A frequency modulation method, system and device based on ultra-capacity energy storage

Abstract

The disclosed embodiment provides a frequency modulation method, system and device based on supercapacitor energy storage, the method comprising: obtaining a frequency modulation command signal; determining the number of decomposition layers in a cycle for multiple times, and for the number of decomposition layers determined in each cycle, decomposing the frequency modulation command signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, and calculating the predicted total aliasing degree between each modal quantity, and predicting the frequency modulation performance index; determining the number of decomposition layers that meet the preset conditions based on the predicted total aliasing degree and the predicted frequency modulation performance index; determining the instruction allocation of the frequency modulation command signal according to the determined number of decomposition layers, and sending corresponding instructions to different energy storage devices, so that the energy storage devices respond to the corresponding instructions for frequency modulation, and the energy storage devices include supercapacitors. The problem of inaccurate frequency modulation command signal allocation caused by modal aliasing is solved, the cost of the energy storage system is reduced, and the revenue of the power plant is increased.

Description

Technical Field

[0001] The present disclosure relates to the technical field of power grid frequency regulation, and in particular to a frequency regulation method, system and device based on ultra-capacity energy storage. Background Art

[0002] Supercapacitors are power-type energy storage devices. The triple benefits of technology, cost, and policy help open up a market worth tens of billions of yuan. Supercapacitors have higher energy density than traditional capacitors and higher power density than batteries. They are a new type of power-type energy storage device with the characteristics of short charging time, long service life, good temperature characteristics, and green environmental protection. Supercapacitors are widely used in the field of power grid frequency modulation technology as power sources.

[0003] The VMD (variational mode decomposition) algorithm distributes the hybrid energy storage power and divides the frequency modulation command into a high-frequency power component and a low-frequency power component. However, the VMD algorithm suffers from the loss of the original signal in the VMD decomposition, and the modal aliasing leads to inaccurate allocation of the rated power and rated capacity, which reduces the life of the thermal power units and increases the cost of the energy storage system. Different command allocations affect the frequency modulation performance indicators and thus affect the profits of the power plant. Summary of the invention

[0004] The embodiments of the present disclosure provide a frequency modulation method, system and device based on ultracapacitor energy storage, so as to solve the problem of inaccurate frequency modulation command signal distribution caused by existing modal aliasing.

[0005] Based on the above problems, a first aspect provides a frequency modulation method based on ultra-capacity energy storage, comprising:

[0006] Obtaining frequency modulation command signal;

[0007] Determine the number of decomposition layers in a cycle for multiple times, and for the number of decomposition layers determined in each cycle, decompose the frequency modulation instruction signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, calculate the predicted total aliasing degree between each modal quantity, and predict the frequency modulation performance index;

[0008] Determining the number of decomposition layers that meets preset conditions based on the predicted total aliasing degree and the predicted frequency modulation performance index;

[0009] The command allocation of the frequency modulation command signal is determined according to the determined number of decomposition layers, and corresponding commands are sent to different energy storage devices so that the energy storage devices perform frequency modulation in response to the corresponding commands, and the energy storage devices include super capacitors.

[0010] In combination with the first aspect, in a possible implementation, the number of decomposition layers is set multiple times in the cycle, and for the number of decomposition layers set in each cycle, the frequency modulation instruction signal is decomposed into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, and the predicted total aliasing degree between the modal quantities is calculated, and the frequency modulation performance index is predicted, including:

[0011] Determine the initial decomposition level and the final decomposition level;

[0012] From the initial decomposition layer to the final decomposition layer, the frequency modulation command signal is decomposed based on a preset algorithm in a loop, and each loop performs the following steps:

[0013] Decomposing the frequency modulation command signal based on a preset algorithm to obtain modal quantities corresponding to the number of decomposition layers of the cycle; and calculating the predicted total aliasing degree between the modal quantities;

[0014] The instruction allocation corresponding to the decomposition level of the cycle is obtained, and the predicted frequency modulation performance index corresponding to the decomposition level is determined according to the instruction allocation.

[0015] In combination with the first aspect, in a possible implementation manner, after decomposing the frequency modulation instruction signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, the predicted total aliasing degree D is determined using the following formula:

[0016]

[0017] in, Characterizes the number of decomposition levels, Characterize the predicted total aliasing level, Characterizes the width of the aliased part of adjacent modal quantities, Characterizes the frequency band occupied by adjacent modal quantities.

[0018] In combination with the first aspect, in a possible implementation manner, determining the number of decomposition layers that meets a preset condition based on the predicted total aliasing degree and the predicted frequency modulation performance index includes:

[0019] The values ​​of all predicted total aliasing degrees and predicted frequency modulation performance indicators are sorted respectively to obtain the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance indicator;

[0020] If the decomposition layer number corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are consistent, the decomposition layer number is determined as the decomposition layer number that meets the preset conditions.

