Prediction method for correlation degree between new energy power generation reserve and maximum frequency deviation

Abstract

The invention discloses a method for predicting the correlation degree between new energy power generation reserve and maximum frequency deviation, and belongs to the technical field of power system new energy clusters.The method comprises the steps that firstly, according to a time sequence, measured values of parameters, used for showing the correlation degree between new energy power generation reserve and maximum frequency deviation, of a target system are obtained; determining a predicted value of the parameter at the next moment based on the obtained measured value of the parameter and an influence factor of the influence of the value of the current parameter on the value of the parameter at the next moment, and then determining the predicted value of the parameter at the next moment according to the predicted value of the parameter at the next moment. And predicting a correlation degree index of the correlation degree between the new energy power generation reserve of the target system at the next moment and the maximum frequency deviation, and adjusting the output of the new energy unit according to the correlation degree index at the next moment. According to the method, the output of the new energy unit can be adjusted according to the predicted association degree index at the next moment, so that new energy consumption is promoted, and power balance of a power system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy clusters in power systems, and in particular to a method for predicting the correlation between new energy power generation standby and maximum frequency deviation. Background Art

[0002] When the frequency fluctuation of the power grid exceeds a certain range, it will cause the collapse of the power grid system. Therefore, it is necessary to maintain the balance between the supply and demand of power in the power grid. In order to maintain the balance of power grid frequency fluctuations, it is necessary to configure power generation reserve capacity in the power system. With the vigorous development of new energy technologies, the power generation reserve capacity of new energy can not only ensure the safe and stable operation of the power grid and improve the regulation capacity of the power system, but also promote the full utilization of new energy to reduce carbon emissions and achieve green development.

[0003] However, as the proportion of renewable energy generation reserve capacity in the power system configuration generation reserve capacity continues to increase, its own instability, volatility and other characteristics will increase the balance fluctuation of the power system, resulting in deviations in the grid frequency. Therefore, in order to maintain the power balance of the grid, it is necessary to accurately predict the correlation between renewable energy generation reserve and the maximum frequency deviation at this stage. Summary of the invention

[0004] The present invention provides a prediction method for the correlation between the renewable energy power generation standby and the maximum frequency deviation, so as to solve the defect that the correlation between the renewable energy power generation standby and the maximum frequency deviation cannot be accurately predicted in the prior art.

[0005] On the one hand, the present invention provides a prediction method for the correlation between renewable energy power generation standby and maximum frequency deviation, the prediction method comprising: obtaining, according to time sequence, the measured values ​​of parameters of a target system used to show the correlation between renewable energy power generation standby and maximum frequency deviation; determining the predicted value of the parameter at the next moment based on the obtained measured values ​​of the parameters and the influence factor of the preset current parameter value on the parameter value at the next moment; predicting the correlation index of the correlation between renewable energy power generation standby and maximum frequency deviation of the target system at the next moment according to the determined predicted value of the parameter at the next moment, the correlation index being used to indicate the correlation between renewable energy power generation standby and maximum frequency deviation; adjusting the output of the renewable energy unit according to the predicted correlation index at the next moment to reduce the frequency deviation of the power grid.

[0006] Optionally, before obtaining the measured values ​​of parameters related to the correlation between the renewable energy power generation reserve and the maximum frequency deviation according to the time sequence, the prediction method also includes: determining a correlation index of the correlation between the renewable energy power generation reserve and the maximum frequency deviation according to the renewable energy power generation reserve ratio of the target system and its influence on the maximum frequency deviation; and determining the parameters used to show the correlation between the renewable energy power generation reserve and the maximum frequency deviation according to the determined correlation index.

[0007] Optionally, the parameters used to show the correlation between new energy power generation reserve and the maximum frequency deviation include at least one of the following parameters: output of other power sources except new energy, output of wind turbines included in grid reserve, output of photovoltaic power generation included in grid reserve, and frequency deviation of the power system.

