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

Abstract

The application discloses a photovoltaic power smoothing energy storage capacity planning method and system based on wavelet packet decomposition, relates to the technical field of energy storage capacity planning, and comprises the following steps: acquiring original output power of a photovoltaic system; using a wavelet packet decomposition method to decompose the original power signal of the photovoltaic system; obtaining the smoothing grid-connected power of the photovoltaic system through wavelet packet decomposition, and distributing the high-frequency power components that need to be suppressed by energy storage to a hybrid energy storage system; and planning 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. The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition provided by the application uses the wavelet packet decomposition method to re-plan the decomposed components, which helps to improve the accuracy of energy storage configuration and improve the income of power station operation.

Description

Technical Field

[0001] This invention relates to the field of energy storage capacity planning technology, specifically to a photovoltaic power smoothing energy storage capacity planning method and system based on wavelet packet decomposition. Background Technology

[0002] According to data from the International Renewable Energy Agency (IRENA), global new photovoltaic (PV) capacity reached 346 GW in 2023, bringing the global PV installed capacity to 1412 GW. In 2023, global PV power generation accounted for over 5% of total electricity generation for the first time, reaching 1.6 trillion kWh. Global PV module installations are projected to reach 364 GW in 2024. With the maturation of energy storage technology and the decline in energy storage prices, the economic viability of "1W PV + 2Wh energy storage" combined PV-storage systems has been met globally, and the PV industry is about to enter a new era of PV-storage integration, driven by the development of the energy storage industry. However, the large-scale integration of intermittent and highly volatile PV power into the grid will increase the grid's frequency regulation and peak-shaving pressure, easily causing imbalances between output power and grid load, leading to grid frequency fluctuations. The rapid increase in PV installed capacity has led to a rapid deterioration in the power supply and demand relationship during midday PV output periods, and the configuration of energy storage remains insufficient. Power constraints will inhibit new PV installations for some time. To support the safe and stable operation of the new power system and enhance the photovoltaic absorption capacity, leveraging the power throughput characteristics of new energy storage systems to smooth out photovoltaic power is an important means. Summary of the Invention

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

[0004] Therefore, the technical problem solved by this invention is that existing photovoltaic system grid connection methods have the problems of large power fluctuations and inability to directly connect to the grid, as well as the shortcomings of insufficient energy storage configuration and difficulty in effectively suppressing high-frequency fluctuations.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition, comprising:

[0006] Obtain the raw 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] Based on the power components obtained after decomposition and the continuous operation requirements of the energy storage system, the power and capacity of the energy storage system are planned.

[0010] As a preferred embodiment of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in this invention, the decomposition includes: determining the number of wavelet packet decomposition levels according to the photovoltaic power grid-connected power fluctuation standard; stopping the decomposition when the decomposed power meets the standard requirements, as expressed in:

[0011]

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

[0013] As a preferred embodiment of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in this invention, the component allocation to the hybrid energy storage system includes the original power of the photovoltaic system obtained by wavelet packet decomposition, and the smoothed grid-connected power of the photovoltaic system and the high-frequency power component that needs to be suppressed by energy storage.

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

[0015] A hybrid energy storage system combining battery energy storage and flywheel energy storage is adopted.

[0016] As a preferred embodiment of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition described in this invention, the component allocation to the hybrid energy storage system is expressed as follows:

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

[0018]

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

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

[0021]

[0022] Among them, P f P bThese are the rated planned power of flywheel energy storage and battery energy storage, respectively; η f and η b The charge / discharge efficiencies, P and P, are for flywheel energy storage and battery energy storage, respectively. f (t) and P b (t) greater than 0 indicates that the energy storage device is discharging, P f (t) and P b (t) less than 0 indicates that the energy storage device is charging.

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

[0024]

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

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

[0027]

[0028] Among them, E f and E b The rated capacity for flywheel energy storage and battery configurations. and The upper and lower limits of the flywheel's SOC (State of Charge). and These are the upper and lower limits of the battery's State of Charge (SOC).