[0021] In combination with the first aspect, in a possible implementation manner, the method further includes:

[0022] If the decomposition layers corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are inconsistent, then for each predicted frequency modulation performance index, the ratio between the predicted frequency modulation performance index and each predicted total aliasing degree is determined respectively to obtain a plurality of first reference ratios;

[0023] For each first reference ratio, determine the decomposition layer numbers corresponding to the predicted total aliasing degree and the predicted frequency modulation performance index of the first reference ratio, and determine the decomposition layer number closest to the average value of the two as the decomposition layer number corresponding to the first reference ratio;

[0024] sorting the plurality of first reference ratios;

[0025] According to the order of the multiple first reference ratios from large to small, the signal integrity at the decomposition levels corresponding to the first reference ratios is determined in sequence until the decomposition level that meets the preset conditions is determined.

[0026] In combination with the first aspect, in a possible implementation manner, the signal integrity at the number of decomposition layers corresponding to the first reference ratio is determined by the following formula:

[0027]

[0028] in, Characterizes the length of a single sequence, Characterize the residual sequence, Characterize the original sequence; by decomposing the frequency modulation command signal to obtain , where K1 is the number of decomposition levels, is the frequency modulation command signal, that is, the original sequence , is the i-th modal quantity (IMF) after decomposition, and the number of modal quantities is the number of decomposition levels. is the residual component after decomposition, that is, the residual sequence .

[0029] In combination with the first aspect, in a possible implementation manner, determining the signal integrity at the number of decomposition layers corresponding to the first reference ratios in descending order until the number of decomposition layers that meets the preset conditions is determined includes:

[0030] Determining the signal integrity at the number of decomposition layers corresponding to the first reference ratios in order from large to small;

[0031] Comparing the determined signal integrity with a preset value until a first signal integrity greater than the preset value is determined;

[0032] The number of decomposition layers corresponding to the first signal integrity is determined as the number of decomposition layers that meets a preset condition.

[0033] In combination with the first aspect, in a possible implementation manner, determining the instruction allocation of the frequency modulation instruction signal according to the determined number of decomposition layers, and sending corresponding instructions to different energy storage devices so that the energy storage devices perform frequency modulation in response to the corresponding instructions, includes:

[0034] Decomposing the frequency modulation command signal into modal quantities of the number of decomposition layers according to the determined number of decomposition layers, mapping the modal quantities of the number of decomposition layers to the frequency domain, determining the split point of the high-frequency power component and the low-frequency power component through the frequency domain distribution of the modal quantities, and then dividing the frequency modulation command signal into the high-frequency power component and the low-frequency power component;

[0035] The high-frequency power component is sent as a supercapacitor frequency modulation power instruction to a supercapacitor energy storage device, and the low-frequency power component is sent as other frequency modulation power instructions to other energy storage devices, so that the supercapacitor energy storage device and the other energy storage devices respond to their respective frequency modulation power instructions and perform frequency modulation.

[0036] In a second aspect, a frequency modulation system based on ultracapacitor energy storage is provided, comprising: an instruction acquisition module for acquiring a frequency modulation instruction signal;

[0037] A cyclic calculation module, used for determining the number of decomposition layers by cyclic multiple times, and for the number of decomposition layers determined in each cycle, decomposing the frequency modulation instruction signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, calculating the predicted total aliasing degree between the modal quantities, and predicting the frequency modulation performance index;

[0038] A judgment and value determination module, used for determining the number of decomposition layers that meets preset conditions based on the predicted total aliasing degree and the predicted frequency modulation performance index;

[0039] The instruction allocation module is used to determine the instruction allocation of the frequency modulation instruction signal according to the determined number of decomposition layers, and send corresponding instructions to different energy storage devices so that the energy storage devices respond to the corresponding instructions to perform frequency modulation. The energy storage devices include super capacitors.

[0040] In conjunction with the second aspect, in a possible implementation manner, the cycle calculation module is used to:

[0041] Determine the initial decomposition level and the final decomposition level;

[0042] From the initial decomposition layer to the final decomposition layer, the frequency modulation command signal is decomposed based on a preset algorithm in a loop, and each loop performs the following steps:

[0043] Decomposing the frequency modulation command signal based on a preset algorithm to obtain modal quantities corresponding to the number of decomposition layers of the cycle; and calculating the predicted total aliasing degree between the modal quantities;

[0044] The instruction allocation corresponding to the decomposition level of the cycle is obtained, and the predicted frequency modulation performance index corresponding to the decomposition level is determined according to the instruction allocation.

