Energy storage frequency modulation instruction control method and system

Abstract

The invention relates to the technical field of energy storage frequency modulation control, and discloses an energy storage frequency modulation instruction control method and system, and the method comprises the steps: obtaining an energy storage frequency modulation instruction, and carrying out the variational mode decomposition; calculating a balance value of the sequence after variational mode decomposition, and generating a supplementary sequence according to the balance value; processing the supplementary sequence to obtain a de-filling sequence, correspondingly adding the sequence after variational mode decomposition and the supplementary sequence, and then forming a new sub-sequence set with the de-filling sequence; and respectively inputting the sequences in the new sub-sequence set into the recurrent neural network to obtain a final control result of the energy storage frequency modulation instruction. According to the method, the problems of high prediction difficulty and low precision caused by too strong fluctuation of the frequency modulation instruction sequence in the prior art are solved, the irregularity and fluctuation of the original sequence are remarkably reduced, the result is more accurate and reliable, the frequency modulation requirement can be responded in advance, and the immediate response capability of the system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage frequency modulation control, and in particular to an energy storage frequency modulation instruction control method and system. Background Art

[0002] Frequency regulation in the power system is a key link to ensure the stable operation of the power grid. Traditional thermal power units have a slow response speed and are difficult to quickly adapt to load changes and maintain the stability of the power grid frequency. In order to improve this situation, a hybrid energy storage system (such as a combination of supercapacitors and lithium batteries) is usually used to assist thermal power units in frequency regulation. In this mode, the hybrid energy storage system is responsible for processing the difference between the frequency modulation command and the output of the thermal power unit, where the high-frequency component is borne by the supercapacitor with a fast response speed, and the low-frequency component is handled by the lithium battery with a higher energy density. However, in actual operation, the transmission of the signal (frequency modulation command is transmitted to the supercapacitor / lithium battery) takes time, and the supercapacitor or lithium battery itself responds. This will lead to inevitable time delays, which not only affects the system's immediate response capability, but also has a negative impact on the economic benefits of the power plant.

[0003] In order to solve this problem, researchers have developed an algorithm to predict the changing trend of the frequency modulation instructions in advance, so that the energy storage system can act in advance, thereby improving the frequency regulation effect and economic benefits. One of the traditional control methods is to use variational mode decomposition (VMD) to decompose the original frequency modulation instruction sequence into multiple subsequences, process these subsequences separately, and finally synthesize the processing results. Although this method can improve the processing accuracy in theory, it is found in practice that the decomposed subsequences are very volatile, which increases the difficulty. This highly volatile subsequence makes it complicated and inaccurate to control each subsequence individually, limiting the improvement of the overall performance. At the same time, it also fails to effectively solve the problem of response delay of the energy storage system, which in turn affects the frequency regulation effect and economic benefits.

[0004] Therefore, a new control method is urgently needed to overcome the shortcomings of the existing technology, that is, to be able to more effectively handle the high volatility of the frequency modulation instruction sequence, while reducing the response delay and improving the frequency regulation capability and economic benefits of the entire energy storage system. Summary of the invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a method and system for controlling energy storage frequency modulation instructions to solve the problem that when the existing method processes the frequency modulation instruction sequence, the sub-sequences after decomposition are very volatile, resulting in high complexity and inaccuracy in processing each sub-sequence individually, and failing to effectively solve the problem of response delay of the energy storage system, thereby affecting the frequency regulation effect and economic benefits.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a method for controlling an energy storage frequency modulation instruction, comprising: Obtain the energy storage frequency modulation instructions of the hybrid energy storage system and perform variational mode decomposition; Calculating the equilibrium value of the sequence after the variational mode decomposition, and generating a supplementary sequence according to the equilibrium value; Processing the supplemented sequence to obtain a defilled sequence, and adding the sequence after the variational mode decomposition and the supplemented sequence accordingly to form a new subsequence set with the defilled sequence; The sequences in the new subsequence set are respectively input into the recursive neural network to obtain the final control result of the energy storage frequency modulation instruction.