[0008] Optionally, the measured values ​​of the parameters obtained according to the time sequence are expressed by the following formula:

[0009]

[0010] in, Indicates that the output of other power sources except new energy sources is at t1, t2, …, t z ,…,t m The measured values ​​at these m moments are Indicates that the output of wind turbines included in the grid reserve is at t1, t2, …, t z ,…,t m The measured values ​​at these m moments are Indicates that the output of photovoltaic power generation included in the grid reserve is at t1, t2, …, t z ,…,t m The measured values ​​at these m moments are Indicates that the frequency deviation of the power system is at t1, t2, …, t z ,…,t m The measured value at these m moments.

[0011] Optionally, the impact factor is expressed by the following formula:

[0012]

[0013] Among them, ψ inf It is the tth z The impact factor of time, P' G,min and P' G,max They are the output of other power sources except new energy at t1, t2, …, t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments, P't WT,min and P't WT,maxThe wind power output is included in the grid reserve at t1, t2, ..., t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments, P't PV,min and P't PV,max The photovoltaic power generation is included in the grid reserve at t1, t2, ..., t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments, Δf' N,min and Δf' N,max is the power system frequency deviation at t1, t2, ..., t z ,...,t m The minimum and maximum values ​​of the measured values ​​at these m moments.

[0014] Optionally, the predicted value of the parameter at the next moment is determined by the following formula:

[0015]

[0016] in, is the predicted value of the output of other power sources except new energy at the next moment, is the predicted value of wind power output to be included in the grid reserve at the next moment, is the predicted value of photovoltaic power generation to be included in the grid reserve at the next moment, is the predicted value of the power system frequency deviation at the next moment, is the influencing factor at time t1, is the influencing factor at time t2, Yes z The influencing factor of time, Yes m The influencing factor of time.

[0017] Optionally, after determining the predicted value of the parameter related to the correlation between the new energy power generation reserve and the maximum frequency deviation at the next moment, the prediction method also includes: normalizing the predicted value of the parameter at the next moment to obtain the processed normalized value; and determining the correlation index between the new energy power generation reserve and the maximum frequency deviation at the next moment based on the obtained normalized value.

[0018] Optionally, the output of the new energy unit is adjusted according to the predicted correlation index at the next moment, including: when the predicted correlation index at the next moment is higher than a preset threshold, increasing the reserve power of new energy; when the predicted correlation index at the next moment is lower than the preset threshold, reducing the proportion of new energy output incorporated into the power grid, and increasing the proportion of new energy output as system load.

[0019] Optionally, the correlation index between the new energy power generation reserve and the maximum frequency deviation at the next moment is determined by the following formula:

[0020]

[0021] in, is the correlation index between the next moment's renewable energy generation reserve and the maximum frequency deviation, is the normalized value of the output of other power sources except new energy at the next moment, The normalized value of wind power output included in the grid reserve at the next moment, is the normalized value of photovoltaic power generation included in the grid reserve at the next moment, It is the normalized value of the power system frequency deviation at the next moment.

[0022] On the other hand, the present invention further provides a control device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned prediction method.

[0023] The method for predicting the correlation between the new energy power generation standby and the maximum frequency deviation provided by the present invention obtains the measured value of the parameter used by the target system to show the correlation between the new energy power generation standby and the maximum frequency deviation according to the time sequence, and determines the predicted value of the parameter at the next moment based on the measured value of the parameter obtained and the influence factor of the preset current parameter value on the value of the parameter at the next moment, and then predicts the correlation index of the correlation between the new energy power generation standby and the maximum frequency deviation of the target system at the next moment according to the predicted value of the parameter at the next moment, and then adjusts the output of the new energy unit according to the correlation index at the next moment. Through the above method, the present invention establishes an effective method for predicting the correlation between the new energy power generation standby and the maximum frequency deviation at the next moment, and realizes the beneficial effect of being able to adjust the output of the new energy unit according to the predicted correlation index to reduce the frequency deviation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 It is a flow chart of a method for predicting the correlation between new energy power generation standby and maximum frequency deviation provided by an embodiment of the present invention;

[0026] Figure 2 A flowchart of a method for predicting the correlation between new energy power generation reserve and maximum frequency deviation provided in another embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] As mentioned above, as the proportion of renewable energy generation reserve capacity in the power system configuration generation reserve capacity continues to increase, its own instability, volatility and other characteristics will increase the balance fluctuation of the power system, resulting in deviations in the grid frequency. Therefore, in order to maintain the power balance of the grid, it is necessary to accurately predict the correlation between renewable energy generation reserve and the maximum frequency deviation at this stage.

