus of claim 4, wherein the internet power calculation module is configured to:

7. A system for calculating wind farm internet power, the system comprising:

the display is used for displaying a plurality of user interfaces, the plurality of user interfaces are used for respectively inputting reduction coefficients of at least one energy generation amount reduction item and coefficients of a plurality of uncertainty factors, wherein the reduction coefficients of each item are determined according to the operation state and the operation environment of the actual wind generating set, the coefficients of the uncertainty factors of each item are determined according to a given calculation method or a given value range of the coefficients of the uncertainty factors of each item, and the at least one energy generation amount reduction item is determined according to the operation state and the operation environment of the actual wind generating set, and comprises at least one of the following reference items: air density reduction items, wake flow reduction items, wind turbine generator set utilization ratio reduction items, wind turbine generator set power curve reduction items, blade pollution loss reduction items, line loss self-power consumption reduction items, control and turbulence influence loss reduction items, climate influence reduction items, icing reduction items, surrounding wind farm influence reduction items and limiting factor reduction items; wind data source uncertainty factors include on-site wind data uncertainty factors including anemometer calibration, anemometer classification, instrument installation impact, and effective data integrity rate, and long-term extrapolation uncertainty factors including annual changes, correlations; wind flow modeling uncertainty factors include input data uncertainty factors, horizontal extrapolation uncertainty factors, and vertical extrapolation uncertainty factors; the loss uncertainty factors include wake uncertainty factors, fan performance uncertainty factors, environmental uncertainty factors, and other technical loss uncertainty factors;

A controller for:

calculating a comprehensive reduction coefficient using the reduction coefficient of the input at least one power generation amount reduction term;

calculating a comprehensive uncertainty coefficient using the coefficients of the plurality of uncertainty factors input;

and calculating the internet power of the wind power plant based on the calculated comprehensive reduction coefficient and the comprehensive uncertainty coefficient.

8. The system of claim 7, wherein the controller calculates the sensitivity coefficient using anemometry data entered through a first user interface of the plurality of user interfaces.

9. The system of claim 8, wherein the controller is to:

calculating a first power generation amount uncertainty coefficient using the sensitivity coefficient and a coefficient of a wind data source uncertainty factor input through a second user interface of the plurality of user interfaces;

calculating a second power generation amount uncertainty coefficient using the sensitivity coefficient and a coefficient of a wind flow modeling uncertainty factor input through a third user interface of the plurality of user interfaces;

calculating a third power generation amount uncertainty coefficient using coefficients of the loss uncertainty factors input through a fourth user interface of the plurality of user interfaces;

A composite uncertainty coefficient is calculated based on the first, second, and third power generation uncertainty coefficients.

10. The system of claim 7, wherein the controller is to:

11. A computer readable storage medium storing a program, characterized in that the program comprises instructions for performing the method of any one of claims 1-3.

12. A computer comprising a readable medium storing a computer program, characterized in that the computer program comprises instructions for performing the method of any of claims 1-3.