[0045] In conjunction with the second aspect, in a possible implementation manner, the determining and value taking module is configured to:

[0046] The values ​​of all predicted total aliasing degrees and predicted frequency modulation performance indicators are sorted respectively to obtain the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance indicator;

[0047] If the decomposition layer number corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are consistent, the decomposition layer number is determined as the decomposition layer number that meets the preset conditions.

[0048] In conjunction with the second aspect, in a possible implementation manner, the value determination module is further configured to:

[0049] If the decomposition layers corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are inconsistent, then for each predicted frequency modulation performance index, the ratio between the predicted frequency modulation performance index and each predicted total aliasing degree is determined respectively to obtain a plurality of first reference ratios;

[0050] For each first reference ratio, determine the decomposition layer numbers corresponding to the predicted total aliasing degree and the predicted frequency modulation performance index of the first reference ratio, and determine the decomposition layer number closest to the average value of the two as the decomposition layer number corresponding to the first reference ratio;

[0051] sorting the plurality of first reference ratios;

[0052] According to the order of the multiple first reference ratios from large to small, the signal integrity at the decomposition levels corresponding to the first reference ratios is determined in sequence until the decomposition level that meets the preset conditions is determined.

[0053] In conjunction with the second aspect, in a possible implementation manner, the instruction allocation module is configured to:

[0054] Decomposing the frequency modulation command signal into modal quantities of the number of decomposition layers according to the determined number of decomposition layers, mapping the modal quantities of the number of decomposition layers to the frequency domain, determining the split point of the high-frequency power component and the low-frequency power component through the frequency domain distribution of the modal quantities, and then dividing the frequency modulation command signal into the high-frequency power component and the low-frequency power component;

[0055] The high-frequency power component is sent as a supercapacitor frequency modulation power instruction to a supercapacitor energy storage device, and the low-frequency power component is sent as other frequency modulation power instructions to other energy storage devices, so that the supercapacitor energy storage device and the other energy storage devices respond to their respective frequency modulation power instructions and perform frequency modulation.

[0056] In a third aspect, a computer device is provided, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of a frequency modulation method based on ultra-capacitor energy storage as described in the first aspect are performed.

[0057] In a fourth aspect, a computer-readable storage medium is provided, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the frequency modulation method based on ultra-capacitor energy storage as described in any one of the first aspects are executed.

[0058] The beneficial effects of the embodiments of the present disclosure include:

[0059] The present disclosure provides a frequency modulation method based on supercapacitor energy storage, including: obtaining a frequency modulation command signal; determining the number of decomposition layers in a cycle for multiple times, and for the number of decomposition layers determined in each cycle, decomposing the frequency modulation command signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, and calculating the predicted total aliasing degree between each modal quantity, and predicting the frequency modulation performance index; determining the number of decomposition layers that meet the preset conditions based on the predicted total aliasing degree and the predicted frequency modulation performance index; determining the instruction allocation of the frequency modulation command signal according to the determined number of decomposition layers, and sending corresponding instructions to different energy storage devices, so that the energy storage devices respond to the corresponding instructions for frequency modulation, and the energy storage devices include supercapacitors. A frequency modulation method based on supercapacitor energy storage provided by an embodiment of the present disclosure can respond in time when the power grid frequency of a power plant fluctuates, obtain the optimal number of decomposition layers through three-layer screening of predicted total aliasing degree, predicted frequency modulation performance index and signal integrity, and thus make the frequency modulation command allocation more accurate, solve the problem of inaccurate frequency modulation command signal allocation caused by modal aliasing, reduce the cost of the energy storage system, and increase the revenue of the power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A flow chart of a frequency modulation method based on ultra-capacitor energy storage provided in an embodiment of the present disclosure;

[0061] Figure 2 A flow chart of a frequency modulation system based on ultra-capacity energy storage provided in an embodiment of the present disclosure;

[0062] Figure 3 A flowchart for selecting the optimal number of decomposition layers provided for an embodiment of the present disclosure;

[0063] Figure 4 A schematic diagram of the frequency domain distribution of modal quantities provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0064] The embodiments of the present disclosure provide a frequency modulation method, system and device based on ultracapacitor energy storage. The preferred embodiments of the present disclosure are described below in conjunction with the drawings of the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present disclosure, and are not used to limit the present disclosure. In addition, the embodiments and features in the embodiments of the present application can be combined with each other if there is no conflict.