[0029] To solve this problem, the present invention provides a method for predicting the correlation between renewable energy power generation standby and maximum frequency deviation, by obtaining the measured value of the parameter of the target system used to show the correlation between renewable energy power generation standby and the maximum frequency deviation, and based on the measured value of the parameter obtained, determining the predicted value of the parameter at the next moment, and then predicting the correlation index of the correlation between renewable energy power generation standby and the maximum frequency deviation of the target system at the next moment according to the predicted value of the parameter at the next moment, thereby establishing an effective method for predicting the correlation between renewable energy power generation standby and the maximum frequency deviation, thereby solving the defects existing in the current technology.

[0030] Combine the following Figure 1 and Figure 2 The present invention is described in detail.

[0031] Figure 1 FIG. 1 is a flow chart of a method for predicting the correlation between the renewable energy generation reserve and the maximum frequency deviation provided by an embodiment of the present invention. Figure 1 As shown, a prediction method for the correlation between the renewable energy power generation reserve and the maximum frequency deviation provided by an embodiment of the present invention can be executed by a controller, and the prediction method can include the following steps:

[0032] Step 101: Obtain, according to a time sequence, a measured value of a parameter of a target system for indicating a correlation between a new energy power generation reserve and a maximum frequency deviation.

[0033] Step 102: Determine a predicted value of the parameter at the next moment based on the obtained measured value of the parameter and an influence factor of the preset current parameter value on the parameter value at the next moment.

[0034] Step 103: predict the correlation index of the correlation between the new energy power generation reserve and the maximum frequency deviation of the target system at the next moment according to the predicted value of the parameter at the next moment determined.

[0035] The correlation index is used to indicate the correlation between the new energy power generation reserve and the maximum frequency deviation.

[0036] Step 104: According to the predicted correlation index at the next moment, the output of the new energy unit is adjusted to reduce the frequency deviation of the power grid.

[0037] Based on the above steps, the prediction method for the correlation between renewable energy power generation standby and the maximum frequency deviation provided by the present invention obtains the measured values ​​of the parameters of the target system used to show the correlation between renewable energy power generation standby and the maximum frequency deviation according to the time sequence, and determines the predicted value of the parameter at the next moment based on the measured value of the parameter obtained and the influence factor of the preset current parameter value on the parameter value at the next moment, and then predicts the correlation index of the correlation between renewable energy power generation standby and the maximum frequency deviation of the target system at the next moment according to the predicted value of the parameter at the next moment, thereby establishing an effective method for predicting the correlation between renewable energy power generation standby and the maximum frequency deviation at the next moment, and realizing the ability to adjust the output of the renewable energy unit according to the predicted correlation index to reduce the frequency deviation of the power grid and ensure the power balance of the power system.

[0038] In order to explain the technical solutions provided by the above embodiments in more detail, the present invention also provides preferred embodiments, such as Figure 2 As shown, the prediction method for the correlation between renewable energy power generation reserve and maximum frequency deviation described in this preferred embodiment can be executed by a controller. In a preferred embodiment of the present invention, the adjustment method for adjusting the output of the renewable energy unit includes but is not limited to adjusting the renewable energy reserve power, the proportion of renewable energy processing incorporated into the power grid, the renewable energy output, etc.

