Photovoltaic power smooth energy storage capacity planning method and system based on wavelet packet decomposition

Abstract

The invention discloses a photovoltaic power smooth energy storage capacity planning method and system based on wavelet packet decomposition, and relates to the technical field of energy storage capacity planning, and the method comprises the steps: obtaining the original output power of a photovoltaic system; decomposing an original power signal of the photovoltaic system by using a wavelet packet decomposition method; the smoothed grid-connected power of the photovoltaic system is obtained through wavelet packet decomposition, and a high-frequency power component needing energy storage suppression is distributed to the hybrid energy storage system; and planning the power and capacity of the energy storage system according to the power component obtained after decomposition and the continuous operation requirement of the energy storage system. According to the photovoltaic power smooth energy storage capacity planning method based on wavelet packet decomposition, a wavelet packet decomposition method is used, decomposed components are re-planned, the accuracy of energy storage configuration is improved, and the benefit of power station operation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage capacity planning, and in particular to a photovoltaic power smoothing energy storage capacity planning method and system based on wavelet packet decomposition. Background Art

[0002] According to data from the International Renewable Energy Agency (IRENA), the world's newly installed photovoltaic capacity will reach 346GW in 2023, and the global photovoltaic installed capacity will reach 1412GW. In 2023, the global photovoltaic power generation accounted for 5% of the total power generation for the first time, reaching 1600 billion kWh. It is estimated that the global photovoltaic module installed capacity will reach 364GW in 2024. With the maturity of energy storage technology and the decline in energy storage prices, the economic conditions of the "1W photovoltaic + 2Wh energy storage" photovoltaic storage combined system have been met worldwide, and the photovoltaic industry is about to enter a new photovoltaic storage period with the development of the energy storage industry. After the large-scale intermittent and volatile photovoltaic power is connected to the grid, the frequency regulation and peak regulation pressure of the grid will be increased, which is likely to cause an imbalance between the output power and the grid load, resulting in fluctuations in the grid frequency. The rapid increase in the number of photovoltaic installed capacity has led to a rapid deterioration in the power supply and demand relationship during the photovoltaic output period at noon. The configuration of energy storage is still insufficient, and the power constraint problem will suppress the new photovoltaic installed capacity for a period of time. In order to support the safe and stable operation of the new power system and improve the photovoltaic absorption capacity, it is an important means to use the throughput characteristics of the fluctuating power of the new energy storage system to smooth the photovoltaic power. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is that the existing photovoltaic system grid-connected method has the problem of large power fluctuation and inability to directly connect to the grid, and the energy storage configuration is not precise enough and it is difficult to effectively suppress high-frequency fluctuations.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition, comprising:

[0006] Get the original output power of the photovoltaic system;

[0007] The original power signal of the photovoltaic system is decomposed using the wavelet packet decomposition method;

[0008] The smoothed grid-connected power of the photovoltaic system is obtained by wavelet packet decomposition, and the high-frequency power components that need to be suppressed by energy storage are allocated to the hybrid energy storage system.

[0009] The power and capacity of the energy storage system are planned based on the decomposed power components and the continuous operation requirements of the energy storage system.

[0010] As a preferred solution of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in the present invention, the decomposition includes determining the number of layers of wavelet packet decomposition according to the photovoltaic power station grid-connected power fluctuation standard, and stopping the decomposition when the decomposed power meets the standard requirements, which is expressed as:

[0011]

[0012] Among them, P n1 (t) is the lowest frequency component after n-times decomposition, ΔP n1 (t) is P n1 The rate of change of (t).

[0013] As a preferred solution of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in the present invention, wherein: the components allocated to the hybrid energy storage system include the original power of the photovoltaic system decomposed by wavelet packets, the smoothed grid-connected power of the photovoltaic system and the high-frequency power components that need to be suppressed by energy storage are obtained;

[0014] A hybrid energy storage system is used to compensate for the smoothed high-frequency power component of the photovoltaic system;

[0015] A hybrid energy storage method of battery energy storage and flywheel energy storage is adopted.