[0029] Another objective of this invention is to provide a photovoltaic power smoothing energy storage capacity planning system based on wavelet packet decomposition. By constructing a photovoltaic power smoothing energy storage capacity planning system based on wavelet packet decomposition, this system solves the problems of power fluctuation and inaccurate energy storage in existing photovoltaic grid connection methods, improves the accuracy of energy storage configuration, and optimizes the operating efficiency of power plants.

[0030] To address the aforementioned technical problems, this invention provides the following technical solution: 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 acquire 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 the 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 includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as described above.

[0032] A computer-readable storage medium having a computer program stored thereon, 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] The beneficial effects of the present invention are as follows: The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition provided by the present invention uses wavelet packet decomposition to re-plan the decomposed components, which helps to improve the accuracy of energy storage configuration and increase the operating benefits of power plants. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 The above is an overall flowchart of a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition provided in one embodiment of the present invention.

[0036] Figure 2 The power smoothing graph is provided in one embodiment of the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition.

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

[0038] Figure 4This is a wavelet packet decomposition diagram illustrating a photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition, provided in an embodiment of the present invention. Detailed Implementation

[0039] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0040] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0041] Example 1

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

[0043] Step 1: Obtain the original output power P of the photovoltaic system over a certain period of time. s (t) will reveal 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; it must be smoothed before it can be connected to the grid. (See diagram below.) Figure 2 As shown.

[0044] Step 2: Wavelet packet decomposition is an improved version of wavelet transform. Compared to wavelet transform, wavelet packets can decompose not only the low-frequency components of a signal but also high-frequency signals, making it a more widely used signal decomposition method. Its principle is as follows... Figure 3 As shown, from top to bottom, these are the components after decomposing the initial data into layers 1, 2, 3...n. P n1 (t) represents the lowest frequency component after n-fold decomposition. P is the highest frequency component after n-fold decomposition. n1 (t) represents the smoothed power of the photovoltaic system after wavelet packet classification.

[0045] Step 3: Based on Step 2, determine the number of decomposition layers, using the photovoltaic power plant grid-connected power fluctuation standard as a basis, when ΔP n1 If the standard requirement (the rate of change is less than the maximum change limit) is met, the decomposition stops; otherwise, the decomposition continues.

[0046]

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

[0048]

[0049] Step 4: Wavelet packet decomposition yields the original power of the photovoltaic system, resulting in the smoothed grid-connected power and the high-frequency power components requiring energy storage suppression. A hybrid energy storage system is used to compensate for the smoothed high-frequency power components of the photovoltaic system. The hybrid energy storage system combines battery energy storage and flywheel energy storage. Battery energy storage has a relatively low charge / discharge rate, and frequent charging and discharging accelerates its degradation and aging, making it difficult to meet short-term, rapidly fluctuating power demands. Therefore, the low- and mid-frequency components of the high-frequency power components requiring energy storage suppression are allocated to the battery, while the remaining high-frequency components are allocated to the flywheel system, which can operate quickly and has a high number of charge / discharge cycles. Assume the required number of decompositions is n.

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

[0051]

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

[0053] Figure 4 The diagram is shown as a result of decomposing the signal into nine segments: the first segment represents the original signal, the second to tenth segments represent wavelet components 9 to 1, and the last segment represents the smoothed power.

[0054] Step 5: Following the energy storage reconfiguration scheme in Step 4, plan the energy storage power and capacity according to the following process. Based on the continuous operation requirements of the energy storage system and the characteristics of energy storage loss, the rated power of the equipment should not be lower than the charging and discharging power required by the equipment at time t, thus completing the power planning.

[0055]

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

[0057] Within one cycle, based on the change in the charging and discharging power of the energy storage device, in one energy storage cycle t i Internal capacity change

[0058]

[0059] In the formula E f (t) and E b (t) represents the cumulative operating capacity of flywheel energy storage and battery energy storage within one frequency regulation cycle.