[0065] The present disclosure provides a frequency modulation method based on ultracapacitor energy storage, such as Figure 1 As shown, including:

[0066] S101, obtaining a frequency modulation command signal;

[0067] S102, looping for multiple times to determine the number of decomposition layers, and for the number of decomposition layers determined in each loop, decomposing the frequency modulation instruction signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, calculating the predicted total aliasing degree between the modal quantities, and predicting the frequency modulation performance index;

[0068] S103, determining the number of decomposition layers that meets preset conditions based on the predicted total aliasing degree and the predicted frequency modulation performance index;

[0069] S104, determining the instruction allocation of the frequency modulation instruction signal according to the determined number of decomposition layers, and sending corresponding instructions to different energy storage devices, so that the energy storage devices perform frequency modulation in response to the corresponding instructions, and the energy storage devices include super capacitors.

[0070] The frequency modulation method based on supercapacitor energy storage provided by the embodiment of the present disclosure adopts new supercapacitors and lithium batteries as energy storage devices and modulates the frequency of the power grid in the power plant when the power supply frequency fluctuates. The state of the power plant power grid is monitored in real time. When the power supply frequency in the power plant power grid fluctuates, a corresponding frequency modulation command signal is generated. After the signal is obtained, the allocation result of the frequency modulation command signal is screened by predicting the total aliasing degree, predicting the frequency modulation performance index and the constraint conditions of the signal integrity to obtain the optimal number of decomposition layers, and the frequency of the power plant power grid is modulated using the command allocation corresponding to the optimal number of decomposition layers.

[0071] In another embodiment provided by the present disclosure, the above step "S102, looping for multiple times to determine the number of decomposition layers, and for the number of decomposition layers determined in each loop, decomposing the frequency modulation instruction signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, and calculating the predicted total aliasing degree between each modal quantity, and predicting the frequency modulation performance index" includes:

[0072] Step 1: Determine the initial decomposition layer number and the final decomposition layer number;

[0073] Step 2: From the initial decomposition layer to the final decomposition layer, the frequency modulation command signal is decomposed based on a preset algorithm in a loop, and each loop executes the following steps:

[0074] Step 3: Decompose the frequency modulation command signal based on a preset algorithm to obtain modal quantities corresponding to the number of decomposition layers of the cycle; and calculate the predicted total aliasing degree between the modal quantities;

[0075] Step 4: Obtain the instruction allocation corresponding to the number of decomposition levels of the current cycle, and determine the predicted frequency modulation performance index corresponding to the number of decomposition levels based on the instruction allocation.

[0076] In this embodiment, it is optional that in each cycle, the frequency modulation command signal is decomposed using the VMD algorithm, and the signal is decomposed into modal quantities corresponding to the number of decomposition layers, and the aliasing parts of adjacent modal quantities in the frequency domain are calculated based on these modal quantities, and all the aliasing parts in the frequency domain are summed to obtain the predicted total aliasing degree. Among them, the split point of the high-frequency power component related to the supercapacitor and the low-frequency power component related to the lithium battery can be determined through the frequency domain distribution of the modal quantity, and the frequency modulation command signal is distributed using the split point to obtain the command distribution, which is the command distribution corresponding to the number of decomposition layers of this cycle.

[0077] In this embodiment, the frequency regulation performance index is currently widely used in the performance evaluation and calculation of AGC (Automatic Generation Control) of power plants as an important index for the assessment of auxiliary frequency regulation of the unit. The frequency regulation performance index indicates how closely the frequency regulation result tracks the original signal. The influencing factors include: load disturbance, moment of inertia, load damping, energy storage capacity, command allocation, and energy storage charging and discharging efficiency. The variable in this scheme is only the command allocation. By inputting the command allocation, the value of the predicted performance index can be output.

[0078] In another embodiment provided by the present disclosure, after the frequency modulation instruction signal is decomposed into modal quantities corresponding to the number of decomposition layers based on a preset algorithm in the above step S102, the predicted total aliasing degree D is determined using the following formula:

[0079]

[0080] in, Characterizes the number of decomposition levels, Characterize the predicted total aliasing level, Characterizes the width of the aliased part of adjacent modal quantities, Characterizes the frequency band occupied by adjacent modal quantities.

[0081] In another embodiment provided by the present disclosure, the above step “S103, determining the number of decomposition layers that meet the preset conditions based on the predicted total aliasing degree and the predicted frequency modulation performance index” includes:

[0082] Step 1: sort the values ​​of all predicted total aliasing degrees and predicted frequency modulation performance indicators respectively to obtain the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance indicator;

[0083] Step 2: If the decomposition layer number corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are consistent, the decomposition layer number is determined as the decomposition layer number that meets the preset conditions.