[0008] As a preferred solution of the energy storage frequency modulation instruction control method described in the present invention, the calculation of the equilibrium value of the sequence after the variational mode decomposition includes: Obtain energy storage frequency modulation instructions, which are decomposed into IMF1, IMF2, IMF3, ..., IMF through variational mode decomposition. i ,......,IMF K ; Set a subsequence after variational mode decomposition as IMF i =[X i1 ,X i2 ,X i3 ,......,X ii ,......,X iN ], where X ii and X iN Respectively represent the i-th element and the N-th element in the subsequence after variational mode decomposition; The average value of the subsequence after the variational mode decomposition is X iavg , the median value is X iz The maximum and minimum values ​​are X max and X min , then the subsequence IMF of the variational mode decomposition is i The equilibrium value is expressed as: , in, Represents the subsequence IMF after variational mode decomposition i The balance value.

[0009] As a preferred solution of the energy storage frequency modulation instruction control method described in the present invention, the generating of the supplementary sequence includes: Traverse a subsequence IMF that has undergone the variational mode decompositioni =[X i1 ,X i2 ,X i3 ,......,X ii ,......,X iN ]; If the value X ii >5X ip , then the corresponding , the formula is: , If the value X ip < X ii <5X ip or 0.2X ip <X ii <X ip , then the corresponding =0; If the value X ii <0.2X ip , then the corresponding , the formula is: , According to the above three situations, the subsequence IMF of the variational mode decomposition is generated i Supplementary sequence IMF i 、 = .

[0010] As a preferred solution of the energy storage frequency modulation instruction control method described in the present invention, the generating of the supplementary sequence further comprises: According to the variational mode decomposition subsequence IMF i The method of obtaining the supplementary sequence of is similar to that of obtaining the supplementary sequence IMF1 of all subsequences. 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 .

[0011] As a preferred solution of the energy storage frequency modulation instruction control method described in the present invention, wherein: the obtaining of the defilling sequence by processing the supplementary sequence comprises: Add the supplementary sequences of all subsequences together IMF1 、 +IMF2 、 +IMF3 、 +.......+IMF K 、Get the defilled sequence S q =[X q1 ,X q2 ,X q3 ,......,X qi ,......,X qN ], where X qi and X qN Respectively represent the i-th element and the N-th element in the defilled sequence; (X q1 +X q2 +X q3 +......+X qi +......+X qN ) / N=0 and a single value close to 0 is the goal, and the supplementary sequence IMF1 of all subsequences is continuously randomized. 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 Each value of , and loop according to the set number of times, to find the random value of the supplementary sequence IMF1 that is closest to the target 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 , where N represents the number of elements in the defilled sequence; The defilled sequence after random processing is S qfit =[X qfit1 ,X qfit2 ,X qfit3 ,......,X qfiti ,......,X qfitN ],(X qfit1 +X qfit2 +X qfit3 +......+X qfiti +......,+X qfitN ) / N=A, where X qfiti and X qfitN They respectively represent the i-th element and the N-th element in the de-filled sequence after random processing, and A represents the average value of the de-filled sequence.

[0012] As a preferred solution of the energy storage frequency modulation instruction control method described in the present invention, the step of obtaining the defilling sequence by processing the supplementary sequence further comprises: If A>6, each value of the defilling sequence needs to be fine-tuned, and the formula is expressed as: , in, Represents the fine-tuned value of the elements in the defilled sequence.