[0016] As a preferred solution of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in the present invention, wherein: the components allocated to the hybrid energy storage system are expressed as:

[0017] P m (t) = P n1 (t)

[0018]

[0019] Among them, P m (t) is the photovoltaic power after wavelet packet decomposition and smoothing, P b (t) is the medium and low frequency components of the high frequency power borne by the battery system after wavelet packet decomposition, P f (t) is the high-frequency component of the high-frequency power borne by the flywheel system after wavelet packet decomposition, and m is the number of segments of medium and low frequency components.

[0020] As a preferred solution of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in the present invention, the power and capacity of the planned energy storage system are expressed as follows:

[0021]

[0022] Among them, P f , P bare the rated planned powers of flywheel energy storage and battery energy storage respectively; η f and η b are the charge and discharge efficiency of flywheel energy storage and battery energy storage, P f (t) and P b (t) greater than 0 indicates that the energy storage device is discharged, P f (t) and P b (t) less than 0 indicates that the energy storage device is charging.

[0023] As a preferred solution of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in the present invention, wherein: according to the charging and discharging power changes of the energy storage device within a cycle, in an energy storage cycle t i The capacity change within is expressed as,

[0024]

[0025] Among them, E f (t) and E b (t) is the cumulative operating capacity of flywheel energy storage and battery energy storage in one frequency modulation cycle.

[0026] As a preferred solution of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in the present invention, in order to avoid the energy storage device exceeding the SOC limit during operation, the rated capacity of each energy storage device is calculated based on the maximum and minimum values ​​of the running cumulative capacity to complete the capacity planning, which is expressed as:

[0027]

[0028] Among them, E f and E b The rated capacity of the flywheel energy storage and battery configuration, and is the upper and lower limits of the flywheel SOC, and The upper and lower limits of the battery SOC.

[0029] Another object of the present invention is to provide a photovoltaic power smoothing energy storage capacity planning system based on wavelet packet decomposition, which can solve the power fluctuation and energy storage inaccuracy problems in existing photovoltaic grid-connected methods by constructing a photovoltaic power smoothing energy storage capacity planning system based on wavelet packet decomposition, improve the accuracy of energy storage configuration and optimize the operating efficiency of the power station.

[0030] To solve the above technical problems, the present invention provides the following technical solutions: a photovoltaic power smoothing energy storage capacity planning system based on wavelet packet decomposition, comprising: a data acquisition module, a signal decomposition module, a power allocation module and a capacity planning module; the data acquisition module is used to obtain the original output power of the photovoltaic system; the signal decomposition module is used to decompose the original power signal of the photovoltaic system using a wavelet packet decomposition method; the power allocation module is used to obtain the smoothed grid-connected power of the photovoltaic system through wavelet packet decomposition, and allocate the high-frequency power components that need to be suppressed by energy storage to the hybrid energy storage system; the capacity planning module is used to plan the power and capacity of the energy storage system according to the power components obtained after decomposition and the continuous operation requirements of the energy storage system.

[0031] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as described above are implemented.

[0032] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as described above.

[0033] Beneficial effects of the present invention: The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition provided by the present invention uses the wavelet packet decomposition method to re-plan the decomposed components, which helps to improve the accuracy of energy storage configuration and enhance the benefits of power station operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] 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.

[0035] Figure 1 An overall flow chart of a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition provided by an embodiment of the present invention.

[0036] Figure 2 A power smoothing graph of a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition provided by an embodiment of the present invention.

[0037] Figure 3 A wavelet packet decomposition principle diagram of a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition provided by an embodiment of the present invention.

[0038] Figure 4A schematic diagram of wavelet packet decomposition of a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] 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.

[0040] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0041] Example 1

[0042] Reference Figure 1-Figure 4 , which is an embodiment of the present invention, provides a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition, comprising:

[0043] Step 1: Obtain the original output power P of the photovoltaic system over a period of time s (t), we can find the original output power P of the photovoltaic system s (t) is a randomly fluctuating power signal that cannot be directly connected to the grid through the node and must be connected to the grid after power smoothing. Figure 2 shown.