[0084] In this embodiment, the number of decomposition layers determines the number of modal quantities into which the frequency modulation command signal is divided by the algorithm. Different numbers of decomposition layers correspond to different numbers of modal quantities in the processing process. Different numbers of modal quantities correspond to different aliasing parts between modal quantities. The predicted total aliasing degree is obtained by summing the aliasing parts between adjacent modal quantities, so the predicted total aliasing degree is also different. Different numbers of decomposition layers correspond to different predicted total aliasing degrees, and the smaller the predicted total aliasing degree is, the smaller the sequence error obtained by decomposing the frequency modulation command signal is. When the predicted total aliasing degree is the smallest, the error generated by the decomposition of the frequency modulation command signal is smaller, and the allocation result is more accurate.

[0085] In this embodiment, the frequency regulation performance index is considered to be an important index for the frequency regulation assessment of energy storage equipment, and the larger the frequency regulation performance index, the better the frequency regulation effect. Therefore, this scheme selects the value of the decomposition layer number corresponding to the maximum frequency regulation performance index.

[0086] In another embodiment provided by the present disclosure, the above step S103 further includes:

[0087] Step 1: if the decomposition levels corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are inconsistent, then for each predicted frequency modulation performance index, the ratio between the predicted frequency modulation performance index and each predicted total aliasing degree is determined to obtain a plurality of first reference ratios;

[0088] Step 2: for each first reference ratio, determine the decomposition layers corresponding to the predicted total aliasing degree and the predicted frequency modulation performance index of the first reference ratio, and determine the decomposition layer number closest to the average value of the two as the decomposition layer number corresponding to the first reference ratio;

[0089] Step 3: sorting the multiple first reference ratios;

[0090] Step 4: determining the signal integrity at the decomposition levels corresponding to the first reference ratios in descending order, until a decomposition level that meets a preset condition is determined;

[0091] In this embodiment, it can be seen from the above description that the smaller the predicted total aliasing degree, the smaller the error, the more accurate the instruction allocation, the larger the predicted frequency modulation performance index, the more accurate the instruction allocation, and the better the frequency modulation effect, and the first reference ratio is the ratio between the predicted frequency modulation performance index and each predicted total aliasing degree, so the larger the first reference ratio, the more accurate the instruction allocation, and the better the frequency modulation effect. However, the signal integrity needs to be considered at the same time, and the signal integrity is used as a constraint condition to select the decomposition layer number corresponding to the value of the first reference ratio that satisfies the higher signal integrity and the largest signal integrity, which is the optimal decomposition layer number.

[0092] In another embodiment provided by the present disclosure, the signal integrity at the number of decomposition layers corresponding to the first reference ratio is determined by the following formula:

[0093]

[0094] in, Characterizes the length of a single sequence, Characterize the residual sequence, Characterize the original sequence; by decomposing the frequency modulation command signal to obtain , where K1 is the number of decomposition levels, is the frequency modulation command signal, that is, the original sequence , is the i-th modal quantity (IMF) after decomposition, and the number of modal quantities is the number of decomposition levels. is the residual component after decomposition, that is, the residual sequence .

[0095] In another embodiment provided by the present disclosure, the signal integrity at the decomposition levels corresponding to the first reference ratios is determined in descending order of the plurality of first reference ratios until a decomposition level that meets a preset condition is determined, including:

[0096] Step 1: determining the signal integrity at the decomposition levels corresponding to the first reference ratios in descending order of the plurality of first reference ratios;

[0097] Step 2: comparing the determined signal integrity with a preset value until a first signal integrity greater than the preset value is determined;

[0098] Step three: determine the number of decomposition layers corresponding to the first signal integrity as the number of decomposition layers that meets preset conditions.

[0099] In another embodiment provided by the present disclosure, the above step “S104, determining the instruction allocation of the frequency modulation instruction signal according to the determined number of decomposition layers, and sending corresponding instructions to different energy storage devices, so that the energy storage devices respond to the corresponding instructions to perform frequency modulation” includes:

[0100] Step 1: decompose the frequency modulation command signal into modal quantities of the decomposition layer number according to the determined decomposition layer number, and map the modal quantities of the decomposition layer number to the frequency domain, determine the split point of the high-frequency power component and the low-frequency power component through the frequency domain distribution of the modal quantity, and then divide the frequency modulation command signal into the high-frequency power component and the low-frequency power component;

[0101] Step 2: Send the high-frequency power component as a supercapacitor frequency modulation power instruction to the supercapacitor energy storage device, and send the low-frequency power component as other frequency modulation power instructions to other energy storage devices, so that the supercapacitor energy storage device and the other energy storage devices respond to their respective frequency modulation power instructions and perform frequency modulation.

[0102] In this embodiment, after the optimal number of decomposition layers is obtained by screening the constraints of the predicted total aliasing degree, the predicted frequency modulation performance index and the signal integrity, the frequency modulation instruction signal is decomposed using the optimal number of decomposition layers to obtain high-frequency power components and low-frequency power components, which are sent to the corresponding energy storage device as frequency modulation instructions. The supercapacitor and lithium battery respond to their respective instructions to provide active charge to complete the frequency modulation of the power plant power grid and maintain the stability of the power plant power grid frequency.

