CN112865204B - Wind power plant frequency support capacity estimation method and device and computer equipment - Google Patents

Abstract

The present application relates to a method, device, computer equipment and computer-readable storage medium for estimating the frequency support capability of a wind farm. The method includes: according to the frequency response strategy, establishing a relationship model between the generated power of the wind turbine and the frequency support capability that the wind turbine can provide; using the historical data of the generated power of the wind turbine to solve the above relationship model to obtain the frequency support capability of the wind turbine The historical data; according to the historical data of wind power generation power and corresponding frequency support capacity, calculate the equivalent power generation power of wind farm and the equivalent frequency support capacity of wind farm; fit the historical data of wind power generation power and frequency support capacity to get the power generation Functional relationship between power and frequency support capability; Substituting the real-time data of wind farm power generation into the above functional relationship to get the estimated result of wind farm frequency support capability. This method can accurately estimate the frequency support capacity of wind farms, and the estimated results can be used as the basis for power system planning.

Description

Wind farm frequency support capability estimation method, device and computer equipment

Technical Field

The present application relates to the technical field of power system planning, and in particular to a method, device, computer equipment and computer-readable storage medium for estimating frequency support capability of a wind farm.

Background Art

In recent years, new energy has been widely used due to its abundant resources and general renewable characteristics. However, the volatility of renewable energy power generation has led to a continuous decline in the frequency support capacity of the power system, such as the inertia coefficient and droop coefficient, seriously affecting the frequency security of the power system.

Traditionally, only synchronous generators can provide frequency support, but the idea of non-synchronous generators providing frequency support has also been widely studied. For example, wind turbines can achieve frequency support by temporarily increasing power and simulating the inertia or droop response of synchronous generator sets.

Since traditional technology makes it difficult to accurately estimate the equivalent frequency support capacity of a wind farm, the equivalent frequency support capacity of a wind farm cannot be included in the planning process when planning the power system, and the function of wind turbines in participating in system frequency regulation cannot be fully utilized.

Summary of the invention

Based on this, it is necessary to provide a method, device, computer equipment and storage medium for estimating the frequency support capacity of a wind farm, which can obtain more accurate estimation results in response to the above technical problems.

A method for estimating frequency support capability of a wind farm, the method comprising:

According to the frequency response strategy, a relationship model between the power generation of the wind turbine set and the frequency support capability that the wind turbine set can provide is established; the historical data of the power generation of the wind turbine set is obtained, and based on the historical data of the power generation of the wind turbine set, the relationship model between the power generation of the wind turbine set and the frequency support capability that the wind turbine set can provide is solved to obtain the corresponding historical data of the frequency support capability of the wind turbine set; based on the historical data of the power generation of the wind turbine set and the corresponding historical data of the frequency support capability of the wind turbine set, the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under different wind conditions are calculated; the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under different wind conditions are fitted to obtain the functional relationship between the power generation of the wind farm and the frequency support capability of the wind farm; the real-time data of the power generation of the wind farm is substituted into the functional relationship between the power generation of the wind farm and the frequency support capability of the wind farm to obtain the estimated result of the frequency support capability of the wind farm.

In one embodiment, the real-time data of the wind farm power generation includes real-time data of the average power of the wind farm within a preset period of time. According to the frequency response strategy, establishing a relationship model between the power generation of the wind turbine and the frequency support capability that the wind turbine can provide includes:

Determine the relationship between the corresponding wind turbine power generation and the reserved reserve power according to the frequency response strategy; determine the relationship between the reserved reserve power and the inertia coefficient representing the frequency support capability; determine the relationship between the reserved reserve power and the droop coefficient representing the frequency support capability; determine the relationship between the power generation and the inertia coefficient based on the relationship between the power generation and the reserved reserve power, and the relationship between the reserved reserve power and the inertia coefficient; determine the relationship between the power generation and the droop coefficient based on the relationship between the power generation and the reserved reserve power, and the relationship between the reserved reserve power and the droop coefficient.

In one embodiment, the frequency response strategy includes at least one of the following:

When the output of a wind turbine is higher than the system set level, the excess part is reserved as standby power, which is used to provide frequency response; the wind turbine maintains standby power at a constant power point, which is used to provide frequency response; the ratio between the standby power of a wind turbine and the generated power of the wind turbine is constant, which is used to provide frequency response.

In one embodiment, obtaining historical data of wind turbine power generation includes:

Determine the functional relationship between the wind speed of the wind turbine set and the power generation of the wind turbine set; obtain historical data of the wind speed of the wind turbine set; and obtain historical data of the power generation of the wind turbine set based on the historical data of the wind speed of the wind turbine set and the functional relationship between the wind speed of the wind turbine set and the power generation of the wind turbine set.

In one embodiment, after determining the relationship between the generated power and the droop coefficient based on the relationship between the generated power and the reserved standby power and the relationship between the reserved standby power and the droop coefficient, the method further includes:

Determine the control error of the wind turbine; based on the control error of the wind turbine, the relationship between the power generation of the wind turbine and the inertia coefficient, determine the relationship between the power generation of the wind turbine and the inertia coefficient under the control error; based on the control error of the wind turbine, the relationship between the power generation of the wind turbine and the droop coefficient, determine the relationship between the power generation of the wind turbine and the droop coefficient under the control error.

In one embodiment, after fitting the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under different wind conditions to obtain a functional relationship between the power generation of the wind farm and the frequency support capability of the wind farm, the method further includes:

Obtain historical data of the average power of the wind farm within a preset time period and historical data of the minimum power of the wind farm within the preset time period; obtain a functional relationship between the average power of the wind farm within the preset time period and the minimum power of the wind farm within the preset time period by fitting; obtain real-time data of the average power of the wind farm within the preset time period, substitute the real-time data of the average power of the wind farm within the preset time period into the functional relationship between the average power of the wind farm within the preset time period and the minimum power of the wind farm within the preset time period, and estimate the real-time data of the minimum power of the wind farm within the corresponding preset time period.

In one embodiment, obtaining historical data of average power of a wind farm within a preset period and historical data of minimum power of a wind farm within a preset period includes:

Obtain historical data of minute-level power generation of the wind farm; calculate the average power of the wind farm within an hour and the minimum power within an hour based on the historical data of minute-level power generation of the wind farm.

A device for estimating frequency support capability of a wind farm, the device comprising:

Creating a module for establishing a relationship model between the power generation of a wind turbine and the frequency support capability that the wind turbine can provide according to a frequency response strategy;

The first solution module is used to obtain historical data of the power generation of the wind turbine set, and solve the relationship model between the power generation of the wind turbine set and the frequency support capability that the wind turbine set can provide based on the historical data of the power generation of the wind turbine set, so as to obtain the corresponding historical data of the frequency support capability of the wind turbine set;

An equivalent module is used to calculate the equivalent power generation power and the equivalent frequency support capacity of the wind farm under different wind conditions according to the historical data of the power generation power of the wind turbine set and the historical data of the frequency support capacity of the corresponding wind turbine set;

The first fitting module is used to fit the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under different wind conditions to obtain a functional relationship between the power generation of the wind farm and the frequency support capability of the wind farm;

The second solution module is used to substitute the real-time data of the wind farm power generation into the functional relationship between the wind farm power generation and the wind farm frequency support capability to obtain an estimated result of the wind farm frequency support capability.

In one embodiment, the real-time data of the wind farm power generation includes real-time data of the average power of the wind farm within a preset period of time, and the creation module is specifically used to:

Determine the relationship between the corresponding wind turbine power generation and the reserved reserve power according to the frequency response strategy; determine the relationship between the reserved reserve power and the inertia coefficient representing the frequency support capability; determine the relationship between the reserved reserve power and the droop coefficient representing the frequency support capability; determine the relationship between the power generation and the inertia coefficient based on the relationship between the power generation and the reserved reserve power, and the relationship between the reserved reserve power and the inertia coefficient; determine the relationship between the power generation and the droop coefficient based on the relationship between the power generation and the reserved reserve power, and the relationship between the reserved reserve power and the droop coefficient.

In one embodiment, the frequency response strategy includes at least one of the following:

When the wind turbine output is higher than the system set level, the excess part is reserved as standby power, which is used to provide frequency response; the wind turbine maintains standby power at a constant power point, which is used to provide frequency response; the ratio between the wind turbine standby power and the wind turbine power generation power is constant, which is used to provide frequency response.