[0013] As a preferred solution of the energy storage frequency modulation instruction control method described in the present invention, the final control result of the energy storage frequency modulation instruction includes: By calculating the variational mode decomposition sequence IMF1, IMF2, IMF3, ..., IMF i ,......,IMF K The equilibrium value generates the supplementary sequence IMF1 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 , add the corresponding items of the variational mode decomposition sequence and the supplemented sequence to obtain IMF1+IMF1 、 ,IMF2+IMF2 、 ,......,IMF K +IMF K 、 ; The sequence after the variational mode decomposition and the supplemented sequence are added to the randomized defilled sequence S qfit A new subsequence set is formed, and each sequence in the new subsequence set is input into the recursive neural network respectively, and the value of the corresponding unknown group is output, and then the value of the unknown group corresponding to each subsequence output is added to obtain the final control result of the energy storage frequency modulation instruction.

[0014] In a second aspect, the present invention provides an energy storage frequency modulation command control system, comprising: An instruction decomposition module is used to obtain the energy storage frequency modulation instructions of the hybrid energy storage system and perform variational mode decomposition; A sequence processing module, used for calculating the equilibrium value of the sequence after the variational mode decomposition, generating a supplementary sequence according to the equilibrium value; obtaining a defilled sequence by processing the supplementary sequence, and forming a new subsequence set with the defilled sequence after adding the sequence after the variational mode decomposition and the supplementary sequence accordingly; The instruction control module is used to input the sequences in the new subsequence set into the recursive neural network respectively to obtain the final control result of the energy storage frequency modulation instruction.

[0015] In a third aspect, the present invention provides an electronic device, comprising: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of a method for controlling energy storage frequency modulation instructions are implemented.

[0016] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of a method for controlling energy storage frequency modulation instructions.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a method and system for controlling energy storage frequency modulation instructions, aiming to solve the problems of high prediction difficulty and low precision caused by excessive volatility of frequency modulation instruction sequences in the prior art, while reducing response delays to improve frequency regulation effects and economic benefits of power plants. The present invention processes the frequency modulation instruction sequence of a hybrid energy storage system through variational mode decomposition technology, effectively reducing the irregularity and volatility of the original sequence, combining the supplementary sequence with the defilling process to generate a new set of subsequences, and using a recursive neural network to obtain the final control result, which not only significantly improves the prediction accuracy and response speed, reduces the prediction difficulty caused by excessive volatility of the instruction sequence, but also realizes early response to frequency modulation needs, and enhances the stability and reliability of the power grid. In addition, the present invention greatly improves the economic benefits of power plants in frequency modulation, and provides strong technical support for the development of smart grids. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0019] Figure 1 The figure is a schematic diagram of the overall process logic of the method described in one embodiment of the present invention.

[0020] Figure 2 The figure is a control flow diagram of a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0022] Example 1, reference Figure 1-Figure 2 As an embodiment of the present invention, the traditional prediction method is to use VMD decomposition to divide the original sequence into a series of subsequences, and then predict them separately, and finally superimpose the predicted results. The problem is that the subsequences after decomposition are very volatile, and the difficulty of prediction is still very large. For this reason, this embodiment proposes a method for controlling energy storage frequency modulation instructions, which fills each highly volatile sequence into a smooth, easy-to-predict sequence, and then forms a defilled sequence, which is then put into a neural network for prediction, aiming to solve the problem of high prediction difficulty and low accuracy caused by the excessive volatility of the frequency modulation instruction sequence in the prior art. Figure 1 The specific steps include: S100: Obtaining energy storage frequency modulation instructions of the hybrid energy storage system and performing variational mode decomposition; S200: calculating the equilibrium value of the sequence after variational mode decomposition, and generating a supplementary sequence according to the equilibrium value; S300: obtaining a defilled sequence by processing the supplemented sequence, and adding the sequence after variational mode decomposition and the supplemented sequence to form a new subsequence set with the defilled sequence; S400: Input the sequences in the new subsequence set into the recursive neural network respectively to obtain the final control result of the energy storage frequency modulation instruction.