[0103] With the above Figure 1 Corresponding to the method shown, the embodiment of the present disclosure also provides a frequency modulation system based on ultra-capacitor energy storage, such as Figure 2 As shown, including:

[0104] 201, a command acquisition module, used to acquire a frequency modulation command signal;

[0105] 202. A loop calculation module, configured to loop multiple times to determine the number of decomposition layers, and for each loop-determined number of decomposition layers, decompose the frequency modulation instruction signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, calculate the predicted total aliasing degree between the modal quantities, and predict the frequency modulation performance index;

[0106] 203. A judgment and value determination module, configured to determine the number of decomposition layers that meets preset conditions based on the predicted total aliasing degree and the predicted frequency modulation performance index;

[0107] 204. An instruction allocation module is used to determine instruction allocation of the frequency modulation instruction signal according to the determined number of decomposition layers, and send corresponding instructions to different energy storage devices so that the energy storage devices perform frequency modulation in response to the corresponding instructions, and the energy storage devices include super capacitors.

[0108] In another embodiment provided by the present disclosure, the cycle calculation module 202 is used to:

[0109] Determine the initial decomposition level and the final decomposition level;

[0110] From the initial decomposition layer to the final decomposition layer, the frequency modulation command signal is decomposed based on a preset algorithm in a loop, and each loop performs the following steps:

[0111] Decomposing the frequency modulation command signal based on a preset algorithm to obtain modal quantities corresponding to the number of decomposition layers of the cycle; and calculating the predicted total aliasing degree between the modal quantities;

[0112] The instruction allocation corresponding to the decomposition level of the cycle is obtained, and the predicted frequency modulation performance index corresponding to the decomposition level is determined according to the instruction allocation.

[0113] In another embodiment provided by the present disclosure, the determination value module 203 is further configured to:

[0114] If the decomposition layers corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are inconsistent, then for each predicted frequency modulation performance index, the ratio between the predicted frequency modulation performance index and each predicted total aliasing degree is determined respectively to obtain a plurality of first reference ratios;

[0115] For each first reference ratio, determine the decomposition layer numbers corresponding to the predicted total aliasing degree and the predicted frequency modulation performance index of the first reference ratio, and determine the decomposition layer number closest to the average value of the two as the decomposition layer number corresponding to the first reference ratio;

[0116] sorting the plurality of first reference ratios;

[0117] According to the order of the multiple first reference ratios from large to small, the signal integrity at the decomposition levels corresponding to the first reference ratios is determined in sequence until the decomposition level that meets the preset conditions is determined.

[0118] In another embodiment provided by the present disclosure, the instruction distribution module 204 is used to:

[0119] Decomposing the frequency modulation command signal into modal quantities of the number of decomposition layers according to the determined number of decomposition layers, mapping the modal quantities of the number of decomposition layers to the frequency domain, determining the split point of the high-frequency power component and the low-frequency power component through the frequency domain distribution of the modal quantities, and then dividing the frequency modulation command signal into the high-frequency power component and the low-frequency power component;

[0120] The high-frequency power component is sent as a supercapacitor frequency modulation power instruction to a supercapacitor energy storage device, and the low-frequency power component is sent as other frequency modulation power instructions to other energy storage devices, so that the supercapacitor energy storage device and the other energy storage devices respond to their respective frequency modulation power instructions and perform frequency modulation.

[0121] The method, system and device provided by the present disclosure are described in detail below with reference to the accompanying drawings using specific embodiments.

[0122] Example 1

[0123] In a frequency modulation method based on ultracapacitor energy storage provided by the present disclosure, the process of solving the optimal number of decomposition layers is as follows: Figure 3 As shown, X(t) is the frequency modulation instruction signal, K1 is the number of decomposition layers, Kmax is the maximum value of all predicted frequency modulation performance indicators K generated in the cycle, Dmin is the minimum value of all predicted total aliasing degrees D generated in the cycle, Z is the ratio of the predicted frequency modulation performance indicator K to the predicted total aliasing degree D (Z=K / D), Zmax is the maximum value of the ratio between the predicted frequency modulation performance indicator and each predicted total aliasing degree determined for each predicted frequency modulation performance indicator in the cycle, and Zmax' is the second largest value that is only less than the current maximum value Zmax.