In one embodiment, the first solution module is specifically used to:

Determine the functional relationship between the wind speed of the wind turbine set and the power generation of the wind turbine set; obtain historical data of the wind speed of the wind turbine set; and obtain historical data of the power generation of the wind turbine set based on the historical data of the wind speed of the wind turbine set and the functional relationship between the wind speed of the wind turbine set and the power generation of the wind turbine set.

In one embodiment, the apparatus further includes an error determination module, a first relationship module, and a second relationship module:

The error determination module is used to determine the control error of the wind turbine generator set;

The first relationship module is used to determine the relationship between the power generation of the wind turbine set and the inertia coefficient under the control error based on the control error of the wind turbine set and the relationship between the power generation of the wind turbine set and the inertia coefficient;

The second relationship module is used to determine the relationship between the power generation of the wind turbine set and the droop coefficient under the control error based on the control error of the wind turbine set and the relationship between the power generation of the wind turbine set and the droop coefficient.

In one embodiment, the device further includes a data acquisition module, a second fitting module, and a third solution module:

The data acquisition module is used to obtain historical data of average power of the wind farm within a preset period and historical data of minimum power of the wind farm within a preset period;

The second fitting module is used to fit the functional relationship between the average power of the wind farm in a preset period and the minimum power of the wind farm in the preset period;

The third solution module is used to obtain real-time data of the average power of the wind farm within a preset time period, substitute the real-time data of the average power of the wind farm within the preset time period into the functional relationship between the average power of the wind farm within the preset time period and the minimum power of the wind farm within the preset time period, and estimate the real-time data of the minimum power of the wind farm within the corresponding preset time period.

In one embodiment, the data acquisition module is specifically used to:

Obtain historical data of minute-level power generation of the wind farm; calculate the average power of the wind farm within an hour and the minimum power within an hour based on the historical data of minute-level power generation of the wind farm.

A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the processor executes any of the above-mentioned methods for estimating the frequency support capability of a wind farm.

A computer-readable storage medium stores a computer program, which, when executed by a processor, implements any of the above-mentioned methods for estimating the frequency support capability of a wind farm.

The above-mentioned wind farm frequency support capacity estimation method, device, computer equipment and computer-readable storage medium first consider different frequency response strategies, and establish relationship models between the power generation power of the wind turbine set and the frequency support capacity that the wind turbine set can provide according to different frequency response strategies; then, based on the historical data of the power generation power of the wind turbine set, solve the relationship model between the power generation power and the frequency support capacity, and obtain the historical data of the frequency support capacity corresponding to the wind turbine set; then, based on the data of a single wind turbine set, calculate the equivalent power generation power and frequency support capacity of the wind farm under different wind conditions; finally, fit the equivalent power generation power of the wind farm under different wind conditions and the frequency support capacity of the wind farm, and obtain the functional relationship between the power generation power of the wind farm and the frequency support capacity of the wind farm. This method of estimating the frequency support capacity of a wind farm takes into account different frequency response strategies and the differences between a single wind turbine and a wind farm. The use of different frequency response strategies by a wind farm will result in different powers used to maintain frequency stability, which in turn affects the frequency support capacity of the wind farm. Due to the different wind speed distributions within a wind farm, the frequency support capacity that a single wind turbine can provide is different. It is necessary to calculate the frequency support capacity of a single wind turbine by the power generation of a single wind turbine, and obtain a more accurate equivalent frequency support capacity of the wind farm. On the basis of considering the above-mentioned frequency response strategies and the differences between single wind turbines, the functional relationship is fitted using a large amount of historical data, which can more accurately estimate the frequency support capacity of a wind farm, and the corresponding estimation results can be used as the basis for power system planning and scheduling.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic flow chart of a method for estimating frequency support capability of a wind farm in one embodiment;

FIG2 is a flow chart of a technical process for establishing a relationship model between the power generation of a wind turbine generator set and the frequency support capability that the wind turbine generator set can provide according to a frequency response strategy in one embodiment;

FIG3 is a flow chart of a technical process for obtaining historical data of wind turbine power generation in one embodiment;

FIG4 is a schematic flow chart of a method for estimating wind farm frequency support capability in another embodiment;

FIG5 is a schematic flow chart of a method for estimating wind farm frequency support capability in another embodiment;

FIG6 is a scatter plot of wind farm power generation and inertia coefficient when three frequency response strategies are adopted in one embodiment;

FIG7 is a scatter diagram and fitting curve of wind farm power generation and inertia coefficient when three frequency response strategies are adopted in one embodiment;

FIG8 is a characteristic curve of hourly average power of a wind farm and minimum power within the hour in one embodiment;

FIG9 is a fitting curve of the hourly average power of a wind farm and the minimum power within the hour in one embodiment;

FIG10 is a structural block diagram of a device for estimating frequency support capability of a wind farm in one embodiment;

FIG11 is a structural block diagram of a device for estimating wind farm frequency support capability in another embodiment;

FIG12 is a structural block diagram of a device for estimating wind farm frequency support capability in another embodiment;

FIG. 13 is a diagram showing the internal structure of a computer device in one embodiment.

DETAILED DESCRIPTION

In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

In the power system, frequency is the operating parameter of the entire power system and can measure the power quality of the power grid. The rated frequency of my country's power system is 50Hz. It is stipulated that the frequency deviation of power systems above 3 million kw shall not exceed ±0.2Hz, and the frequency deviation of power systems below 3 million kw shall not exceed ±0.5Hz. Unstable frequency may cause many hazards such as damage to equipment in the system, reduced production efficiency, and even large-scale power outages. Generally speaking, frequency instability will occur when the power generation power does not match the power load.

With the development of technology, the penetration rate of fluctuating renewable energy continues to increase. In some countries, the power generation of fluctuating renewable energy has exceeded 20% of the total. China has also proposed a goal of 60% of fluctuating renewable energy by 2050. However, renewable energy power generation has the characteristics of intermittent supply and cannot continuously output stable power. Compared with the stable transmission of traditional thermal power, the popularization of fluctuating renewable energy has brought new challenges to maintaining the stability of power system frequency.

In order to maintain the stability of the power system frequency, it is necessary to store backup power as additional power. For example, wind turbines can simulate the inertia or droop response of synchronous machines by temporarily increasing power to achieve frequency support. The frequency support capacity is expressed by the inertia coefficient and droop coefficient of the power system. The larger the inertia coefficient and droop coefficient, the stronger the wind turbine's ability to provide frequency support. When planning a power system that includes new energy, in order to maintain frequency stability, it is necessary to estimate the frequency support capacity of the power supply farm in advance. However, traditional technology makes it difficult to accurately estimate the frequency support capacity of a wind farm, and therefore it is impossible to incorporate the frequency support capacity of a wind farm into the planning process, resulting in a waste of resources.

In view of this, an embodiment of the present application provides a method for estimating the frequency support capacity of a wind farm, in which different frequency response strategies are considered to establish a relationship model between the power generation of a wind turbine and the frequency support capacity that the wind turbine can provide; historical data on the power generation of the wind turbine is obtained, and the historical data is substituted into the relationship model between the power generation and the frequency support capacity to obtain the historical data on the frequency support capacity of the wind turbine. According to the power generation of the wind turbine and the corresponding frequency support capacity, the equivalent power generation and frequency support capacity of the wind farm under different wind conditions are calculated; the equivalent power generation and frequency support capacity of the wind farm under different wind conditions are fitted to obtain the functional relationship between the power generation of the wind farm and the frequency support capacity of the wind farm; the real-time data on the power generation of the wind farm is substituted into the functional relationship between the power generation of the wind farm and the frequency support capacity of the wind farm to obtain the estimated result of the frequency support capacity of the wind farm. This method for estimating the frequency support capability of a wind farm takes into account the different frequency response strategies of wind turbines and the differences between individual wind turbines and wind farms. It uses a large amount of historical data fitting of the target wind farm to effectively improve the accuracy of the wind farm frequency support capability estimation and provide a reliable basis for power system planning.