[0023] It should be noted that the present invention provides a method and system for controlling energy storage frequency modulation instructions, aiming to solve the problems of high prediction difficulty and low precision caused by excessive volatility of frequency modulation instruction sequences in the prior art, while reducing response delays to improve frequency regulation effects and economic benefits of power plants. The present invention processes the frequency modulation instruction sequence of a hybrid energy storage system through variational mode decomposition technology, effectively reducing the irregularity and volatility of the original sequence, combining the supplementary sequence with the defilling process to generate a new set of subsequences, and using a recursive neural network to obtain the final control result, which not only significantly improves the prediction accuracy and response speed, reduces the prediction difficulty caused by excessive volatility of the instruction sequence, but also realizes early response to frequency modulation needs, and enhances the stability and reliability of the power grid. In addition, the present invention greatly improves the economic benefits of power plants in frequency modulation, and provides strong technical support for the development of smart grids.

[0024] In an embodiment of the present invention, the above step S100 of obtaining the energy storage frequency modulation instruction of the hybrid energy storage system and performing variational mode decomposition includes: The energy storage frequency modulation instruction is set as Pt=[X1,X2,X3,......,X i ,......,X N ]; The energy storage frequency modulation instruction Pt is subjected to variational mode decomposition, and the sequence after variational mode decomposition is expressed as IMF1, IMF2, IMF3, ..., IMF K ; It should be noted that the above step S100 uses variational mode decomposition to process the energy storage frequency modulation instructions, which can effectively extract the multi-scale features in the original instruction sequence, reduce its volatility and complexity, and provide more stable and easy-to-analyze sequence data for subsequent steps, thereby improving the accuracy and efficiency of the entire control process.

[0025] In the embodiment of the present invention, the above step S200 calculates the equilibrium value of the sequence after variational mode decomposition, and generates the supplementary sequence according to the equilibrium value, including: Specifically, calculating the equilibrium value of the sequence after variational mode decomposition includes: Set a subsequence after variational mode decomposition as IMF i =[X i1 ,X i2 ,X i3 ,......,X ii ,......,X iN ], where X ii and X iN Respectively represent the i-th element and the N-th element in the subsequence after variational mode decomposition; The average value of the subsequence after variational mode decomposition is X iavg , the median value is X iz The maximum and minimum values ​​are X max and X min , then the subsequence IMF of variational mode decomposition is i The equilibrium value is expressed as: , in, Represents the subsequence IMF after variational mode decomposition i The balance value.

[0026] Specifically, the steps of generating a supplementary sequence according to the balance value include: Traverse a subsequence IMF after variational mode decomposition i =[X i1 ,X i2 ,Xi3 ,......,X ii ,......,X iN ]; If the value X ii >5X ip , then the corresponding , the formula is: , If the value X ip < X ii <5X ip or 0.2X ip <X ii <X ip , then the corresponding =0; If the value X ii <0.2X ip , then the corresponding , the formula is: , Generate the subsequence IMF of variational mode decomposition according to the above three situations i Supplementary sequence IMF i 、 = , according to the subsequence IMF of variational mode decomposition i The method of obtaining the supplementary sequence of is similar to that of obtaining the supplementary sequence IMF1 of all subsequences. 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 .

[0027] It should be noted that the above step S200 generates a supplementary sequence by calculating the equilibrium value of the sequence after variational mode decomposition, which effectively reduces the volatility and irregularity of the original frequency modulation instruction sequence, making the de-filled sequence obtained by subsequent processing more stable, thereby improving the accuracy and reliability of the final result.