[0039] Before step 101, the prediction method may further include: step S1011, determining a correlation index of the correlation between the renewable energy generation reserve and the maximum frequency deviation according to the renewable energy generation reserve ratio of the target system and its influence on the maximum frequency deviation. In a preferred embodiment of the present invention, data analysis and / or expert experience may be performed on parameters related to the correlation between renewable energy generation reserve and the maximum frequency deviation, and the correlation index may be defined as:

[0040]

[0041] Among them, t1, t2, ..., t z ,…,t m is m moments (also called time, time period, etc.), where m is a natural number, m∈1,2,L, z is the zth moment, z is a natural number, and z∈{1,2,L,m}, Yes z In addition to renewable energy, other power sources are always available. Yes z The wind turbines are always included in the grid's reserve output. Yes z The photovoltaic power generation is always included in the grid reserve output. Yes z The power system frequency deviation at the moment, P G,max is t1, t2, …, t z ,…,t m The maximum value of the output of other power sources except new energy in these m moments, Pt WT,max is t1, t2, …, t z ,…,t m The maximum value of the wind turbine output included in the grid reserve during these m moments, Pt PV,max is t1, t2, …, t z ,…,t m The maximum value of the photovoltaic power generation included in the grid reserve during these m moments, Δf N,max is t1, t2, …, t z ,…,t m The maximum value of the power system frequency deviation during these m moments.

[0042] The prediction method may also include: step S1012, determining the parameter used to show the correlation between the renewable energy power generation standby and the maximum frequency deviation according to the determined correlation index. Based on this, in a preferred embodiment of the present invention, the parameter used to show the correlation between the renewable energy power generation standby and the maximum frequency deviation may include at least one of the following parameters: the output of other power sources other than renewable energy, the output of wind turbines included in the grid standby, the output of photovoltaic power generation included in the grid standby, the frequency deviation of the power system, etc. In step 101, according to the time sequence, the measured value of the parameter obtained can be expressed by the following formula:

[0043]

[0044] in, Indicates that the output of other power sources except new energy sources is at t1, t2, …, t z ,…,t mThe measured values ​​at these m moments are Indicates that the output of wind turbines included in the grid reserve is at t1, t2, …, t z ,…,t m The measured values ​​at these m moments are Indicates that the output of photovoltaic power generation included in the grid reserve is at t1, t2, …, t z ,…,t m The measured values ​​at these m moments are Indicates that the frequency deviation of the power system is at t1, t2, …, t z ,…,t m The measured value at these m moments.

[0045] In step 102, through a large amount of data analysis, the influencing factor shown in the following formula can be determined:

[0046]

[0047] Among them, ψ inf It is the tth z The impact factor of time, P' G,min and P' G,max They are the output of other power sources except new energy at t1, t2, …, t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments, P't WT,min and P't WT,max The wind power output is included in the grid reserve at t1, t2, ..., t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments, P't PV,min and P't PV,max The photovoltaic power generation is included in the grid reserve at t1, t2, ..., t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments, Δf' N,min and Δf' N,max is the power system frequency deviation at t1, t2, …, t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments.

[0048] In step 103, the predicted value of the parameter at the next moment can be expressed by the following formula:

[0049]

[0050] in, is the predicted value of the output of other power sources except new energy at the next moment, is the predicted value of wind power output to be included in the grid reserve at the next moment, is the predicted value of photovoltaic power generation to be included in the grid reserve at the next moment, is the predicted value of the power system frequency deviation at the next moment, is the influencing factor at time t1, is the influencing factor at time t2, Yes z The influencing factor of time, Yes m The influencing factors of the time (the explanations of the repeated parameters in the formula have been omitted here and will not be repeated here, the same below).

[0051] Before step 103, the prediction method may further include: step S1031, normalizing the predicted value of the parameter at the next moment to obtain a normalized value after processing, and determining the correlation index between the new energy power generation reserve and the maximum frequency deviation at the next moment according to the obtained normalized value. Based on this, in a preferred embodiment of the present invention, the normalization process can be expressed by the following formula:

[0052]

[0053] in, is the normalized value of the output of other power sources except new energy at the next moment, The normalized value of wind power output included in the grid reserve at the next moment, is the normalized value of photovoltaic power generation included in the grid reserve at the next moment, It is the normalized value of the power system frequency deviation at the next moment.

[0054] Based on this, in a preferred embodiment of the present invention, the correlation index between the determined new energy power generation reserve and the maximum frequency deviation at the next moment can be expressed by the following formula:

[0055]

[0056] in, It is the correlation index between the new energy power generation reserve and the maximum frequency deviation at the next moment.