In one embodiment, as shown in FIG1 , a method for estimating frequency support capability of a wind farm is provided, comprising the following steps:

Step 102: Establish a relationship model between the power generation of the wind turbines and the frequency support capability that the wind turbines can provide according to the frequency response strategy of the wind farm.

Among them, the wind turbine will reserve some standby power while generating electricity. When the frequency of the power system fluctuates, the wind turbine will temporarily increase the reserved standby power to provide frequency support. The method for the wind turbine to determine the standby power based on the generated power and rated power is a frequency response strategy. In an optional embodiment of the present application, the frequency response strategy may include that the standby power is affected by the rated power and generated power of the wind turbine, and the standby power is only related to the generated power of the wind turbine.

In an optional embodiment of the present application, the wind turbine reserve power will provide a frequency response in the form of an equivalent synchronous machine, that is, the reserve power can provide an equivalent inertial response and droop response:

表示系统频率的变化量对时间的微分。用惯性系数和下垂系数表征该风电机组的频率支撑能力，惯性系数和下垂系数的值越大，该风电机组的频率支撑能力越强。Where ΔP ^W is the power used by the wind turbine to provide frequency response, H ^W represents the equivalent inertia coefficient provided by the wind turbine, k ^W represents the equivalent droop coefficient provided by the wind turbine, and Δf represents the change in system frequency.

It represents the differential of the change of system frequency with respect to time. The frequency support capability of the wind turbine is characterized by the inertia coefficient and the droop coefficient. The larger the value of the inertia coefficient and the droop coefficient, the stronger the frequency support capability of the wind turbine.

In an optional embodiment of the present application, the frequency response strategy determines the relationship between the power generation and the reserve power of the wind turbine, and the reserve power can provide an equivalent inertial response and a droop response. Formula (1) reflects the relationship between the reserve power and the inertia coefficient and the droop coefficient that characterize the frequency support capability. With the reserve power as an intermediate variable, a relationship model between the power generation and the frequency support capability of the wind turbine is established.

Step 104, obtaining historical data of the wind turbine generator set's power generation, solving a relationship model between the wind turbine generator set's power generation and the frequency support capability that the wind turbine generator set can provide based on the historical data of the wind turbine generator set's power generation, and obtaining corresponding historical data of the wind turbine generator set's frequency support capability.

The wind farm will monitor each wind turbine in the farm, and the monitoring data includes the historical data of various indicators of the wind turbine. For a certain wind condition in the wind farm, the actual wind speed of each wind turbine is different, and the power generation capacity will be different.

In an optional embodiment of the present application, the historical data of the power generation of each wind turbine set under the same wind condition in the wind farm is first obtained. Assuming that there are n wind turbine sets in the wind farm, and the wind condition of the wind farm is represented by vm, the historical data set of the power generation of each wind turbine set under the wind condition v1 is {P ₁ ^v1 , P ₂ ^v1 , …, P _n ^v1 }. Then, the historical data of the power generation of each wind turbine set under other wind conditions is obtained, and the historical data set of the power generation of each wind turbine set under other wind conditions is {P ₁ ^v2 , P ₂ ^v2 , …, P _n ^v2 }, {P ₁ ^v3 , P ₂ ^v3 , …, P _n ^v3 }, …{P ₁ ^vm , P ₂ ^vm , …, P _n ^vm }.

In an optional embodiment of the present application, the historical data of the wind turbine generator set's generated power under different wind conditions obtained above are substituted into the relationship model between the wind turbine generator set's generated power and the frequency support capability obtained in step 102 to ^{solve the frequency support capability corresponding to the wind turbine generator set, so as to obtain a historical data set of the frequency support capability of the wind turbine generator set under different wind conditions, and the inertia coefficient set is {{H1v1, H2v1,…, Hnv1}, {H1v2 ,} _H2v2 ^{, …} _{, Hnv2} ^} _{, …} ^{, { H1vm} _, ^H2vm _, ^… _{, Hnvm} ^{} }} , _and the droop ^coefficient set is {{ _k1v1 , _k2v1 ,…, _knv1 }, { ^{k1v2 ,} _k2v2 ,…, _knv2 ^} ,…, { ^k1vm , _k2vm , _… ^{, knvm} _} }.

Step 106, calculating the equivalent power generation power and the equivalent frequency support capability of the wind farm under different wind conditions based on the historical data of the power generation power of the wind turbine set and the historical data of the corresponding frequency support capability of the wind turbine set.

When considering the frequency response strategy, the actual wind speed distribution of individual wind turbines in the power farm is different, resulting in different reserve power reserves, and the frequency support capacity of the wind farm cannot be calculated using the total power generation data of the wind farm. Calculating the power generation and reserve power of a single wind turbine, and then equivalently obtaining the power generation and reserve power of the wind farm takes into account the differences of individual wind turbines, which can make the prediction results more accurate.

In an optional embodiment of the present application, the historical data of the wind turbine generator set power generation under the same wind condition is summed to obtain the equivalent power generation of the wind farm under the wind condition, and the historical data of the wind turbine generator set frequency support capacity under the same wind condition is summed to obtain the equivalent frequency support capacity of the wind farm under the wind condition. Finally, the equivalent power generation of the wind farm and the equivalent frequency support capacity of the wind farm under different wind conditions are obtained. The data pair of the equivalent power generation of the wind farm and the equivalent frequency support capacity of the wind farm under the wind condition vm is (P ^vm , H ^vm ), (P ^vm , k ^vm ), where:

Step 108: Fitting the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under the different wind conditions to obtain a functional relationship between the power generation of the wind farm and the frequency support capability of the wind farm.

Fitting is a method of processing discrete data. Assuming that a number of discrete data are distributed on a function curve, the fitting process is to minimize the difference between the function and the known discrete data by adjusting a number of unknown coefficients in the function.

In an optional embodiment of the present application, the historical data of the equivalent power generation of the wind farm and the equivalent inertia coefficient of the wind farm obtained under different wind conditions can obtain several discrete values, (P ^v1 , H ^v1 ), (P ^v2 , H ^v2 ) ... (P ^vm , H ^vm ), and the above several discrete values are fitted to obtain the functional relationship between the power generation of the wind farm and the inertia coefficient of the wind farm. The historical data of the equivalent power generation of the wind farm and the equivalent droop coefficient of the wind farm obtained under different wind conditions can obtain several discrete values (P ^v1 , k ^v1 ), (P ^v2 , k ^v2 ) ... (P ^vm , k ^vm ), and the above several discrete values are fitted to obtain the functional relationship between the power generation of the wind farm and the droop coefficient of the wind farm. In an optional embodiment of the present application, the fitting can be a linear fitting.

Step 110: Substitute the real-time data of the wind farm power generation into the functional relationship between the wind farm power generation and the wind farm frequency support capability to obtain an estimated result of the wind farm frequency support capability.

In an optional embodiment of the present application, the real-time data of the wind farm power generation includes the instantaneous power generation of the wind farm and the average power within a preset time period. In an optional embodiment of the present application, the average power within the preset time period may include minute-level average power, hour-level average power, or daily average power.

In an optional embodiment of the present application, the real-time data of the wind farm power generation is substituted into the functional relationship between the wind farm power generation and the wind farm inertia coefficient obtained in step 108 to obtain an estimated result of the wind farm inertia coefficient. In an optional embodiment of the present application, the minute-level average power of the wind farm is substituted into the functional relationship between the wind farm power generation and the wind farm inertia coefficient to obtain an estimated result of the minute-level average inertia coefficient of the wind farm.

The above-mentioned wind farm frequency support capacity estimation method first considers different frequency response strategies, and according to different frequency response strategies, establishes the relationship model between the power generation of the wind turbine and the frequency support capacity that the wind turbine can provide; then, based on the historical data of the power generation of the wind turbine, solves the relationship model between the power generation and the frequency support capacity, and obtains the historical data of the frequency support capacity corresponding to the wind turbine; then, based on the data of a single wind turbine, calculates the equivalent power generation and frequency support capacity of the wind farm under different wind conditions; finally, the equivalent power generation of the wind farm under different wind conditions and the frequency support capacity of the wind farm are fitted to obtain the functional relationship between the power generation of the wind farm and the frequency support capacity of the wind farm. This method for estimating the frequency support capacity of a wind farm takes into account different frequency response strategies and the differences between a single wind turbine and a wind farm. The use of different frequency response strategies by a wind farm will result in different powers used to maintain frequency stability, which in turn affects the frequency support capacity of the wind farm. Due to the different wind speed distributions within a wind farm, the frequency support capabilities that a single wind turbine can provide are different. It is necessary to calculate the frequency support capacity of a single wind turbine by the power generation power of a single wind turbine, and obtain a more accurate equivalent frequency support capacity of the wind farm. This embodiment, based on the consideration of the above-mentioned frequency response strategies and the differences between a single wind turbine and a wind farm, uses a large amount of historical data to fit the functional relationship, and can more accurately estimate the frequency support capacity of a wind farm. The corresponding estimation results can be used as a basis for power system planning and scheduling.