[0124] Example 2

[0125] Taking the decomposition level K1=9 as an example, the frequency modulation command signal is decomposed into K1 modal quantities (IMF i ), the K1 IMFs obtained by decomposition i Mapped to the frequency domain, such as Figure 4 As shown,

[0126] Taking the aliasing part D1 between the modal quantity IMF1 and the modal quantity IMF2 as an example, the width of the aliasing part D1 is ω(i+1)-(1); the frequency band occupied by the modal quantity IMF2 and the modal quantity IMF1 is ω(i+1)max-ω(i)min, and the division point between the high-frequency power component and the low-frequency power component is determined through the frequency domain distribution of the modal quantity.

[0127] An embodiment of the present disclosure provides a computer device, including: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps provided in any embodiment of the present disclosure are performed.

[0128] The computer device provided in the embodiment of the present application includes a processor, a memory, and a bus. The memory is used to store execution instructions, including internal memory and external memory; the internal memory here is also called internal memory, which is used to temporarily store the operation data in the processor and the data exchanged with the external memory such as the hard disk. The processor exchanges data with the external memory through the internal memory. When the electronic device is running, the processor and the memory communicate through the bus, so that the processor executes the following instructions:

[0129] Obtaining frequency modulation command signal;

[0130] The number of decomposition layers is determined by looping for multiple times, and for the number of decomposition layers determined in each loop, the frequency modulation command signal is decomposed into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, and the predicted total aliasing degree between each modal quantity is calculated, and the frequency modulation performance index is predicted;

[0131] Based on the predicted total aliasing degree and the predicted frequency modulation performance index, the number of decomposition layers that meets the preset conditions is determined;

[0132] The command allocation of the frequency modulation command signal is determined according to the determined number of decomposition layers, and corresponding commands are sent to different energy storage devices so that the energy storage devices respond to the corresponding commands for frequency modulation.

[0133] The embodiment of the present disclosure provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps provided in any embodiment of the present disclosure are executed. The storage medium may be a volatile or non-volatile computer-readable storage medium.

[0134] Through the description of the above implementation methods, those skilled in the art can clearly understand that the embodiments of the present disclosure can be implemented by hardware, or by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a read-only CD, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present disclosure.

[0135] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes in the accompanying drawings are not necessarily required for implementing the present disclosure.

[0136] Those skilled in the art can understand that the modules in the device in the embodiment can be distributed in the device in the embodiment according to the description of the embodiment, or can be changed accordingly and located in one or more devices different from the present embodiment. The modules in the above embodiment can be combined into one module, or can be further divided into multiple sub-modules.

[0137] The serial numbers of the above-mentioned embodiments of the present disclosure are only for description and do not represent the advantages or disadvantages of the embodiments.

[0138] Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. A frequency modulation method based on supercapacitor energy storage, characterized in that: include: Obtaining frequency modulation command signal; Determine the number of decomposition layers in a cycle for multiple times, and for the number of decomposition layers determined in each cycle, decompose the frequency modulation instruction signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, calculate the predicted total aliasing degree between each modal quantity, and predict the frequency modulation performance index; Based on the predicted total aliasing degree and the predicted frequency modulation performance index, determining the number of decomposition layers that meets preset conditions; Determine the command allocation of the frequency modulation command signal according to the determined number of decomposition layers, and send corresponding commands to different energy storage devices so that the energy storage devices perform frequency modulation in response to the corresponding commands, wherein the energy storage devices include super capacitors; The number of decomposition layers is determined by looping for multiple times, and for the number of decomposition layers determined in each loop, the frequency modulation command signal is decomposed into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, and the predicted total aliasing degree between each modal quantity is calculated, and the frequency modulation performance index is predicted, including: Determine the initial decomposition level and the final decomposition level; From the initial decomposition layer to the final decomposition layer, the frequency modulation command signal is decomposed based on a preset algorithm in a loop, and each loop performs the following steps: Decomposing the frequency modulation command signal based on a preset algorithm to obtain modal quantities corresponding to the number of decomposition layers of the cycle; and calculating the predicted total aliasing degree between the modal quantities; Obtaining instruction allocation corresponding to the number of decomposition levels of the cycle, and determining the predicted frequency modulation performance index corresponding to the number of decomposition levels according to the instruction allocation; Wherein, based on the predicted total aliasing degree and the predicted frequency modulation performance index, determining the number of decomposition layers that meets the preset conditions includes: The values ​​of all predicted total aliasing degrees and predicted frequency modulation performance indicators are sorted respectively to obtain the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance indicator; If the decomposition layer number corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are consistent, the decomposition layer number is determined as the decomposition layer number that meets the preset conditions.

2. The method according to claim 1, characterized in that After the frequency modulation command signal is decomposed into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, the predicted total aliasing degree D is determined using the following formula: in, Characterizes the number of decomposition levels, Characterize the predicted total aliasing level, Characterizes the width of the aliased part of adjacent modal quantities, Characterizes the frequency band occupied by adjacent modal quantities.