[0057] After step 104, the prediction method may further include: step S1041, when the predicted correlation index of the next moment is higher than the preset threshold, the reserve power of new energy is increased; when the predicted correlation index of the next moment is lower than the preset threshold, the proportion of new energy output incorporated into the power grid is reduced, and the proportion of new energy output as system load is increased.

[0058] By way of example, the preset threshold (e.g., 0.54) can be determined through data analysis and / or through expert experience. For example, when the predicted correlation index at the next moment is higher than 0.54, the reserve power of new energy is increased to timely adjust the power balance of the power grid and reduce the frequency deviation. When the predicted correlation index at the next moment is lower than 0.54, the proportion of new energy output incorporated into the power grid is reduced, and the proportion of new energy output as system load is increased to promote the consumption of new energy.

[0059] According to the method provided in this embodiment, at least one of the parameters such as the output of other power sources other than new energy, the output of wind turbines included in the grid reserve, the output of photovoltaic power generation included in the grid reserve, and the frequency deviation of the power system is monitored and measured in real time, and the measured values ​​of the above parameters are sorted in time, and then the influencing factor of the current parameter value on the parameter value at the next moment is determined, and then the predicted value of the parameter at the next moment is determined by the influencing factor and the measured value of the current parameter. After the predicted value of the parameter at the next moment is normalized, the obtained normalized value is calculated to obtain the predicted value of the correlation index of the new energy power generation reserve and the maximum frequency deviation at the next moment, and by comparing the value of the correlation index at the next moment, an effective method for predicting the correlation between the new energy power generation reserve and the maximum frequency deviation at the next moment is established, so that the output of the new energy unit can be adjusted according to the predicted correlation index to reduce the grid frequency deviation and ensure the power balance of the power system.

[0060] Based on the same general inventive concept, the present invention also protects a control device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the prediction method for the correlation between new energy power generation reserve and maximum frequency deviation in any of the above-mentioned embodiments.

[0061] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0062] On the other hand, the present invention also protects a machine-readable storage medium having instructions stored thereon, the instructions enabling a machine to execute any of the above-mentioned methods for predicting the output fault tolerance of a new energy cluster of a power system.

[0063] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0064] In addition, the terms "system" and "network" are often used interchangeably in this article. The term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0065] It should be understood that in the embodiment of the present invention, "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0066] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0067] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0068] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0069] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0070] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0071] Through the description of the above embodiments, it is clear to those skilled in the art that the present invention can be implemented in hardware, firmware, or a combination thereof. When software is used for implementation, the above functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein the communication media include any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that a computer can access. Taking this as an example but not limited to: a computer-readable medium can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer. In addition. Any connection can be appropriately a computer-readable medium. For example, if the software is transmitted from a website, a server or other remote source using a coaxial cable, an optical fiber cable, a twisted pair, a digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, then the coaxial cable, optical fiber cable, twisted pair, DSL, or wireless technologies such as infrared, wireless, and microwaves are included in the fixing of the medium. As used in the present invention, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and blue-ray disc, wherein disk usually reproduces data magnetically, while disc uses laser to reproduce data optically. The above combination should also be included in the scope of protection of computer-readable media.

[0072] In short, the above is only a preferred embodiment of the technical solution of the present invention, and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting the correlation between new energy power generation reserve and maximum frequency deviation, characterized in that: The prediction method comprises: Acquire, in chronological order, a measured value of a parameter of the target system for indicating a correlation between the renewable energy generation reserve and the maximum frequency deviation; Determine the predicted value of the parameter at the next moment based on the obtained measured value of the parameter and the influence factor of the preset current parameter value on the value of the parameter at the next moment; According to the predicted value of the parameter at the next moment, the correlation index of the correlation between the new energy generation reserve and the maximum frequency deviation of the target system at the next moment is predicted. The correlation index is used to indicate the correlation between the new energy generation reserve and the maximum frequency deviation; According to the predicted correlation index at the next moment, the output of the new energy unit is adjusted to reduce the frequency deviation of the power grid.