[0044] Step 2: The wavelet packet decomposition method is an improved version of the wavelet transform. Compared with the wavelet transform, the wavelet packet can not only decompose the low-frequency part of the signal, but also decompose the high-frequency signal. It is a more widely used signal decomposition method. Figure 3 As shown in the figure, from top to bottom, they are the components after the initial data is decomposed into 1 layer, 2 layers, 3 layers, and n layers. n1 (t) is the lowest frequency component after n-times decomposition, is the highest frequency component after n-times decomposition. n1 (t) is the smoothed power of the photovoltaic system after wavelet packet classification.

[0045] Step 3: Determine the number of decomposition layers based on step 2, based on the grid-connected power fluctuation standard of photovoltaic power plants. n1 (t) If the standard requirements are met (the rate of change is less than the maximum change limit), the decomposition is stopped; otherwise, the decomposition is continued.

[0046]

[0047] Among them, ΔP n1 (t) is P n1 The rate of change of (t).

[0048]

[0049] Step 4: Decompose the original power of the photovoltaic system by wavelet packets to obtain the smoothed grid-connected power of the photovoltaic system and the high-frequency power components that need energy storage to suppress. A hybrid energy storage system is used to compensate for the smoothed high-frequency power components of the photovoltaic system. Hybrid energy storage uses battery energy storage and flywheel energy storage. The battery energy storage charge and discharge rate is relatively low, and frequent charging and discharging will accelerate its attenuation and aging, making it difficult to meet the power demand with rapid short-term fluctuations. Therefore, the medium and low frequency components of the high-frequency power components that need energy storage to suppress are distributed to the battery, and the remaining high-frequency components are distributed to the flywheel system that can act quickly and has a large number of charge and discharge times. Assume that the number of decompositions that meet the requirements is n times.

[0050] P m (t) = P n1 (t)

[0051]

[0052] Among them, P m (t) is the photovoltaic power after wavelet packet decomposition and smoothing, P b (t) is the medium and low frequency components of the high frequency power borne by the battery system after wavelet packet decomposition, P f (t) is the high-frequency component of the high-frequency power borne by the flywheel system after wavelet packet decomposition. m is the number of segments of the medium and low frequency components.

[0053] Figure 4 It is shown as a legend after decomposition into 9 segments: the first one is the original signal, the second to tenth ones are wavelet component 9 to wavelet component 1, and the last one is the power after smoothing.

[0054] Step 5: After referring to the energy storage reconstruction plan in step 4, follow the following process to plan the energy storage power and capacity. Based on the continuous operation requirements of the energy storage system and the loss characteristics of the energy storage process, the rated power of the equipment planning shall not be lower than the charging and discharging task power that the equipment needs to complete at time t, thereby completing the power planning.

[0055]

[0056] In the formula: P f , P b are the rated planned powers of flywheel energy storage and battery energy storage respectively; η f and ηb are the charge and discharge efficiencies of flywheel energy storage and battery energy storage (between 0 and 1). f (t) and P b (t) greater than 0 indicates that the energy storage device is discharged, P f (t) and P b (t) less than 0 indicates that the energy storage device is charging.

[0057] In one cycle, according to the charging and discharging power changes of the energy storage device, in one energy storage cycle t i Capacity changes within

[0058]

[0059] Where E f (t) and E b (t) is the cumulative operating capacity of flywheel energy storage and battery energy storage in one frequency modulation cycle.

[0060] At the same time, in order to prevent the energy storage equipment from exceeding the SOC limit during operation, the rated capacity of each energy storage device is calculated based on the maximum and minimum values ​​of the cumulative operating capacity to complete the capacity planning:

[0061]

[0062] Where E f and E b The rated capacity of the flywheel energy storage and battery configuration, and The upper and lower limits of the flywheel SOC are preferably 0.2 and 0.8, and The upper and lower limits of the battery's SOC are preferably 0.3 and 0.7, and the equipment from different manufacturers is slightly different.

[0063] Step 6: P f and P b , E f and E b That is the planned energy storage power and capacity.

[0064] Example 2

[0065] According to an embodiment of the present invention, a photovoltaic power smoothing energy storage capacity planning system based on wavelet packet decomposition is provided, comprising:

[0066] Data acquisition module, signal decomposition module, power allocation module and capacity planning module;

[0067] The data acquisition module is used to obtain the original output power of the photovoltaic system;

[0068] The signal decomposition module is used to decompose the original power signal of the photovoltaic system using the wavelet packet decomposition method;

[0069] The power distribution module is used to obtain the smoothed grid-connected power of the photovoltaic system through wavelet packet decomposition, and distribute the high-frequency power components that need energy storage suppression to the hybrid energy storage system;

[0070] The capacity planning module is used to plan the power and capacity of the energy storage system according to the decomposed power components and the continuous operation requirements of the energy storage system.