[0060] Meanwhile, to prevent energy storage devices from exceeding their State of Charge (SOC) limits during operation, the rated capacity of each energy storage device is calculated based on the maximum and minimum cumulative operating capacity, thus completing capacity planning.

[0061]

[0062] In the formula E f and E b The rated capacity for flywheel energy storage and battery configurations. and The preferred upper and lower limits of the SOC for the flywheel are 0.2 and 0.8, respectively. and The preferred upper and lower limits of the SOC for the battery are 0.3 and 0.7, respectively, although these may vary slightly depending on the manufacturer's equipment.

[0063] Step 6: P f and P b E f and E b This refers to the planned energy storage power and capacity.

[0064] Example 2

[0065] As one 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 raw output power of the photovoltaic system;

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

[0069] The power allocation module is used to obtain the smoothed grid-connected power of the photovoltaic system through wavelet packet decomposition, and to allocate the high-frequency power components that need to be suppressed by energy storage to the hybrid energy storage system.

[0070] The capacity planning module is used to plan the power and capacity of the energy storage system based on the power components obtained after decomposition and the continuous operation requirements of the energy storage system.

[0071] Example 3

[0072] One embodiment of the present invention differs from the previous two embodiments in that:

[0073] If the aforementioned functions are implemented as 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 a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

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

[0075] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0076] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0077] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within 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: Obtain the raw 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. Based on the power components obtained after decomposition and the continuous operation requirements of the energy storage system, the power and capacity of the energy storage system are planned. The power and capacity of the planned energy storage system are expressed as follows: Among them, P f P b These are the rated planned power of flywheel energy storage and battery energy storage, respectively; η f and η b The charge / discharge efficiencies, P and P, are for flywheel energy storage and battery energy storage, respectively. f (t) and P b (t) greater than 0 indicates that the energy storage device is discharging, P f (t) and P b (t) less than 0 indicates that the energy storage device is charging; Within one cycle, based on the change in the charging and discharging power of the energy storage device, in one energy storage cycle t i The change in capacity within is expressed as, Among them, E f (t) and E b (t) represents the cumulative operating capacity of flywheel energy storage and battery energy storage within one frequency regulation cycle; To prevent energy storage devices from exceeding their State of Charge (SOC) limits during operation, the rated capacity of each energy storage device is calculated based on the maximum and minimum cumulative operating capacity, thus completing capacity planning, denoted as: Among them, E f and E b The rated capacity for flywheel energy storage and battery configurations. and The upper and lower limits of the flywheel's SOC (State of Charge). and These are the upper and lower limits of the battery's State of Charge (SOC).

2. The photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as described in claim 1, characterized in that: The decomposition process includes determining the number of wavelet packet decomposition levels based on the photovoltaic power grid-connected power fluctuation standard. Decomposition stops when the decomposed power meets the standard requirements, as shown below. Among them, P n1 (t) represents the lowest frequency component after n-fold 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 described in claim 2, characterized in that: The components allocated to the hybrid energy storage system include the original power of the photovoltaic system obtained by wavelet packet decomposition, 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 components of the photovoltaic system. A hybrid energy storage system combining 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 described in claim 3, characterized in that: The allocation of the component to the hybrid energy storage system is expressed as follows: P m (t)=P n1 (t) Among them, P m (t) represents the photovoltaic power after wavelet packet decomposition and smoothing, P b (t) represents the mid-to-low frequency components of the high-frequency power supplied by the battery system after wavelet packet decomposition, P f (t) represents the high-frequency component of the high-frequency power carried by the flywheel system after wavelet packet decomposition, and m represents the number of segments of the mid-low frequency components.

5. A system employing the photovoltaic power smoothing energy storage capacity planning method based on wavelet packet decomposition as described in any one of claims 1 to 4, 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 the 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 to 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 based on the power components obtained after decomposition and the continuous operation requirements of the energy storage system.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements 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 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements 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 4.

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