[0028] In the embodiment of the present invention, the above step S300 processes the supplemented sequence to obtain the de-filled sequence, and adds the sequence after variational mode decomposition and the supplemented sequence to form a new subsequence set with the de-filled sequence, specifically including: Add the supplementary sequences of all subsequences together IMF1 、 +IMF2 、 +IMF3 、 +.......+IMFK 、 Get the defilled sequence S q =[X q1 ,X q2 ,X q3 ,......,X qi ,......,X qN ], where X qi and X qN Respectively represent the i-th element and the N-th element in the defilled sequence; (X q1 +X q2 +X q3 +......+X qi +......+X qN ) / N=0 and a single value close to 0 is the goal, and the supplementary sequence IMF1 of all subsequences is continuously randomized 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 Each value of , and loop according to the set number of times, to find the random value closest to the target that supplementary sequence IMF1 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 , where N represents the number of elements in the defilled sequence; The defilled sequence after random processing is S qfit =[X qfit1 ,X qfit2 ,X qfit3 ,......,X qfiti ,......,X qfitN ],(X qfit1 +X qfit2 +X qfit3 +......+X qfiti +......,+X qfitN ) / N=A, where X qfiti and X qfitN They respectively represent the i-th element and the N-th element in the de-filled sequence after random processing, and A represents the average value of the de-filled sequence.

[0029] If A>6, each value of the defilling sequence needs to be fine-tuned, and the formula is expressed as: , in, Represents the fine-tuned value of the elements in the defilled sequence.

[0030] It should be noted that the above step S300 obtains the defilled sequence by processing the supplemented sequence, and combines it with the sequence after variational mode decomposition and the supplemented sequence to generate a new subsequence set, which effectively reduces the irregularity and volatility of the original sequence, lays the foundation for the subsequent accurate acquisition of energy storage frequency modulation instructions, and improves the accuracy and reliability of the results.

[0031] In the embodiment of the present invention, the above step S400 inputs the sequences in the new subsequence set into the recursive neural network respectively, and obtains the final control result of the energy storage frequency modulation instruction, which specifically includes: By calculating the variational mode decomposition sequence IMF1, IMF2, IMF3, ..., IMF i ,......,IMF K The equilibrium value generates the supplementary sequence IMF1 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 , add the corresponding terms of the variational mode decomposition sequence and the supplementary sequence to obtain IMF1+IMF1 、 ,IMF2+IMF2 、 ,......,IMF K +IMF K 、 ; The sequence after variational mode decomposition and the supplementary sequence are added together and then added to the randomized defilled sequence S qfit A new set of subsequences is formed, and each sequence in the new set of subsequences is input into the recursive neural network, and the corresponding unknown group value is output. Then, the value of the unknown group corresponding to each subsequence output is added to obtain the final control result of the energy storage frequency modulation instruction. The detailed process is as follows: Figure 2 .

[0032] It should be noted that the above step S400 can accurately predict the energy storage frequency modulation instructions by inputting the new subsequence set into the recursive neural network, effectively reducing the prediction difficulty caused by the irregularity and volatility of the original sequence, improving the prediction accuracy and the system's instant response capability, thereby enhancing the stability and reliability of the power grid and improving the economic benefits of the power plant.

[0033] Embodiment 2: Based on the previous embodiment, this embodiment provides an application example of a method and system for controlling energy storage frequency modulation instructions, in order to verify and illustrate the technical effects adopted in this method.

[0034] In order to further verify the advantages of the present invention, this embodiment uses the energy storage frequency modulation instruction control method and the VMD-GRU control method provided by the present invention to process the frequency modulation sequence. The results are shown in Table 1, and the definitions of the four evaluation indicators are shown in Table 2.

[0035] Table 1: Results of the frequency modulation sequence processed by the method of the present invention and the control method of VMD-GRU

[0036] Table 2: 4 evaluation indicators

[0037] in, represents the sample size, and Represent the actual value and predicted value at time n respectively.

[0038] It can be seen from the above comparison results that the energy storage frequency modulation instruction control method provided by the present invention performs well in all four evaluation indicators and is better than the VMD-GRU control method.