As described above, the method for determining the reserve power of a wind turbine based on the generated power and the rated power can be used as a frequency response strategy. In one embodiment, the frequency response strategy includes:

表示风电机组的额定功率。R ^W represents the reserve power of the wind turbine, P ^W represents the power generation of the wind turbine, λ ^W represents the reserve coefficient,

Indicates the rated power of the wind turbine.

The first frequency response strategy of the wind turbine is that when the wind turbine power generation power is higher than the system setting level, the excess power is reserved as standby power, and the standby power is used to provide frequency response. This response strategy is called a de-rating strategy. The system setting level refers to the power value pre-set by the system. In an optional embodiment of the present application, the system setting level may be proportional to the rated power of the wind turbine. In an optional embodiment of the present application, the de-rating strategy is:

当风电机组的发电功率未达到系统设定水平时，无法提供备用功率；当风电机组的发电功率高于系统设定水平时，高出的部分留作备用功率。The system setting level is

When the power generation of the wind turbine set does not reach the system set level, it cannot provide backup power; when the power generation of the wind turbine set is higher than the system set level, the excess is reserved as backup power.

The second frequency response strategy of the wind turbine is to maintain the reserve power of the wind turbine at a constant power point, and the reserve power is used to provide frequency response. This response strategy is called a delta strategy. In an optional embodiment of the present application, the delta strategy is:

当风电机组的发电功率小于该恒定值时，则风电机组全部的发电功率都留作备用功率。Under this frequency response strategy, the backup power provided by the wind turbine is constant, that is,

When the power generation of the wind turbine set is less than the constant value, all the power generation of the wind turbine set is reserved as standby power.

The third frequency response strategy of the wind turbine is that the ratio between the reserve power of the wind turbine and the generated power of the wind turbine is constant, and the reserve power is used to provide frequency response. This response strategy is called the percentage strategy. In an optional embodiment of the present application, the percentage strategy is:

R ^W = λ ^W P ^W (7)

Under this frequency response strategy, the ratio of wind turbine standby power to wind turbine generating power is λ ^W , ^which can be adjusted manually according to the power system conditions.

In one embodiment, as shown in FIG. 2 , an exemplary technical process of “establishing a relationship model between the power generation of a wind turbine and the frequency support capability that the wind turbine can provide according to a frequency response strategy” is shown. The technical process includes the following steps:

Step 202: Determine the relationship between the corresponding wind turbine generator set power generation and the reserved standby power according to the frequency response strategy.

In the application scenario where wind farms provide frequency support, due to the different situations of the fluctuating new energy farms that need to supply energy and the wind farms that provide backup power, wind farms will choose different frequency response strategies to provide frequency support. Therefore, when estimating the frequency support capacity of wind farms, considering different frequency response strategies is more in line with practical applications.

The method of determining the generated power of a wind turbine and the reserved backup power through a frequency response strategy has been described in detail above and will not be repeated here.

Step 204, determining the relationship between the reserved standby power and the inertia coefficient representing the frequency support capability.

As described above, the wind turbine reserve power will provide frequency response in the form of an equivalent synchronous machine, that is, the reserve power can provide equivalent inertial response and droop response. In an optional embodiment of the present application, in the reserve power R ^W , a fixed proportion of the reserve power is used to provide inertial response, and the fixed proportion of the reserve power is δR ^W. According to the expression (1) that the reserve power provides equivalent inertial response and droop response, the reserve power that provides inertial response should satisfy:

According to expression (8), the inertia coefficient satisfies:

则风电机组所能提供的最大等效惯性系数为：Consider the maximum frequency change rate allowed by the power system

The maximum equivalent inertia coefficient that the wind turbine can provide is:

Step 206, determining the relationship between the reserved standby power and the droop coefficient representing the frequency support capability.

In an optional embodiment of the present application, in the reserve power R ^W , a fixed proportion of the reserve power δR ^W is used to provide an inertial response, and the remaining reserve power is used to provide a droop response, and the reserve power providing a droop response is (1-δ)R ^W. According to the expression (1) that the reserve power provides an equivalent inertial response and a droop response, the reserve power providing a droop response should satisfy:

(1-δ)R ^W ≥-k ^W Δf (11)

According to expression (11), the droop coefficient satisfies:

k ^W ≤(1-δ)R ^W /|Δf| (12)

则风电机组所能提供的最大等效下垂系数为：Consider the maximum frequency deviation allowed by the power system

The maximum equivalent droop coefficient that the wind turbine can provide is:

Step 208, determining the relationship between the generated power and the inertia coefficient based on the relationship between the generated power and the reserved standby power, and the relationship between the reserved standby power and the inertia coefficient.

As described above, the relationship between the generated power P ^W and the standby power R ^W of the wind turbine is determined according to the frequency response strategy. By deducing equations (8), (9), and (10) in step 204, the relationship between the standby power of the wind turbine and the equivalent inertia coefficient provided by the wind turbine is obtained. With the standby power of the wind turbine as the medium, the relationship between the generated power of the wind turbine and the equivalent inertia coefficient provided by the wind turbine can be obtained.

Step 210, determining the relationship between the generated power and the droop coefficient based on the relationship between the generated power and the reserved standby power, and the relationship between the reserved standby power and the droop coefficient.

As described above, the relationship between the generated power P ^W and the standby power R ^W of the wind turbine is determined according to the frequency response strategy. By deducing equations (11), (12), and (13) in step 206, the relationship between the standby power of the wind turbine and the equivalent inertia coefficient provided by the wind turbine is obtained. With the standby power of the wind turbine as the medium, the relationship between the generated power of the wind turbine and the equivalent inertia coefficient provided by the wind turbine can be obtained.

As described above, it is necessary to obtain the historical data of the wind turbine power generation, and then substitute the historical data of the wind turbine power generation into the relationship model between the wind turbine power generation and the frequency support capability that the wind turbine can provide, to obtain the corresponding historical data of the wind turbine frequency support capability. In one embodiment, as shown in FIG3 , it shows an exemplary technical process of “obtaining the historical data of the wind turbine power generation”, which includes the following steps:

Step 302: determine the functional relationship between the wind speed of the wind turbine generator set and the power generated by the wind turbine generator set.

In an optional embodiment of the present application, the relationship between the power generation of the wind turbine and the actual wind speed of the wind turbine is:

风电机组的额定功率。Where P ^W is the power generation of the wind turbine, v is the actual wind speed of the wind turbine, _vin is the rated cut-in wind speed of the wind turbine, and _vout is the rated cut-out wind speed of the wind turbine.

Rated power of the wind turbine.

Step 304, obtaining historical data of wind speed of the wind turbine.

In a wind power generation system, the historical data of wind speed of a wind turbine is raw data and can be obtained without calculation. In addition to directly obtaining the historical data of wind turbine power generation, the historical data of wind turbine power generation can also be further calculated by obtaining the historical data of wind speed of the wind turbine.

Step 306: Obtain historical data of the wind turbine generator set's generated power according to the historical data of the wind speed of the wind turbine generator set and the functional relationship between the wind speed of the wind turbine generator set and the generated power of the wind turbine generator set.

The acquired historical data of the wind speed of the wind turbine set is substituted into the functional relationship between the wind speed of the wind turbine set and the generated power of the wind turbine set determined in step 302 to obtain the historical data of the generated power of the wind turbine set.

In one embodiment, as shown in FIG4 , after determining the relationship between the generated power and the reserved standby power and the relationship between the reserved standby power and the droop coefficient, the method for estimating the frequency support capability of a wind farm further includes:

Step 402: determining a control error of the wind turbine generator system.