2. The prediction method according to claim 1, characterized in that: Before obtaining the measured values ​​of the parameters related to the correlation between the new energy power generation reserve and the maximum frequency deviation according to the time sequence, the prediction method further includes: Determining a correlation index of the correlation between the renewable energy generation reserve and the maximum frequency deviation according to the renewable energy generation reserve ratio of the target system and its influence on the maximum frequency deviation; According to the determined correlation index, the parameter for showing the correlation between the new energy power generation reserve and the maximum frequency deviation is determined.

3. The prediction method according to claim 1 or 2, characterized in that: The parameters used to show the correlation between new energy power generation reserve and maximum frequency deviation include at least one of the following parameters: output of other power sources except new energy, output of wind turbines included in grid reserve, output of photovoltaic power generation included in grid reserve, and power system frequency deviation.

4. The prediction method according to claim 1, characterized in that: The following formula expresses the measured values ​​of the parameters obtained in chronological order: in, Indicates that the output of other power sources except new energy sources is at t1, t2, …, t z ,…,t m The measured values ​​at these m moments are Indicates that the output of wind turbines included in the grid reserve is at t1, t2, …, t z ,…,t m The measured values ​​at these m moments are Indicates that the output of photovoltaic power generation included in the grid reserve is at t1, t2, …, t z ,…,t m The measured values ​​at these m moments are Indicates that the frequency deviation of the power system is at t1, t2, …, t z ,…,t m The measured value at these m moments.

5. The prediction method according to claim 1, characterized in that: The impact factor is expressed by the following formula: Among them, ψ inf It is the tth z The impact factor of time, P' G,min and P' G,max They are the output of other power sources except new energy at t1, t2, …, t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments, P't WT,min and P't WT,max The wind power output is included in the grid reserve at t1, t2, ..., t z ,...,t m The minimum and maximum values ​​of the measured values ​​at these m moments, P't PV,min and P't PV,max The photovoltaic power generation is included in the grid reserve at t1, t2, ..., t z ,...,t m The minimum and maximum values ​​of the measured values ​​at these m moments, Δf' N,min and Δf' N,max is the power system frequency deviation at t1, t2, …, t z ,…,t m The minimum and maximum values ​​of the measured values ​​at these m moments.

6. The prediction method according to claim 4, characterized in that: The predicted value of the parameter at the next moment is determined by the following formula: in, is the predicted value of the output of other power sources except new energy at the next moment, is the predicted value of wind power output to be included in the grid reserve at the next moment. is the predicted value of photovoltaic power generation to be included in the grid reserve at the next moment, is the predicted value of the power system frequency deviation at the next moment, is the influencing factor at time t1, is the influencing factor at time t2, Yes z The influencing factor of time, Yes m The influencing factor of time.

7. The prediction method according to claim 1, characterized in that: After determining the predicted value of the parameter related to the correlation between the new energy power generation reserve and the maximum frequency deviation at the next moment, the prediction method further includes: Normalizing the predicted value of the parameter at the next moment to obtain a processed normalized value; The correlation index between the new energy power generation reserve and the maximum frequency deviation at the next moment is determined according to the obtained normalized value.

8. The prediction method according to claim 1, characterized in that: The step of adjusting the output of the new energy generating unit according to the predicted correlation index at the next moment includes: When the predicted correlation index at the next moment is higher than a preset threshold, the reserve power of new energy is increased; When the predicted correlation index at the next moment is lower than a preset threshold, the proportion of renewable energy output incorporated into the power grid is reduced, and the proportion of renewable energy output as system load is increased.

9. The prediction method according to claim 7, characterized in that: The correlation index between the new energy generation reserve and the maximum frequency deviation at the next moment is determined by the following formula: in, is the correlation index between the next moment's renewable energy generation reserve and the maximum frequency deviation, is the normalized value of the output of other power sources except new energy at the next moment, The normalized value of wind power output included in the grid reserve at the next moment, is the normalized value of photovoltaic power generation included in the grid reserve at the next moment, It is the normalized value of the frequency deviation of the power system at the next moment.

10. A control device, characterized in that: The control device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the prediction method according to any one of claims 1-9.

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