[0039] Therefore, the present invention provides a method and system for controlling energy storage frequency modulation instructions, aiming to solve the problems of high prediction difficulty and low precision caused by excessive volatility of frequency modulation instruction sequences in the prior art, while reducing response delays to improve frequency regulation effects and economic benefits of power plants. The present invention processes the frequency modulation instruction sequence of a hybrid energy storage system through variational mode decomposition technology, effectively reducing the irregularity and volatility of the original sequence, combining the supplementary sequence with the defilling process to generate a new set of subsequences, and using a recursive neural network to obtain the final control result, which not only significantly improves the prediction accuracy and response speed, and reduces the prediction difficulty caused by excessive volatility of the instruction sequence, but also realizes early response to frequency modulation needs, and enhances the stability and reliability of the power grid. In addition, the present invention greatly improves the economic benefits of power plants in frequency modulation, and provides strong technical support for the development of smart grids.

[0040] Embodiment 3, this embodiment provides an energy storage frequency modulation command control system, including a command decomposition module, a sequence processing module and a command control module; Specifically, the instruction decomposition module is used to obtain the energy storage frequency modulation instruction of the hybrid energy storage system and perform variational mode decomposition; Specifically, the sequence processing module is used to calculate the equilibrium value of the sequence after variational mode decomposition, and generate a supplementary sequence according to the equilibrium value; obtain a defilled sequence by processing the supplementary sequence, and add the sequence after variational mode decomposition and the supplementary sequence accordingly to form a new subsequence set with the defilled sequence; Specifically, the instruction control module is used to input the sequences in the new subsequence set into the recursive neural network respectively to obtain the final control result of the energy storage frequency modulation instruction.

[0041] It should be noted that the technical solution of the energy storage frequency modulation command control system and the technical solution of the above-mentioned energy storage frequency modulation command control method belong to the same concept. For the details not described in detail in the technical solution of the energy storage frequency modulation command control system in this embodiment, please refer to the description of the technical solution of the above-mentioned energy storage frequency modulation command control method.

[0042] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0043] This embodiment also provides an electronic device, which includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, 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 communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for controlling energy storage frequency modulation instructions is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0044] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method proposed in the above embodiment is implemented.

[0045] The storage medium proposed in this embodiment and the method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0046] Through the above description of the implementation mode, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation mode. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer's floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform the method of the embodiment of the present invention.

[0047] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0048] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The solutions in the embodiments of the present invention may be implemented in various computer languages.

[0049] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0050] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0051] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0052] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0053] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling energy storage frequency modulation instructions, characterized in that: include: Obtain the energy storage frequency modulation instructions of the hybrid energy storage system and perform variational mode decomposition; Calculating the equilibrium value of the sequence after the variational mode decomposition, and generating a supplementary sequence according to the equilibrium value; Processing the supplemented sequence to obtain a defilled sequence, and adding the sequence after the variational mode decomposition and the supplemented sequence accordingly to form a new subsequence set with the defilled sequence; The sequences in the new subsequence set are respectively input into the recursive neural network to obtain the final control result of the energy storage frequency modulation instruction.

2. The energy storage frequency modulation instruction control method according to claim 1, characterized in that: The calculation of the equilibrium value of the sequence after the variational mode decomposition includes: Obtain energy storage frequency modulation instructions, which are decomposed into IMF1, IMF2, IMF3, ..., IMF i ,......,IMF K ; Set a subsequence after variational mode decomposition as IMF i =[X i1 ,X i2 ,X i3 ,......,X ii ,......,X iN ], where X ii and X iN Respectively represent the i-th element and the N-th element in the subsequence after variational mode decomposition; The average value of the subsequence after the variational mode decomposition is X iavg , the median value is X iz The maximum and minimum values ​​are X max and X min , then the subsequence IMF of the variational mode decomposition is i The equilibrium value is expressed as: ， in, Represents the subsequence IMF after variational mode decomposition i The balance value.

3. A method for controlling energy storage frequency modulation instructions as claimed in claim 2, characterized in that: Generating the supplementary sequence comprises: Traverse a subsequence IMF that has undergone the variational mode decomposition i =[X i1 ,X i2 ,X i3 ,......,X ii ,......,X iN ]; If the value X ii >5X ip , then the corresponding , the formula is: ， If the value X ip < X ii <5X ip or 0.2X ip <X ii <X ip , then the corresponding =0; If the value X ii <0.2X ip , then the corresponding , the formula is: ， According to the above three situations, the subsequence IMF of the variational mode decomposition is generated i Supplementary sequence IMF i 、 = .