Frequency response strategy is a kind of energy storage scheme that is expected to be achieved in advance. When the wind turbine is actually executed, it is inevitable that there will be inconsistencies with the pre-set situation. This deviation is called control error. The control error of the wind turbine can be determined based on the deviation between the set energy storage and the actual energy storage of the wind turbine.

Step 404 : Based on the control error of the wind turbine generator set and the relationship between the power generation of the wind turbine generator set and the inertia coefficient, determine the relationship between the power generation of the wind turbine generator set and the inertia coefficient under the control error.

When the control error is σ%, and the original inertia coefficient is H ^W , the actual equivalent inertia coefficient of the wind turbine considering the control error is (1+%)H ^W. As described above, the relationship between the wind turbine power generation and the inertia coefficient is determined according to the frequency response strategy, and the actual equivalent inertia coefficient of the wind turbine considering the control error is substituted into the relationship between the wind turbine power generation and the inertia coefficient to obtain the relationship between the wind turbine power generation and the inertia coefficient considering the control error.

Step 406: Based on the control error of the wind turbine generator set and the relationship between the power generation of the wind turbine generator set and the droop coefficient, determine the relationship between the power generation of the wind turbine generator set and the droop coefficient under the control error.

When the control error is σ%, and the original droop coefficient is k ^W , the actual equivalent droop coefficient of the wind turbine considering the control error is (1+%) k ^W. As described above, the relationship between the wind turbine power generation and the droop coefficient is determined according to the frequency response strategy, and the actual equivalent droop coefficient of the wind turbine considering the control error is substituted into the relationship between the wind turbine power generation and the droop coefficient, and the relationship between the wind turbine power generation and the droop coefficient when the control error is considered is obtained.

The above-mentioned method for estimating the frequency support capacity of a wind farm first determines the control error of the wind turbine; based on the control error of the wind turbine and the relationship between the wind turbine power generation and the inertia coefficient, determines the relationship between the wind turbine power generation and the inertia coefficient under the control error; based on the control of the wind turbine and the relationship between the wind turbine power generation and the droop coefficient, determines the relationship between the wind turbine power generation and the droop coefficient under the control error. This method takes into account the possible errors that may exist when the wind turbine actually provides frequency response. Determining the relationship between the wind turbine power generation and the inertia coefficient, and the wind turbine power generation and the droop coefficient under the control error is more in line with the actual operation of the wind turbine, and the wind farm frequency support capacity result calculated by this relationship model is also more accurate.

In one embodiment, as shown in FIG5 , after obtaining the functional relationship between the wind farm power generation and the wind farm frequency support capability, the wind farm frequency support capability estimation method further includes:

Step 502: Obtain historical data of average power of the wind farm within a preset period and historical data of minimum power of the wind farm within a preset period.

In an optional embodiment of the present application, the preset time period may include any time length, such as 1 hour or 24 hours. When the preset time period is 1 hour, step 502 obtains the historical data of the average power of the wind farm within a certain hour and the historical data of the minimum power of the wind farm within the hour. When the preset time period is 24 hours, step 502 obtains the historical data of the average power of the wind farm within a certain day and the historical data of the minimum power of the wind farm within the day.

In an optional embodiment of the present application, the historical data of the minute-level average power of each wind turbine in the wind farm is first obtained, and the historical data of the minute-level average power of each wind turbine is summed to obtain the historical data of the minute-level equivalent average power of the wind farm. Using the historical data of the minute-level equivalent average power of the wind farm, the average power of the wind farm in a certain hour, a certain day or any preset time period, as well as the minimum power of the wind farm in the corresponding time period can be calculated.

Step 504 : obtaining by fitting a functional relationship between the average power of the wind farm in a preset period and the minimum power of the wind farm in the preset period.

其中

代表统计的第x小时风电场平均功率的历史数据，

代表统计的第x小时风电场最小功率的历史数据。利用上述若干小时级风电场平均功率和最小功率的数据对制作特性曲线，再通过线性拟合，得到小时级“风电场平均功率-风电场最小功率”的函数关系。In an optional embodiment of the present application, after obtaining a large amount of historical data of the average power of the wind farm in a preset period and the minimum power of the wind farm in the preset period, a characteristic curve of "average power of the wind farm - minimum power of the wind farm" in the preset period is prepared, and the functional relationship of "average power of the wind farm - minimum power of the wind farm" in the preset period is obtained by fitting. In an optional embodiment of the present application, the hourly average power of the wind farm and the minimum power of the wind farm in the hour are calculated through the historical data of the minute-level average power of the wind farm, and the data pair of the hourly average power and the minimum power of the wind farm in several hours are obtained.

in

Represents the historical data of the average power of the wind farm at the xth hour.

Represents the historical data of the minimum power of the wind farm at the xth hour. The characteristic curve is made using the data pairs of the average power and minimum power of the wind farm at the hourly level, and then the functional relationship of "average power of the wind farm - minimum power of the wind farm" at the hourly level is obtained through linear fitting.

Step 506, obtaining real-time data of the average power of the wind farm in a preset period, substituting the real-time data of the average power of the wind farm in the preset period into the functional relationship between the average power of the wind farm in the preset period and the minimum power of the wind farm in the preset period, and estimating the real-time data of the minimum power of the wind farm in the corresponding preset period.

In an optional embodiment of the present application, the preset time period in "obtaining real-time data of average power of the wind farm within a preset time period" needs to be the same as the preset time period time span in the functional relationship of "average power of the wind farm - minimum power of the wind farm" within the preset time period obtained in step 504. If the functional relationship of "average power of the wind farm - minimum power of the wind farm" at the hourly level is obtained in step 504, then this step needs to obtain the real-time data of the average power of the wind farm at the hourly level. Substituting the real-time data of the average power of the wind farm at the hourly level into the functional relationship of "average power of the wind farm - minimum power of the wind farm" obtained in step 504, the real-time data of the minimum power of the wind farm in the corresponding preset time period can be estimated.

Step 508: Substitute the real-time data of the minimum power of the wind farm in the preset period into the functional relationship between the wind farm power generation and the wind farm frequency support capability to obtain an estimated result of the minimum frequency support capability of the wind farm in the preset period.

As described above, the functional relationship between the wind farm power generation and the wind farm frequency support capability is obtained by fitting historical data. The real-time data of the wind farm minimum power in the preset time period estimated in step 506 is substituted into the functional relationship between the wind farm power generation and the wind farm frequency support capability, and the minimum frequency support capability that can be provided by the average power of the wind farm in the preset time period can be obtained.

This embodiment obtains historical data of the average power of the wind farm and the minimum power of the wind farm in a preset period, uses the above historical data to make a characteristic curve of the average power of the wind farm and the minimum power of the wind farm, and obtains the functional relationship between the average power of the wind farm and the minimum power of the wind farm in the preset period after fitting. After obtaining the real-time data of the average power of the wind farm in the preset period, the functional relationship between the average power of the wind farm and the minimum power of the wind farm in the preset period is substituted to obtain the minimum power of the wind farm in the preset period. The minimum power of the wind farm in the preset period is substituted into the functional relationship between the wind farm power generation power and the wind farm frequency support capacity to obtain the minimum frequency support capacity of the wind farm in the preset period. Using this method, as long as the average power of the wind farm in the preset period is obtained, the minimum frequency support capacity in the preset period can be predicted. When planning the power system, knowing the lower limit of the wind farm's external energy supply can ensure the smooth operation of the power system, and will not cause deviations in the planning due to fluctuations in the frequency support capacity provided by the wind farm, thereby affecting the stability of the power system.

In a specific embodiment, a method for estimating the frequency support capability of a wind farm is applied to a wind farm in North my country. The method includes:

Step 602: Establish a relationship model between the power generation of the wind turbine generator set and the frequency support capability of the wind turbine generator set according to the frequency response strategy.