3. The method according to claim 1, characterized in that The method further comprises: If the decomposition layers corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance index are inconsistent, then for each predicted frequency modulation performance index, the ratio between the predicted frequency modulation performance index and each predicted total aliasing degree is determined respectively to obtain a plurality of first reference ratios; For each first reference ratio, determine the decomposition layer numbers corresponding to the predicted total aliasing degree and the predicted frequency modulation performance index of the first reference ratio, and determine the decomposition layer number closest to the average value of the two as the decomposition layer number corresponding to the first reference ratio; sorting the plurality of first reference ratios; According to the order of the multiple first reference ratios from large to small, the signal integrity at the decomposition levels corresponding to the first reference ratios is determined in sequence until the decomposition level that meets the preset conditions is determined.

4. The method according to claim 3, characterized in that The signal integrity at the decomposition level corresponding to the first reference ratio is determined by the following formula: in, Characterizes the length of a single sequence, Characterize the residual sequence, Characterize the original sequence; by decomposing the frequency modulation command signal to obtain , where K1 is the number of decomposition levels, is the frequency modulation command signal, that is, the original sequence , is the i-th modal quantity after decomposition, and the number of modal quantities is the number of decomposition levels. is the residual component after decomposition, that is, the residual sequence .

5. The method according to claim 3, characterized in that The step of determining the signal integrity at the number of decomposition layers corresponding to the first reference ratios in order from large to small, until a number of decomposition layers that meets a preset condition is determined, includes: Determining the signal integrity at the number of decomposition layers corresponding to the first reference ratios in order from large to small; Comparing the determined signal integrity with a preset value until a first signal integrity greater than the preset value is determined; The number of decomposition layers corresponding to the first signal integrity is determined as the number of decomposition layers that meets a preset condition.

6. The method according to claim 1, characterized in that The step of determining the instruction allocation of the frequency modulation instruction signal according to the determined number of decomposition layers, and sending corresponding instructions to different energy storage devices so that the energy storage devices perform frequency modulation in response to the corresponding instructions, includes: Decomposing the frequency modulation command signal into modal quantities of the number of decomposition layers according to the determined number of decomposition layers, mapping the modal quantities of the number of decomposition layers to the frequency domain, determining the split point of the high-frequency power component and the low-frequency power component through the frequency domain distribution of the modal quantities, and then dividing the frequency modulation command signal into the high-frequency power component and the low-frequency power component; The high-frequency power component is sent as a supercapacitor frequency modulation power instruction to a supercapacitor energy storage device, and the low-frequency power component is sent as other frequency modulation power instructions to other energy storage devices, so that the supercapacitor energy storage device and the other energy storage devices respond to their respective frequency modulation power instructions and perform frequency modulation.

7. A frequency modulation system based on supercapacitor energy storage, characterized in that: include: An instruction acquisition module, used to acquire a frequency modulation instruction signal; A cyclic calculation module, used for determining the number of decomposition layers by cyclic multiple times, and for the number of decomposition layers determined in each cycle, decomposing the frequency modulation instruction signal into modal quantities corresponding to the number of decomposition layers based on a preset algorithm, calculating the predicted total aliasing degree between the modal quantities, and predicting the frequency modulation performance index; A judgment and value determination module, used for determining the number of decomposition layers that meets preset conditions based on the predicted total aliasing degree and the predicted frequency modulation performance index; An instruction allocation module, used to determine the instruction allocation of the frequency modulation instruction signal according to the determined number of decomposition layers, and send corresponding instructions to different energy storage devices so that the energy storage devices perform frequency modulation in response to the corresponding instructions, wherein the energy storage devices include super capacitors; A cyclic calculation module is used to determine the initial decomposition layer number and the termination decomposition layer number; From the initial decomposition layer to the final decomposition layer, the frequency modulation instruction signal is decomposed based on a preset algorithm in a loop, and the following steps are performed in each loop: the frequency modulation instruction signal is decomposed based on a preset algorithm to obtain a number of modal quantities corresponding to the number of decomposition layers of this loop; and the predicted total aliasing degree between the modal quantities is calculated; the instruction allocation corresponding to the number of decomposition layers of this loop is obtained, and the predicted frequency modulation performance index corresponding to the number of decomposition layers is determined according to the instruction allocation; The judgment value module is used to sort the values ​​of all predicted total aliasing degrees and predicted frequency modulation performance indicators respectively to obtain the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance indicator; if the decomposition layers corresponding to the minimum value of the predicted total aliasing degree and the maximum value of the predicted frequency modulation performance indicator are consistent, then the decomposition layer number is determined as the decomposition layer number that meets the preset conditions.

8. A computer device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the frequency modulation method based on ultra-capacitor energy storage are performed as described in any one of claims 1 to 6.

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