4. The energy storage frequency modulation instruction control method according to claim 3, characterized in that: Generating the supplementary sequence further comprises: According to the variational mode decomposition subsequence IMF i The method of obtaining the supplementary sequence of is similar to that of obtaining the supplementary sequence IMF1 of all subsequences. 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 .

5. The energy storage frequency modulation instruction control method according to claim 4, characterized in that: The obtaining of the defilled sequence by processing the supplemented sequence comprises: Add the supplementary sequences of all subsequences together IMF1 、 +IMF2 、 +IMF3 、 +.......+IMF K 、 Get the defilled sequence S q =[X q1 ,X q2 ,X q3 ,......,X qi ,......,X qN ], where X qi and X qN Respectively represent the i-th element and the N-th element in the defilled sequence; (X q1 +X q2 +X q3 +......+X qi +......+X qN ) / N=0 and a single value close to 0 is the goal, and the supplementary sequence IMF1 of all subsequences is continuously randomized. 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 Each value of , and loop according to the set number of times, to find the random value of the supplementary sequence IMF1 that is closest to the target 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 , where N represents the number of elements in the defilled sequence; The defilled sequence after random processing is S qfit =[X qfit1 ,X qfit2 ,X qfit3 ,......,X qfiti ,......,X qfitN ],(X qfit1 +X qfit2 +X qfit3 +......+X qfiti +......,+X qfitN ) / N=A, where X qfiti and X qfitN They respectively represent the i-th element and the N-th element in the de-filled sequence after random processing, and A represents the average value of the de-filled sequence.

6. A method for controlling energy storage frequency modulation instructions as claimed in claim 5, characterized in that: The obtaining of the defilled sequence by processing the supplemented sequence further comprises: If A>6, each value of the defilling sequence needs to be fine-tuned, and the formula is expressed as: ， in, Represents the fine-tuned value of the elements in the defilled sequence.

7. The energy storage frequency modulation instruction control method according to claim 6, characterized in that: The final control result of obtaining the energy storage frequency modulation instruction includes: By calculating the variational mode decomposition sequence IMF1, IMF2, IMF3, ..., IMF i ,......,IMF K The equilibrium value generates the supplementary sequence IMF1 、 ,IMF2 、 ,IMF3 、 ,......,IMF i 、 ,......,IMF K 、 , add the corresponding items of the variational mode decomposition sequence and the supplemented sequence to obtain IMF1+IMF1 、 ,IMF2+IMF2 、 ,......,IMF K +IMF K 、 ; The sequence after the variational mode decomposition and the supplemented sequence are added to the randomized defilled sequence S qfit A new subsequence set is formed, and each sequence in the new subsequence set is input into the recursive neural network respectively, and the value of the corresponding unknown group is output, and then the value of the unknown group corresponding to each subsequence output is added to obtain the final control result of the energy storage frequency modulation instruction.

8. An energy storage frequency modulation command control system, using the method according to any one of claims 1 to 7, characterized in that: include: An instruction decomposition module is used to obtain the energy storage frequency modulation instructions of the hybrid energy storage system and perform variational mode decomposition; A sequence processing module, used for calculating the equilibrium value of the sequence after the variational mode decomposition, generating a supplementary sequence according to the equilibrium value; obtaining a defilled sequence by processing the supplementary sequence, and forming a new subsequence set with the defilled sequence after adding the sequence after the variational mode decomposition and the supplementary sequence accordingly; The instruction control module is used to input the sequences in the new subsequence set into the recursive neural network respectively to obtain the final control result of the energy storage frequency modulation instruction.

9. An electronic device, comprising a memory and a processor, characterized in that: The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that: When the computer executable instructions are executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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