As mentioned above, the frequency response strategy includes the de-rating strategy, the delta strategy and the percentage strategy. In an optional embodiment of the present application, the reserve coefficient λ ^W in the frequency response strategy is taken as 0.1, and the rated power of the wind turbine is 1.5MW. According to the de-rating strategy, the relationship model between the wind turbine power generation and the wind turbine frequency support capability is:

According to the delta strategy, the relationship model between the wind turbine power generation and the wind turbine frequency support capability is:

According to the percentage strategy, the relationship model between the wind turbine power generation and the wind turbine frequency support capability is:

R ^W ＝0.1P ^W (17)

则风电机组所能提供的最大等效惯性系数和备用功率的关系为：In an optional embodiment, a fixed proportion of the reserve power provides an inertial response, and the fixed proportion is 24%, that is, 24% of the reserve power is used to provide an inertial response, and the remaining 76% of the power is used to provide a droop response. According to the above derivation, considering the maximum frequency change rate allowed by the power system

The relationship between the maximum equivalent inertia coefficient and the reserve power that the wind turbine can provide is:

则风电机组所能提供的最小等效下垂系数和备用功率的关系为：Consider the maximum frequency deviation allowed by the power system

The relationship between the minimum equivalent droop coefficient and the reserve power that the wind turbine can provide is:

Then under the de-rating strategy:

The relationship between the wind turbine power generation P ^W and the inertia coefficient H ^W that characterizes the frequency support capability is:

The relationship between the wind turbine power generation P ^W and the droop coefficient k ^W that characterizes the frequency support capability is:

Then under the delta strategy:

The relationship between the wind turbine power generation P ^W and the inertia coefficient H ^W that characterizes the frequency support capability is:

The relationship between the wind turbine power generation P ^W and the droop coefficient k ^W that characterizes the frequency support capability is:

Then under the percentage strategy:

The relationship between the wind turbine power generation P ^W and the inertia coefficient H ^W that characterizes the frequency support capability is:

The relationship between the wind turbine power generation P ^W and the droop coefficient k ^W that characterizes the frequency support capability is:

The control error σ% is determined to be 0.1, and the relationship between the generated power and the inertia coefficient is determined taking the control error into account:

Step 604, obtain the historical data of wind speed of each wind turbine in the wind farm under different wind conditions, and calculate the historical data of power generation of each wind turbine in the wind farm by expression (14), wherein the rated cut-in wind speed of the wind turbine is 3m/s, and the rated cut-out wind speed of the wind turbine is 25m/s. According to expressions (26) and (27) derived in step 602, calculate the inertia coefficient and droop coefficient corresponding to the power generation of the wind turbine under the de-rating strategy, delta strategy and percentage strategy respectively.

经过计算各风电机组发电功率和下垂系数的数据对为

Under the de-rating strategy, the data pairs of the power generation and inertia coefficient of each wind turbine are calculated as follows:

After calculating the data of each wind turbine generator set's power generation and droop coefficient, we can get

经过计算各风电机组发电功率和下垂系数的数据对为

Under the delta strategy, the data pairs of the power generation and inertia coefficient of each wind turbine are calculated as follows:

After calculating the data of each wind turbine generator set's power generation and droop coefficient, we can get

经过计算各风电机组发电功率和下垂系数的数据对为

Under the percentage strategy, the data pairs of the power generation and inertia coefficient of each wind turbine are calculated as follows:

After calculating the data of each wind turbine generator set's power generation and droop coefficient, we can get

Step 606, based on the historical data of wind turbine generator set power generation under different wind conditions obtained in step 604 and the historical data of wind turbine generator set frequency support capability, calculate the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under different wind conditions.

According to the historical data obtained in step 604, the power generation of each wind turbine in the wind farm under the same wind condition is summed to obtain the equivalent power generation of the wind farm under the wind condition; the inertia coefficient of each wind turbine in the wind farm under the same wind condition is summed to obtain the equivalent inertia coefficient of the wind farm under the wind condition; the droop coefficient of each wind turbine in the wind farm under the same wind condition is summed to obtain the equivalent droop coefficient of the wind farm under the wind condition. The specific calculation process is shown in expressions (2), (3), and (4). Finally, under the de-rating strategy, the data pairs of power generation and inertia coefficient under different wind conditions of the wind farm are (P ^v1 , H ^v1 ) _de-rating , (P ^v2 , H ^v2 ) _de-rating …(P ^vm , H ^vm ) _de-rating ; the data pairs of power generation and droop coefficient under different wind conditions of the wind farm are (P ^v1 , k ^v1 ) _de-rating , (P ^v2 , k ^v2 ) _de-rating …(P ^vm , k ^vm ) _de-rating . Under the delta strategy, the data pairs of the power generation and inertia coefficient under different wind conditions of the wind farm are (P ^v1 , H ^v1 ) _delta , (P ^v2 , H ^v2 ) _delta …(P ^vm , H ^vm ) _delta ; the data pairs of the power generation and droop coefficient under different wind conditions of the wind farm are (P ^v1 , k ^v1 ) _delta , (P ^v2 , k ^v2 ) _delta …(P ^vm , k ^vm ) _delta . Under the percentage strategy, the data pairs of the power generation and inertia coefficient under different wind conditions of the wind farm are (P ^v1 , H ^v1 ) _percentage , (P ^v2 , H ^v2 ) _percentage …(P ^vm , H ^vm ) _percentage ; the data pairs of the power generation and droop coefficient under different wind conditions of the wind farm are (P ^v1 , k ^v1 ) _percentage , (P ^v2 , k ^v2 ) _percentage …(P ^vm , k ^vm ) _percentage .

Step 608, fitting the equivalent power generation of the wind farm under the different wind conditions and the equivalent inertia coefficient of the wind farm to obtain the functional relationship between the power generation of the wind farm and the inertia coefficient of the wind farm; fitting the equivalent power generation of the wind farm under the different wind conditions and the equivalent droop coefficient of the wind farm to obtain the functional relationship between the power generation of the wind farm and the droop coefficient of the wind farm.

The equivalent power generation and equivalent inertia coefficient of the wind farm under the three frequency response strategies obtained in step 606 are fitted to obtain the relationship between the power generation and inertia coefficient of the wind farm under the de-rating strategy, delta strategy and percentage strategy. As shown in FIG6 , the abscissa of FIG6 represents the equivalent power of the wind farm in MW (megawatt); the ordinate represents the equivalent inertia coefficient of the wind farm in MW·s/Hz (megawatt·second/Hertz). A scatter plot between the power generation and inertia coefficient of the wind farm under the de-rating frequency response strategy is prepared using (P ^v1 , H ^v1 ) _de-rating , (P ^v2 , H ^v2 ) _de-rating …(P ^vm , H ^vm ) _de-rating data, and the scatter plot is further fitted to obtain the functional relationship between the power generation and inertia coefficient of the wind farm under the de-rating strategy. A scatter plot between the wind farm power generation and the inertia coefficient under the delta frequency response strategy is prepared using (P ^v1 , H ^v1 ) _delta , (P ^v2 , H ^v2 ) _delta …(P ^vm , H ^vm ) _delta data, and the scatter plot is further fitted to obtain the functional relationship between the wind farm power generation and the inertia coefficient under the delta strategy. A scatter plot between the wind farm power generation and the inertia coefficient under the percentage frequency response strategy is prepared using (P ^v1 , H ^v1 ) _percentage , (P ^v2 , H ^v2 ) _percentage …(P ^vm , H ^vm ) _percentage data, and the scatter plot is further fitted to obtain the functional relationship between the wind farm power generation and the inertia coefficient under the percentage strategy. FIG7 shows a function curve obtained by fitting the above scatter plot. The horizontal axis of FIG7 represents the equivalent power of the wind farm, and the unit is pu; the vertical axis represents the equivalent inertia coefficient of the wind farm, and the unit is pu. Pu represents per unit value, which is a numerical notation method commonly used in power system analysis and engineering calculations, and represents the relative values of various physical quantities and parameters.

Step 610, obtain historical data of minute-level power generation of the wind farm, calculate the average power of the wind farm within a certain hour and the minimum power within the hour based on the historical data of minute-level power generation, and obtain the functional relationship between the hour-level average power and the minimum power of the wind farm by fitting based on the historical data of the hour-level average power and the minimum power of the wind farm.

Figure 8 shows the characteristic curve of hourly average power and minimum power of a wind farm. The horizontal axis of Figure 8 represents the hourly average power of the wind farm, in p.u.; the vertical axis represents the minimum power of the wind farm in the hour, in p.u. Figure 9 is the functional relationship between the hourly average power and minimum power of the wind farm obtained by fitting the characteristic curve. The horizontal axis of Figure 9 represents the hourly average power of the wind farm, in p.u.; the vertical axis represents the minimum power of the wind farm in the hour, in p.u.