[0071] Example 3

[0072] An embodiment of the present invention is different from the first two embodiments in that:

[0073] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0074] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0075] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0076] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0077] 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.

Claims

1. A photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition, characterized in that: include: Get the original output power of the photovoltaic system; The original power signal of the photovoltaic system is decomposed using the wavelet packet decomposition method; The smoothed grid-connected power of the photovoltaic system is obtained by wavelet packet decomposition, and the high-frequency power components that need to be suppressed by energy storage are allocated to the hybrid energy storage system. The power and capacity of the energy storage system are planned based on the decomposed power components and the continuous operation requirements of the energy storage system.

2. The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition according to claim 1 is characterized in that: The decomposition includes determining the number of layers of wavelet packet decomposition according to the grid-connected power fluctuation standard of the photovoltaic power station, and stopping the decomposition when the decomposed power meets the standard requirements, which is expressed as: Among them, P n1 (t) is the lowest frequency component after n-times decomposition, ΔP n1 (t) is P n1 The rate of change of (t).

3. The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as claimed in claim 2 is characterized by: The components allocated to the hybrid energy storage system include the original power of the photovoltaic system decomposed by wavelet packets, the smoothed grid-connected power of the photovoltaic system and the high-frequency power components that need to be suppressed by energy storage; A hybrid energy storage system is used to compensate for the smoothed high-frequency power component of the photovoltaic system; A hybrid energy storage method of battery energy storage and flywheel energy storage is adopted.

4. The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as claimed in claim 3 is characterized by: The components allocated to the hybrid energy storage system are expressed as, P m (t)=P n1 (t) Among them, P m (t) is the photovoltaic power after wavelet packet decomposition and smoothing, P b (t) is the medium and low frequency components of the high frequency power borne by the battery system after wavelet packet decomposition, P f (t) is the high-frequency component of the high-frequency power borne by the flywheel system after wavelet packet decomposition, and m is the number of segments of medium and low frequency components.

5. The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as claimed in claim 4 is characterized by: The power and capacity of the planned energy storage system are expressed as: Among them, P f , P b are the rated planned powers of flywheel energy storage and battery energy storage respectively; η f and η b are the charge and discharge efficiency of flywheel energy storage and battery energy storage, P f (t) and P b (t) greater than 0 indicates that the energy storage device is discharged, P f (t) and P b (t) less than 0 indicates that the energy storage device is charging.

6. The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as claimed in claim 5, characterized in that: In one cycle, according to the charging and discharging power changes of the energy storage device, in one energy storage cycle t i The capacity change within is expressed as, Among them, E f (t) and E b (t) is the cumulative operating capacity of flywheel energy storage and battery energy storage in one frequency modulation cycle.

7. The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition according to claim 6 is characterized in that: In order to prevent the energy storage equipment from exceeding the SOC limit during operation, the rated capacity of each energy storage device is calculated based on the maximum and minimum values ​​of the cumulative capacity, and the capacity planning is completed, which is expressed as: Among them, E f and E b The rated capacity of the flywheel energy storage and battery configuration, and is the upper and lower limits of the flywheel SOC, and The upper and lower limits of the battery SOC.

8. A system using the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as claimed in any one of claims 1 to 7, characterized in that: include: Data acquisition module, signal decomposition module, power allocation module and capacity planning module; The data acquisition module is used to obtain the original output power of the photovoltaic system; The signal decomposition module is used to decompose the original power signal of the photovoltaic system using a wavelet packet decomposition method; The power distribution module is used to obtain the smoothed grid-connected power of the photovoltaic system through wavelet packet decomposition, and distribute the high-frequency power components that need energy storage suppression to the hybrid energy storage system; The capacity planning module is used to plan the power and capacity of the energy storage system according to the power components obtained after decomposition and the continuous operation requirements of the energy storage system.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition according to any one of claims 1 to 7 are implemented.

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