Step 612, obtain the real-time data of the hourly average power of the wind farm, substitute the real-time data of the hourly average power of the wind farm into the functional relationship between the average power of the wind farm and the minimum power obtained in step 610, and obtain the estimated result of the minimum power of the wind farm in that hour; substitute the estimated result of the minimum power of the wind farm into the functional relationship between the wind farm power generation and the wind farm inertia coefficient obtained in step 606, and obtain the estimated result of the minimum inertia coefficient of the wind farm in that hour; substitute the estimated result of the minimum power of the wind farm into the functional relationship between the wind farm power generation and the wind farm droop coefficient obtained in step 606, and obtain the estimated result of the minimum droop coefficient of the wind farm in that hour.

It should be understood that, although the various steps in the flowcharts of Figures 1-5 are displayed in sequence according to the indications of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in Figures 1-5 may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the steps or stages in other steps.

In one embodiment, a wind farm frequency support capability estimation device 1000 is provided. As shown in FIG10 , the wind farm frequency support capability estimation device 1000 includes: a creation module 1001 , a first solution module 1002 , an equivalent module 1003 , a first fitting module 1004 and a second solution module 1005 .

The creation module 1001 is used to establish a relationship model between the power generation of the wind turbine and the frequency support capability that the wind turbine can provide according to the frequency response strategy.

The first solving module 1002 is used to obtain historical data of the power generation of the wind turbine set, and solve the relationship model between the power generation of the wind turbine set and the frequency support capability that the wind turbine set can provide based on the historical data of the power generation of the wind turbine set, so as to obtain the corresponding historical data of the frequency support capability of the wind turbine set.

The equivalent module 1003 is used to calculate the equivalent power generation power and the equivalent frequency support capability of the wind farm under different wind conditions according to the historical data of the power generation power of the wind turbine set and the historical data of the corresponding frequency support capability of the wind turbine set.

The first fitting module 1004 is used to fit the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under different wind conditions to obtain a functional relationship between the power generation of the wind farm and the frequency support capability of the wind farm.

The second solution module 1005 is used to substitute the real-time data of the wind farm power generation into the functional relationship between the wind farm power generation and the wind farm frequency support capability to obtain an estimated result of the wind farm frequency support capability.

In an optional embodiment of the present application, the real-time data of the wind farm's generated power includes real-time data of the average power within a preset time period of the wind farm, and the creation module 1001 is specifically used to: determine the relationship between the corresponding wind turbine generated power and the reserved standby power according to the frequency response strategy; determine the relationship between the reserved standby power and the inertia coefficient characterizing the frequency support capability; determine the relationship between the reserved standby power and the droop coefficient characterizing the frequency support capability; determine the relationship between the generated power and the reserved standby power, and the relationship between the reserved standby power and the inertia coefficient; determine the relationship between the generated power and the droop coefficient, and the relationship between the generated power and the reserved standby power, and the relationship between the reserved standby power and the droop coefficient.

In an optional embodiment of the present application, the frequency response strategy includes at least one of the following: when the output of the wind turbine group is higher than the system set level, the excess portion is reserved as standby power, and the standby power is used to provide frequency response; the wind turbine group maintains standby power at a constant power point, and the standby power is used to provide frequency response; the ratio between the standby power of the wind turbine group and the generated power of the wind turbine group is constant, and the standby power is used to provide frequency response.

In an optional embodiment of the present application, the first solution module is specifically used to: determine the functional relationship between the wind speed of the wind turbine and the power generation of the wind turbine; obtain the historical data of the wind speed of the wind turbine; and obtain the historical data of the power generation of the wind turbine based on the historical data of the wind speed of the wind turbine and the functional relationship between the wind speed of the wind turbine and the power generation of the wind turbine.

Please refer to Figure 11, which shows a block diagram of another wind farm frequency support capability estimation device 1100 provided in an embodiment of the present application. In addition to the various modules included in the wind farm frequency support capability estimation device 1000, the wind farm frequency support capability estimation device 1100 optionally also includes an error determination module 1006, a first relationship module 1007 and a second relationship module 1008.

The error determination module 1006 is specifically used to determine the control error of the wind turbine generator set.

The first relationship module 1007 is specifically used to determine the relationship between the power generation of the wind turbine and the inertia coefficient under the control error based on the control error of the wind turbine and the relationship between the power generation of the wind turbine and the inertia coefficient.

The second relationship module 1008 is specifically used to determine the relationship between the power generation of the wind turbine set and the droop coefficient under the control error based on the control error of the wind turbine set and the relationship between the power generation of the wind turbine set and the droop coefficient.

Please refer to Figure 12, which shows a block diagram of another wind farm frequency support capability estimation device 1200 provided in an embodiment of the present application. In addition to the various modules included in the wind farm frequency support capability estimation device 1000, the wind farm frequency support capability estimation device 1200 optionally also includes a data acquisition module 1009, a second fitting module 1010, and a third solution module 1011.

The data acquisition module 1009 is specifically used to obtain the historical data of the average power of the wind farm within a preset period of time and the historical data of the minimum power of the wind farm within a preset period of time.

The second fitting module 1010 is specifically used to fit and obtain a functional relationship between the average power of the wind farm in a preset period and the minimum power of the wind farm in the preset period.

The third solution module 1011 is specifically used to obtain the real-time data of the average power of the wind farm within a preset time period, substitute the real-time data of the average power of the wind farm within the preset time period into the functional relationship between the average power of the wind farm within the preset time period and the minimum power of the wind farm within the preset time period, and estimate the real-time data of the minimum power of the wind farm within the corresponding preset time period.

In an optional embodiment of the present application, the data acquisition module 1009 is specifically used to obtain historical data of minute-level power generation of the wind farm; based on the historical data of minute-level power generation of the wind farm, calculate the average power of the wind farm within an hour and the minimum power within an hour.

For the specific limitations of the wind farm frequency support capability estimation device, please refer to the limitations of the wind farm frequency support capability estimation method above, which will not be repeated here. Each module in the above-mentioned wind farm frequency support capability device can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in FIG13. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for estimating the frequency support capacity of a wind farm is implemented.

Those skilled in the art will understand that the structure shown in FIG. 13 is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

According to the frequency response strategy, a relationship model between the power generation of the wind turbine set and the frequency support capability that the wind turbine set can provide is established; the historical data of the power generation of the wind turbine set is obtained, and based on the historical data of the power generation of the wind turbine set, the relationship model between the power generation of the wind turbine set and the frequency support capability that the wind turbine set can provide is solved to obtain the corresponding historical data of the frequency support capability of the wind turbine set; based on the historical data of the power generation of the wind turbine set and the corresponding historical data of the frequency support capability of the wind turbine set, the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under different wind conditions are calculated; the equivalent power generation of the wind farm and the equivalent frequency support capability of the wind farm under different wind conditions are fitted to obtain the functional relationship between the power generation of the wind farm and the frequency support capability of the wind farm; the real-time data of the power generation of the wind farm is substituted into the functional relationship between the power generation of the wind farm and the frequency support capability of the wind farm to obtain the estimated result of the frequency support capability of the wind farm.

The real-time data of the wind farm's generated power includes real-time data of the average power within a preset time period of the wind farm. In one embodiment, the processor further implements the following steps when executing the computer program: determining the relationship between the generated power of the corresponding wind turbine and the reserved standby power according to the frequency response strategy; determining the relationship between the reserved standby power and the inertia coefficient representing the frequency support capability; determining the relationship between the reserved standby power and the droop coefficient representing the frequency support capability; determining the relationship between the generated power and the inertia coefficient based on the relationship between the generated power and the reserved standby power, and the relationship between the reserved standby power and the inertia coefficient; determining the relationship between the generated power and the droop coefficient based on the relationship between the generated power and the reserved standby power, and the relationship between the reserved standby power and the droop coefficient.

The frequency response strategy includes at least one of the following: when the wind turbine output is higher than the system set level, the excess is reserved as standby power, and the standby power is used to provide frequency response; the wind turbine maintains standby power at a constant power point, and the standby power is used to provide frequency response; the ratio between the standby power of the wind turbine and the power generation of the wind turbine is constant, and the standby power is used to provide frequency response. In one embodiment, the processor further implements the following steps when executing the computer program: determining the functional relationship between the wind speed of the wind turbine and the power generation of the wind turbine; obtaining historical data of the wind speed of the wind turbine; obtaining historical data of the power generation of the wind turbine according to the historical data of the wind speed of the wind turbine and the functional relationship between the wind speed of the wind turbine and the power generation of the wind turbine.

In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the control error of the wind turbine group; determining the relationship between the power generation power of the wind turbine group and the inertia coefficient under the control error based on the relationship between the control error of the wind turbine group and the power generation power and the inertia coefficient of the wind turbine group; determining the relationship between the power generation power of the wind turbine group and the droop coefficient under the control error based on the control error of the wind turbine group and the relationship between the power generation power of the wind turbine group and the droop coefficient.

In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining historical data of the average power of the wind farm within a preset time period and historical data of the minimum power of the wind farm within the preset time period; fitting to obtain the functional relationship between the average power of the wind farm within the preset time period and the minimum power of the wind farm within the preset time period; obtaining real-time data of the average power of the wind farm within the preset time period, substituting the real-time data of the average power of the wind farm within the preset time period into the functional relationship between the average power of the wind farm within the preset time period and the minimum power of the wind farm within the preset time period, and estimating the real-time data of the minimum power of the wind farm within the corresponding preset time period.

In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining historical data of minute-level power generation of the wind farm; and calculating the average power and minimum power of the wind farm within an hour based on the historical data of minute-level power generation of the wind farm.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage or other media used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims (10)

1. A wind power plant frequency support capability estimation method is characterized by comprising the following steps:

establishing a relation model between the generating power of the wind turbine generator and the frequency supporting capacity which can be provided by the wind turbine generator according to a frequency response strategy; the frequency response strategy is used for determining the relation between the generated power and the standby power of the wind turbine generator; the standby power is in corresponding relation with an inertia coefficient and a droop coefficient which represent the frequency supporting capacity; the standby power is used as an intermediate variable to establish a relation model between the generating power of the wind turbine generator and the frequency supporting capacity;

acquiring historical data of the generating power of the wind turbine generator, and solving a relation model between the generating power of the wind turbine generator and the frequency supporting capacity which can be provided by the wind turbine generator according to the historical data of the generating power of the wind turbine generator to obtain the historical data of the frequency supporting capacity of the corresponding wind turbine generator;

calculating the equivalent generating power of the wind power plant and the equivalent frequency supporting capability of the wind power plant under different wind conditions according to the historical data of the generating power of the wind power plant and the historical data of the corresponding frequency supporting capability of the wind power plant;

fitting the equivalent generating power of the wind power plant and the equivalent frequency supporting capacity of the wind power plant under different wind conditions to obtain a functional relation between the generating power of the wind power plant and the frequency supporting capacity of the wind power plant;

and substituting the real-time data of the wind power plant generating power into the functional relation between the wind power plant generating power and the wind power plant frequency supporting capacity to obtain the estimation result of the wind power plant frequency supporting capacity.

2. The method of claim 1, wherein the real-time data of the wind farm generated power comprises real-time data of average power over a preset period of time of the wind farm; the establishing of the relation model between the generating power of the wind turbine generator and the frequency supporting capacity provided by the wind turbine generator according to the frequency response strategy comprises the following steps:

determining the relation between the generated power of the corresponding wind turbine generator and the reserved standby power according to a frequency response strategy;

determining the relation between the reserved reserve power and an inertia coefficient representing the frequency supporting capacity;

determining the relation between the reserved reserve power and a droop coefficient representing the frequency supporting capacity;

determining the relation between the generated power and the inertia coefficient according to the relation between the generated power and the reserved standby power and the relation between the reserved standby power and the inertia coefficient;

and determining the relation between the generated power and the droop coefficient according to the relation between the generated power and the reserved standby power and the relation between the reserved standby power and the droop coefficient.

3. The method of claim 2, wherein the frequency response policy comprises at least one of:

when the output of the wind turbine generator is higher than the set level of the system, the higher part is reserved as standby power, and the standby power is used for providing frequency response;

the method comprises the steps that a wind turbine generator maintains standby power of a constant power point, wherein the standby power is used for providing frequency response;

the ratio between the reserve power of the wind turbine, which is used to provide the frequency response, and the generated power of the wind turbine is constant.

4. The method of claim 1, wherein the obtaining historical data of the power generated by the wind turbine comprises:

determining a functional relation between the wind speed of the wind turbine generator and the generating power of the wind turbine generator;

acquiring historical data of wind speed of a wind turbine generator;

and obtaining historical data of the generated power of the wind turbine generator according to the historical data of the wind speed of the wind turbine generator and the functional relation between the wind speed of the wind turbine generator and the generated power of the wind turbine generator.

5. The method of claim 2, wherein after determining the relationship between the generated power and the droop coefficient from the relationship between the generated power and the reserved reserve power and the relationship between the reserved reserve power and the droop coefficient, the method further comprises:

determining a control error of the wind turbine generator;

determining the relation between the generated power of the wind turbine generator and the inertia coefficient under the control error based on the control error of the wind turbine generator and the relation between the generated power of the wind turbine generator and the inertia coefficient;

and determining the relation between the generated power of the wind turbine generator and the droop coefficient under the control error based on the control error of the wind turbine generator and the relation between the generated power of the wind turbine generator and the droop coefficient.

6. The method according to any one of claims 1 to 5, wherein after fitting the equivalent generated power of the wind farm and the equivalent frequency supporting capability of the wind farm under the different wind conditions to obtain a functional relationship between the wind farm generated power and the wind farm frequency supporting capability, the method further comprises:

acquiring historical data of the average power of the wind power plant in a preset time period and historical data of the minimum power of the wind power plant in the preset time period;

fitting to obtain a functional relation between the average power of the wind power plant in the preset time period and the minimum power of the wind power plant in the preset time period;

and acquiring real-time data of the average power of the wind farm in a preset time period, substituting the real-time data of the average power of the wind farm in the preset time period into a functional relation between the average power of the wind farm in the preset time period and the minimum power of the wind farm in the preset time period, and estimating the corresponding real-time data of the minimum power of the wind farm in the preset time period.

7. The method according to claim 6, wherein the obtaining historical data of the average power of the wind farm in the preset time period and historical data of the minimum power of the wind farm in the preset time period comprises:

acquiring historical data of the minute-level generated power of the wind power plant;

and calculating the average power in hours and the minimum power in hours of the wind power plant according to historical data of the generation power of the wind power plant in minutes.

8. A wind farm frequency support capability estimation apparatus, the apparatus comprising:

the system comprises a creating module, a frequency response module and a power generation module, wherein the creating module is used for creating a relation model between the generated power of a wind turbine generator and the frequency supporting capacity which can be provided by the wind turbine generator according to a frequency response strategy; the frequency response strategy is used for determining the relation between the generated power and the standby power of the wind turbine generator; the standby power corresponds to the existence of an inertia coefficient and a droop coefficient which represent the frequency supporting capacity; the standby power is used as an intermediate variable to establish a relation model between the generating power of the wind turbine generator and the frequency supporting capacity;

the first solving module is used for acquiring historical data of the generating power of the wind turbine generator, and solving a relation model between the generating power of the wind turbine generator and the frequency supporting capacity which can be provided by the wind turbine generator according to the historical data of the generating power of the wind turbine generator to obtain the historical data of the frequency supporting capacity of the corresponding wind turbine generator;

the equivalent module is used for calculating the equivalent generating power of the wind power plant and the equivalent frequency supporting capability of the wind power plant under different wind conditions according to the historical data of the generating power of the wind power plant and the historical data of the corresponding frequency supporting capability of the wind power plant;

the first fitting module is used for fitting the equivalent generating power of the wind power plant and the equivalent frequency supporting capacity of the wind power plant under different wind conditions to obtain a functional relation between the generating power of the wind power plant and the frequency supporting capacity of the wind power plant;

and the second solving module is used for substituting the real-time data of the wind power plant generating power into the functional relation between the wind power plant generating power and the wind power plant frequency supporting capacity to obtain an estimated result of the wind power plant frequency supporting capacity.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.

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